Contribution of LANDSAT-4 thematic mapper data to geologic exploration

NASA Technical Reports Server (NTRS)

Everett, J. R.; Dykstra, J. D.; Sheffield, C. A.

1983-01-01

The increased number of carefully selected narrow spectral bands and the increased spatial resolution of thematic mapper data over previously available satellite data contribute greatly to geologic exploration, both by providing spectral information that permits lithologic differentiation and recognition of alteration and spatial information that reveals structure. As vegetation and soil cover increase, the value of spectral components of TM data decreases relative to the value of the spatial component of the data. However, even in vegetated areas, the greater spectral breadth and discrimination of TM data permits improved recognition and mapping of spatial elements of the terrain. As our understanding of the spectral manifestations of the responses of soils and vegetation to unusual chemical environments increases, the value of spectral components of TM data to exploration will greatly improve in covered areas.

Using Small Drone (UAS) Imagery to Bridge the Gap Between Field- and Satellite-Based Measurements of Vegetation Structure and Change

NASA Astrophysics Data System (ADS)

Mayes, M. T.; Estes, L. D.; Gago, X.; Debats, S. R.; Caylor, K. K.; Manfreda, S.; Oudemans, P.; Ciraolo, G.; Maltese, A.; Nadal, M.; Estrany, J.

2016-12-01

Leaf area is an important ecosystem variable that relates to vegetation biomass, productivity, water and nutrient use in natural and agricultural systems globally. Since the 1980s, optical satellite image-based estimates of leaf area based on indices such as Normalized Difference Vegetation Index (NDVI) have greatly improved understanding of vegetation structure, function, and responses to disturbance at landscape (10^3 km2) to continental (10^6 km2) spatial scales. However, at landscape scales, satellites have failed to capture many leaf area patterns indicative of vegetation succession, crop types, stress and other conditions important for ecological processes. Small drones (UAS - unmanned aerial systems) offer new means for assessing leaf area and vegetation structure at higher spatial resolutions (<1 m) and land cover features such as substrate exposure that may affect estimates of vegetation structure in satellite data. Yet it is unclear how differences in spatial and spectral resolution between UAS and satellite data affect their relationships to each other, and to common field measurements of leaf area (e.g. LiCOR photosensors) and land cover. Constraining these relationships is important for leveraging UAS data to improve scaling of field data on leaf area and biomass to satellite data from Landsat, Sentinel-2, and increasing numbers of commercial sensors. Here, we quantify relationships among field, UAS and satellite estimates of vegetation leaf area and biomass in three case study landscapes spanning semi-arid Mediterranean (Matera, Southern Italy and Mallorca, Spain) and North American temperate ecosystems (New Jersey, USA). We assess how land cover and sensor spectral characteristics affect UAS and satellite-derived NDVI, leaf-area and biomass estimates. Then, we assess the fidelity of UAS, WorldView-2, and Landsat leaf-area and biomass estimates to field-measured landscape changes and variability, including vegetation recovery from fire (Mallorca), and leaf-area and biomass variability due to orchard type and agro-ecosystem management (Matera, New Jersey). Finally, we highlight promising ways forward for improving field data collection and the use of UAS observations to monitor vegetation leaf-area and biomass change at landscape scales in natural and agricultural systems.

Predicting opportunities for greening and patterns of vegetation on private urban lands

Treesearch

Austin R. Troy; J. Morgan Grove; Jarlath P.M. O' Neil-Dunne; Steward T.A. Pickett; Mary L. Cadenasso

2007-01-01

This paper examines predictors of vegetative cover on private lands in Baltimore, Maryland. Using high-resolution spatial data, we generated two measures: "possible stewardship," which is the proportion of private land that does not have built structures on it and hence has the possibility of supporting vegetation, and "realized stewardship," which...

Should heterogeneity be the basis for conservation? Grassland bird response to fire and grazing

USGS Publications Warehouse

Fuhlendorf, S.D.; Harrell, W.C.; Engle, David M.; Hamilton, R.G.; Davis, C.A.; Leslie, David M.

2006-01-01

In tallgrass prairie, disturbances such as grazing and fire can generate patchiness across the landscape, contributing to a shifting mosaic that presumably enhances biodiversity. Grassland birds evolved within the context of this shifting mosaic, with some species restricted to one or two patch types created under spatially and temporally distinct disturbance regimes. Thus, management-driven reductions in heterogeneity may be partly responsible for declines in numbers of grassland birds. We experimentally altered spatial heterogeneity of vegetation structure within a tallgrass prairie by varying the spatial and temporal extent of fire and by allowing grazing animals to move freely among burned and unburned patches (patch treatment). We contrasted this disturbance regime with traditional agricultural management of the region that promotes homogeneity (traditional treatment). We monitored grassland bird abundance during the breeding seasons of 2001-2003 to determine the influence of altered spatial heterogeneity on the grassland bird community. Focal disturbances of patch burning and grazing that shifted through the landscape over several years resulted in a more heterogeneous pattern of vegetation than uniform application of fire and grazing. Greater spatial heterogeneity in vegetation provided greater variability in the grassland bird community. Some bird species occurred in greatest abundance within focally disturbed patches, while others occurred in relatively undisturbed patches in our patch treatment. Henslow's Sparrow, a declining species, occurred only within the patch treatment. Upland Sandpiper and some other species were more abundant on recently disturbed patches within the same treatment. The patch burn treatment created the entire gradient of vegetation structure required to maintain a suite of grassland bird species that differ in habitat preferences. Our study demonstrated that increasing spatial and temporal heterogeneity of disturbance in grasslands increases variability in vegetation structure that results in greater variability at higher trophic levels. Thus, management that creates a shifting mosaic using spatially and temporally discrete disturbances in grasslands can be a useful tool in conservation. In the case of North American tallgrass prairie, discrete fires that capitalize on preferential grazing behavior of large ungulates promote a shifting mosaic of habitat types that maintain biodiversity and agricultural productivity. ?? 2006 by the Ecological Society of America.

Disentangling how landscape spatial and temporal heterogeneity affects Savanna birds.

PubMed

Price, Bronwyn; McAlpine, Clive A; Kutt, Alex S; Ward, Doug; Phinn, Stuart R; Ludwig, John A

2013-01-01

In highly seasonal tropical environments, temporal changes in habitat and resources are a significant determinant of the spatial distribution of species. This study disentangles the effects of spatial and mid to long-term temporal heterogeneity in habitat on the diversity and abundance of savanna birds by testing four competing conceptual models of varying complexity. Focussing on sites in northeast Australia over a 20 year time period, we used ground cover and foliage projected cover surfaces derived from a time series of Landsat Thematic Mapper imagery, rainfall data and site-level vegetation surveys to derive measures of habitat structure at local (1-100 ha) and landscape (100-1000s ha) scales. We used generalised linear models and an information theoretic approach to test the independent effects of spatial and temporal influences on savanna bird diversity and the abundance of eight species with different life-history behaviours. Of four competing models defining influences on assemblages of savanna birds, the most parsimonious included temporal and spatial variability in vegetation cover and site-scale vegetation structure, suggesting savanna bird species respond to spatial and temporal habitat heterogeneity at both the broader landscape scale and at the fine-scale. The relative weight, strength and direction of the explanatory variables changed with each of the eight species, reflecting their different ecology and behavioural traits. This study demonstrates that variations in the spatial pattern of savanna vegetation over periods of 10 to 20 years at the local and landscape scale strongly affect bird diversity and abundance. Thus, it is essential to monitor and manage both spatial and temporal variability in avian habitat to achieve long-term biodiversity outcomes.

Disentangling How Landscape Spatial and Temporal Heterogeneity Affects Savanna Birds

PubMed Central

Price, Bronwyn; McAlpine, Clive A.; Kutt, Alex S.; Ward, Doug; Phinn, Stuart R.; Ludwig, John A.

2013-01-01

In highly seasonal tropical environments, temporal changes in habitat and resources are a significant determinant of the spatial distribution of species. This study disentangles the effects of spatial and mid to long-term temporal heterogeneity in habitat on the diversity and abundance of savanna birds by testing four competing conceptual models of varying complexity. Focussing on sites in northeast Australia over a 20 year time period, we used ground cover and foliage projected cover surfaces derived from a time series of Landsat Thematic Mapper imagery, rainfall data and site-level vegetation surveys to derive measures of habitat structure at local (1–100 ha) and landscape (100–1000s ha) scales. We used generalised linear models and an information theoretic approach to test the independent effects of spatial and temporal influences on savanna bird diversity and the abundance of eight species with different life-history behaviours. Of four competing models defining influences on assemblages of savanna birds, the most parsimonious included temporal and spatial variability in vegetation cover and site-scale vegetation structure, suggesting savanna bird species respond to spatial and temporal habitat heterogeneity at both the broader landscape scale and at the fine-scale. The relative weight, strength and direction of the explanatory variables changed with each of the eight species, reflecting their different ecology and behavioural traits. This study demonstrates that variations in the spatial pattern of savanna vegetation over periods of 10 to 20 years at the local and landscape scale strongly affect bird diversity and abundance. Thus, it is essential to monitor and manage both spatial and temporal variability in avian habitat to achieve long-term biodiversity outcomes. PMID:24066138

Sampling and estimation procedures for the vegetation diversity and structure indicator

Treesearch

Bethany K. Schulz; William A. Bechtold; Stanley J. Zarnoch

2009-01-01

The Vegetation Diversity and Structure Indicator (VEG) is an extensive inventory of vascular plants in the forests of the United States. The VEG indicator provides baseline data to assess trends in forest vascular plant species richness and composition, and the relative abundance and spatial distribution of those species, including invasive and introduced species. The...

Shade tree spatial structure and pod production explain frosty pod rot intensity in cacao agroforests, Costa Rica.

PubMed

Gidoin, Cynthia; Avelino, Jacques; Deheuvels, Olivier; Cilas, Christian; Bieng, Marie Ange Ngo

2014-03-01

Vegetation composition and plant spatial structure affect disease intensity through resource and microclimatic variation effects. The aim of this study was to evaluate the independent effect and relative importance of host composition and plant spatial structure variables in explaining disease intensity at the plot scale. For that purpose, frosty pod rot intensity, a disease caused by Moniliophthora roreri on cacao pods, was monitored in 36 cacao agroforests in Costa Rica in order to assess the vegetation composition and spatial structure variables conducive to the disease. Hierarchical partitioning was used to identify the most causal factors. Firstly, pod production, cacao tree density and shade tree spatial structure had significant independent effects on disease intensity. In our case study, the amount of susceptible tissue was the most relevant host composition variable for explaining disease intensity by resource dilution. Indeed, cacao tree density probably affected disease intensity more by the creation of self-shading rather than by host dilution. Lastly, only regularly distributed forest trees, and not aggregated or randomly distributed forest trees, reduced disease intensity in comparison to plots with a low forest tree density. A regular spatial structure is probably crucial to the creation of moderate and uniform shade as recommended for frosty pod rot management. As pod production is an important service expected from these agroforests, shade tree spatial structure may be a lever for integrated management of frosty pod rot in cacao agroforests.

Effects of grazing on spatiotemporal variations in community structure and ecosystem function on the grasslands of Inner Mongolia, China.

PubMed

Su, Rina; Cheng, Junhui; Chen, Dima; Bai, Yongfei; Jin, Hua; Chao, Lumengqiqige; Wang, Zhijun; Li, Junqing

2017-02-28

Grasslands worldwide are suffering from overgrazing, which greatly alters plant community structure and ecosystem functioning. However, the general effects of grazing on community structure and ecosystem function at spatial and temporal scales has rarely been examined synchronously in the same grassland. Here, during 2011-2013, we investigated community structure (cover, height, and species richness) and aboveground biomass (AGB) using 250 paired field sites (grazed vs. fenced) across three vegetation types (meadow, typical, and desert steppes) on the Inner Mongolian Plateau. Grazing, vegetation type, and year all had significant effects on cover, height, species richness, and AGB, although the primary factor influencing variations in these variables was vegetation type. Spatially, grazing significantly reduced the measured variables in meadow and typical steppes, whereas no changes were observed in desert steppe. Temporally, both linear and quadratic relationships were detected between growing season precipitation and cover, height, richness, or AGB, although specific relationships varied among observation years and grazing treatments. In each vegetation type, the observed community properties were significantly correlated with each other, and the shape of the relationship was unaffected by grazing treatment. These findings indicate that vegetation type is the most important factor to be considered in grazing management for this semi-arid grassland.

Semi-arid grassland bird responses to patch-burn grazing and drought

USGS Publications Warehouse

Skagen, Susan K.; Augustine, David J.; Derner, Justin D.

2018-01-01

As grassland birds of central North America experience steep population declines with changes in land use, management of remaining tracts becomes increasingly important for population viability. The integrated use of fire and grazing may enhance vegetation heterogeneity and diversity in breeding birds, but the subsequent effects on reproduction are unknown. We examined the influence of patch-burn grazing management in shortgrass steppe in eastern Colorado on habitat use and reproductive success of 3 grassland bird species, horned lark (Eremophila alpestris), lark bunting (Calamospiza melanocorys), and McCown’s longspur (Rhynchophanes mccownii), at several spatial scales during 2011 and 2012. Although no simple direct relationship to patch-burn grazing treatment existed, habitat selection depended on precipitation- and management-induced vegetation conditions and spatial scale. All species selected taller-than-expected vegetation at the nest site, whereas at the territory scale, horned larks and McCown’s longspurs selected areas with low vegetation height and sparse cover of tall plants (taller than the dominant shortgrasses). Buntings nested primarily in unburned grassland under average rainfall. Larks and longspurs shifted activity from patch burns during average precipitation (2011) to unburned pastures during drought (2012). Daily survival rate (DSR) of nests varied with time in season, species, weather, and vegetation structure. Daily survival rate of McCown’s longspur nests did not vary with foliar cover of relatively tall vegetation at the nest under average precipitation but declined with increasing cover during drought. At the 200-m scale, increasing cover of shortgrasses, rather than taller plant species, improved DSR of larks and longspurs. These birds experience tradeoffs in the selection of habitat at different spatial scales: tall structure at nests may reduce visual detection by predators and provide protection from sun, wind, and rain, yet taller structure surrounding territories may host nest predators. Patch-burn grazing management in combination with other strategies that retain taller-structured vegetation may help sustain a diversity of breeding habitats for shortgrass birds under varying weather conditions.

Heteroskedasticity as a leading indicator of desertification in spatially explicit data.

PubMed

Seekell, David A; Dakos, Vasilis

2015-06-01

Regime shifts are abrupt transitions between alternate ecosystem states including desertification in arid regions due to drought or overgrazing. Regime shifts may be preceded by statistical anomalies such as increased autocorrelation, indicating declining resilience and warning of an impending shift. Tests for conditional heteroskedasticity, a type of clustered variance, have proven powerful leading indicators for regime shifts in time series data, but an analogous indicator for spatial data has not been evaluated. A spatial analog for conditional heteroskedasticity might be especially useful in arid environments where spatial interactions are critical in structuring ecosystem pattern and process. We tested the efficacy of a test for spatial heteroskedasticity as a leading indicator of regime shifts with simulated data from spatially extended vegetation models with regular and scale-free patterning. These models simulate shifts from extensive vegetative cover to bare, desert-like conditions. The magnitude of spatial heteroskedasticity increased consistently as the modeled systems approached a regime shift from vegetated to desert state. Relative spatial autocorrelation, spatial heteroskedasticity increased earlier and more consistently. We conclude that tests for spatial heteroskedasticity can contribute to the growing toolbox of early warning indicators for regime shifts analyzed with spatially explicit data.

Linking models and data on vegetation structure

NASA Astrophysics Data System (ADS)

Hurtt, G. C.; Fisk, J.; Thomas, R. Q.; Dubayah, R.; Moorcroft, P. R.; Shugart, H. H.

2010-06-01

For more than a century, scientists have recognized the importance of vegetation structure in understanding forest dynamics. Now future satellite missions such as Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI) hold the potential to provide unprecedented global data on vegetation structure needed to reduce uncertainties in terrestrial carbon dynamics. Here, we briefly review the uses of data on vegetation structure in ecosystem models, develop and analyze theoretical models to quantify model-data requirements, and describe recent progress using a mechanistic modeling approach utilizing a formal scaling method and data on vegetation structure to improve model predictions. Generally, both limited sampling and coarse resolution averaging lead to model initialization error, which in turn is propagated in subsequent model prediction uncertainty and error. In cases with representative sampling, sufficient resolution, and linear dynamics, errors in initialization tend to compensate at larger spatial scales. However, with inadequate sampling, overly coarse resolution data or models, and nonlinear dynamics, errors in initialization lead to prediction error. A robust model-data framework will require both models and data on vegetation structure sufficient to resolve important environmental gradients and tree-level heterogeneity in forest structure globally.

Patterns of seed bank and vegetation diversity along a tidal freshwater river.

PubMed

Elsey-Quirk, Tracy; Leck, Mary Allessio

2015-12-01

Species richness and diversity may increase with spatial scale related to increased area and heterogeneity of habitat. Yet, in bidirectional hydrologically connected tidal ecosystems, secondary dispersal via hydrochory has the potential to homogenize seed banks, and both life history characteristics and tolerances to environmental conditions influence the composition of plant communities. How species richness, diversity, and composition of seed banks and vegetation change along environmental gradients and at different spatial scales is not well understood. We explored the relationships of seed bank and vegetation diversity across 135 plots along a tidal freshwater river in the Delaware Estuary, USA. Species richness and diversity were partitioned across three hierarchical spatial scales: individual plots, transects perpendicular to the tidal channel, and river kilometers. Community structure was also examined as it related to distance from the tidal channel and location along the tidal river. Species richness was 89 in the seed bank and 54 in the vegetation. Species-area relationships revealed that species richness reached a near maximum asymptote inland (20 m from channel) for the seed bank and at the edge (0 m) for the vegetation. Rare occurrences of species in the seed bank and vegetation were greatest 5 m from the channel edge. As spatial scale increased, seed bank richness increased, associated with the progressive accumulation of species. Seed bank diversity, however, was maximized within small plot areas and along the river. Diversity of the vegetation was maximized locally due to the abundance of a few common species. These findings suggest that suites of common species contributed to high localized vegetation diversity, yet large spatial scales maximized the number and diversity of species in the seed bank and vegetation through rare encounters, as well as the complexity of the landscape. © 2015 Botanical Society of America.

Relating vegetation condition to grazing management systems in the central Keiskamma catchment, Eastern Cape Province, South Africa

NASA Astrophysics Data System (ADS)

Kakembo, Vincent; Ndou, Naledzani

2017-04-01

An investigation of the temporal changes in vegetation condition across the communal villages of the central Keiskamma catchment, Eastern Cape Province, in relation to local grazing management systems was conducted. Landsat TM images of 1984 and 1999, in conjunction with SPOT imagery of 2011 were used to assess the spatial trends in vegetation. Information regarding the functionality of local grazing management structures was obtained through structured interviews. Vegetation condition was related to grazing management systems using the logistic regression in Idrisi Selva remote sensing software. Analysis of vegetation condition trends revealed a consistent deterioration of vegetation condition in villages with weak grazing management systems. A statistically significant correlation between vegetation condition and grazing management systems was identified. High levels of vegetation degradation were associated with villages that did not adhere to sound grazing management practices. The introduction of another layer governance in the form of elected municipal committees weakened traditional village management structures. Strengthening traditional management committees should be the point of departure for vegetation restoration.

Assessing Anthropogenic Influence and Edge Effect Influence on Forested Riparian Buffer Spatial Configuration and Structure: An Example Using Lidar Remote Sensing Methods

NASA Astrophysics Data System (ADS)

Wasser, L. A.; Chasmer, L. E.

2012-12-01

Forested riparian buffers (FRB) perform numerous critical ecosystem services. However, globally, FRB spatial configuration and structure have been modified by anthropogenic development resulting in widespread ecological degradation as seen in the Gulf of Mexico and the Chesapeake Bay. Riparian corridors within developed areas are particularly vulnerable to disturbance given two edges - the naturally occurring stream edge and the matrix edge. Increased edge length predisposes riparian vegetation to "edge effects", characterized by modified physical and environmental conditions at the interface between the forested buffer and the adjacent landuse, or matrix and forest fragment degradation. The magnitude and distance of edge influence may be further influenced by adjacent landuse type and the width of the buffer corridor at any given location. There is a need to quantify riparian buffer spatial configuration and structure over broad geographic extents and within multiple riparian systems in support of ecologically sound management and landuse decisions. This study thus assesses the influence of varying landuse types (agriculture, suburban development and undeveloped) on forested riparian buffer 3-dimensional structure and spatial configuration using high resolution Light Detection and Ranging (LiDAR) data collected within a headwater watershed. Few studies have assessed riparian buffer structure and width contiguously for an entire watershed, an integral component of watershed planning and restoration efforts such as those conducted throughout the Chesapeake Bay. The objectives of the study are to 1) quantify differences in vegetation structure at the stream and matrix influenced riparian buffer edges, compared to the forested interior and 2) assess continuous patterns of changes in vegetation structure throughout the buffer corridor beginning at the matrix edge and ending at the stream within buffers a) of varying width and b) that are adjacent to varying landuse types. Results suggest that 1) the spatial configuration of riparian forests has a strong influence on forest structure compared to a weaker association with adjacent landuse type 2) developed landuse types are often associated with increased understory vegetation density 3) that riparian vegetation canopy cover is dense regardless of corridor width or adjacent landuse type and 4) the degree to which edge effects propagate into the buffer corridor is most influenced by corridor width. The study further demonstrates the utility of automated algorithms that sample lidar data in watershed-wide ecological analysis. Results suggest that landuse regulations should encourage wider buffers which will in turn support a greater range of ecosystem services including improved wildlife habitat, stream shading and detrital inputs.

Using repeat electrical resistivity surveys to assess heterogeneity in soil moisture dynamics under contrasting vegetation types

NASA Astrophysics Data System (ADS)

Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris

2018-04-01

As the relationship between vegetation and soil moisture is complex and reciprocal, there is a need to understand how spatial patterns in soil moisture influence the distribution of vegetation, and how the structure of vegetation canopies and root networks regulates the partitioning of precipitation. Spatial patterns of soil moisture are often difficult to visualise as usually, soil moisture is measured at point scales, and often difficult to extrapolate. Here, we address the difficulties in collecting large amounts of spatial soil moisture data through a study combining plot- and transect-scale electrical resistivity tomography (ERT) surveys to estimate soil moisture in a 3.2 km2 upland catchment in the Scottish Highlands. The aim was to assess the spatio-temporal variability in soil moisture under Scots pine forest (Pinus sylvestris) and heather moorland shrubs (Calluna vulgaris); the two dominant vegetation types in the Scottish Highlands. The study focussed on one year of fortnightly ERT surveys. The surveyed resistivity data was inverted and Archie's law was used to calculate volumetric soil moisture by estimating parameters and comparing against field measured data. Results showed that spatial soil moisture patterns were more heterogeneous in the forest site, as were patterns of wetting and drying, which can be linked to vegetation distribution and canopy structure. The heather site showed a less heterogeneous response to wetting and drying, reflecting the more uniform vegetation cover of the shrubs. Comparing soil moisture temporal variability during growing and non-growing seasons revealed further contrasts: under the heather there was little change in soil moisture during the growing season. Greatest changes in the forest were in areas where the trees were concentrated reflecting water uptake and canopy partitioning. Such differences have implications for climate and land use changes; increased forest cover can lead to greater spatial variability, greater growing season temporal variability, and reduced levels of soil moisture, whilst projected decreasing summer precipitation may alter the feedbacks between soil moisture and vegetation water use and increase growing season soil moisture deficits.

Effects of vegetation structure on soil carbon, nutrients and greenhouse gas exchange in a savannah ecosystem of Mount Kilimanjaro Region

NASA Astrophysics Data System (ADS)

Becker, J.

2015-12-01

The savannah biome is a hotspot for biodiversity and wildlife conservation in Africa and recently got in the focus of research on carbon sequestration. Savannah ecosystems are under strong pressure from climate and land-use change, especially around populous areas like the Mt. Kilimanjaro region. Savannah vegetation consists of grassland with isolated trees and is therefore characterized by high spatial variation of canopy cover, aboveground biomass and root structure. The canopy structure is a major regulator for soil ecological parameters and soil-atmospheric trace gas exchange (CO2, N2O, CH4) in water limited environments. The spatial distribution of these parameters and the connection between above and belowground processes are important to understand and predict ecosystem changes and estimate its vulnerability. Our objective was to determine spatial trends and changes of soil parameters and relate their variability to the vegetation structure. We chose three trees from each of the two most dominant species (Acacia nilotica and Balanites aegyptiaca) in our research area. For each tree, we selected transects with nine sampling points of the same relative distances to the stem. At these each sampling point a soil core was taken and separated in 0-10 cm and 10-30 cm depth. We measured soil carbon (C) and nitrogen (N) storage, microbial biomass C and N, Natural δ13C, soil respiration, available nutrients, pH, cation exchange capacity (CEC) as well as root biomass and -density, soil temperature and soil water content. Concentrations and stocks of C and N fractions, CEC and K+ decreased up to 50% outside the crown covered area. Microbial C:N ratio and CO2 efflux was about 30% higher outside the crown. This indicates N limitation and low C use efficiency in soil outside the crown area. We conclude that the spatial structure of aboveground biomass in savanna ecosystems leads to a spatial variance in nutrient limitation. Therefore, the capability of a savanna ecosystem to act as a C sink is directly and indirectly dependent on the vegetation structure.

Sensitivity to spatial and temporal scale and fire regime inputs in deriving fire regime condition class

Treesearch

Linda Tedrow; Wendel J. Hann

2015-01-01

The Fire Regime Condition Class (FRCC) is a composite departure measure that compares current vegetation structure and fire regime to historical reference conditions. FRCC is computed as the average of: 1) Vegetation departure (VDEP) and 2) Regime (frequency and severity) departure (RDEP). In addition to the FRCC rating, the Vegetation Condition Class (VCC) and Regime...

Considerations for Achieving Cross-Platform Point Cloud Data Fusion across Different Dryland Ecosystem Structural States

PubMed Central

Swetnam, Tyson L.; Gillan, Jeffrey K.; Sankey, Temuulen T.; McClaran, Mitchel P.; Nichols, Mary H.; Heilman, Philip; McVay, Jason

2018-01-01

Remotely sensing recent growth, herbivory, or disturbance of herbaceous and woody vegetation in dryland ecosystems requires high spatial resolution and multi-temporal depth. Three dimensional (3D) remote sensing technologies like lidar, and techniques like structure from motion (SfM) photogrammetry, each have strengths and weaknesses at detecting vegetation volume and extent, given the instrument's ground sample distance and ease of acquisition. Yet, a combination of platforms and techniques might provide solutions that overcome the weakness of a single platform. To explore the potential for combining platforms, we compared detection bias amongst two 3D remote sensing techniques (lidar and SfM) using three different platforms [ground-based, small unmanned aerial systems (sUAS), and manned aircraft]. We found aerial lidar to be more accurate for characterizing the bare earth (ground) in dense herbaceous vegetation than either terrestrial lidar or aerial SfM photogrammetry. Conversely, the manned aerial lidar did not detect grass and fine woody vegetation while the terrestrial lidar and high resolution near-distance (ground and sUAS) SfM photogrammetry detected these and were accurate. UAS SfM photogrammetry at lower spatial resolution under-estimated maximum heights in grass and shrubs. UAS and handheld SfM photogrammetry in near-distance high resolution collections had similar accuracy to terrestrial lidar for vegetation, but difficulty at measuring bare earth elevation beneath dense herbaceous cover. Combining point cloud data and derivatives (i.e., meshes and rasters) from two or more platforms allowed for more accurate measurement of herbaceous and woody vegetation (height and canopy cover) than any single technique alone. Availability and costs of manned aircraft lidar collection preclude high frequency repeatability but this is less limiting for terrestrial lidar, sUAS and handheld SfM. The post-processing of SfM photogrammetry data became the limiting factor at larger spatial scale and temporal repetition. Despite the utility of sUAS and handheld SfM for monitoring vegetation phenology and structure, their spatial extents are small relative to manned aircraft. PMID:29379511

Considerations for Achieving Cross-Platform Point Cloud Data Fusion across Different Dryland Ecosystem Structural States.

PubMed

Swetnam, Tyson L; Gillan, Jeffrey K; Sankey, Temuulen T; McClaran, Mitchel P; Nichols, Mary H; Heilman, Philip; McVay, Jason

2017-01-01

Remotely sensing recent growth, herbivory, or disturbance of herbaceous and woody vegetation in dryland ecosystems requires high spatial resolution and multi-temporal depth. Three dimensional (3D) remote sensing technologies like lidar, and techniques like structure from motion (SfM) photogrammetry, each have strengths and weaknesses at detecting vegetation volume and extent, given the instrument's ground sample distance and ease of acquisition. Yet, a combination of platforms and techniques might provide solutions that overcome the weakness of a single platform. To explore the potential for combining platforms, we compared detection bias amongst two 3D remote sensing techniques (lidar and SfM) using three different platforms [ground-based, small unmanned aerial systems (sUAS), and manned aircraft]. We found aerial lidar to be more accurate for characterizing the bare earth (ground) in dense herbaceous vegetation than either terrestrial lidar or aerial SfM photogrammetry. Conversely, the manned aerial lidar did not detect grass and fine woody vegetation while the terrestrial lidar and high resolution near-distance (ground and sUAS) SfM photogrammetry detected these and were accurate. UAS SfM photogrammetry at lower spatial resolution under-estimated maximum heights in grass and shrubs. UAS and handheld SfM photogrammetry in near-distance high resolution collections had similar accuracy to terrestrial lidar for vegetation, but difficulty at measuring bare earth elevation beneath dense herbaceous cover. Combining point cloud data and derivatives (i.e., meshes and rasters) from two or more platforms allowed for more accurate measurement of herbaceous and woody vegetation (height and canopy cover) than any single technique alone. Availability and costs of manned aircraft lidar collection preclude high frequency repeatability but this is less limiting for terrestrial lidar, sUAS and handheld SfM. The post-processing of SfM photogrammetry data became the limiting factor at larger spatial scale and temporal repetition. Despite the utility of sUAS and handheld SfM for monitoring vegetation phenology and structure, their spatial extents are small relative to manned aircraft.

Vegetation dynamics

Treesearch

Sammy L. King; Terry J. Antrobus; Sarah Billups

2000-01-01

A disturbance can be defined as "any relatively discrete event in time that disrupts ecosystem, community, or population structure and changes resources, substrate availability, or the physical environment" (Pickett and White 1985). Vegetation dynamics are a function of the temporal and spatial patterns of the disturbance regime. Natural disturbance regimes...

Multiangular Contributions for Discriminate Seasonal Structural Changes in the Amazon Rainforest Using MODIS MAIAC Data

NASA Astrophysics Data System (ADS)

Moura, Y. M.; Hilker, T.; Galvão, L. S.; Santos, J. R.; Lyapustin, A.; Sousa, C. H. R. D.; McAdam, E.

2014-12-01

The sensitivity of the Amazon rainforests to climate change has received great attention by the scientific community due to the important role that this vegetation plays in the global carbon, water and energy cycle. The spatial and temporal variability of tropical forests across Amazonia, and their phenological, ecological and edaphic cycles are still poorly understood. The objective of this work was to infer seasonal and spatial variability of forest structure in the Brazilian Amazon based on anisotropy of multi-angle satellite observations. We used observations from the Moderate Resolution Imaging Spectroradiometer (MODIS/Terra and Aqua) processed by a new Multi-Angle Implementation Atmospheric Correction Algorithm (MAIAC) to investigate how multi-angular spectral response from satellite imagery can be used to analyze structural variability of Amazon rainforests. We calculated differences acquired from forward and backscatter reflectance by modeling the bi-directional reflectance distribution function to infer seasonal and spatial changes in vegetation structure. Changes in anisotropy were larger during the dry season than during the wet season, suggesting intra-annual changes in vegetation structure and density. However, there were marked differences in timing and amplitude depending on forest type. For instance differences between reflectance hotspot and darkspot showed more anisotropy in the open Ombrophilous forest than in the dense Ombrophilous forest. Our results show that multi-angle data can be useful for analyzing structural differences in various forest types and for discriminating different seasonal effects within the Amazon basin. Also, multi-angle data could help solve uncertainties about sensitivity of different tropical forest types to light versus rainfall. In conclusion, multi-angular information, as expressed by the anisotropy of spectral reflectance, may complement conventional studies and provide significant improvements over approaches that are based on vegetation indices alone.

Quantifying spatial patterns in the Yakama Nation Tribal Forest and Okanogan-Wenatchee National Forest to assess forest health

NASA Astrophysics Data System (ADS)

Wilder, T. F.

2013-05-01

Over the past century western United States have experienced drastic anthropogenic land use change from practices such as agriculture, fire exclusion, and timber harvesting. These changes have complex social, cultural, economic, and ecological interactions and consequences. This research studied landscapes patterns of watersheds with similar LANDFIRE potential vegetation in the Southern Washington Cascades physiographic province, within the Yakama Nation Tribal Forest (YTF) and Okanogan-Wenatchee National Forest, Naches Ranger District (NRD). In the selected watersheds, vegetation-mapping units were delineated and populated based on physiognomy of homogeneous areas of vegetative composition and structure using high-resolution aerial photos. Cover types and structural classes were derived from the raw, photo-interpreted vegetation attributes for individual vegetation mapping units and served as individual and composite response variables to quantify and assess spatial patterns and forest health conditions between the two ownerships. Structural classes in both the NRD and YTF were spatially clustered (Z-score 3.1, p-value 0.01; Z-score 2.3, p-value 0.02, respectively), however, ownership and logging type both explained a significant amount of variance in structural class composition. Based on FRAGSTATS landscape metrics, structural classes in the NRD displayed greater clustering and fragmentation with lower interspersion relative to the YTF. The NRD landscape was comprised of 47.4% understory reinitiation structural class type and associated high FRAGASTAT class metrics demonstrated high aggregation with moderate interspersion. Stem exclusion open canopy displayed the greatest dispersal of structural class types throughout the NRD, but adjacencies were correlated to other class types. In the YTF, stem exclusion open canopy comprised 37.7% of the landscape and displayed a high degree of aggregation and interspersion about clusters throughout the YTF. Composite cover type-structural class spatial autocorrelation was clustered in the NRD (Z-score 5.1, p-value 0.01), while the YTF exhibited a random spatial pattern. After accounting for location effects, logging type was the most significant factor explaining variation in composite cover-structure composition. FRAGSTATS landscape metrics identified composite cover-structure classes in the NRD displayed greater aggregation and fragmentation with lower interspersion relative to the YTF. The NRD landscape was comprised of 30.5% Pinus ponderosa-understory reinitiation and associated class metrics demonstrated a high degree of aggregation and fragmentation with low interspersion. Pinus ponderosa-stem exclusion open canopy comprised 24.6% of the YTF landscape and associated class metrics displayed moderate aggregation and fragmentation with high interspersion. A discussion integrating the results and existing relevant literature was indited to assess management regime influences on landscape patterns and, in turn, forest health attributes. This dialog is in provision of enhancing collaboration to optimize forest-health restoration activities across ownerships throughout the study area.

High-spatial resolution multispectral and panchromatic satellite imagery for mapping perennial desert plants

NASA Astrophysics Data System (ADS)

Alsharrah, Saad A.; Bruce, David A.; Bouabid, Rachid; Somenahalli, Sekhar; Corcoran, Paul A.

2015-10-01

The use of remote sensing techniques to extract vegetation cover information for the assessment and monitoring of land degradation in arid environments has gained increased interest in recent years. However, such a task can be challenging, especially for medium-spatial resolution satellite sensors, due to soil background effects and the distribution and structure of perennial desert vegetation. In this study, we utilised Pleiades high-spatial resolution, multispectral (2m) and panchromatic (0.5m) imagery and focused on mapping small shrubs and low-lying trees using three classification techniques: 1) vegetation indices (VI) threshold analysis, 2) pre-built object-oriented image analysis (OBIA), and 3) a developed vegetation shadow model (VSM). We evaluated the success of each approach using a root of the sum of the squares (RSS) metric, which incorporated field data as control and three error metrics relating to commission, omission, and percent cover. Results showed that optimum VI performers returned good vegetation cover estimates at certain thresholds, but failed to accurately map the distribution of the desert plants. Using the pre-built IMAGINE Objective OBIA approach, we improved the vegetation distribution mapping accuracy, but this came at the cost of over classification, similar to results of lowering VI thresholds. We further introduced the VSM which takes into account shadow for further refining vegetation cover classification derived from VI. The results showed significant improvements in vegetation cover and distribution accuracy compared to the other techniques. We argue that the VSM approach using high-spatial resolution imagery provides a more accurate representation of desert landscape vegetation and should be considered in assessments of desertification.

Influence of lidar, Landsat imagery, disturbance history, plot location accuracy, and plot size on accuracy of imputation maps of forest composition and structure

Treesearch

Harold S.J. Zald; Janet L. Ohmann; Heather M. Roberts; Matthew J. Gregory; Emilie B. Henderson; Robert J. McGaughey; Justin Braaten

2014-01-01

This study investigated how lidar-derived vegetation indices, disturbance history from Landsat time series (LTS) imagery, plot location accuracy, and plot size influenced accuracy of statistical spatial models (nearest-neighbor imputation maps) of forest vegetation composition and structure. Nearest-neighbor (NN) imputation maps were developed for 539,000 ha in the...

Remote sensing of Sonoran Desert vegetation structure and phenology with ground-based LiDAR

USGS Publications Warehouse

Sankey, Joel B.; Munson, Seth M.; Webb, Robert H.; Wallace, Cynthia S.A.; Duran, Cesar M.

2015-01-01

Long-term vegetation monitoring efforts have become increasingly important for understanding ecosystem response to global change. Many traditional methods for monitoring can be infrequent and limited in scope. Ground-based LiDAR is one remote sensing method that offers a clear advancement to monitor vegetation dynamics at high spatial and temporal resolution. We determined the effectiveness of LiDAR to detect intra-annual variability in vegetation structure at a long-term Sonoran Desert monitoring plot dominated by cacti, deciduous and evergreen shrubs. Monthly repeat LiDAR scans of perennial plant canopies over the course of one year had high precision. LiDAR measurements of canopy height and area were accurate with respect to total station survey measurements of individual plants. We found an increase in the number of LiDAR vegetation returns following the wet North American Monsoon season. This intra-annual variability in vegetation structure detected by LiDAR was attributable to a drought deciduous shrub Ambrosia deltoidea, whereas the evergreen shrub Larrea tridentata and cactus Opuntia engelmannii had low variability. Benefits of using LiDAR over traditional methods to census desert plants are more rapid, consistent, and cost-effective data acquisition in a high-resolution, 3-dimensional context. We conclude that repeat LiDAR measurements can be an effective method for documenting ecosystem response to desert climatology and drought over short time intervals and at detailed-local spatial scale.

Green spaces are not all the same for the provision of air purification and climate regulation services: The case of urban parks.

PubMed

Vieira, Joana; Matos, Paula; Mexia, Teresa; Silva, Patrícia; Lopes, Nuno; Freitas, Catarina; Correia, Otília; Santos-Reis, Margarida; Branquinho, Cristina; Pinho, Pedro

2018-01-01

The growing human population concentrated in urban areas lead to the increase of road traffic and artificial areas, consequently enhancing air pollution and urban heat island effects, among others. These environmental changes affect citizen's health, causing a high number of premature deaths, with considerable social and economic costs. Nature-based solutions are essential to ameliorate those impacts in urban areas. While the mere presence of urban green spaces is pointed as an overarching solution, the relative importance of specific vegetation structure, composition and management to improve the ecosystem services of air purification and climate regulation are overlooked. This avoids the establishment of optimized planning and management procedures for urban green spaces with high spatial resolution and detail. Our aim was to understand the relative contribution of vegetation structure, composition and management for the provision of ecosystem services of air purification and climate regulation in urban green spaces, in particular the case of urban parks. This work was done in a large urban park with different types of vegetation surrounded by urban areas. As indicators of microclimatic effects and of air pollution levels we selected different metrics: lichen diversity and pollutants accumulation in lichens. Among lichen diversity, functional traits related to nutrient and water requirements were used as surrogates of the capacity of vegetation to filter air pollution and to regulate climate, and provide air purification and climate regulation ecosystem services, respectively. This was also obtained with very high spatial resolution which allows detailed spatial planning for optimization of ecosystem services. We found that vegetation type characterized by a more complex structure (trees, shrubs and herbaceous layers) and by the absence of management (pruning, irrigation and fertilization) had a higher capacity to provide the ecosystems services of air purification and climate regulation. By contrast, lawns, which have a less complex structure and are highly managed, were associated to a lower capacity to provide these services. Tree plantations showed an intermediate effect between the other two types of vegetation. Thus, vegetation structure, composition and management are important to optimize green spaces capacity to purify air and regulate climate. Taking this into account green spaces can be managed at high spatial resolutions to optimize these ecosystem services in urban areas and contribute to improve human well-being. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Spatial vegetation patterns and neighborhood competition among woody plants in an East African savanna.

PubMed

Dohn, Justin; Augustine, David J; Hanan, Niall P; Ratnam, Jayashree; Sankaran, Mahesh

2017-02-01

The majority of research on savanna vegetation dynamics has focused on the coexistence of woody and herbaceous vegetation. Interactions among woody plants in savannas are relatively poorly understood. We present data from a 10-yr longitudinal study of spatially explicit growth patterns of woody vegetation in an East African savanna following exclusion of large herbivores and in the absence of fire. We examined plant spatial patterns and quantified the degree of competition among woody individuals. Woody plants in this semiarid savanna exhibit strongly clumped spatial distributions at scales of 1-5 m. However, analysis of woody plant growth rates relative to their conspecific and heterospecific neighbors revealed evidence for strong competitive interactions at neighborhood scales of up to 5 m for most woody plant species. Thus, woody plants were aggregated in clumps despite significantly decreased growth rates in close proximity to neighbors, indicating that the spatial distribution of woody plants in this region depends on dispersal and establishment processes rather than on competitive, density-dependent mortality. However, our documentation of suppressive effects of woody plants on neighbors also suggests a potentially important role for tree-tree competition in controlling vegetation structure and indicates that the balanced-competition hypothesis may contribute to well-known patterns in maximum tree cover across rainfall gradients in Africa. © 2016 by the Ecological Society of America.

Spatial fuel data products of the LANDFIRE Project

USGS Publications Warehouse

Reeves, M.C.; Ryan, K.C.; Rollins, M.G.; Thompson, T.G.

2009-01-01

The Landscape Fire and Resource Management Planning Tools (LANDFIRE) Project is mapping wildland fuels, vegetation, and fire regime characteristics across the United States. The LANDFIRE project is unique because of its national scope, creating an integrated product suite at 30-m spatial resolution and complete spatial coverage of all lands within the 50 states. Here we describe development of the LANDFIRE wildland fuels data layers for the conterminous 48 states: surface fire behavior fuel models, canopy bulk density, canopy base height, canopy cover, and canopy height. Surface fire behavior fuel models are mapped by developing crosswalks to vegetation structure and composition created by LANDFIRE. Canopy fuels are mapped using regression trees relating field-referenced estimates of canopy base height and canopy bulk density to satellite imagery, biophysical gradients and vegetation structure and composition data. Here we focus on the methods and data used to create the fuel data products, discuss problems encountered with the data, provide an accuracy assessment, demonstrate recent use of the data during the 2007 fire season, and discuss ideas for updating, maintaining and improving LANDFIRE fuel data products.

Quantifying vegetation distribution and structure using high resolution drone-based structure-from-motion photogrammetry

NASA Astrophysics Data System (ADS)

Zhang, J.; Okin, G.

2017-12-01

Vegetation is one of the most important driving factors of different ecosystem processes in drylands. The structure of vegetation controls the spatial distribution of moisture and heat in the canopy and the surrounding area. Also, the structure of vegetation influences both airflow and boundary layer resistance above the land surface. Multispectral satellite remote sensing has been widely used to monitor vegetation coverage and its change; however, it can only capture 2D images, which do not contain the vertical information of vegetation. In situ observation uses different methods to measure the structure of vegetation, and their results are accurate; however, these methods are laborious and time-consuming, and susceptible to undersampling in spatial heterogeneity. Drylands are sparsely covered by short plants, which allows the drone fly at a relatively low height to obtain ultra-high resolution images. Structure-from-motion (SfM) is a photogrammetric method that was proved to produce 3D model based on 2D images. Drone-based remote sensing can obtain the multiangle images for one object, which can be used to constructed 3D models of vegetation in drylands. Using these images detected by the drone, the orthomosaics and digital surface model (DSM) can be built. In this study, the drone-based remote sensing was conducted in Jornada Basin, New Mexico, in the spring of 2016 and 2017, and three derived vegetation parameters (i.e., canopy size, bare soil gap size, and plant height) were compared with those obtained with field measurement. The correlation coefficient of canopy size, bare soil gap size, and plant height between drone images and field data are 0.91, 0.96, and 0.84, respectively. The two-year averaged root-mean-square error (RMSE) of canopy size, bare soil gap size, and plant height between drone images and field data are 0.61 m, 1.21 m, and 0.25 cm, respectively. The two-year averaged measure error (ME) of canopy size, bare soil gap size, and plant height between drone images and field data are 0.02 m, -0.03, and -0.1 m, respectively. These results indicate a good agreement between drone-based remote sensing and field measurement.

Hydrological networks and associated topographic variation as templates for the spatial organization of tropical forest vegetation.

PubMed

Detto, Matteo; Muller-Landau, Helene C; Mascaro, Joseph; Asner, Gregory P

2013-01-01

An understanding of the spatial variability in tropical forest structure and biomass, and the mechanisms that underpin this variability, is critical for designing, interpreting, and upscaling field studies for regional carbon inventories. We investigated the spatial structure of tropical forest vegetation and its relationship to the hydrological network and associated topographic structure across spatial scales of 10-1000 m using high-resolution maps of LiDAR-derived mean canopy profile height (MCH) and elevation for 4930 ha of tropical forest in central Panama. MCH was strongly associated with the hydrological network: canopy height was highest in areas of positive convexity (valleys, depressions) close to channels draining 1 ha or more. Average MCH declined strongly with decreasing convexity (transition to ridges, hilltops) and increasing distance from the nearest channel. Spectral analysis, performed with wavelet decomposition, showed that the variance in MCH had fractal similarity at scales of ∼30-600 m, and was strongly associated with variation in elevation, with peak correlations at scales of ∼250 m. Whereas previous studies of topographic correlates of tropical forest structure conducted analyses at just one or a few spatial grains, our study found that correlations were strongly scale-dependent. Multi-scale analyses of correlations of MCH with slope, aspect, curvature, and Laplacian convexity found that MCH was most strongly related to convexity measured at scales of 20-300 m, a topographic variable that is a good proxy for position with respect to the hydrological network. Overall, our results support the idea that, even in these mesic forests, hydrological networks and associated topographical variation serve as templates upon which vegetation is organized over specific ranges of scales. These findings constitute an important step towards a mechanistic understanding of these patterns, and can guide upscaling and downscaling.

Assessing the effects of land use spatial structure on urban heat islands using HJ-1B remote sensing imagery in Wuhan, China

NASA Astrophysics Data System (ADS)

Wu, Hao; Ye, Lu-Ping; Shi, Wen-Zhong; Clarke, Keith C.

2014-10-01

Urban heat islands (UHIs) have attracted attention around the world because they profoundly affect biological diversity and human life. Assessing the effects of the spatial structure of land use on UHIs is essential to better understanding and improving the ecological consequences of urbanization. This paper presents the radius fractal dimension to quantify the spatial variation of different land use types around the hot centers. By integrating remote sensing images from the newly launched HJ-1B satellite system, vegetation indexes, landscape metrics and fractal dimension, the effects of land use patterns on the urban thermal environment in Wuhan were comprehensively explored. The vegetation indexes and landscape metrics of the HJ-1B and other remote sensing satellites were compared and analyzed to validate the performance of the HJ-1B. The results have showed that land surface temperature (LST) is negatively related to only positive normalized difference vegetation index (NDVI) but to Fv across the entire range of values, which indicates that fractional vegetation (Fv) is an appropriate predictor of LST more than NDVI in forest areas. Furthermore, the mean LST is highly correlated with four class-based metrics and three landscape-based metrics, which suggests that the landscape composition and the spatial configuration both influence UHIs. All of them demonstrate that the HJ-1B satellite has a comparable capacity for UHI studies as other commonly used remote sensing satellites. The results of the fractal analysis show that the density of built-up areas sharply decreases from the hot centers to the edges of these areas, while the densities of water, forest and cropland increase. These relationships reveal that water, like forest and cropland, has a significant effect in mitigating UHIs in Wuhan due to its large spatial extent and homogeneous spatial distribution. These findings not only confirm the applicability and effectiveness of the HJ-1B satellite system for studying UHIs but also reveal the impacts of the spatial structure of land use on UHIs, which is helpful for improving the planning and management of the urban environment.

Estimating the relationship between urban 3D morphology and land surface temperature using airborne LiDAR and Landsat-8 Thermal Infrared Sensor data

NASA Astrophysics Data System (ADS)

Lee, J. H.

2015-12-01

Urban forests are known for mitigating the urban heat island effect and heat-related health issues by reducing air and surface temperature. Beyond the amount of the canopy area, however, little is known what kind of spatial patterns and structures of urban forests best contributes to reducing temperatures and mitigating the urban heat effects. Previous studies attempted to find the relationship between the land surface temperature and various indicators of vegetation abundance using remote sensed data but the majority of those studies relied on two dimensional area based metrics, such as tree canopy cover, impervious surface area, and Normalized Differential Vegetation Index, etc. This study investigates the relationship between the three-dimensional spatial structure of urban forests and urban surface temperature focusing on vertical variance. We use a Landsat-8 Thermal Infrared Sensor image (acquired on July 24, 2014) to estimate the land surface temperature of the City of Sacramento, CA. We extract the height and volume of urban features (both vegetation and non-vegetation) using airborne LiDAR (Light Detection and Ranging) and high spatial resolution aerial imagery. Using regression analysis, we apply empirical approach to find the relationship between the land surface temperature and different sets of variables, which describe spatial patterns and structures of various urban features including trees. Our analysis demonstrates that incorporating vertical variance parameters improve the accuracy of the model. The results of the study suggest urban tree planting is an effective and viable solution to mitigate urban heat by increasing the variance of urban surface as well as evaporative cooling effect.

Habitat fragmentation effects on the orchid bee communities in remnant forests of southeastern Brazil.

PubMed

Knoll, Fátima do Rosário Naschenveng; Penatti, N C

2012-10-01

The effect of habitat fragmentation on the structure of orchid bee communities was analyzed by the investigation of the existence of a spatial structure in the richness and abundance of Euglossini species and by determining the relationship between these data and environmental factors. The surveys were carried out in four different forest fragments and one university campus. Richness, abundance, and diversity of species were analyzed in relation to abiotic (size of the area, extent of the perimeter, perimeter/area ratio, and shape index) and biotic characteristics (vegetation index of the fragment and of the matrix of each of the locations studied). We observed a highly significant positive correlation between the diversity index and the vegetation index of the fragment, landscape and shape index. Our analysis demonstrated that the observed variation could be explained mainly by the vegetation index and the size of the fragment. Variations in relative abundance showed a tendency toward an aggregated spatial distribution between the fragments studied, as well as between the sampling stations within the same habitat, demonstrating the existence of a spatial structure on a small scale in the populations of Euglossini. This distribution will determine the composition of species that coexist in the area after fragmentation. These data help in understanding the differences and similarities in the structure of communities of Euglossini resulting from forest fragmentation.

Four millennia of woodland structure and dynamics at the Arctic treeline of eastern Canada.

PubMed

Auger, Sarah; Payette, Serge

2010-05-01

Paleoecological analysis using complementary indicators of vegetation and soil can provide spatially explicit information on ecological processes influencing trajectories of long-term ecosystem change. Here we document the structure and dynamics of an old-growth woodland before and after its inception 1000 years ago. We infer vegetation and soil characteristics from size and age distributions of black spruce (Picea mariana (Mill.) B.S.P.), soil properties, plant fossils, and paleosols. Radiocarbon ages of charcoal on the ground and in the soil indicate that the fire return interval was approximately 300 years between 2750 and 1000 cal. yr BP. No fire evidence was found before and after this period despite the presence of spruce since 4200 cal. yr BP. The size structures of living and dead spruce suggest that the woodland is in equilibrium with present climate in absence of fire. Tree establishment and mortality occurred regularly since the last fire event around 950 cal. yr BP. Both layering and occasional seeding have contributed to stabilize the spatial distribution of spruce over the past 1000 years. Since initial afforestation, soil development has been homogenized by the changing spatial distribution of spruce following each fire. We conclude that the history of the woodland is characterized by vegetation shifts associated with fire and soil disturbances and by millennial-scale maintenance of the woodland's structure despite changing climatic conditions.

Linking vegetation structure, function and physiology through spectroscopic remote sensing

NASA Astrophysics Data System (ADS)

Serbin, S.; Singh, A.; Couture, J. J.; Shiklomanov, A. N.; Rogers, A.; Desai, A. R.; Kruger, E. L.; Townsend, P. A.

2015-12-01

Terrestrial ecosystem process models require detailed information on ecosystem states and canopy properties to properly simulate the fluxes of carbon (C), water and energy from the land to the atmosphere and assess the vulnerability of ecosystems to perturbations. Current models fail to adequately capture the magnitude, spatial variation, and seasonality of terrestrial C uptake and storage, leading to significant uncertainties in the size and fate of the terrestrial C sink. By and large, these parameter and process uncertainties arise from inadequate spatial and temporal representation of plant traits, vegetation structure, and functioning. With increases in computational power and changes to model architecture and approaches, it is now possible for models to leverage detailed, data rich and spatially explicit descriptions of ecosystems to inform parameter distributions and trait tradeoffs. In this regard, spectroscopy and imaging spectroscopy data have been shown to be invaluable observational datasets to capture broad-scale spatial and, eventually, temporal dynamics in important vegetation properties. We illustrate the linkage of plant traits and spectral observations to supply key data constraints for model parameterization. These constraints can come either in the form of the raw spectroscopic data (reflectance, absorbtance) or physiological traits derived from spectroscopy. In this presentation we highlight our ongoing work to build ecological scaling relationships between critical vegetation characteristics and optical properties across diverse and complex canopies, including temperate broadleaf and conifer forests, Mediterranean vegetation, Arctic systems, and agriculture. We focus on work at the leaf, stand, and landscape scales, illustrating the importance of capturing the underlying variability in a range of parameters (including vertical variation within canopies) to enable more efficient scaling of traits related to functional diversity of ecosystems.

Spatial models reveal the microclimatic buffering capacity of old-growth forests

PubMed Central

Frey, Sarah J. K.; Hadley, Adam S.; Johnson, Sherri L.; Schulze, Mark; Jones, Julia A.; Betts, Matthew G.

2016-01-01

Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by combined effects of elevation, microtopography, and vegetation, but their relative effects at fine spatial scales are poorly known. We used boosted regression trees to model the spatial distribution of fine-scale, under-canopy air temperatures in mountainous terrain. Spatial models predicted observed independent test data well (r = 0.87). As expected, elevation strongly predicted temperatures, but vegetation and microtopography also exerted critical effects. Old-growth vegetation characteristics, measured using LiDAR (light detection and ranging), appeared to have an insulating effect; maximum spring monthly temperatures decreased by 2.5°C across the observed gradient in old-growth structure. These cooling effects across a gradient in forest structure are of similar magnitude to 50-year forecasts of the Intergovernmental Panel on Climate Change and therefore have the potential to mitigate climate warming at local scales. Management strategies to conserve old-growth characteristics and to curb current rates of primary forest loss could maintain microrefugia, enhancing biodiversity persistence in mountainous systems under climate warming. PMID:27152339

Spatial models reveal the microclimatic buffering capacity of old-growth forests.

PubMed

Frey, Sarah J K; Hadley, Adam S; Johnson, Sherri L; Schulze, Mark; Jones, Julia A; Betts, Matthew G

2016-04-01

Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by combined effects of elevation, microtopography, and vegetation, but their relative effects at fine spatial scales are poorly known. We used boosted regression trees to model the spatial distribution of fine-scale, under-canopy air temperatures in mountainous terrain. Spatial models predicted observed independent test data well (r = 0.87). As expected, elevation strongly predicted temperatures, but vegetation and microtopography also exerted critical effects. Old-growth vegetation characteristics, measured using LiDAR (light detection and ranging), appeared to have an insulating effect; maximum spring monthly temperatures decreased by 2.5°C across the observed gradient in old-growth structure. These cooling effects across a gradient in forest structure are of similar magnitude to 50-year forecasts of the Intergovernmental Panel on Climate Change and therefore have the potential to mitigate climate warming at local scales. Management strategies to conserve old-growth characteristics and to curb current rates of primary forest loss could maintain microrefugia, enhancing biodiversity persistence in mountainous systems under climate warming.

Remote sensing of vegetation structure using computer vision

NASA Astrophysics Data System (ADS)

Dandois, Jonathan P.

High-spatial resolution measurements of vegetation structure are needed for improving understanding of ecosystem carbon, water and nutrient dynamics, the response of ecosystems to a changing climate, and for biodiversity mapping and conservation, among many research areas. Our ability to make such measurements has been greatly enhanced by continuing developments in remote sensing technology---allowing researchers the ability to measure numerous forest traits at varying spatial and temporal scales and over large spatial extents with minimal to no field work, which is costly for large spatial areas or logistically difficult in some locations. Despite these advances, there remain several research challenges related to the methods by which three-dimensional (3D) and spectral datasets are joined (remote sensing fusion) and the availability and portability of systems for frequent data collections at small scale sampling locations. Recent advances in the areas of computer vision structure from motion (SFM) and consumer unmanned aerial systems (UAS) offer the potential to address these challenges by enabling repeatable measurements of vegetation structural and spectral traits at the scale of individual trees. However, the potential advances offered by computer vision remote sensing also present unique challenges and questions that need to be addressed before this approach can be used to improve understanding of forest ecosystems. For computer vision remote sensing to be a valuable tool for studying forests, bounding information about the characteristics of the data produced by the system will help researchers understand and interpret results in the context of the forest being studied and of other remote sensing techniques. This research advances understanding of how forest canopy and tree 3D structure and color are accurately measured by a relatively low-cost and portable computer vision personal remote sensing system: 'Ecosynth'. Recommendations are made for optimal conditions under which forest structure measurements should be obtained with UAS-SFM remote sensing. Ultimately remote sensing of vegetation by computer vision offers the potential to provide an 'ecologist's eye view', capturing not only canopy 3D and spectral properties, but also seeing the trees in the forest and the leaves on the trees.

Vegetation and Ecological Characteristics of Mixed-Conifer and Red Fir Forests at the Teakettle Experimental Forest

Treesearch

Malcolm North; Brian Oakley; Jiquan Chen; Heather Erickson; Andrew Gray; Antonio Izzo; Dale Johnson; Siyan Ma; Jim Marra; Marc Meyer; Kathryn Purcell; Tom Rambo; Dave Rizzo; Brent Roath; Tim Schowalter

2002-01-01

Detailed analysis of mixed-conifer and red fir forests were made from extensive, large vegetation sampling, systematically conducted throughout the Teakettle Experimental Forest. Mixed conifer is characterized by distinct patch conditions of closed-canopy tree clusters, persistent gaps and shrub thickets. This heterogeneous spatial structure provides contrasting...

Integrated modeling of long-term vegetation and hydrologic dynamics in Rocky Mountain watersheds

Treesearch

Robert Steven Ahl

2007-01-01

Changes in forest structure resulting from natural disturbances, or managed treatments, can have negative and long lasting impacts on water resources. To facilitate integrated management of forest and water resources, a System for Long-Term Integrated Management Modeling (SLIMM) was developed. By combining two spatially explicit, continuous time models, vegetation...

The feasibility of using a universal Random Forest model to map tree height across different locations and vegetation types

NASA Astrophysics Data System (ADS)

Su, Y.; Guo, Q.; Jin, S.; Gao, S.; Hu, T.; Liu, J.; Xue, B. L.

2017-12-01

Tree height is an important forest structure parameter for understanding forest ecosystem and improving the accuracy of global carbon stock quantification. Light detection and ranging (LiDAR) can provide accurate tree height measurements, but its use in large-scale tree height mapping is limited by the spatial availability. Random Forest (RF) has been one of the most commonly used algorithms for mapping large-scale tree height through the fusion of LiDAR and other remotely sensed datasets. However, how the variances in vegetation types, geolocations and spatial scales of different study sites influence the RF results is still a question that needs to be addressed. In this study, we selected 16 study sites across four vegetation types in United States (U.S.) fully covered by airborne LiDAR data, and the area of each site was 100 km2. The LiDAR-derived canopy height models (CHMs) were used as the ground truth to train the RF algorithm to predict canopy height from other remotely sensed variables, such as Landsat TM imagery, terrain information and climate surfaces. To address the abovementioned question, 22 models were run under different combinations of vegetation types, geolocations and spatial scales. The results show that the RF model trained at one specific location or vegetation type cannot be used to predict tree height in other locations or vegetation types. However, by training the RF model using samples from all locations and vegetation types, a universal model can be achieved for predicting canopy height across different locations and vegetation types. Moreover, the number of training samples and the targeted spatial resolution of the canopy height product have noticeable influence on the RF prediction accuracy.

Potential and Limitations of Low-Cost Unmanned Aerial Systems for Monitoring Altitudinal Vegetation Phenology in the Tropics

NASA Astrophysics Data System (ADS)

Silva, T. S. F.; Torres, R. S.; Morellato, P.

2017-12-01

Vegetation phenology is a key component of ecosystem function and biogeochemical cycling, and highly susceptible to climatic change. Phenological knowledge in the tropics is limited by lack of monitoring, traditionally done by laborious direct observation. Ground-based digital cameras can automate daily observations, but also offer limited spatial coverage. Imaging by low-cost Unmanned Aerial Systems (UAS) combines the fine resolution of ground-based methods with and unprecedented capability for spatial coverage, but challenges remain in producing color-consistent multitemporal images. We evaluated the applicability of multitemporal UAS imaging to monitor phenology in tropical altitudinal grasslands and forests, answering: 1) Can very-high resolution aerial photography from conventional digital cameras be used to reliably monitor vegetative and reproductive phenology? 2) How is UAS monitoring affected by changes in illumination and by sensor physical limitations? We flew imaging missions monthly from Feb-16 to Feb-17, using a UAS equipped with an RGB Canon SX260 camera. Flights were carried between 10am and 4pm, at 120-150m a.g.l., yielding 5-10cm spatial resolution. To compensate illumination changes caused by time of day, season and cloud cover, calibration was attempted using reference targets and empirical models, as well as color space transformations. For vegetative phenological monitoring, multitemporal response was severely affected by changes in illumination conditions, strongly confounding the phenological signal. These variations could not be adequately corrected through calibration due to sensor limitations. For reproductive phenology, the very-high resolution of the acquired imagery allowed discrimination of individual reproductive structures for some species, and its stark colorimetric differences to vegetative structures allowed detection of the reproductive timing on the HSV color space, despite illumination effects. We conclude that reliable vegetative phenology monitoring may exceed the capabilities of consumer cameras, but reproductive phenology can be successfully monitored for species with conspicuous reproductive structures. Further research is being conducted to improve calibration methods and information extraction through machine learning.

Development and assessment of 30-meter pine density maps for landscape-level modeling of mountain pine beetle dynamics

Treesearch

Benjamin A. Crabb; James A. Powell; Barbara J. Bentz

2012-01-01

Forecasting spatial patterns of mountain pine beetle (MPB) population success requires spatially explicit information on host pine distribution. We developed a means of producing spatially explicit datasets of pine density at 30-m resolution using existing geospatial datasets of vegetation composition and structure. Because our ultimate goal is to model MPB population...

Analysis of Alaskan burn severity patterns using remotely sensed data

USGS Publications Warehouse

Duffy, P.A.; Epting, J.; Graham, J.M.; Rupp, T.S.; McGuire, A.D.

2007-01-01

Wildland fire is the dominant large-scale disturbance mechanism in the Alaskan boreal forest, and it strongly influences forest structure and function. In this research, patterns of burn severity in the Alaskan boreal forest are characterised using 24 fires. First, the relationship between burn severity and area burned is quantified using a linear regression. Second, the spatial correlation of burn severity as a function of topography is modelled using a variogram analysis. Finally, the relationship between vegetation type and spatial patterns of burn severity is quantified using linear models where variograms account for spatial correlation. These results show that: 1) average burn severity increases with the natural logarithm of the area of the wildfire, 2) burn severity is more variable in topographically complex landscapes than in flat landscapes, and 3) there is a significant relationship between burn severity and vegetation type in flat landscapes but not in topographically complex landscapes. These results strengthen the argument that differential flammability of vegetation exists in some boreal landscapes of Alaska. Additionally, these results suggest that through feedbacks between vegetation and burn severity, the distribution of forest vegetation through time is likely more stable in flat terrain than it is in areas with more complex topography. ?? IAWF 2007.

Rapid Characterisation of Vegetation Structure to Predict Refugia and Climate Change Impacts across a Global Biodiversity Hotspot

PubMed Central

Schut, Antonius G. T.; Wardell-Johnson, Grant W.; Yates, Colin J.; Keppel, Gunnar; Baran, Ireneusz; Franklin, Steven E.; Hopper, Stephen D.; Van Niel, Kimberley P.; Mucina, Ladislav; Byrne, Margaret

2014-01-01

Identification of refugia is an increasingly important adaptation strategy in conservation planning under rapid anthropogenic climate change. Granite outcrops (GOs) provide extraordinary diversity, including a wide range of taxa, vegetation types and habitats in the Southwest Australian Floristic Region (SWAFR). However, poor characterization of GOs limits the capacity of conservation planning for refugia under climate change. A novel means for the rapid identification of potential refugia is presented, based on the assessment of local-scale environment and vegetation structure in a wider region. This approach was tested on GOs across the SWAFR. Airborne discrete return Light Detection And Ranging (LiDAR) data and Red Green and Blue (RGB) imagery were acquired. Vertical vegetation profiles were used to derive 54 structural classes. Structural vegetation types were described in three areas for supervised classification of a further 13 GOs across the region. Habitat descriptions based on 494 vegetation plots on and around these GOs were used to quantify relationships between environmental variables, ground cover and canopy height. The vegetation surrounding GOs is strongly related to structural vegetation types (Kappa = 0.8) and to its spatial context. Water gaining sites around GOs are characterized by taller and denser vegetation in all areas. The strong relationship between rainfall, soil-depth, and vegetation structure (R2 of 0.8–0.9) allowed comparisons of vegetation structure between current and future climate. Significant shifts in vegetation structural types were predicted and mapped for future climates. Water gaining areas below granite outcrops were identified as important putative refugia. A reduction in rainfall may be offset by the occurrence of deeper soil elsewhere on the outcrop. However, climate change interactions with fire and water table declines may render our conclusions conservative. The LiDAR-based mapping approach presented enables the integration of site-based biotic assessment with structural vegetation types for the rapid delineation and prioritization of key refugia. PMID:24416149

Rapid characterisation of vegetation structure to predict refugia and climate change impacts across a global biodiversity hotspot.

PubMed

Schut, Antonius G T; Wardell-Johnson, Grant W; Yates, Colin J; Keppel, Gunnar; Baran, Ireneusz; Franklin, Steven E; Hopper, Stephen D; Van Niel, Kimberley P; Mucina, Ladislav; Byrne, Margaret

2014-01-01

Identification of refugia is an increasingly important adaptation strategy in conservation planning under rapid anthropogenic climate change. Granite outcrops (GOs) provide extraordinary diversity, including a wide range of taxa, vegetation types and habitats in the Southwest Australian Floristic Region (SWAFR). However, poor characterization of GOs limits the capacity of conservation planning for refugia under climate change. A novel means for the rapid identification of potential refugia is presented, based on the assessment of local-scale environment and vegetation structure in a wider region. This approach was tested on GOs across the SWAFR. Airborne discrete return Light Detection And Ranging (LiDAR) data and Red Green and Blue (RGB) imagery were acquired. Vertical vegetation profiles were used to derive 54 structural classes. Structural vegetation types were described in three areas for supervised classification of a further 13 GOs across the region. Habitat descriptions based on 494 vegetation plots on and around these GOs were used to quantify relationships between environmental variables, ground cover and canopy height. The vegetation surrounding GOs is strongly related to structural vegetation types (Kappa = 0.8) and to its spatial context. Water gaining sites around GOs are characterized by taller and denser vegetation in all areas. The strong relationship between rainfall, soil-depth, and vegetation structure (R(2) of 0.8-0.9) allowed comparisons of vegetation structure between current and future climate. Significant shifts in vegetation structural types were predicted and mapped for future climates. Water gaining areas below granite outcrops were identified as important putative refugia. A reduction in rainfall may be offset by the occurrence of deeper soil elsewhere on the outcrop. However, climate change interactions with fire and water table declines may render our conclusions conservative. The LiDAR-based mapping approach presented enables the integration of site-based biotic assessment with structural vegetation types for the rapid delineation and prioritization of key refugia.

Large-scale impacts of herbivores on the structural diversity of African savannas

PubMed Central

Asner, Gregory P.; Levick, Shaun R.; Kennedy-Bowdoin, Ty; Knapp, David E.; Emerson, Ruth; Jacobson, James; Colgan, Matthew S.; Martin, Roberta E.

2009-01-01

African savannas are undergoing management intensification, and decision makers are increasingly challenged to balance the needs of large herbivore populations with the maintenance of vegetation and ecosystem diversity. Ensuring the sustainability of Africa's natural protected areas requires information on the efficacy of management decisions at large spatial scales, but often neither experimental treatments nor large-scale responses are available for analysis. Using a new airborne remote sensing system, we mapped the three-dimensional (3-D) structure of vegetation at a spatial resolution of 56 cm throughout 1640 ha of savanna after 6-, 22-, 35-, and 41-year exclusions of herbivores, as well as in unprotected areas, across Kruger National Park in South Africa. Areas in which herbivores were excluded over the short term (6 years) contained 38%–80% less bare ground compared with those that were exposed to mammalian herbivory. In the longer-term (> 22 years), the 3-D structure of woody vegetation differed significantly between protected and accessible landscapes, with up to 11-fold greater woody canopy cover in the areas without herbivores. Our maps revealed 2 scales of ecosystem response to herbivore consumption, one broadly mediated by geologic substrate and the other mediated by hillslope-scale variation in soil nutrient availability and moisture conditions. Our results are the first to quantitatively illustrate the extent to which herbivores can affect the 3-D structural diversity of vegetation across large savanna landscapes. PMID:19258457

Vegetation Patterns and Degradation Thresholds in the Mulga Landscapes of Australia

NASA Astrophysics Data System (ADS)

Azadi, Samira; Saco, Patricia; Moreno-de las Heras, Mariano; Willgoose, Garry

2017-04-01

Drylands are often characterised by a spatially heterogeneous vegetation cover forming mosaics of patches dense vegetation within bare soil. This 'patterned' or 'patchy' vegetation cover is sensitive to human pressures. Previous work suggests that within these landscapes there is a critical vegetation cover threshold below which the landscape functionality is lost. This threshold behaviour is tightly linked to the overland flow redistribution and an increase in hydrologic connectivity that induces loss of resources (i.e., leakiness). In fact, disturbances (such as wildfire, overgrazing or harvesting activities) can disrupt the spatial structure of vegetation, increase landscape hydrologic connectivity, trigger erosion and produce a substantial loss of water. All these effects affect ecosystem functionality. Here we present the results of exploring the impact of degradation processes induced by vegetation disturbances (mainly grazing) on ecosystem functionality and connectivity in semiarid landscapes with various types of vegetation patterns. The sites are carefully selected in Mulga landscapes bioregion (New South Wales, Queensland) and in sites of Northern Territory in Australia, which display similar vegetation characteristics but with different vegetation patterns and good quality rainfall information. The analysis of vegetation patterns is derived from high resolution remote sensing images (IKONOS, QuickBird, Pleiades). Using MODIS NDVI and local precipitation data, we compute rainfall use efficiency and precipitation marginal response in order to assess the ecosystem functionality. We use vegetation binary maps and digital elevation models to estimate mean Flowlength as an indicator of structural hydrologic connectivity. We compare the trends for several sites with varying vegetation patterns (i.e., banded versus spotted patterns). Our results show that disturbances increase hydrologic connectivity and suggest threshold behaviour that affects landscape functionality. Though this threshold behaviour is found in all sites, the plots in higher rainfall landscapes with banded vegetation patterns show evidence of higher resilience. We will also present some preliminary modelling results that complement this analysis and capture the coevolution of vegetation and landforms (erosion), leading to this type of threshold behaviour.

Ground-Vegetation Clutter Affects Phyllostomid Bat Assemblage Structure in Lowland Amazonian Forest.

PubMed

Marciente, Rodrigo; Bobrowiec, Paulo Estefano D; Magnusson, William E

2015-01-01

Vegetation clutter is a limiting factor for bats that forage near ground level, and may determine the distribution of species and guilds. However, many studies that evaluated the effects of vegetation clutter on bats have used qualitative descriptions rather than direct measurements of vegetation density. Moreover, few studies have evaluated the effect of vegetation clutter on a regional scale. Here, we evaluate the influence of the physical obstruction of vegetation on phyllostomid-bat assemblages along a 520 km transect in continuous Amazonian forest. We sampled bats using mist nets in eight localities during 80 nights (3840 net-hours) and estimated the ground-vegetation density with digital photographs. The total number of species, number of animalivorous species, total number of frugivorous species, number of understory frugivorous species, and abundance of canopy frugivorous bats were negatively associated with vegetation clutter. The bat assemblages showed a nested structure in relation to degree of clutter, with animalivorous and understory frugivorous bats distributed throughout the vegetation-clutter gradient, while canopy frugivores were restricted to sites with more open vegetation. The species distribution along the gradient of vegetation clutter was not closely associated with wing morphology, but aspect ratio and wing load differed between frugivores and animalivores. Vegetation structure plays an important role in structuring assemblages of the bats at the regional scale by increasing beta diversity between sites. Differences in foraging strategy and diet of the guilds seem to have contributed more to the spatial distribution of bats than the wing characteristics of the species alone.

Ecohydrology of an outbreak: Mountain pine beetle impacts trees in drier landscape positions first

Treesearch

Kendra E. Kaiser; Ryan E. Emanuel

2013-01-01

Vegetation pattern and landscape structure intersect to exert strong control over ecohydrological dynamics at the watershed scale. The hydrologic implications of vegetation disturbance (e.g. fire, disease) depend on the spatial pattern and form of environmental change. Here, we investigate this intersection at Tenderfoot Creek Experimental Forest (TCEF), Montana, with...

Fire Impacts on Mixed Pine-oak Forests Assessed with High Spatial Resolution Imagery, Imaging Spectroscopy, and LiDAR

NASA Astrophysics Data System (ADS)

Meng, R.; Wu, J.; Zhao, F. R.; Kathy, S. L.; Dennison, P. E.; Cook, B.; Hanavan, R. P.; Serbin, S.

2016-12-01

As a primary disturbance agent, fire significantly influences forest ecosystems, including the modification or resetting of vegetation composition and structure, which can then significantly impact landscape-scale plant function and carbon stocks. Most ecological processes associated with fire effects (e.g. tree damage, mortality, and vegetation recovery) display fine-scale, species specific responses but can also vary spatially within the boundary of the perturbation. For example, both oak and pine species are fire-adapted, but fire can still induce changes in composition, structure, and dominance in a mixed pine-oak forest, mainly because of their varying degrees of fire adaption. Evidence of post-fire shifts in dominance between oak and pine species has been documented in mixed pine-oak forests, but these processes have been poorly investigated in a spatially explicit manner. In addition, traditional field-based means of quantifying the response of partially damaged trees across space and time is logistically challenging. Here we show how combining high resolution satellite imagery (i.e. Worldview-2,WV-2) and airborne imaging spectroscopy and LiDAR (i.e. NASA Goddard's Lidar, Hyperspectral and Thermal airborne imager, G-LiHT) can be effectively used to remotely quantify spatial and temporal patterns of vegetation recovery following a top-killing fire that occurred in 2012 within mixed pine-oak forests in the Long Island Central Pine Barrens Region, New York. We explore the following questions: 1) what are the impacts of fire on species composition, dominance, plant health, and vertical structure; 2) what are the recovery trajectories of forest biomass, structure, and spectral properties for three years following the fire; and 3) to what extent can fire impacts be captured and characterized by multi-sensor remote sensing techniques from active and passive optical remote sensing.

Estimating riparian understory vegetation cover with beta regression and copula models

USGS Publications Warehouse

Eskelson, Bianca N.I.; Madsen, Lisa; Hagar, Joan C.; Temesgen, Hailemariam

2011-01-01

Understory vegetation communities are critical components of forest ecosystems. As a result, the importance of modeling understory vegetation characteristics in forested landscapes has become more apparent. Abundance measures such as shrub cover are bounded between 0 and 1, exhibit heteroscedastic error variance, and are often subject to spatial dependence. These distributional features tend to be ignored when shrub cover data are analyzed. The beta distribution has been used successfully to describe the frequency distribution of vegetation cover. Beta regression models ignoring spatial dependence (BR) and accounting for spatial dependence (BRdep) were used to estimate percent shrub cover as a function of topographic conditions and overstory vegetation structure in riparian zones in western Oregon. The BR models showed poor explanatory power (pseudo-R2 ≤ 0.34) but outperformed ordinary least-squares (OLS) and generalized least-squares (GLS) regression models with logit-transformed response in terms of mean square prediction error and absolute bias. We introduce a copula (COP) model that is based on the beta distribution and accounts for spatial dependence. A simulation study was designed to illustrate the effects of incorrectly assuming normality, equal variance, and spatial independence. It showed that BR, BRdep, and COP models provide unbiased parameter estimates, whereas OLS and GLS models result in slightly biased estimates for two of the three parameters. On the basis of the simulation study, 93–97% of the GLS, BRdep, and COP confidence intervals covered the true parameters, whereas OLS and BR only resulted in 84–88% coverage, which demonstrated the superiority of GLS, BRdep, and COP over OLS and BR models in providing standard errors for the parameter estimates in the presence of spatial dependence.

Dynamics of Vegetatin Indices in Tropical and Subtropical Savannas Defined by Ecoregions and Moderate Resolution Imaging Spectoradiometer (MODIS) Land Cover

NASA Technical Reports Server (NTRS)

Hill, Michael J.; Roman, Miguel O.; Schaaf, Crytal B.

2011-01-01

In this study, we explored the capacity of vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance products to characterize global savannas in Australia, Africa and South America. The savannas were spatially defined and subdivided using the World Wildlife Fund (WWF) global ecoregions and MODIS land cover classes. Average annual profiles of Normalized Difference Vegetation Index, shortwave infrared ratio (SWIR32), White Sky Albedo (WSA) and the Structural Scattering Index (SSI) were created. Metrics derived from average annual profiles of vegetation indices were used to classify savanna ecoregions. The response spaces between vegetation indices were used to examine the potential to derive structural and fractional cover measures. The ecoregions showed distinct temporal profiles and formed groups with similar structural properties, including higher levels of woody vegetation, similar forest savanna mixtures and similar grassland predominance. The potential benefits from the use of combinations of indices to characterize savannas are discussed.

The Dual Role of Vegetation as a Constraint on Mass and Energy Flux into the Critical Zone and as an Emergent Property of Geophysical Critical Zone Structure

NASA Astrophysics Data System (ADS)

Brooks, P. D.; Swetnam, T. L.; Barnard, H. R.; Singha, K.; Harpold, A.; Litvak, M. E.

2017-12-01

Spatial patterns in vegetation long have been used to scale both landsurface-atmosphere exchanges of water and carbon as well as to infer subsurface structure. These pursuits typical proceed in isolation and rarely do inferences gained from one community propagate to related efforts in another. Perhaps more importantly, vegetation often is treated as an emergent property of landscape-climate interactions rather than an active modifier of both critical zone structure and energy fluxes. We posit that vegetation structure and activity are under utilized as a tool towards understanding landscape evolution and present examples that begin to disentangle the role of vegetation as both an emergent property and an active control on critical zone structure and function. As climate change, population growth, and land use changes threaten water resources worldwide, the need for the new insights vegetation can provide becomes not just a basic science priority, but a pressing applied science question with clear societal importance. This presentation will provide an overview of recent efforts to address the dual role of vegetation in both modifying and reflecting critical zone structure in the western North American forests. For example, interactions between topography and stand scale vegetation structure influence both solar radiation and turbulence altering landscape scale partitioning of evaporation vs transpiration with major impacts of surface water supply. Similarly, interactions between topographic shading, lateral redistribution of plant available water, and subsurface storage create a mosaic of drought resistance and resilience across complex terrain. These complex interactions between geophysical and vegetation components of critical zone structure result in predictable patterns in catchment scale hydrologic partitioning within individual watersheds while simultaneously suggesting testable hypotheses for why catchments under similar climate regimes respond so differently to drought stress.

The landscape configuration of zoonotic transmission of Ebola virus disease in West and Central Africa: interaction between population density and vegetation cover.

PubMed

Walsh, Michael G; Haseeb, Ma

2015-01-01

Ebola virus disease (EVD) is an emerging infectious disease of zoonotic origin that has been responsible for high mortality and significant social disruption in West and Central Africa. Zoonotic transmission of EVD requires contact between susceptible human hosts and the reservoir species for Ebolaviruses, which are believed to be fruit bats. Nevertheless, features of the landscape that may facilitate such points of contact have not yet been adequately identified. Nor have spatial dependencies between zoonotic EVD transmission and landscape structures been delineated. This investigation sought to describe the spatial relationship between zoonotic EVD transmission events, or spillovers, and population density and vegetation cover. An inhomogeneous Poisson process model was fitted to all precisely geolocated zoonotic transmissions of EVD in West and Central Africa. Population density was strongly associated with spillover; however, there was significant interaction between population density and green vegetation cover. In areas of very low population density, increasing vegetation cover was associated with a decrease in risk of zoonotic transmission, but as population density increased in a given area, increasing vegetation cover was associated with increased risk of zoonotic transmission. This study showed that the spatial dependencies of Ebolavirus spillover were associated with the distribution of population density and vegetation cover in the landscape, even after controlling for climate and altitude. While this is an observational study, and thus precludes direct causal inference, the findings do highlight areas that may be at risk for zoonotic EVD transmission based on the spatial configuration of important features of the landscape.

Hydrological Networks and Associated Topographic Variation as Templates for the Spatial Organization of Tropical Forest Vegetation

PubMed Central

Detto, Matteo; Muller-Landau, Helene C.; Mascaro, Joseph; Asner, Gregory P.

2013-01-01

An understanding of the spatial variability in tropical forest structure and biomass, and the mechanisms that underpin this variability, is critical for designing, interpreting, and upscaling field studies for regional carbon inventories. We investigated the spatial structure of tropical forest vegetation and its relationship to the hydrological network and associated topographic structure across spatial scales of 10–1000 m using high-resolution maps of LiDAR-derived mean canopy profile height (MCH) and elevation for 4930 ha of tropical forest in central Panama. MCH was strongly associated with the hydrological network: canopy height was highest in areas of positive convexity (valleys, depressions) close to channels draining 1 ha or more. Average MCH declined strongly with decreasing convexity (transition to ridges, hilltops) and increasing distance from the nearest channel. Spectral analysis, performed with wavelet decomposition, showed that the variance in MCH had fractal similarity at scales of ∼30–600 m, and was strongly associated with variation in elevation, with peak correlations at scales of ∼250 m. Whereas previous studies of topographic correlates of tropical forest structure conducted analyses at just one or a few spatial grains, our study found that correlations were strongly scale-dependent. Multi-scale analyses of correlations of MCH with slope, aspect, curvature, and Laplacian convexity found that MCH was most strongly related to convexity measured at scales of 20–300 m, a topographic variable that is a good proxy for position with respect to the hydrological network. Overall, our results support the idea that, even in these mesic forests, hydrological networks and associated topographical variation serve as templates upon which vegetation is organized over specific ranges of scales. These findings constitute an important step towards a mechanistic understanding of these patterns, and can guide upscaling and downscaling. PMID:24204610

EPIC-Simulated and MODIS-Derived Leaf Area Index (LAI) Comparisons Across mMltiple Spatial Scales RSAD Oral Poster based session

EPA Science Inventory

Leaf Area Index (LAI) is an important parameter in assessing vegetation structure for characterizing forest canopies over large areas at broad spatial scales using satellite remote sensing data. However, satellite-derived LAI products can be limited by obstructed atmospheric cond...

Sentinel-1 backscatter sensitivity to vegetation dynamics at the field scale.

NASA Astrophysics Data System (ADS)

Vreugdenhil, Mariette; Eder, Alexander; Bauer-Marschallinger, Bernhard; Cao, Senmao; Naeimi, Vahid; Oismueller, Markus; Strauss, Peter; Wagner, Wolfgang

2017-04-01

Vegetation monitoring is pivotal to improve our understanding of the role vegetation dynamics play in the global carbon-, energy- and hydrological cycle. And with the increasing stress on food supply due to the growing world populating and changing climate, vegetation monitoring is of great importance in agricultural areas. By closely tracking crop conditions, droughts and subsequent crop losses could be mitigated. Sensors operating in the microwave domain are sensitive to several surface characteristics, including soil moisture and vegetation. Hence, spaceborne microwave remote sensing provides the means to monitor vegetation and soil conditions on different scales, ranging from field scale to global scale. However, it also presents a challenge since multiple combinations of soil and vegetation characteristics can lead to a similar measurement. Copernicus Sentinel-1 (S-1) is a series of two satellites, developed by the European Space Agency (ESA) , which carry C-band Synthetic Aperture Radars. The C-SAR sensors provide VV, HH, VH and HV backscatter at a 5 m by 20 m spatial resolution. The temporal revisit time of the two satellites is 3-6 days. With their unique capacity for temporally dense and spatially detailed data, the S-1 satellite series provides for the first time the chance to investigate vegetation dynamics at high temporal and spatial resolution. The aim of this study is to assess the sensitivity of Sentinel-1 backscatter to vegetation dynamics. The study is performed in the Hydrological Open Air Laboratory (HOAL), which is a 66 hectare large catchment located in Petzenkirchen, Austria. In the HOAL several vegetation parameters were measured during the course of the growing season (2016) at the overpass time of S-1a. Vegetation height was obtained ten times for the whole catchment, using georeferenced photos made by a motorized paraglider and a Land Surface Model. In addition, vegetation water content, Leaf Area Index and soil moisture were measured in four different cropfields. An in situ soil moisture network provides continuous soil moisture measurements at 31 locations within the catchment. Different polarizations and ratios thereof were calculated and compared, both spatially and temporally, to the in situ measurements of vegetation height, LAI, vegetation water content and soil moisture. Preliminary results show a clear spatial pattern in cross-polarized backscatter, which is related to different crop types. Time series analysis suggests that a ratio between cross- and co-polarized backscatter is affected by both vegetation water content and vegetation structure. This presentation will provide a comprehensive assessment of Sentinel-1's capability for monitoring of vegetation over croplands, using in situ reference data obtained over a full growing season.

Effects of a large wildfire on vegetation structure in a variable fire mosaic.

PubMed

Foster, C N; Barton, P S; Robinson, N M; MacGregor, C I; Lindenmayer, D B

2017-12-01

Management guidelines for many fire-prone ecosystems highlight the importance of maintaining a variable mosaic of fire histories for biodiversity conservation. Managers are encouraged to aim for fire mosaics that are temporally and spatially dynamic, include all successional states of vegetation, and also include variation in the underlying "invisible mosaic" of past fire frequencies, severities, and fire return intervals. However, establishing and maintaining variable mosaics in contemporary landscapes is subject to many challenges, one of which is deciding how the fire mosaic should be managed following the occurrence of large, unplanned wildfires. A key consideration for this decision is the extent to which the effects of previous fire history on vegetation and habitats persist after major wildfires, but this topic has rarely been investigated empirically. In this study, we tested to what extent a large wildfire interacted with previous fire history to affect the structure of forest, woodland, and heath vegetation in Booderee National Park in southeastern Australia. In 2003, a summer wildfire burned 49.5% of the park, increasing the extent of recently burned vegetation (<10 yr post-fire) to more than 72% of the park area. We tracked the recovery of vegetation structure for nine years following the wildfire and found that the strength and persistence of fire effects differed substantially between vegetation types. Vegetation structure was modified by wildfire in forest, woodland, and heath vegetation, but among-site variability in vegetation structure was reduced only by severe fire in woodland vegetation. There also were persistent legacy effects of the previous fire regime on some attributes of vegetation structure including forest ground and understorey cover, and woodland midstorey and overstorey cover. For example, woodland midstorey cover was greater on sites with higher fire frequency, irrespective of the severity of the 2003 wildfire. Our results show that even after a large, severe wildfire, underlying fire histories can contribute substantially to variation in vegetation structure. This highlights the importance of ensuring that efforts to reinstate variation in vegetation fire age after large wildfires do not inadvertently reduce variation in vegetation structure generated by the underlying invisible mosaic. © 2017 by the Ecological Society of America.

Snow depth spatial structure from hillslope to basin scale

NASA Astrophysics Data System (ADS)

Deems, J. S.

2017-12-01

Knowledge of spatial patterns of snow accumulation is required for understanding the hydrology, climatology, and ecology of mountain regions. Spatial structure in snow accumulation patterns changes with the scale of observation, a feature that has been characterized using fractal dimensions calculated from lidar-derived snow depth maps: fractal scaling structure at short length scales, with a `scale break' transition to more stochastic patterns at longer separation distances. Previous work has shown that this fractal structure of snow depth distributions differs between sites with different vegetation and terrain characteristics. Forested areas showed a transition to a nearly random spatial distribution at a much shorter lag distance than do unforested sites, enabling a statistical characterization. Alpine areas, however, showed strong spatial structure for a much wider scale range, and were the source of the dominant spatial pattern observable over a wider area. These spatial structure characteristics suggest that the choice of measurement or model resolution (satellite sensor, DEM, field survey point spacing, etc.) will strongly affect the estimates of snow volume or mass, as well as the magnitude of spatial variability. These prior efforts used data sets that were high resolution ( 1 m laser point spacing) but of limited extent ( 1 km2), constraining detection of scale features such as fractal dimension or scale breaks to areas of relatively similar characteristics and to lag distances of under 500 m. New datasets available from the NASA JPL Airborne Snow Observatory (ASO) provide similar resolution but over large areas, enabling assessment of snow spatial structure across an entire watershed, or in similar vegetation or physiography but in different parts of the basin. Additionally, the multi-year ASO time series allows an investigation into the temporal stability of these scale characteristics, within a single snow season and between seasons of strongly varying accumulation totals and patterns. This presentation will explore initial results from this study, using data from the Tuolumne River Basin in California, USA. Fractal scaling characteristics derived from ASO lidar snow depth measurements are examined at the basin scale, as well as in varying topographic and forest cover environments.

A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape.

PubMed

Lausch, Angela; Pause, Marion; Merbach, Ines; Zacharias, Steffen; Doktor, Daniel; Volk, Martin; Seppelt, Ralf

2013-02-01

Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the "One Sensor at Different Scales" (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R (2) of 0.83, which was transferred to airborne hyperspectral data on the local and regional scales. For this purpose, hyperspectral imagery was collected at three altitudes over a land cover gradient of 25 km within a timeframe of a few minutes, yielding a spatial resolution from 1 to 3 m. For all recorded spatial scales, both the LAI and the NDVI were determined. The spatial properties of LAI and NDVI of all recorded hyperspectral images were compared using semivariance metrics derived from the variogram. The first results show spatial differences in the heterogeneity of LAI and NDVI from 1 to 3 m with the recorded hyperspectral data. That means that differently recorded data on different scales might not sufficiently maintain the spatial properties of high spatial resolution hyperspectral images.

Enhanced canopy fuel mapping by integrating lidar data

USGS Publications Warehouse

Peterson, Birgit E.; Nelson, Kurtis J.

2016-10-03

BackgroundThe Wildfire Sciences Team at the U.S. Geological Survey’s Earth Resources Observation and Science Center produces vegetation type, vegetation structure, and fuel products for the United States, primarily through the Landscape Fire and Resource Management Planning Tools (LANDFIRE) program. LANDFIRE products are used across disciplines for a variety of applications. The LANDFIRE data retain their currency and relevancy through periodic updating or remapping. These updating and remapping efforts provide opportunities to improve the LANDFIRE product suite by incorporating data from other sources. Light detection and ranging (lidar) is uniquely suitable for gathering information on vegetation structure and spatial arrangement because it can collect data in three dimensions. The Wildfire Sciences Team has several completed and ongoing studies focused on integrating lidar into vegetation and fuels mapping.

Assessing the drivers shaping global patterns of urban vegetation landscape structure.

PubMed

Dobbs, C; Nitschke, C; Kendal, D

2017-08-15

Vegetation is one of the main resources involve in ecosystem functioning and providing ecosystem services in urban areas. Little is known on the landscape structure patterns of vegetation existing in urban areas at the global scale and the drivers of these patterns. We studied the landscape structure of one hundred cities around the globe, and their relation to demography (population), socioeconomic factors (GDP, Gini Index), climate factors (temperature and rain) and topographic characteristics (altitude, variation in altitude). The data revealed that the best descriptors of landscape structure were amount, fragmentation and spatial distribution of vegetation. Populated cities tend to have less, more fragmented, less connected vegetation with a centre of the city with low vegetation cover. Results also provided insights on the influence of socioeconomics at a global scale, as landscape structure was more fragmented in areas that are economically unequal and coming from emergent economies. This study shows the effects of the social system and climate on urban landscape patterns that gives useful insights for the distribution in the provision of ecosystem services in urban areas and therefore the maintenance of human well-being. This information can support local and global policy and planning which is committing our cities to provide accessible and inclusive green space for all urban inhabitants. Copyright © 2017 Elsevier B.V. All rights reserved.

Ground-Vegetation Clutter Affects Phyllostomid Bat Assemblage Structure in Lowland Amazonian Forest

PubMed Central

Marciente, Rodrigo; Bobrowiec, Paulo Estefano D.; Magnusson, William E.

2015-01-01

Vegetation clutter is a limiting factor for bats that forage near ground level, and may determine the distribution of species and guilds. However, many studies that evaluated the effects of vegetation clutter on bats have used qualitative descriptions rather than direct measurements of vegetation density. Moreover, few studies have evaluated the effect of vegetation clutter on a regional scale. Here, we evaluate the influence of the physical obstruction of vegetation on phyllostomid-bat assemblages along a 520 km transect in continuous Amazonian forest. We sampled bats using mist nets in eight localities during 80 nights (3840 net-hours) and estimated the ground-vegetation density with digital photographs. The total number of species, number of animalivorous species, total number of frugivorous species, number of understory frugivorous species, and abundance of canopy frugivorous bats were negatively associated with vegetation clutter. The bat assemblages showed a nested structure in relation to degree of clutter, with animalivorous and understory frugivorous bats distributed throughout the vegetation-clutter gradient, while canopy frugivores were restricted to sites with more open vegetation. The species distribution along the gradient of vegetation clutter was not closely associated with wing morphology, but aspect ratio and wing load differed between frugivores and animalivores. Vegetation structure plays an important role in structuring assemblages of the bats at the regional scale by increasing beta diversity between sites. Differences in foraging strategy and diet of the guilds seem to have contributed more to the spatial distribution of bats than the wing characteristics of the species alone. PMID:26066654

Geographical ecology of the palms (Arecaceae): determinants of diversity and distributions across spatial scales

PubMed Central

Eiserhardt, Wolf L.; Svenning, Jens-Christian; Kissling, W. Daniel; Balslev, Henrik

2011-01-01

Background The palm family occurs in all tropical and sub-tropical regions of the world. Palms are of high ecological and economical importance, and display complex spatial patterns of species distributions and diversity. Scope This review summarizes empirical evidence for factors that determine palm species distributions, community composition and species richness such as the abiotic environment (climate, soil chemistry, hydrology and topography), the biotic environment (vegetation structure and species interactions) and dispersal. The importance of contemporary vs. historical impacts of these factors and the scale at which they function is discussed. Finally a hierarchical scale framework is developed to guide predictor selection for future studies. Conclusions Determinants of palm distributions, composition and richness vary with spatial scale. For species distributions, climate appears to be important at landscape and broader scales, soil, topography and vegetation at landscape and local scales, hydrology at local scales, and dispersal at all scales. For community composition, soil appears important at regional and finer scales, hydrology, topography and vegetation at landscape and local scales, and dispersal again at all scales. For species richness, climate and dispersal appear to be important at continental to global scales, soil at landscape and broader scales, and topography at landscape and finer scales. Some scale–predictor combinations have not been studied or deserve further attention, e.g. climate on regional to finer scales, and hydrology and topography on landscape and broader scales. The importance of biotic interactions – apart from general vegetation structure effects – for the geographic ecology of palms is generally underexplored. Future studies should target scale–predictor combinations and geographic domains not studied yet. To avoid biased inference, one should ideally include at least all predictors previously found important at the spatial scale of investigation. PMID:21712297

Reproductive phenology of coastal plain Atlantic forest vegetation: comparisons from seashore to foothills.

PubMed

Staggemeier, Vanessa Graziele; Morellato, Leonor Patrícia Cerdeira

2011-11-01

The diversity of tropical forest plant phenology has called the attention of researchers for a long time. We continue investigating the factors that drive phenological diversity on a wide scale, but we are unaware of the variation of plant reproductive phenology at a fine spatial scale despite the high spatial variation in species composition and abundance in tropical rainforests. We addressed fine scale variability by investigating the reproductive phenology of three contiguous vegetations across the Atlantic rainforest coastal plain in Southeastern Brazil. We asked whether the vegetations differed in composition and abundance of species, the microenvironmental conditions and the reproductive phenology, and how their phenology is related to regional and local microenvironmental factors. The study was conducted from September 2007 to August 2009 at three contiguous sites: (1) seashore dominated by scrub vegetation, (2) intermediary covered by restinga forest and (3) foothills covered by restinga pre-montane transitional forest. We conducted the microenvironmental, plant and phenological survey within 30 transects of 25 m × 4 m (10 per site). We detected significant differences in floristic, microenvironment and reproductive phenology among the three vegetations. The microenvironment determines the spatial diversity observed in the structure and composition of the flora, which in turn determines the distinctive flowering and fruiting peaks of each vegetation (phenological diversity). There was an exchange of species providing flowers and fruits across the vegetation complex. We conclude that plant reproductive patterns as described in most phenological studies (without concern about the microenvironmental variation) may conceal the fine scale temporal phenological diversity of highly diverse tropical vegetation. This phenological diversity should be taken into account when generating sensor-derived phenologies and when trying to understand tropical vegetation responses to environmental changes.

Historical Maps from Modern Images: Using Remote Sensing to Model and Map Century-Long Vegetation Change in a Fire-Prone Region

PubMed Central

Callister, Kate E.; Griffioen, Peter A.; Avitabile, Sarah C.; Haslem, Angie; Kelly, Luke T.; Kenny, Sally A.; Nimmo, Dale G.; Farnsworth, Lisa M.; Taylor, Rick S.; Watson, Simon J.; Bennett, Andrew F.; Clarke, Michael F.

2016-01-01

Understanding the age structure of vegetation is important for effective land management, especially in fire-prone landscapes where the effects of fire can persist for decades and centuries. In many parts of the world, such information is limited due to an inability to map disturbance histories before the availability of satellite images (~1972). Here, we describe a method for creating a spatial model of the age structure of canopy species that established pre-1972. We built predictive neural network models based on remotely sensed data and ecological field survey data. These models determined the relationship between sites of known fire age and remotely sensed data. The predictive model was applied across a 104,000 km2 study region in semi-arid Australia to create a spatial model of vegetation age structure, which is primarily the result of stand-replacing fires which occurred before 1972. An assessment of the predictive capacity of the model using independent validation data showed a significant correlation (rs = 0.64) between predicted and known age at test sites. Application of the model provides valuable insights into the distribution of vegetation age-classes and fire history in the study region. This is a relatively straightforward method which uses widely available data sources that can be applied in other regions to predict age-class distribution beyond the limits imposed by satellite imagery. PMID:27029046

Exploring new topography-based subgrid spatial structures for improving land surface modeling

DOE PAGES

Tesfa, Teklu K.; Leung, Lai-Yung Ruby

2017-02-22

Topography plays an important role in land surface processes through its influence on atmospheric forcing, soil and vegetation properties, and river network topology and drainage area. Land surface models with a spatial structure that captures spatial heterogeneity, which is directly affected by topography, may improve the representation of land surface processes. Previous studies found that land surface modeling, using subbasins instead of structured grids as computational units, improves the scalability of simulated runoff and streamflow processes. In this study, new land surface spatial structures are explored by further dividing subbasins into subgrid structures based on topographic properties, including surface elevation,more » slope and aspect. Two methods (local and global) of watershed discretization are applied to derive two types of subgrid structures (geo-located and non-geo-located) over the topographically diverse Columbia River basin in the northwestern United States. In the global method, a fixed elevation classification scheme is used to discretize subbasins. The local method utilizes concepts of hypsometric analysis to discretize each subbasin, using different elevation ranges that also naturally account for slope variations. The relative merits of the two methods and subgrid structures are investigated for their ability to capture topographic heterogeneity and the implications of this on representations of atmospheric forcing and land cover spatial patterns. Results showed that the local method reduces the standard deviation (SD) of subgrid surface elevation in the study domain by 17 to 19 % compared to the global method, highlighting the relative advantages of the local method for capturing subgrid topographic variations. The comparison between the two types of subgrid structures showed that the non-geo-located subgrid structures are more consistent across different area threshold values than the geo-located subgrid structures. Altogether the local method and non-geo-located subgrid structures effectively and robustly capture topographic, climatic and vegetation variability, which is important for land surface modeling.« less

Exploring new topography-based subgrid spatial structures for improving land surface modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tesfa, Teklu K.; Leung, Lai-Yung Ruby

Topography plays an important role in land surface processes through its influence on atmospheric forcing, soil and vegetation properties, and river network topology and drainage area. Land surface models with a spatial structure that captures spatial heterogeneity, which is directly affected by topography, may improve the representation of land surface processes. Previous studies found that land surface modeling, using subbasins instead of structured grids as computational units, improves the scalability of simulated runoff and streamflow processes. In this study, new land surface spatial structures are explored by further dividing subbasins into subgrid structures based on topographic properties, including surface elevation,more » slope and aspect. Two methods (local and global) of watershed discretization are applied to derive two types of subgrid structures (geo-located and non-geo-located) over the topographically diverse Columbia River basin in the northwestern United States. In the global method, a fixed elevation classification scheme is used to discretize subbasins. The local method utilizes concepts of hypsometric analysis to discretize each subbasin, using different elevation ranges that also naturally account for slope variations. The relative merits of the two methods and subgrid structures are investigated for their ability to capture topographic heterogeneity and the implications of this on representations of atmospheric forcing and land cover spatial patterns. Results showed that the local method reduces the standard deviation (SD) of subgrid surface elevation in the study domain by 17 to 19 % compared to the global method, highlighting the relative advantages of the local method for capturing subgrid topographic variations. The comparison between the two types of subgrid structures showed that the non-geo-located subgrid structures are more consistent across different area threshold values than the geo-located subgrid structures. Altogether the local method and non-geo-located subgrid structures effectively and robustly capture topographic, climatic and vegetation variability, which is important for land surface modeling.« less

Capability of ERTS-1 imagery to investigate geological and structural features in a sedimentary basin (Bassin Parisien, France)

NASA Technical Reports Server (NTRS)

Cavelier, C.; Scanvic, J. Y.; Weecksteen, G.; Zizerman, A.

1973-01-01

A preliminary study of the MSS imagery of a sedimentary basin whose structure is regular is reported. Crops and natural vegetation are distributed all over the site located under temperate climate. Ground data available concern plant species geology and tectonic and are correlated with results from ERTS 1 imagery. This comparison shows a good correlation. The main geological units are detected or enhanced by way of agricultural land use and/or natural vegetation. Alluvial deposits are outlined by vegetation grass land and poplar trees. Some spatial relationship of geostructures, suspected until now, are identified or extended in associating results from different spectral bands.

Quantitative characterization of the regressive ecological succession by fractal analysis of plant spatial patterns

USGS Publications Warehouse

Alados, C.L.; Pueyo, Y.; Giner, M.L.; Navarro, T.; Escos, J.; Barroso, F.; Cabezudo, B.; Emlen, J.M.

2003-01-01

We studied the effect of grazing on the degree of regression of successional vegetation dynamic in a semi-arid Mediterranean matorral. We quantified the spatial distribution patterns of the vegetation by fractal analyses, using the fractal information dimension and spatial autocorrelation measured by detrended fluctuation analyses (DFA). It is the first time that fractal analysis of plant spatial patterns has been used to characterize the regressive ecological succession. Plant spatial patterns were compared over a long-term grazing gradient (low, medium and heavy grazing pressure) and on ungrazed sites for two different plant communities: A middle dense matorral of Chamaerops and Periploca at Sabinar-Romeral and a middle dense matorral of Chamaerops, Rhamnus and Ulex at Requena-Montano. The two communities differed also in the microclimatic characteristics (sea oriented at the Sabinar-Romeral site and inland oriented at the Requena-Montano site). The information fractal dimension increased as we moved from a middle dense matorral to discontinuous and scattered matorral and, finally to the late regressive succession, at Stipa steppe stage. At this stage a drastic change in the fractal dimension revealed a change in the vegetation structure, accurately indicating end successional vegetation stages. Long-term correlation analysis (DFA) revealed that an increase in grazing pressure leads to unpredictability (randomness) in species distributions, a reduction in diversity, and an increase in cover of the regressive successional species, e.g. Stipa tenacissima L. These comparisons provide a quantitative characterization of the successional dynamic of plant spatial patterns in response to grazing perturbation gradient. ?? 2002 Elsevier Science B.V. All rights reserved.

Hydrological drivers of wetland vegetational biodiversity patterns within Everglades National Park, Florida

NASA Astrophysics Data System (ADS)

Todd, J.; Pumo, D.; Azaele, S.; Muneepeerakul, R.; Miralles-Wilhelm, F. R.; Rinaldo, A.; Rodriguez-Iturbe, I.

2009-12-01

The influence of hydrological dynamics on vegetational biodiversity and structuring of wetland environments is of growing interest as wetlands are modified by human alteration and the increasing threat from climate change. Hydrology has long been considered a driving force in shaping wetland communities as the frequency of inundation along with the duration and depth of flooding are key determinants of wetland structure. We attempt to link hydrological dynamics with vegetational distribution and species richness across Everglades National Park (ENP) using two publicly available datasets. The first, the Everglades Depth Estimation Network (EDEN),is a water-surface model which determines the median daily measure of water level across a 400mX400m grid over seven years of measurement. The second is a vegetation map and classification system at the 1:15,000 scale which categorizes vegetation within the Everglades into 79 community types. From these data, we have studied the probabilistic structure of the frequency, duration, and depth of hydroperiods. Preliminary results indicate that the percentage of time a location is inundated is a principal structuring variable with individual communities responding differently. For example, sawgrass appears to be more of a generalist community as it is found across a wide range of time inundated percentages while spike rush has a more restricted distribution and favors wetter environments disproportionately more than predicted at random. Further, the diversity of vegetation communities (e.g. a measure of biodiversity) found across a hydrologic variable does not necessarily match the distribution function for that variable on the landscape. For instance, the number of communities does not differ across the percentage of time inundated. Different measures of vegetation biodiversity such as the local number of community types are also studied at different spatial scales with some characteristics, like the slope of the semi-logarithmic relation between rank and occupancy, found to be robust to scale changes. The ENP offers an expansive natural environment in which to study how vegetational dynamics and community composition are affected by hydrologic variables from the small scale (at the individual community level) to the large (biodiversity measures at differing spatial scales).

Spatial heterogeneity and air pollution removal by an urban forest

Treesearch

Francisco J. Escobedo; David J. Nowak

2009-01-01

Estimates of air pollution removal by the urban forest have mostly been based on mean values of forest structure variables for an entire city. However, the urban forest is not uniformly distributed across a city because of biophysical and social factors. Consequently, air pollution removal function by urban vegetation should vary because of this spatial heterogeneity....

Considering Spatial Scale and Reproductive Consequences of Habitat Selection when Managing Grasslands for a Threatened Species

PubMed Central

Pearson, Scott F.; Knapp, Shannon M.

2016-01-01

Habitat selection that has fitness consequences has important implications for conservation activities. For example, habitat characteristics that influence nest success in birds can be manipulated to improve habitat quality with the goal of ultimately improving reproductive success. We examined habitat selection by the threatened streaked horned lark (Eremophila alpestris strigata) at both the breeding-site (territory) and nest-site scales. Larks were selective at both spatial scales but with contrasting selection. At the territory scale, male larks selected sparsely vegetated grasslands with relatively short vegetation. At the nest-site scale, female larks selected sites within territories with higher vegetation density and more perennial forbs. These nest-site scale choices had reproductive consequences, with greater nest success in areas with higher densities of perennial forbs. We experimentally manipulated lark habitat structure in an attempt to mimic the habitat conditions selected by larks by using late summer prescribed fires. After the burn, changes in vegetation structure were in the direction preferred by larks but habitat effects attenuated by the following year. Our results highlight the importance of evaluating habitat selection at spatial scales appropriate to the species of interest, especially when attempting to improve habitat quality for rare and declining species. They also highlight the importance of conducting restoration activities in a research context. For example, because the sparsely vegetated conditions created by fire attenuate, there may be value in examining more frequent burns or hotter fires as the next management and research action. We hope the design outlined in this study will serve as an integrated research and management example for conserving grassland birds generally. PMID:27322196

The Forest Vegetation Simulator: A review of its structure, content, and applications

Treesearch

Nicholas L. Crookston; Gary E. Dixon

2005-01-01

The Forest Vegetation Simulator (FVS) is a distance-independent, individual-tree forest growth model widely used in the United States to support management decisionmaking. Stands are the basic projection unit, but the spatial scope can be many thousands of stands. The temporal scope is several hundred years at a resolution of 5­10 years. Projections start with a...

Patterns in woody vegetation structure across African savannas

NASA Astrophysics Data System (ADS)

Axelsson, Christoffer R.; Hanan, Niall P.

2017-07-01

Vegetation structure in water-limited systems is to a large degree controlled by ecohydrological processes, including mean annual precipitation (MAP) modulated by the characteristics of precipitation and geomorphology that collectively determine how rainfall is distributed vertically into soils or horizontally in the landscape. We anticipate that woody canopy cover, crown density, crown size, and the level of spatial aggregation among woody plants in the landscape will vary across environmental gradients. A high level of woody plant aggregation is most distinct in periodic vegetation patterns (PVPs), which emerge as a result of ecohydrological processes such as runoff generation and increased infiltration close to plants. Similar, albeit weaker, forces may influence the spatial distribution of woody plants elsewhere in savannas. Exploring these trends can extend our knowledge of how semi-arid vegetation structure is constrained by rainfall regime, soil type, topography, and disturbance processes such as fire. Using high-spatial-resolution imagery, a flexible classification framework, and a crown delineation method, we extracted woody vegetation properties from 876 sites spread over African savannas. At each site, we estimated woody cover, mean crown size, crown density, and the degree of aggregation among woody plants. This enabled us to elucidate the effects of rainfall regimes (MAP and seasonality), soil texture, slope, and fire frequency on woody vegetation properties. We found that previously documented increases in woody cover with rainfall is more consistently a result of increasing crown size than increasing density of woody plants. Along a gradient of mean annual precipitation from the driest (< 200 mm yr-1) to the wettest (1200-1400 mm yr-1) end, mean estimates of crown size, crown density, and woody cover increased by 233, 73, and 491 % respectively. We also found a unimodal relationship between mean crown size and sand content suggesting that maximal savanna tree sizes do not occur in either coarse sands or heavy clays. When examining the occurrence of PVPs, we found that the same factors that contribute to the formation of PVPs also correlate with higher levels of woody plant aggregation elsewhere in savannas and that rainfall seasonality plays a key role for the underlying processes.

Characterizing 3D Vegetation Structure from Space: Mission Requirements

NASA Technical Reports Server (NTRS)

Hall, Forrest G.; Bergen, Kathleen; Blair, James B.; Dubayah, Ralph; Houghton, Richard; Hurtt, George; Kellndorfer, Josef; Lefsky, Michael; Ranson, Jon; Saatchi, Sasan;

Effects of land use pattern on soil water in revegetation watersheds in semi-arid Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Yang, Lei; Chen, Liding; Wei, Wei

2017-04-01

Soil water stored below rainfall infiltration depth is a reliable water resource for plant growth in arid and semi-arid regions. For decreasing serious soil erosion, large-scale human-introduced vegetation restoration was initiated in Chinese Loess Plateau in late 1990s. However, these activities may result in excessive water consumption and soil water deficit if no appropriate scientific guidance were offered. This in turn impacts the regional ecological restoration and sustainable management of water resources. In this study, soil water content data in depth of 0-5 m was obtained by long-term field observation and geostatistical method in 6 small watersheds covered with different land use pattern. Profile characteristics and spatial-temporal patterns of soil water were compared between different land use types, hillslopes, and watersheds. The results showed that: (1) Introduced vegetation consumed excessive amount of water when compared with native grassland and farmland, and induced temporally stable soil desiccation in depth of 0-5 m. The introduced vegetation decreased soil water content to levels lower than the reference value representing no human impact in all soil layers. (2) The analysis of differences in soil water at hillslope and watershed scales indicated that land use determined the spatial and temporal variability of soil water. Soil water at watershed scale increased with the increasing area of farmland, and decreased with increasing percentage of introduced vegetation. Land use structure determined the soil water condition and land use pattern determined the spatial-temporal variability of soil water at watershed scale. (3) Large-scale revegetation with introduced vegetation diminished the spatial heterogeneity of soil water at different scales. Land use pattern adjustment could be used to improve the water resources management and maintain the sustainability of vegetation restoration.

Effects of Telecoupling on Global Vegetation Dynamics

NASA Astrophysics Data System (ADS)

Viña, A.; Liu, J.

2016-12-01

With the ever increasing trend in telecoupling processes, such as international trade, all countries around the world are becoming more interdependent. However, the effects of this growing interdependence on vegetation (e.g., shifts in the geographic extent and distribution) remain unknown even though vegetation dynamics are crucially important for food production, carbon sequestration, provision of other ecosystem services, and biodiversity conservation. In this study we evaluate the effects of international trade on the spatio-temporal trajectories of vegetation at national and global scales, using vegetation index imagery collected over more than three decades by the Advanced Very High Resolution Radiometer (AVHRR) satellite sensor series together with concurrent national and international data on international trade (and its associated movement of people, goods, services and information). The spatio-temporal trajectories of vegetation are obtained using the scale of fluctuation technique, which is based on the decomposition of the AVHRR image time series to obtain information on its spatial dependence structure over time. Similar to the correlation length, the scale of fluctuation corresponds to the range over which fluctuations in the vegetation index are spatially correlated. Results indicate that global vegetation has changed drastically over the last three decades. These changes are not uniform across space, with hotspots in active trading countries. This study not only has direct implications for understanding global vegetation dynamics, but also sheds important insights on the complexity of human-nature interactions across telecoupled systems.

Environmental factors explaining the vegetation patterns in a temperate peatland.

PubMed

Pellerin, Stéphanie; Lagneau, Louis-Adrien; Lavoie, Martin; Larocque, Marie

2009-08-01

Although ombrotrophic temperate peatlands are important ecosystems for maintaining biodiversity in eastern North America, the environmental factors influencing their flora are only partly understood. The relationships between plant species distribution and environmental factors were thus studied within the oldest temperate peatland of Québec. Plant assemblages were identified by cluster analysis while CCA was used to related vegetation gradients to environmental factors. Five assemblages were identified; three typical of open bog and two characterized by more minerotrophic vegetation. Thicker peat deposit was encounter underlying the bog assemblages while higher water table level and percentage of free surface water distinguished the minerotrophic assemblages. Overall, the floristic patterns observed were spatially structured along the margins and the expanse. The most important environmental factors explaining this spatial gradient were the percentage of free surface water and the highest water-table level.

Estimating urban vegetation fraction across 25 cities in pan-Pacific using Landsat time series data

NASA Astrophysics Data System (ADS)

Lu, Yuhao; Coops, Nicholas C.; Hermosilla, Txomin

2017-04-01

Urbanization globally is consistently reshaping the natural landscape to accommodate the growing human population. Urban vegetation plays a key role in moderating environmental impacts caused by urbanization and is critically important for local economic, social and cultural development. The differing patterns of human population growth, varying urban structures and development stages, results in highly varied spatial and temporal vegetation patterns particularly in the pan-Pacific region which has some of the fastest urbanization rates globally. Yet spatially-explicit temporal information on the amount and change of urban vegetation is rarely documented particularly in less developed nations. Remote sensing offers an exceptional data source and a unique perspective to map urban vegetation and change due to its consistency and ubiquitous nature. In this research, we assess the vegetation fractions of 25 cities across 12 pan-Pacific countries using annual gap-free Landsat surface reflectance products acquired from 1984 to 2012, using sub-pixel, spectral unmixing approaches. Vegetation change trends were then analyzed using Mann-Kendall statistics and Theil-Sen slope estimators. Unmixing results successfully mapped urban vegetation for pixels located in urban parks, forested mountainous regions, as well as agricultural land (correlation coefficient ranging from 0.66 to 0.77). The greatest vegetation loss from 1984 to 2012 was found in Shanghai, Tianjin, and Dalian in China. In contrast, cities including Vancouver (Canada) and Seattle (USA) showed stable vegetation trends through time. Using temporal trend analysis, our results suggest that it is possible to reduce noise and outliers caused by phenological changes particularly in cropland using dense new Landsat time series approaches. We conclude that simple yet effective approaches of unmixing Landsat time series data for assessing spatial and temporal changes of urban vegetation at regional scales can provide critical information for urban planners and anthropogenic studies globally.

Fire mosaics and reptile conservation in a fire-prone region.

PubMed

Nimmo, D G; Kelly, L T; Spence-Bailey, L M; Watson, S J; Taylor, R S; Clarke, M F; Bennett, A F

2013-04-01

Fire influences the distribution of fauna in terrestrial biomes throughout the world. Use of fire to achieve a mosaic of vegetation in different stages of succession after burning (i.e., patch-mosaic burning) is a dominant conservation practice in many regions. Despite this, knowledge of how the spatial attributes of vegetation mosaics created by fire affect fauna is extremely scarce, and it is unclear what kind of mosaic land managers should aim to achieve. We selected 28 landscapes (each 12.6 km(2) ) that varied in the spatial extent and diversity of vegetation succession after fire in a 104,000 km(2) area in the semiarid region of southeastern Australia. We surveyed for reptiles at 280 sites nested within the 28 landscapes. The landscape-level occurrence of 9 of the 22 species modeled was associated with the spatial extent of vegetation age classes created by fire. Biogeographic context and the extent of a vegetation type influenced 7 and 4 species, respectively. No species were associated with the diversity of vegetation ages within a landscape. Negative relations between reptile occurrence and both extent of recently burned vegetation (≤10 years postfire, n = 6) and long unburned vegetation (>35 years postfire, n = 4) suggested that a coarse-grained mosaic of areas (e.g. >1000 ha) of midsuccessional vegetation (11-35 years postfire) may support the fire-sensitive reptile species we modeled. This age class coincides with a peak in spinifex cover, a keystone structure for reptiles in semiarid and arid Australia. Maintaining over the long term a coarse-grained mosaic of large areas of midsuccessional vegetation in mallee ecosystems will need to be balanced against the short-term negative effects of large fires on many reptile species and a documented preference by species from other taxonomic groups, particularly birds, for older vegetation. © 2012 Society for Conservation Biology.

Land cover and land use changes in the oil and gas regions of Northwestern Siberia under changing climatic conditions

NASA Astrophysics Data System (ADS)

Yu, Qin; Epstein, Howard E.; Engstrom, Ryan; Shiklomanov, Nikolay; Strelestskiy, Dmitry

2015-12-01

Northwestern Siberia has been undergoing a range of land cover and land use changes associated with climate change, animal husbandry and development of mineral resources, particularly oil and gas. The changes caused by climate and oil/gas development Southeast of the city of Nadym were investigated using multi-temporal and multi-spatial remotely sensed images. Comparison between high spatial resolution imagery acquired in 1968 and 2006 indicates that 8.9% of the study area experienced an increase in vegetation cover (e.g. establishment of new saplings, extent of vegetated cover) in response to climate warming while 10.8% of the area showed a decrease in vegetation cover due to oil and gas development and logging activities. Waterlogging along linear structures and vehicle tracks was found near the oil and gas development site, while in natural landscapes the drying of thermokarst lakes is evident due to warming caused permafrost degradation. A Landsat time series dataset was used to document the spatial and temporal dynamics of these ecosystems in response to climate change and disturbances. The impacts of land use on surface vegetation, radiative, and hydrological properties were evaluated using Landsat image-derived biophysical indices. The spatial and temporal analyses suggest that the direct impacts associated with infrastructure development were mostly within 100 m distance from the disturbance source. While these impacts are rather localized they persist for decades despite partial recovery of vegetation after the initial disturbance and can have significant implications for changes in permafrost dynamics and surface energy budgets at landscape and regional scales.

Habitat selection by owls in a seasonal semi-deciduous forest in southern Brazil.

PubMed

Menq, W; Anjos, L

2015-11-01

This paper tested the hypothesis that the structural components of vegetation have impact over the distribution of owl species in a fragment of a semi-deciduous seasonal forest. This paper also determined which vegetation variables contributed to the spatial distribution of owl species. It was developed in the Perobas Biological Reserve (PBR) between September and December 2011. To conduct the owl census, a playback technique was applied at hearing points distributed to cover different vegetation types in the study area. A total of 56 individual owls of six species were recorded: Tropical Screech-Owl (Megascops choliba), Black-capped Screech-Owl (Megascops atricapilla), Tawny-browed Owl (Pulsatrix koeniswaldiana), Ferruginous Pygmy-Owl (Glaucidium brasilianum), Mottled Owl (Strix virgata) and Stygian Owl (Asio stygius). The results suggest that the variables of vegetation structure have impact on the occurrence of owls. The canopy height, the presence of hollow trees, fallen trees and glades are the most important structural components influencing owl distribution in the sampled area.

Monitoring of Vegetation Impact Due to Trampling on Cadillac Mountain Summit Using High Spatial Resolution Remote Sensing Data Sets

NASA Astrophysics Data System (ADS)

Kim, Min-Kook; Daigle, John J.

2012-11-01

Cadillac Mountain—the highest peak along the eastern seaboard of the United States—is a major tourist destination in Acadia National Park, Maine. Managing vegetation impact due to trampling on the Cadillac Mountain summit is extremely challenging because of the large number of visitors and the general open nature of landscape in this fragile subalpine environmental setting. Since 2000, more intensive management strategies—based on placing physical barriers and educational messages for visitors—have been employed to protect threatened vegetation, decrease vegetation impact, and enhance vegetation recovery in the vicinity of the summit loop trail. The primary purpose of this study was to evaluate the effect of the management strategies employed. For this purpose, vegetation cover changes between 2001 and 2007 were detected using multispectral high spatial resolution remote sensing data sets. A normalized difference vegetation index was employed to identify the rates of increase and decrease in the vegetation areas. Three buffering distances (30, 60, and 90 m) from the edges of the trail were used to define multiple spatial extents of the site, and the same spatial extents were employed at a nearby control site that had no visitors. No significant differences were detected between the mean rates of vegetation increase and decrease at the experimental site compared with a nearby control site in the case of a small spatial scale (≤30 m) comparison (in all cases P > 0.05). However, in the medium (≤60 m) and large (≤90 m) spatial scales, the rates of increased vegetation were significantly greater and rates of decreased vegetation significantly lower at the experimental site compared with the control site (in all cases P < 0.001). Research implications are explored that relate to the spatial extent of the radial patterns of impact of trampling on vegetation at the site level. Management implications are explored in terms of the spatial strategies used to decrease the impact of trampling on vegetation.

Monitoring of vegetation impact due to trampling on Cadillac Mountain summit using high spatial resolution remote sensing data sets.

PubMed

Kim, Min-Kook; Daigle, John J

2012-11-01

Cadillac Mountain--the highest peak along the eastern seaboard of the United States--is a major tourist destination in Acadia National Park, Maine. Managing vegetation impact due to trampling on the Cadillac Mountain summit is extremely challenging because of the large number of visitors and the general open nature of landscape in this fragile subalpine environmental setting. Since 2000, more intensive management strategies--based on placing physical barriers and educational messages for visitors--have been employed to protect threatened vegetation, decrease vegetation impact, and enhance vegetation recovery in the vicinity of the summit loop trail. The primary purpose of this study was to evaluate the effect of the management strategies employed. For this purpose, vegetation cover changes between 2001 and 2007 were detected using multispectral high spatial resolution remote sensing data sets. A normalized difference vegetation index was employed to identify the rates of increase and decrease in the vegetation areas. Three buffering distances (30, 60, and 90 m) from the edges of the trail were used to define multiple spatial extents of the site, and the same spatial extents were employed at a nearby control site that had no visitors. No significant differences were detected between the mean rates of vegetation increase and decrease at the experimental site compared with a nearby control site in the case of a small spatial scale (≤30 m) comparison (in all cases P > 0.05). However, in the medium (≤60 m) and large (≤90 m) spatial scales, the rates of increased vegetation were significantly greater and rates of decreased vegetation significantly lower at the experimental site compared with the control site (in all cases P < 0.001). Research implications are explored that relate to the spatial extent of the radial patterns of impact of trampling on vegetation at the site level. Management implications are explored in terms of the spatial strategies used to decrease the impact of trampling on vegetation.

Vegetation responsees to landscape structure at multiple scales across a Northern Wisconsin, USA, pine barrens landscape

Treesearch

K.D. Brosofske; J. Chen; Thomas R. Crow; S.C. Saunders

1999-01-01

Increasing awareness of the importance of scale and landscape structure to landscape processes and concern about loss of biodiversity has resulted in efforts to understand patterns of biodiversity across multiple scales. We examined plant species distributions and their relationships to landscape structure at varying spatial scales across a pine barrens landscape in...

Quantifying early-seral forest composition with remote sensing

Treesearch

Rayma A. Cooley; Peter T. Wolter; Brian R. Sturtevant

2016-01-01

Spatially explicit modeling of recovering forest structure within two years following wildfire disturbance has not been attempted, yet such knowledge is critical for determining successional pathways. We used remote sensing and field data, along with digital climate and terrain data, to model and map early-seral aspen structure and vegetation species richness following...

Variability of pesticide exposure in a stream mesocosm system: macrophyte-dominated vs. non-vegetated sections.

PubMed

Beketov, Mikhail A; Liess, Matthias

2008-12-01

For flowing water bodies no information is available about patterns of contaminant distribution in flowing water compared to macrophyte-dominated structures. The aim of the study was to examine temporal dynamic and spatial cross-channel variability of pulse exposure of the insecticide thiacloprid in outdoor stream mesocosms. Two distinct cross-channel sections have been considered: macrophyte-dominated littoral and non-vegetated midstream. Median disappearance time ranged from 17 to 43 h (water phase, midstream). We showed that during the exposure pulse (10h) thiacloprid concentrations in the macrophyte-dominated section were 20-60% lower than those in the non-vegetated section. This suggests that spatial variability in contaminant concentrations, particularly in streams containing macrophytes, should be taken into account to enable a more realistic assessment of (i) exposure and associated effects and (ii) mass transport of pesticides and other chemicals into river systems (e.g. losses with surface runoff).

Extracting temporal and spatial information from remotely sensed data for mapping wildlife habitat: Tucson

USGS Publications Warehouse

Wallace, Cynthia S.A.; Advised by Marsh, Stuart E.

2002-01-01

The research accomplished in this dissertation used both mathematical and statistical techniques to extract and evaluate measures of landscape temporal dynamics and spatial structure from remotely sensed data for the purpose of mapping wildlife habitat. By coupling the landscape measures gleaned from the remotely sensed data with various sets of animal sightings and population data, effective models of habitat preference were created.Measures of temporal dynamics of vegetation greenness as measured by National Oceanographic and Atmospheric Administration’s Advanced Very High Resolution Radiometer (AVHRR) satellite were used to effectively characterize and map season specific habitat of the Sonoran pronghorn antelope, as well as produce preliminary models of potential yellow-billed cuckoo habitat in Arizona. Various measures that capture different aspects of the temporal dynamics of the landscape were derived from AVHRR Normalized Difference Vegetation Index composite data using three main classes of calculations: basic statistics, standardized principal components analysis, and Fourier analysis. Pronghorn habitat models based on the AVHRR measures correspond visually and statistically to GIS-based models produced using data that represent detailed knowledge of ground-condition.Measures of temporal dynamics also revealed statistically significant correlations with annual estimates of elk population in selected Arizona Game Management Units, suggesting elk respond to regional environmental changes that can be measured using satellite data. Such relationships, once verified and established, can be used to help indirectly monitor the population.Measures of landscape spatial structure derived from IKONOS high spatial resolution (1-m) satellite data using geostatistics effectively map details of Sonoran pronghorn antelope habitat. Local estimates of the nugget, sill, and range variogram parameters calculated within 25 x 25-meter image windows describe the spatial autocorrelation of the image, permitting classification of all pixels into coherent units whose signature graphs exhibit a classic variogram shape. The variogram parameters captured in these signatures have been shown in previous studies to discriminate between different species-specific vegetation associations.The synoptic view of the landscape provided by satellite data can inform resource management efforts. The ability to characterize the spatial structure and temporal dynamics of habitat using repeatable remote sensing data allows closer monitoring of the relationship between a species and its landscape.

Assessing land ownership as a driver of change in the distribution, structure, and composition of California's forests.

NASA Astrophysics Data System (ADS)

Easterday, K.; Kelly, M.; McIntyre, P. J.

2015-12-01

Climate change is forecasted to have considerable influence on the distribution, structure, and function of California's forests. However, human interactions with forested landscapes (e.g. fire suppression, resource extraction and etc.) have complicated scientific understanding of the relative contributions of climate change and anthropogenic land management practices as drivers of change. Observed changes in forest structure towards smaller, denser forests across California have been attributed to both climate change (e.g. increased temperatures and declining water availability) and management practices (e.g. fire suppression and logging). Disentangling how these drivers of change act both together and apart is important to developing sustainable policy and land management practices as well as enhancing knowledge of human and natural system interactions. To that end, a comprehensive historical dataset - the Vegetation Type Mapping project (VTM) - and a modern forest inventory dataset (FIA) are used to analyze how spatial variations in vegetation composition and structure over a ~100 year period can be explained by land ownership.Climate change is forecasted to have considerable influence on the distribution, structure, and function of California's forests. However, human interactions with forested landscapes (e.g. fire suppression, resource extraction and etc.) have complicated scientific understanding of the relative contributions of climate change and anthropogenic land management practices as drivers of change. Observed changes in forest structure towards smaller, denser forests across California have been attributed to both climate change (e.g. increased temperatures and declining water availability) and management practices (e.g. fire suppression and logging). Disentangling how these drivers of change act both together and apart is important to developing sustainable policy and land management practices as well as enhancing knowledge of human and natural system interactions. To that end, a comprehensive historical dataset - the Vegetation Type Mapping project (VTM) - and a modern forest inventory dataset (FIA) are used to analyze how spatial variations in vegetation composition and structure over a ~100 year period can be explained by land ownership.

A multi-scale approach of fluvial biogeomorphic dynamics using photogrammetry.

PubMed

Hortobágyi, Borbála; Corenblit, Dov; Vautier, Franck; Steiger, Johannes; Roussel, Erwan; Burkart, Andreas; Peiry, Jean-Luc

2017-11-01

Over the last twenty years, significant technical advances turned photogrammetry into a relevant tool for the integrated analysis of biogeomorphic cross-scale interactions within vegetated fluvial corridors, which will largely contribute to the development and improvement of self-sustainable river restoration efforts. Here, we propose a cost-effective, easily reproducible approach based on stereophotogrammetry and Structure from Motion (SfM) technique to study feedbacks between fluvial geomorphology and riparian vegetation at different nested spatiotemporal scales. We combined different photogrammetric methods and thus were able to investigate biogeomorphic feedbacks at all three spatial scales (i.e., corridor, alluvial bar and micro-site) and at three different temporal scales, i.e., present, recent past and long term evolution on a diversified riparian landscape mosaic. We evaluate the performance and the limits of photogrammetric methods by targeting a set of fundamental parameters necessary to study biogeomorphic feedbacks at each of the three nested spatial scales and, when possible, propose appropriate solutions. The RMSE varies between 0.01 and 2 m depending on spatial scale and photogrammetric methods. Despite some remaining difficulties to properly apply them with current technologies under all circumstances in fluvial biogeomorphic studies, e.g. the detection of vegetation density or landform topography under a dense vegetation canopy, we suggest that photogrammetry is a promising instrument for the quantification of biogeomorphic feedbacks at nested spatial scales within river systems and for developing appropriate river management tools and strategies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial environmental heterogeneity affects plant growth and thermal performance on a green roof.

PubMed

Buckland-Nicks, Michael; Heim, Amy; Lundholm, Jeremy

2016-05-15

Green roofs provide ecosystem services, including stormwater retention and reductions in heat transfer through the roof. Microclimates, as well as designed features of green roofs, such as substrate and vegetation, affect the magnitude of these services. Many green roofs are partially shaded by surrounding buildings, but the effects of this within-roof spatial environmental heterogeneity on thermal performance and other ecosystem services have not been examined. We quantified the effects of spatial heterogeneity in solar radiation, substrate depth and other variables affected by these drivers on vegetation and ecosystem services in an extensive green roof. Spatial heterogeneity in substrate depth and insolation were correlated with differential growth, survival and flowering in two focal plant species. These effects were likely driven by the resulting spatial heterogeneity in substrate temperature and moisture content. Thermal performance (indicated by heat flux and substrate temperature) was influenced by spatial heterogeneity in vegetation cover and substrate depth. Areas with less insolation were cooler in summer and had greater substrate moisture, leading to more favorable conditions for plant growth and survival. Spatial variation in substrate moisture (7%-26% volumetric moisture content) and temperature (21°C-36°C) during hot sunny conditions in summer could cause large differences in stormwater retention and heat flux within a single green roof. Shaded areas promote smaller heat fluxes through the roof, leading to energy savings, but lower evapotranspiration in these areas should reduce stormwater retention capacity. Spatial heterogeneity can thus result in trade-offs between different ecosystem services. The effects of these spatial heterogeneities are likely widespread in green roofs. Structures that provide shelter from sun and wind may be productively utilized to design higher functioning green roofs and increase biodiversity by providing habitat heterogeneity. Copyright © 2016 Elsevier B.V. All rights reserved.

Developing a global mixed-canopy, height-variable vegetation structure dataset for estimating global vegetation albedo and biomass in the NASA Ent Terrestrial Biosphere Model and GISS GCM

NASA Astrophysics Data System (ADS)

Montes, C.; Kiang, N. Y.; Yang, W.; Ni-Meister, W.; Schaaf, C.; Aleinov, I. D.; Jonas, J.; Zhao, F. A.; Yao, T.; Wang, Z.; Sun, Q.

2015-12-01

Processes determining biosphere-atmosphere coupling are strongly influenced by vegetation structure. Thus, ecosystem carbon sequestration and evapotranspiration affecting global carbon and water balances will depend upon the spatial extent of vegetation, its vertical structure, and its physiological variability. To represent this globally, Dynamic Global Vegetation Models (DGVMs) coupled to General Circulation Models (GCMs) make use of satellite and/or model-based vegetation classifications often composed by homogeneous communities. This work aims at developing a new Global Vegetation Structure Dataset (GVSD) by incorporating varying vegetation heights for mixed plant communities to be used as input to the Ent Terrestrial Biosphere Model (TBM), the DGVM coupled to the NASA Goddard Institute for Space Studies (GISS) GCM. Information sources include the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover and plant functional types (PFTs) (Friedl et al., 2010), vegetation height from the Geoscience Laser Altimeter System (GLAS) on board ICESat (Ice, Cloud, and land Elevation Satellite) (Simard et al., 2011; Tang et al., 2014) along with the Global Data Sets of Vegetation Leaf Area Index (LAI)3g (Zhu et al. 2013). Further PFT partitioning is performed according to a climate classification utilizing the Climate Research Unit (CRU) and the NOAA Global Precipitation Climatology Centre (GPCC) data. Final products are a GVSD consisting of mixed plant communities (e.g. mixed forests, savannas, mixed PFTs) following the Ecosystem Demography model (Moorcroft et al., 2001) approach represented by multi-cohort community patches at the sub-grid level of the GCM, which are ensembles of identical individuals whose differences are represented by PFTs, canopy height, density and vegetation structure sensitivity to allometric parameters. To assess the sensitivity of the GISS GCM to vegetation structure, we produce a range of estimates of Ent TBM biomass and plant densities by varying allometric specifications. Ultimately, this GVSD will serve as a template for community data sets, and be used as boundary conditions to the Ent TBM for prediction of canopy albedo in the Analytical Clumped Two-Stream canopy radiative transfer scheme, biomass, primary productivity, respiration, and GISS GCM climate.

Genet-specific DNA methylation probabilities detected in a spatial epigenetic analysis of a clonal plant population.

PubMed

Araki, Kiwako S; Kubo, Takuya; Kudoh, Hiroshi

2017-01-01

In sessile organisms such as plants, spatial genetic structures of populations show long-lasting patterns. These structures have been analyzed across diverse taxa to understand the processes that determine the genetic makeup of organismal populations. For many sessile organisms that mainly propagate via clonal spread, epigenetic status can vary between clonal individuals in the absence of genetic changes. However, fewer previous studies have explored the epigenetic properties in comparison to the genetic properties of natural plant populations. Here, we report the simultaneous evaluation of the spatial structure of genetic and epigenetic variation in a natural population of the clonal plant Cardamine leucantha. We applied a hierarchical Bayesian model to evaluate the effects of membership of a genet (a group of individuals clonally derived from a single seed) and vegetation cover on the epigenetic variation between ramets (clonal plants that are physiologically independent individuals). We sampled 332 ramets in a 20 m × 20 m study plot that contained 137 genets (identified using eight SSR markers). We detected epigenetic variation in DNA methylation at 24 methylation-sensitive amplified fragment length polymorphism (MS-AFLP) loci. There were significant genet effects at all 24 MS-AFLP loci in the distribution of subepiloci. Vegetation cover had no statistically significant effect on variation in the majority of MS-AFLP loci. The spatial aggregation of epigenetic variation is therefore largely explained by the aggregation of ramets that belong to the same genets. By applying hierarchical Bayesian analyses, we successfully identified a number of genet-specific changes in epigenetic status within a natural plant population in a complex context, where genotypes and environmental factors are unevenly distributed. This finding suggests that it requires further studies on the spatial epigenetic structure of natural populations of diverse organisms, particularly for sessile clonal species.

Characterization of ASTER GDEM Elevation Data over Vegetated Area Compared with Lidar Data

NASA Technical Reports Server (NTRS)

Ni, Wenjian; Sun, Guoqing; Ranson, Kenneth J.

2013-01-01

Current researches based on areal or spaceborne stereo images with very high resolutions (less than 1 meter) have demonstrated that it is possible to derive vegetation height from stereo images. The second version of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) is a state-of-the-art global elevation data-set developed by stereo images. However, the resolution of ASTER stereo images (15 meters) is much coarser than areal stereo images, and the ASTER GDEM is compiled products from stereo images acquired over 10 years. The forest disturbances as well as forest growth are inevitable in 10 years time span. In this study, the features of ASTER GDEM over vegetated areas under both flat and mountainous conditions were investigated by comparisons with lidar data. The factors possibly affecting the extraction of vegetation canopy height considered include (1) co-registration of DEMs; (2) spatial resolution of digital elevation models (DEMs); (3) spatial vegetation structure; and (4) terrain slope. The results show that accurate co-registration between ASTER GDEM and the National Elevation Dataset (NED) is necessary over mountainous areas. The correlation between ASTER GDEM minus NED and vegetation canopy height is improved from 0.328 to 0.43 by degrading resolutions from 1 arc-second to 5 arc-seconds and further improved to 0.6 if only homogenous vegetated areas were considered.

Recent Structural Change in Remote Sensing Data Time Series Linked to Farm Management in Horn of Africa (1999-2009)

NASA Astrophysics Data System (ADS)

Crisci, A.; Vignaroli, P.; Genesio, L.; Grasso, V.; Bacci, M.; Tarchiani, V.; Capecchi, V.

2011-01-01

Food security in East Africa region essentially depends on the stability of rain-fed crops farming, which renders its society vulnerable to climatic fluctuations. These ones in Africa are most widely and directly related to rainfall. In this study, the relation between recent spatial rainfall variability and vegetation dynamics has been investigated for East Africa territories. Satellite raster products SPOT-4 Vegetation 1 km resolution (Saint, 1995) and RFE (rainfall estimates) from Famine Early Warning Systems Network (FEWS NET) are used. The survey is carried out at administrative level scale using 10-day summaries extracted from raster data for each spatial area unit thanks to specific polygonal layers. Time series covers two different periods: 1996-2009 for rainfall estimates and 1999-2009 for NDVI. The first step of the analysis has been to build for each administrative unit a coherent set of data, along the time series, suitable to be processed with state-of-art statistical tools. The analysis is based on the assumption that every structural break in vegetation dynamics could be caused by two alternative/complementary causes, namely: (i) modifications in crop farming systems (adaptation strategy) related to eventual break-shift in rainfall regime and/or (ii) other socio-economic factors. BFAST (Verbesselt et al, 2010) R package are employed to lead a comprehensive breakpoint analysis on 10-day RFE (spatial mean and standard deviation) and 10-day NDVI ones (spatial mean, mode and standard deviation). The cross-viewing of the years where significant breaks have occurred, throughout opportune GIS layering, provides an explorative interpretation of spatial climate/vegetation dynamics in the whole area. Moreover, the spatial and temporal pattern of ecosystem dynamics in response to climatic variability has been investigated using wavelet coherency by SOWAS R package (Maraun, 2007). The wavelet coherency (WCOH) is a normalized time and scale resolved measure for the relationship between two time series (Maraun and Kurths, 2004). This kind of multi-scale temporal investigation provides an explanation of break detected in time series, confirming or not their climatic linkage; results of the analysis are shown. Finally, in order to support the dissemination and sharing of information, interactive vegetation maps have been implemented with Google Earth mash-up. The maturity of Web-based GIS enables the generation of thematic maps dynamically and efficiently, with a thin/thick client or hybrid architectures. This could be a great support for the understanding environmental phenomena.

Spatial patterns of ecohydrologic properties on a hillslope-alluvial fan transect, central New Mexico

USGS Publications Warehouse

Bedford, D.R.; Small, E.E.

2008-01-01

Spatial patterns of soil properties are linked to patchy vegetation in arid and semi-arid landscapes. The patterns of soil properties are generally assumed to be linked to the ecohydrological functioning of patchy dryland vegetation ecosystems. We studied the effects of vegetation canopy, its spatial pattern, and landforms on soil properties affecting overland flow and infiltration in shrublands at the Sevilleta National Wildlife Refuge/LTER in central New Mexico, USA. We studied the patterns of microtopography and saturated conductivity (Ksat), and generally found it to be affected by vegetation canopy and pattern, as well as landform type. On gently sloping alluvial fans, both microtopography and Ksat are high under vegetation canopy and decay with distance from plant center. On steeper hillslope landforms, only microtopography was significantly higher under vegetation canopy, while there was no significant difference in Ksat between vegetation and interspaces. Using geostatistics, we found that the spatial pattern of soil properties was determined by the spatial pattern of vegetation. Most importantly, the effects of vegetation were present in the unvegetated interspaces 2-4 times the extent of vegetation canopy, on the order of 2-3??m. Our results have implications for the understanding the ecohydrologic function of semi-arid ecosystems as well as the parameterization of hydrologic models. ?? 2007 Elsevier B.V. All rights reserved.

The Interplay among Acorn Abundance and Rodent Behavior Drives the Spatial Pattern of Seedling Recruitment in Mature Mediterranean Oak Forests.

PubMed

Sunyer, Pau; Boixadera, Ester; Muñoz, Alberto; Bonal, Raúl; Espelta, Josep Maria

2015-01-01

The patterns of seedling recruitment in animal-dispersed plants result from the interactions among environmental and behavioral variables. However, we know little on the contribution and combined effect of both kinds of variables. We designed a field study to assess the interplay between environment (vegetation structure, seed abundance, rodent abundance) and behavior (seed dispersal and predation by rodents, and rooting by wild boars), and their contribution to the spatial patterns of seedling recruitment in a Mediterranean mixed-oak forest. In a spatially explicit design, we monitored intensively all environmental and behavioral variables in fixed points at a small spatial scale from autumn to spring, as well as seedling emergence and survival. Our results revealed that the spatial patterns of seedling emergence were strongly related to acorn availability on the ground, but not by a facilitation effect of vegetation cover. Rodents changed seed shadows generated by mother trees by dispersing most seeds from shrubby to open areas, but the spatial patterns of acorn dispersal/predation had no direct effect on recruitment. By contrast, rodents had a strong impact on recruitment as pilferers of cached seeds. Rooting by wild boars also reduced recruitment by reducing seed abundance, but also by changing rodent's behavior towards higher consumption of acorns in situ. Hence, seed abundance and the foraging behavior of scatter-hoarding rodents and wild boars are driving the spatial patterns of seedling recruitment in this mature oak forest, rather than vegetation features. The contribution of vegetation to seedling recruitment (e.g. facilitation by shrubs) may be context dependent, having a little role in closed forests, or being overridden by directed seed dispersal from shrubby to open areas. We warn about the need of using broad approaches that consider the combined action of environment and behavior to improve our knowledge on the dynamics of natural regeneration in forests.

The Interplay among Acorn Abundance and Rodent Behavior Drives the Spatial Pattern of Seedling Recruitment in Mature Mediterranean Oak Forests

PubMed Central

Boixadera, Ester; Bonal, Raúl

2015-01-01

The patterns of seedling recruitment in animal-dispersed plants result from the interactions among environmental and behavioral variables. However, we know little on the contribution and combined effect of both kinds of variables. We designed a field study to assess the interplay between environment (vegetation structure, seed abundance, rodent abundance) and behavior (seed dispersal and predation by rodents, and rooting by wild boars), and their contribution to the spatial patterns of seedling recruitment in a Mediterranean mixed-oak forest. In a spatially explicit design, we monitored intensively all environmental and behavioral variables in fixed points at a small spatial scale from autumn to spring, as well as seedling emergence and survival. Our results revealed that the spatial patterns of seedling emergence were strongly related to acorn availability on the ground, but not by a facilitationeffect of vegetation cover. Rodents changed seed shadows generated by mother trees by dispersing most seeds from shrubby to open areas, but the spatial patterns of acorn dispersal/predation had no direct effect on recruitment. By contrast, rodents had a strong impact on recruitment as pilferers of cached seeds. Rooting by wild boars also reduced recruitment by reducing seed abundance, but also by changing rodent’s behavior towards higher consumption of acorns in situ. Hence, seed abundance and the foraging behavior of scatter-hoarding rodents and wild boars are driving the spatial patterns of seedling recruitment in this mature oak forest, rather than vegetation features. The contribution of vegetation to seedling recruitment (e.g. facilitation by shrubs) may be context dependent, having a little role in closed forests, or being overridden by directed seed dispersal from shrubby to open areas. We warn about the need of using broad approaches that consider the combined action of environment and behavior to improve our knowledge on the dynamics of natural regeneration in forests. PMID:26070129

Signs of critical transition in the Everglades wetlands in response to climate and anthropogenic changes.

PubMed

Foti, Romano; del Jesus, Manuel; Rinaldo, Andrea; Rodriguez-Iturbe, Ignacio

2013-04-16

The increasing pressure of climatic change and anthropogenic activities is predicted to have major effects on ecosystems around the world. With their fragility and sensitivity to hydrologic shifts and land-use changes, wetlands are among the most vulnerable of such ecosystems. Focusing on the Everglades National Park, we here assess the impact of changes in the hydrologic regime, as well as habitat loss, on the spatial configuration of vegetation species. Because the current structuring of vegetation clusters in the Everglades exhibits power-law behavior and such behavior is often associated with self-organization and dynamics occurring near critical transition points, the quantification and prediction of the impact of those changes on the ecosystem is deemed of paramount importance. We implement a robust model able to identify the main hydrologic and local drivers of the vegetation species spatial structuring and apply it for quantitative assessment. We find that shifts in the hydropatterns will mostly affect the relative abundance of species that currently colonize specific hydroperiod niches. Habitat loss or disruption, however, would have a massive impact on all plant communities, which are found to exhibit clear threshold behaviors when a given percentage of habitable habitat is lost.

Signs of critical transition in the Everglades wetlands in response to climate and anthropogenic changes

PubMed Central

Foti, Romano; del Jesus, Manuel; Rinaldo, Andrea; Rodriguez-Iturbe, Ignacio

2013-01-01

The increasing pressure of climatic change and anthropogenic activities is predicted to have major effects on ecosystems around the world. With their fragility and sensitivity to hydrologic shifts and land-use changes, wetlands are among the most vulnerable of such ecosystems. Focusing on the Everglades National Park, we here assess the impact of changes in the hydrologic regime, as well as habitat loss, on the spatial configuration of vegetation species. Because the current structuring of vegetation clusters in the Everglades exhibits power-law behavior and such behavior is often associated with self-organization and dynamics occurring near critical transition points, the quantification and prediction of the impact of those changes on the ecosystem is deemed of paramount importance. We implement a robust model able to identify the main hydrologic and local drivers of the vegetation species spatial structuring and apply it for quantitative assessment. We find that shifts in the hydropatterns will mostly affect the relative abundance of species that currently colonize specific hydroperiod niches. Habitat loss or disruption, however, would have a massive impact on all plant communities, which are found to exhibit clear threshold behaviors when a given percentage of habitable habitat is lost. PMID:23576751

The patch mosaic and ecological decomposition across spatial scales in a managed landscape of northern Wisconsin, USA

Treesearch

Sari C. ​Saunders; Jiquan Chen; Thomas D. Drummer; Thomas R. Crow; Kimberley D. Brosofske; Eric J. Gustafson

2002-01-01

Understanding landscape organization across scales is vital for determining the impacts of management and retaining structurally and functionally diverse ecosystems. We studied the relationships of a functional variable, decomposition, to microclimatic, vegetative and structural features at multiple scales in two distinct landscapes of northern Wisconsin, USA. We hoped...

Allocating fuel breaks to optimally protect structures in the wildland-urban interface

Treesearch

Avi Bar-Massada; Volker C. Radeloff; Susan I. Stewart

2011-01-01

Wildland fire is a major concern in the wildland-urban interface (WUI), where human structures intermingle with wildland vegetation. Reducing wildfire risk in the WUI is more complicated than in wildland areas, owing to interactions between spatial patterns of housing and wildland fuels. Fuel treatments are commonly applied in wildlands surrounding WUI communities....

Effects of Fine-Scale Landscape Variability on Satellite-Derived Land Surface Temperature Products Over Sparse Vegetation Canopies

NASA Astrophysics Data System (ADS)

Powell, R. L.; Goulden, M.; Peterson, S.; Roberts, D. A.; Still, C. J.

2015-12-01

Temperature is a primary environmental control on biological systems and processes at a range of spatial and temporal scales, from controlling biochemical processes such as photosynthesis to influencing continental-scale species distribution. The Landsat satellite series provides a long record (since the mid-1980s) of relatively high spatial resolution thermal infrared (TIR) imagery, from which we derive land surface temperature (LST) grids. Here, we investigate fine spatial resolution factors that influence Landsat-derived LST over a spectrally and spatially heterogeneous landscape. We focus on paired sites (inside/outside a 1994 fire scar) within a pinyon-juniper scrubland in Southern California. The sites have nearly identical micro-meteorology and vegetation species composition, but distinctly different vegetation abundance and structure. The tower at the unburned site includes a number of in-situ imaging tools to quantify vegetation properties, including a thermal camera on a pan-tilt mount, allowing hourly characterization of landscape component temperatures (e.g., sunlit canopy, bare soil, leaf litter). We use these in-situ measurements to assess the impact of fine-scale landscape heterogeneity on estimates of LST, including sensitivity to (i) the relative abundance of component materials, (ii) directional effects due to solar and viewing geometry, (iii) duration of sunlit exposure for each compositional type, and (iv) air temperature. To scale these properties to Landsat spatial resolution (~100-m), we characterize the sub-pixel composition of landscape components (in addition to shade) by applying spectral mixture analysis (SMA) to the Landsat Operational Land Imager (OLI) spectral bands and test the sensitivity of the relationships established with the in-situ data at this coarser scale. The effects of vegetation abundance and cover height versus other controls on satellite-derived estimates of LST will be assessed by comparing estimates at the burned vs. unburned sites across multiple seasons (~30 dates).

Roles of climate, vegetation and soil in regulating the spatial variations in ecosystem carbon dioxide fluxes in the Northern Hemisphere.

PubMed

Chen, Zhi; Yu, Guirui; Ge, Jianping; Wang, Qiufeng; Zhu, Xianjin; Xu, Zhiwei

2015-01-01

Climate, vegetation, and soil characteristics play important roles in regulating the spatial variation in carbon dioxide fluxes, but their relative influence is still uncertain. In this study, we compiled data from 241 eddy covariance flux sites in the Northern Hemisphere and used Classification and Regression Trees and Redundancy Analysis to assess how climate, vegetation, and soil affect the spatial variations in three carbon dioxide fluxes (annual gross primary production (AGPP), annual ecosystem respiration (ARE), and annual net ecosystem production (ANEP)). Our results showed that the spatial variations in AGPP, ARE, and ANEP were significantly related to the climate and vegetation factors (correlation coefficients, R = 0.22 to 0.69, P < 0.01) while they were not related to the soil factors (R = -0.11 to 0.14, P > 0.05) in the Northern Hemisphere. The climate and vegetation together explained 60% and 58% of the spatial variations in AGPP and ARE, respectively. Climate factors (mean annual temperature and precipitation) could account for 45-47% of the spatial variations in AGPP and ARE, but the climate constraint on the vegetation index explained approximately 75%. Our findings suggest that climate factors affect the spatial variations in AGPP and ARE mainly by regulating vegetation properties, while soil factors exert a minor effect. To more accurately assess global carbon balance and predict ecosystem responses to climate change, these discrepant roles of climate, vegetation, and soil are required to be fully considered in the future land surface models. Moreover, our results showed that climate and vegetation factors failed to capture the spatial variation in ANEP and suggest that to reveal the underlying mechanism for variation in ANEP, taking into account the effects of other factors (such as climate change and disturbances) is necessary.

Roles of Climate, Vegetation and Soil in Regulating the Spatial Variations in Ecosystem Carbon Dioxide Fluxes in the Northern Hemisphere

PubMed Central

Chen, Zhi; Yu, Guirui; Ge, Jianping; Wang, Qiufeng; Zhu, Xianjin; Xu, Zhiwei

2015-01-01

Climate, vegetation, and soil characteristics play important roles in regulating the spatial variation in carbon dioxide fluxes, but their relative influence is still uncertain. In this study, we compiled data from 241 eddy covariance flux sites in the Northern Hemisphere and used Classification and Regression Trees and Redundancy Analysis to assess how climate, vegetation, and soil affect the spatial variations in three carbon dioxide fluxes (annual gross primary production (AGPP), annual ecosystem respiration (ARE), and annual net ecosystem production (ANEP)). Our results showed that the spatial variations in AGPP, ARE, and ANEP were significantly related to the climate and vegetation factors (correlation coefficients, R = 0.22 to 0.69, P < 0.01) while they were not related to the soil factors (R = -0.11 to 0.14, P > 0.05) in the Northern Hemisphere. The climate and vegetation together explained 60 % and 58 % of the spatial variations in AGPP and ARE, respectively. Climate factors (mean annual temperature and precipitation) could account for 45 - 47 % of the spatial variations in AGPP and ARE, but the climate constraint on the vegetation index explained approximately 75 %. Our findings suggest that climate factors affect the spatial variations in AGPP and ARE mainly by regulating vegetation properties, while soil factors exert a minor effect. To more accurately assess global carbon balance and predict ecosystem responses to climate change, these discrepant roles of climate, vegetation, and soil are required to be fully considered in the future land surface models. Moreover, our results showed that climate and vegetation factors failed to capture the spatial variation in ANEP and suggest that to reveal the underlying mechanism for variation in ANEP, taking into account the effects of other factors (such as climate change and disturbances) is necessary. PMID:25928452

Spatial-temporal Evolution of Vegetation Coverage and Analysis of it’s Future Trends in Wujiang River Basin

NASA Astrophysics Data System (ADS)

Xiao, Jianyong; Bai, Xiaoyong; Zhou, Dequan; Qian, Qinghuan; Zeng, Cheng; Chen, Fei

2018-01-01

Vegetation coverage dynamics is affected by climatic, topography and human activities, which is an important indicator reflecting the regional ecological environment. Revealing the spatial-temporal characteristics of vegetation coverage is of great significance to the protection and management of ecological environment. Based on MODIS NDVI data and the Maximum Value Composites (MVC), we excluded soil spectrum interference to calculate Fractional Vegetation Coverage (FVC). Then the long-term FVC was used to calculate the spatial pattern and temporal variation of vegetation in Wujiang River Basin from 2000 to 2016 by using Trend analysis and Hurst index. The relationship between topography and spatial distribution of FVC was analyzed. The main conclusions are as follows: (1) The multi-annual mean vegetation coverage reveals a spatial distribution variation characteristic of low value in midstream and high level in other parts of the basin, owing a mean value of 0.6567. (2) From 2000 to 2016, the FVC of the Wujiang River Basin fluctuated between 0.6110 and 0.7380, and the overall growth rate of FVC was 0.0074/a. (3) The area of vegetation coverage tending to improve is more than that going to degrade in the future. Grass land, Arable land and Others improved significantly; karst rocky desertification comprehensive management project lead to persistent vegetation coverage improvement of Grass land, Arable land and Others. Residential land is covered with obviously degraded vegetation, resulting of urban sprawl; (4) The spatial distribution of FVC is positively correlated with TNI. Researches of spatial-temporal evolution of vegetation coverage have significant meaning for the ecological environment protection and management of the Wujiang River Basin.

Spatial heterogeneity study of vegetation coverage at Heihe River Basin

NASA Astrophysics Data System (ADS)

Wu, Lijuan; Zhong, Bo; Guo, Liyu; Zhao, Xiangwei

2014-11-01

Spatial heterogeneity of the animal-landscape system has three major components: heterogeneity of resource distributions in the physical environment, heterogeneity of plant tissue chemistry, heterogeneity of movement modes by the animal. Furthermore, all three different types of heterogeneity interact each other and can either reinforce or offset one another, thereby affecting system stability and dynamics. In previous studies, the study areas are investigated by field sampling, which costs a large amount of manpower. In addition, uncertain in sampling affects the quality of field data, which leads to unsatisfactory results during the entire study. In this study, remote sensing data is used to guide the sampling for research on heterogeneity of vegetation coverage to avoid errors caused by randomness of field sampling. Semi-variance and fractal dimension analysis are used to analyze the spatial heterogeneity of vegetation coverage at Heihe River Basin. The spherical model with nugget is used to fit the semivariogram of vegetation coverage. Based on the experiment above, it is found, (1)there is a strong correlation between vegetation coverage and distance of vegetation populations within the range of 0-28051.3188m at Heihe River Basin, but the correlation loses suddenly when the distance greater than 28051.3188m. (2)The degree of spatial heterogeneity of vegetation coverage at Heihe River Basin is medium. (3)Spatial distribution variability of vegetation occurs mainly on small scales. (4)The degree of spatial autocorrelation is 72.29% between 25% and 75%, which means that spatial correlation of vegetation coverage at Heihe River Basin is medium high.

Identification and Simulation of Subsurface Soil patterns using hidden Markov random fields and remote sensing and geophysical EMI data sets

NASA Astrophysics Data System (ADS)

Wang, Hui; Wellmann, Florian; Verweij, Elizabeth; von Hebel, Christian; van der Kruk, Jan

2017-04-01

Lateral and vertical spatial heterogeneity of subsurface properties such as soil texture and structure influences the available water and resource supply for crop growth. High-resolution mapping of subsurface structures using non-invasive geo-referenced geophysical measurements, like electromagnetic induction (EMI), enables a characterization of 3D soil structures, which have shown correlations to remote sensing information of the crop states. The benefit of EMI is that it can return 3D subsurface information, however the spatial dimensions are limited due to the labor intensive measurement procedure. Although active and passive sensors mounted on air- or space-borne platforms return 2D images, they have much larger spatial dimensions. Combining both approaches provides us with a potential pathway to extend the detailed 3D geophysical information to a larger area by using remote sensing information. In this study, we aim at extracting and providing insights into the spatial and statistical correlation of the geophysical and remote sensing observations of the soil/vegetation continuum system. To this end, two key points need to be addressed: 1) how to detect and recognize the geometric patterns (i.e., spatial heterogeneity) from multiple data sets, and 2) how to quantitatively describe the statistical correlation between remote sensing information and geophysical measurements. In the current study, the spatial domain is restricted to shallow depths up to 3 meters, and the geostatistical database contains normalized difference vegetation index (NDVI) derived from RapidEye satellite images and apparent electrical conductivities (ECa) measured from multi-receiver EMI sensors for nine depths of exploration ranging from 0-2.7 m. The integrated data sets are mapped into both the physical space (i.e. the spatial domain) and feature space (i.e. a two-dimensional space framed by the NDVI and the ECa data). Hidden Markov Random Fields (HMRF) are employed to model the underlying heterogeneities in spatial domain and finite Gaussian mixture models are adopted to quantitatively describe the statistical patterns in terms of center vectors and covariance matrices in feature space. A recently developed parallel stochastic clustering algorithm is adopted to implement the HMRF models and the Markov chain Monte Carlo based Bayesian inference. Certain spatial patterns such as buried paleo-river channels covered by shallow sediments are investigated as typical examples. The results indicate that the geometric patterns of the subsurface heterogeneity can be represented and quantitatively characterized by HMRF. Furthermore, the statistical patterns of the NDVI and the EMI data from the soil/vegetation-continuum system can be inferred and analyzed in a quantitative manner.

Regional and local species richness in an insular environment: Serpentine plants in California

USGS Publications Warehouse

Harrison, S.; Safford, H.D.; Grace, J.B.; Viers, J.H.; Davies, K.F.

2006-01-01

We asked how the richness of the specialized (endemic) flora of serpentine rock outcrops in California varies at both the regional and local scales. Our study had two goals: first, to test whether endemic richness is affected by spatial habitat structure (e.g., regional serpentine area, local serpentine outcrop area, regional and local measures of outcrop isolation), and second, to conduct this test in the context of a broader assessment of environmental influences (e.g., climate, soils, vegetation, disturbance) and historical influences (e.g., geologic age, geographic province) on local and regional species richness. We measured endemic and total richness and environmental variables in 109 serpentine sites (1000-m2 paired plots) in 78 serpentine-containing regions of the state. We used structural equation modeling (SEM) to simultaneously relate regional richness to regionalscale predictors, and local richness to both local-scale and regional-scale predictors. Our model for serpentine endemics explained 66% of the variation in local endemic richness based on local environment (vegetation, soils, rock cover) and on regional endemic richness. It explained 73% of the variation in regional endemic richness based on regional environment (climate and productivity), historical factors (geologic age and geographic province), and spatial structure (regional total area of serpentine, the only significant spatial variable in our analysis). We did not find a strong influence of spatial structure on species richness. However, we were able to distinguish local vs. regional influences on species richness to a novel extent, despite the existence of correlations between local and regional conditions. ?? 2006 by the Ecological Society of America.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model.

PubMed

Shafer, Sarah L; Bartlein, Patrick J; Gray, Elizabeth M; Pelltier, Richard T

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0-58.0°N latitude by 136.6-103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070-2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Spatial Self-Organization of Vegetation Subject to Climatic Stress-Insights from a System Dynamics-Individual-Based Hybrid Model.

PubMed

Vincenot, Christian E; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco

2016-01-01

In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)-Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non-linearly total biomass density. Remarkably, lower precipitation resulted in lower mean plant age yet higher mean individual biomass. Moreover, seasonal variations in rainfall greater than a threshold (here, ±0.45 mm from the 1.3 mm baseline) decreased mean total biomass and generated limit cycles, which, in the case of large variations, were preceded by chaotic demographic and spatial behavior. In some cases, peculiar spatial patterns (e.g., rings) were also engendered. On a technical note, the shortcomings of the present model and the benefit of hybrid modeling for virtual investigations in plant science are discussed.

Spatial Self-Organization of Vegetation Subject to Climatic Stress—Insights from a System Dynamics—Individual-Based Hybrid Model

PubMed Central

Vincenot, Christian E.; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco

2016-01-01

In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)—Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non-linearly total biomass density. Remarkably, lower precipitation resulted in lower mean plant age yet higher mean individual biomass. Moreover, seasonal variations in rainfall greater than a threshold (here, ±0.45 mm from the 1.3 mm baseline) decreased mean total biomass and generated limit cycles, which, in the case of large variations, were preceded by chaotic demographic and spatial behavior. In some cases, peculiar spatial patterns (e.g., rings) were also engendered. On a technical note, the shortcomings of the present model and the benefit of hybrid modeling for virtual investigations in plant science are discussed. PMID:27252707

Ecosystem engineering varies spatially: a test of the vegetation modification paradigm for prairie dogs

USGS Publications Warehouse

Baker, Bruce W.; Augustine, David J.; Sedgwick, James A.; Lubow, Bruce C.

2013-01-01

Colonial, burrowing herbivores can be engineers of grassland and shrubland ecosystems worldwide. Spatial variation in landscapes suggests caution when extrapolating single-place studies of single species, but lack of data and the need to generalize often leads to ‘model system’ thinking and application of results beyond appropriate statistical inference. Generalizations about the engineering effects of prairie dogs (Cynomys sp.) developed largely from intensive study at a single complex of black-tailed prairie dogs C. ludovicianus in northern mixed prairie, but have been extrapolated to other ecoregions and prairie dog species in North America, and other colonial, burrowing herbivores. We tested the paradigm that prairie dogs decrease vegetation volume and the cover of grasses and tall shrubs, and increase bare ground and forb cover. We sampled vegetation on and off 279 colonies at 13 complexes of 3 prairie dog species widely distributed across 5 ecoregions in North America. The paradigm was generally supported at 7 black-tailed prairie dog complexes in northern mixed prairie, where vegetation volume, grass cover, and tall shrub cover were lower, and bare ground and forb cover were higher, on colonies than at paired off-colony sites. Outside the northern mixed prairie, all 3 prairie dog species consistently reduced vegetation volume, but their effects on cover of plant functional groups varied with prairie dog species and the grazing tolerance of dominant perennial grasses. White-tailed prairie dogs C. leucurus in sagebrush steppe did not reduce shrub cover, whereas black-tailed prairie dogs suppressed shrub cover at all complexes with tall shrubs in the surrounding habitat matrix. Black-tailed prairie dogs in shortgrass steppe and Gunnison's prairie dogs C. gunnisoni in Colorado Plateau grassland both had relatively minor effects on grass cover, which may reflect the dominance of grazing-tolerant shortgrasses at both complexes. Variation in modification of vegetation structure may be understood in terms of the responses of different dominant perennial grasses to intense defoliation and differences in foraging behavior among prairie dog species. Spatial variation in the engineering role of prairie dogs suggests spatial variation in their keystone role, and spatial variation in the roles of other ecosystem engineers. Thus, ecosystem engineering can have a spatial component not evident from single-place studies.

Post Fire Vegetation Recovery in Portugal

NASA Astrophysics Data System (ADS)

Gouveia, Celia; Bastos, Ana; DaCamara, Carlos; Trigo, Ricardo M.

2011-01-01

Fires in Portugal, as in the Mediterranean ecosystems, have a complex effect on vegetation regeneration due to the different responses of vegetation to the variety of fire regimes and to the complexity of landscape structures. A thorough evaluation of vegetation recovery after fire events becomes therefore crucial in land management. In 2005, Portugal suffered a strong damage from forest fires that damaged an area of 300 000 ha of forest and shrub. This year are particularly interesting because it is associated the severe drought of 2005. The aim of the present study is to identify large burnt scars in Portugal during the 2005 fire seasons and monitoring vegetation behaviour throughout the pre and the post fire periods. The mono-parametric model developed by Gouveia et al. (2010), based on monthly values of NDVI, at the 1km×1km spatial scale, as obtained from the VEGETATION-SPOT5 instrument, from 1999 to 2009, was used.

The spatial distribution and temporal variation of desert riparian forests and their influencing factors in the downstream Heihe River basin, China

NASA Astrophysics Data System (ADS)

Ding, Jingyi; Zhao, Wenwu; Daryanto, Stefani; Wang, Lixin; Fan, Hao; Feng, Qiang; Wang, Yaping

2017-05-01

Desert riparian forests are the main restored vegetation community in Heihe River basin. They provide critical habitats and a variety of ecosystem services in this arid environment. Since desert riparian forests are also sensitive to disturbance, examining the spatial distribution and temporal variation of these forests and their influencing factors is important to determine the limiting factors of vegetation recovery after long-term restoration. In this study, field experiment and remote sensing data were used to determine the spatial distribution and temporal variation of desert riparian forests and their relationship with the environmental factors. We classified five types of vegetation communities at different distances from the river channel. Community coverage and diversity formed a bimodal pattern, peaking at the distances of 1000 and 3000 m from the river channel. In general, the temporal normalized difference vegetation index (NDVI) trend from 2000 to 2014 was positive at different distances from the river channel, except for the region closest to the river bank (i.e. within 500 m from the river channel), which had been undergoing degradation since 2011. The spatial distribution of desert riparian forests was mainly influenced by the spatial heterogeneity of soil properties (e.g. soil moisture, bulk density and soil particle composition). Meanwhile, while the temporal variation of vegetation was affected by both the spatial heterogeneity of soil properties (e.g. soil moisture and soil particle composition) and to a lesser extent, the temporal variation of water availability (e.g. annual average and variability of groundwater, soil moisture and runoff). Since surface (0-30 cm) and deep (100-200 cm) soil moisture, bulk density and the annual average of soil moisture at 100 cm obtained from the remote sensing data were regarded as major determining factors of community distribution and temporal variation, conservation measures that protect the soil structure and prevent soil moisture depletion (e.g. artificial soil cover and water conveyance channels) were suggested to better protect desert riparian forests under climate change and intensive human disturbance.

Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI)

NASA Technical Reports Server (NTRS)

Donnellan, Andrea; Rosen, Paul; Ranson, Jon; Zebker, Howard

2008-01-01

The National Research Council Earth Science Decadal Survey, Earth Science Applications from Space, recommends that DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice), an integrated L-band InSAR and multibeam Lidar mission, launch in the 2010- 2013 timeframe. The mission will measure surface deformation for solid Earth and cryosphere objectives and vegetation structure for understanding the carbon cycle. InSAR has been used to study surface deformation of the solid Earth and cryosphere and more recently vegetation structure for estimates of biomass and ecosystem function. Lidar directly measures topography and vegetation structure and is used to estimate biomass and detect changes in surface elevation. The goal of DESDynI is to take advantage of the spatial continuity of InSAR and the precision and directness of Lidar. There are several issues related to the design of the DESDynI mission, including combining the two instruments into a single platform, optimizing the coverage and orbit for the two techniques, and carrying out the science modeling to define and maximize the scientific output of the mission.

Modeling the effects of vegetation heterogeneity on wildland fire behavior

NASA Astrophysics Data System (ADS)

Atchley, A. L.; Linn, R.; Sieg, C.; Middleton, R. S.

2017-12-01

Vegetation structure and densities are known to drive fire-spread rate and burn severity. Many fire-spread models incorporate an average, homogenous fuel density in the model domain to drive fire behavior. However, vegetation communities are rarely homogenous and instead present significant heterogeneous structure and fuel densities in the fires path. This results in observed patches of varied burn severities and mosaics of disturbed conditions that affect ecological recovery and hydrologic response. Consequently, to understand the interactions of fire and ecosystem functions, representations of spatially heterogeneous conditions need to be incorporated into fire models. Mechanistic models of fire disturbance offer insight into how fuel load characterization and distribution result in varied fire behavior. Here we use a physically-based 3D combustion model—FIRETEC—that solves conservation of mass, momentum, energy, and chemical species to compare fire behavior on homogenous representations to a heterogeneous vegetation distribution. Results demonstrate the impact vegetation heterogeneity has on the spread rate, intensity, and extent of simulated wildfires thus providing valuable insight in predicted wildland fire evolution and enhanced ability to estimate wildland fire inputs into regional and global climate models.

Differences in the structure and functioning of two communities: Frondose and turf-forming macroalgal dominated habitats.

PubMed

M Martins, Gustavo; Hipólito, Cláudia; Parreira, Filipe; C L Prestes, Afonso; Dionísio, Maria A; N Azevedo, José M; Neto, Ana I

2016-05-01

In many coastal regions, vegetated habitats (e.g. kelps forests, seagrass beds) play a key role in the structure and functioning of shallow subtidal reef ecosystems, by modifying local environmental conditions and by providing food and habitat for a wide range of organisms. In some regions of the world, however, such idiosyncratic ecosystems are largely absent and are often replaced by less notable ecosystem formers. In the present study, we empirically compared the structure and functioning of two distinct shallow-water habitats present in the Azores: one dominated by smaller frondose brown macroalgae (Dictyotaceae and Halopteris) and one dominated by low-lying turfs. Two replicated areas of each habitat were sampled at two different times of the year, to assess spatial and temporal consistency of results. Habitats dominated by small fronds were significantly (ca. 3 times) more productive (when standardized per algal mass) compared to the turf-dominated habitats, and supported a distinct assemblage (both in terms of composition and abundance) of associated macrofauna. Unlike other well-known and studied vegetated habitats (i.e. kelp forests), however, no effects of habitat were found on the structure of benthonic fish assemblages. Results were spatially and temporally consistent suggesting that, in warmer temperate oceans, habitats dominated by species of smaller frondose brown algae can also play an important role in the structure and functioning of subtidal communities and may, to a certain extent, be considered analogous to other well-known vegetated habitats around the world (i.e. kelp forests, seagrass beds). Copyright © 2016 Elsevier Ltd. All rights reserved.

Historical and current forest and range landscapes in the interior Columbia River basin and portions of the Klamath and Great Basins. Part 1: Linking vegetation patterns and landscape vulnerability to potential insect and pathogen disturbances.

Treesearch

Paul F. Hessburg; Bradley G. Smith; Scott D. Kreiter; Craig A. Miller; R. Brion Salter; Cecilia H. McNicoll; Wendel J. Hann

1999-01-01

Management activities of the 20th century, especially fire exclusion, timber harvest, and domestic livestock grazing, have significantly modified vegetation spatial patterns of forests and ranges in the interior Columbia basin. Compositional patterns as well as patterns of living and dead structure have changed. Dramatic change in vital ecosystem processes such as fire...

Stair-Step Pattern of Soil Bacterial Diversity Mainly Driven by pH and Vegetation Types Along the Elevational Gradients of Gongga Mountain, China

PubMed Central

Li, Jiabao; Shen, Zehao; Li, Chaonan; Kou, Yongping; Wang, Yansu; Tu, Bo; Zhang, Shiheng; Li, Xiangzhen

2018-01-01

Ecological understandings of soil bacterial community succession and assembly mechanism along elevational gradients in mountains remain not well understood. Here, by employing the high-throughput sequencing technique, we systematically examined soil bacterial diversity patterns, the driving factors, and community assembly mechanisms along the elevational gradients of 1800–4100 m on Gongga Mountain in China. Soil bacterial diversity showed an extraordinary stair-step pattern along the elevational gradients. There was an abrupt decrease of bacterial diversity between 2600 and 2800 m, while no significant change at either lower (1800–2600 m) or higher (2800–4100 m) elevations, which coincided with the variation in soil pH. In addition, the community structure differed significantly between the lower and higher elevations, which could be primarily attributed to shifts in soil pH and vegetation types. Although there was no direct effect of MAP and MAT on bacterial community structure, our partial least squares path modeling analysis indicated that bacterial communities were indirectly influenced by climate via the effect on vegetation and the derived effect on soil properties. As for bacterial community assembly mechanisms, the null model analysis suggested that environmental filtering played an overwhelming role in the assembly of bacterial communities in this region. In addition, variation partition analysis indicated that, at lower elevations, environmental attributes explained much larger fraction of the β-deviation than spatial attributes, while spatial attributes increased their contributions at higher elevations. Our results highlight the importance of environmental filtering, as well as elevation-related spatial attributes in structuring soil bacterial communities in mountain ecosystems. PMID:29636740

Investigating the influence of LiDAR ground surface errors on the utility of derived forest inventories

Treesearch

Wade T. Tinkham; Alistair M. S. Smith; Chad Hoffman; Andrew T. Hudak; Michael J. Falkowski; Mark E. Swanson; Paul E. Gessler

2012-01-01

Light detection and ranging, or LiDAR, effectively produces products spatially characterizing both terrain and vegetation structure; however, development and use of those products has outpaced our understanding of the errors within them. LiDAR's ability to capture three-dimensional structure has led to interest in conducting or augmenting forest inventories with...

Using satellite and airborne LiDAR to model woodpecker habitat occupancy at the landscape scale

Treesearch

Lee A. Vierling; Kerri T. Vierling; Patrick Adam; Andrew T. Hudak

2013-01-01

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR...

Identification of the key ecological factors influencing vegetation degradation in semi-arid agro-pastoral ecotone considering spatial scales

NASA Astrophysics Data System (ADS)

Peng, Yu; Wang, Qinghui; Fan, Min

2017-11-01

When assessing re-vegetation project performance and optimizing land management, identification of the key ecological factors inducing vegetation degradation has crucial implications. Rainfall, temperature, elevation, slope, aspect, land use type, and human disturbance are ecological factors affecting the status of vegetation index. However, at different spatial scales, the key factors may vary. Using Helin County, Inner-Mongolia, China as the study site and combining remote sensing image interpretation, field surveying, and mathematical methods, this study assesses key ecological factors affecting vegetation degradation under different spatial scales in a semi-arid agro-pastoral ecotone. It indicates that the key factors are different at various spatial scales. Elevation, rainfall, and temperature are identified as crucial for all spatial extents. Elevation, rainfall and human disturbance are key factors for small-scale quadrats of 300 m × 300 m and 600 m × 600 m, temperature and land use type are key factors for a medium-scale quadrat of 1 km × 1 km, and rainfall, temperature, and land use are key factors for large-scale quadrats of 2 km × 2 km and 5 km × 5 km. For this region, human disturbance is not the key factor for vegetation degradation across spatial scales. It is necessary to consider spatial scale for the identification of key factors determining vegetation characteristics. The eco-restoration programs at various spatial scales should identify key influencing factors according their scales so as to take effective measurements. The new understanding obtained in this study may help to explore the forces which driving vegetation degradation in the degraded regions in the world.

Assessing vegetation structure and ANPP dynamics in a grassland-shrubland Chihuahuan ecotone using NDVI-rainfall relationships

NASA Astrophysics Data System (ADS)

Moreno-de las Heras, M.; Diaz-Sierra, R.; Turnbull, L.; Wainwright, J.

2015-01-01

Climate change and the widespread alteration of natural habitats are major drivers of vegetation change in drylands. A classic case of vegetation change is the shrub-encroachment process that has been taking place over the last 150 years in the Chihuahuan Desert, where large areas of grasslands dominated by perennial grass species (black grama, Bouteloua eriopoda, and blue grama, B. gracilis) have transitioned to shrublands dominated by woody species (creosotebush, Larrea tridentata, and mesquite, Prosopis glandulosa), accompanied by accelerated water and wind erosion. Multiple mechanisms drive the shrub-encroachment process, including exogenous triggering factors such as precipitation variations and land-use change, and endogenous amplifying mechanisms brought about by soil erosion-vegetation feedbacks. In this study, simulations of plant biomass dynamics with a simple modelling framework indicate that herbaceous (grasses and forbs) and shrub vegetation in drylands have different responses to antecedent precipitation due to functional differences in plant growth and water-use patterns, and therefore shrub encroachment may be reflected in the analysis of landscape-scale vegetation-rainfall relationships. We analyze the structure and dynamics of vegetation at an 18 km2 grassland-shrubland ecotone in the northern edge of the Chihuahuan Desert (McKenzie Flats, Sevilleta National Wildlife Refuge, NM, USA) by investigating the relationship between decade-scale (2000-2013) records of medium-resolution remote sensing of vegetation greenness (MODIS NDVI) and precipitation. Spatial evaluation of NDVI-rainfall relationship at the studied ecotone indicates that herbaceous vegetation shows quick growth pulses associated with short-term (previous 2 months) precipitation, while shrubs show a slow response to medium-term (previous 5 months) precipitation. We use these relationships to (a) classify landscape types as a function of the spatial distribution of dominant vegetation, and to (b) decompose the NDVI signal into partial primary production components for herbaceous vegetation and shrubs across the study site. We further apply remote-sensed annual net primary production (ANPP) estimations and landscape type classification to explore the influence of inter-annual variations in seasonal precipitation on the production of herbaceous and shrub vegetation. Our results suggest that changes in the amount and temporal pattern of precipitation comprising reductions in monsoonal summer rainfall and/or increases in winter precipitation may enhance the shrub-encroachment process in desert grasslands of the American Southwest.

Land use, spatial scale, and stream systems: Lessons from an agricultural region

USGS Publications Warehouse

Vondracek, B.; Blann, K.L.; Cox, C.B.; Nerbonne, J.F.; Mumford, K.G.; Nerbonne, B.A.; Sovell, L.A.; Zimmerman, J.K.H.

2005-01-01

We synthesized nine studies that examined the influence of land use at different spatial scales in structuring biotic assemblages and stream channel characteristics in southeastern Minnesota streams. Recent studies have disagreed about the relative importance of catchment versus local characteristics in explaining variation in fish assemblages. Our synthesis indicates that both riparian- and catchment-scale land use explained significant variation in water quality, channel morphology, and fish distribution and density. Fish and macroinvertebrate assemblages can be positively affected by increasing the extent of perennial riparian and upland vegetation. Our synthesis is robust; more than 425 stream reaches were examined in an area that includes a portion of three ecoregions. Fishes ranged from coldwater to warmwater adapted. We suggest that efforts to rehabilitate stream system form and function over the long term should focus on increasing perennial vegetation in both riparian areas and uplands and on managing vegetation in large, contiguous blocks. ?? 2005 Springer Science+Business Media, Inc.

Beyond habitat structure: Landscape heterogeneity explains the monito del monte (Dromiciops gliroides) occurrence and behavior at habitats dominated by exotic trees.

PubMed

Salazar, Daniela A; Fontúrbel, Francisco E

2016-09-01

Habitat structure determines species occurrence and behavior. However, human activities are altering natural habitat structure, potentially hampering native species due to the loss of nesting cavities, shelter or movement pathways. The South American temperate rainforest is experiencing an accelerated loss and degradation, compromising the persistence of many native species, and particularly of the monito del monte (Dromiciops gliroides Thomas, 1894), an arboreal marsupial that plays a key role as seed disperser. Aiming to compare 2 contrasting habitats (a native forest and a transformed habitat composed of abandoned Eucalyptus plantations and native understory vegetation), we assessed D. gliroides' occurrence using camera traps and measured several structural features (e.g. shrub and bamboo cover, deadwood presence, moss abundance) at 100 camera locations. Complementarily, we used radio telemetry to assess its spatial ecology, aiming to depict a more complete scenario. Moss abundance was the only significant variable explaining D. gliroides occurrence between habitats, and no structural variable explained its occurrence at the transformed habitat. There were no differences in home range, core area or inter-individual overlapping. In the transformed habitats, tracked individuals used native and Eucalyptus-associated vegetation types according to their abundance. Diurnal locations (and, hence, nesting sites) were located exclusively in native vegetation. The landscape heterogeneity resulting from the vicinity of native and Eucalyptus-associated vegetation likely explains D. gliroides occurrence better than the habitat structure itself, as it may be use Eucalyptus-associated vegetation for feeding purposes but depend on native vegetation for nesting. © 2016 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Spatial and spectral resolution necessary for remotely sensed vegetation studies

NASA Technical Reports Server (NTRS)

Rock, B. N.

1982-01-01

An outline is presented of the required spatial and spectral resolution needed for accurate vegetation discrimination and mapping studies as well as for determination of state of health (i.e., detection of stress symptoms) of actively growing vegetation. Good success was achieved in vegetation discrimination and mapping of a heterogeneous forest cover in the ridge and valley portion of the Appalachians using multispectral data acquired with a spatial resolution of 15 m (IFOV). A sensor system delivering 10 to 15 m spatial resolution is needed for both vegetation mapping and detection of stress symptoms. Based on the vegetation discrimination and mapping exercises conducted at the Lost River site, accurate products (vegetation maps) are produced using broad-band spectral data ranging from the .500 to 2.500 micron portion of the spectrum. In order of decreasing utility for vegetation discrimination, the four most valuable TM simulator VNIR bands are: 6 (1.55 to 1.75 microns), 3 (0.63 to 0.69 microns), 5 (1.00 to 1.30 microns) and 4 (0.76 to 0.90 microns).

From high spatial resolution imagery to spatial indicators : Application for hydromorphy follow-up on Bourgneuf wetland

NASA Astrophysics Data System (ADS)

Bailly, J. S.; Puech, C.; Lukac, F.; Massé, J.

2003-04-01

On Atlantic coastal wetlands, the understanding of hydrological processes may refer to hydraulic surface structures characterization as small ditches or channels networks, permanent and temporary water bodies. Moreover to improve the understanding, this characerization should be realized regarding different seasons and different spatial scales: elementary parcel, managment unit and whole wetland scales. In complement to usual observations on a few local ground points, high spatial resolution remote sensing may be a good information support for extraction and characterization on elementary objects, especially water bodies, permanents or temporary ones and ditches. To carry out a floow-up on wetlands, a seasonal image acquisition rate, reachable from most of satelite systems, is in that case informative for hydrological needs. In this work, georeferencing methods on openfield wetlands have been handled with care in order to use diachronic images or combined geographical data; lack of relief, short vegetation and well structured landscape make this preprocess easier in comparison to other landscape situations. In this presentation we focus on spatial hydromorphy parameters constructed from images with specific processes. Especially, hydromorphy indicators for parcels or managment units have been developped using an IRC winter-spring-summer metric resolution set of images: these descriptors are based on water areas evolution or hydrophyl vegetations presence traducing hydrodynamic submersion behaviour in temporary water bodies. An other example presents a surface water network circulation indicator elaborated on IRC aerial photography combined with vectorized geographic database. This indicator is based on ditches width and vegetation presence : a specific process uses vectorized geo data set to define transects across ditches on which classified image analysis is carried out (supervised classification). These first results proposing hydromorphy descriptors from very high resolution don't give complete indicators for follow-up and monitoring of coastal wetlands, but their combinaison, aggregation should present good technical bases to carry it out with success.

Global sampling of the seasonal changes in vegetation biophysical properties and associated carbon flux dynamics: using the synergy of information captured by spectral time series

NASA Astrophysics Data System (ADS)

Campbell, P. K. E.; Huemmrich, K. F.; Middleton, E.; Voorhis, S.; Landis, D.

2016-12-01

Spatial heterogeneity and seasonal dynamics in vegetation function contribute significantly to the uncertainties in regional and global CO2 budgets. High spectral resolution imaging spectroscopy ( 10 nm, 400-2500 nm) provides an efficient tool for synoptic evaluation of the factors significantly affecting the ability of the vegetation to sequester carbon and to reflect radiation, due to changes in vegetation chemical and structural composition. EO-1 Hyperion has collected more than 15 years of repeated observations for vegetation studies, and currently Hyperion time series are available for study of vegetation carbon dynamics at a number of FLUX sites. This study presents results from the analysis of EO-1 Hyperion and FLUX seasonal composites for a range of ecosystems across the globe. Spectral differences and seasonal trends were evaluated for each vegetation type and specific phenology. Evaluating the relationships between CO2 flux parameters (e.g., Net ecosystem production - NEP; Gross Ecosystem Exchange - GEE, CO2 flux, μmol m-2 s-1) and spectral parameters for these very different ecosystems, high correlations were established to parameters associated with canopy water and chlorophyll content for deciduous, and photosynthetic function for conifers. Imaging spectrometry provided high spatial resolution maps of CO2 fluxes absorbed by vegetation, and was efficient in tracing seasonal flux dynamics. This study will present examples for key ecosystem tipes to demonstrate the ability of imaging spectrometry and EO-1 Hyperion to map and compare CO2 flux dynamics across the globe.

Linking morphology to ecosystem structure using satellite for monitoring Wetlands

NASA Astrophysics Data System (ADS)

Filipponi, F.; Valentini, E.; Taramelli, A.; Giulio, S.; Persichillo, M.; D'Alpaos, A.

2013-12-01

Modern views on the behavior of complex systems, like the low lying coastal areas, allow the interpretation of phenomenological coastal landscape as a steady state that corresponds to a dynamic equilibrium, and to a self-organized exogenic order of the edge of the chaos. Space-borne data, coupled with field spectral measurements and observations, are quantitative tools for the research on feedbacks between the biological influences and physical forming processes steering landscape changes, allowing the identification of critical thresholds beyond which the ecosystem reach a new steady state. This research deals with a multi-temporal change analysis of halophytic vegetation and morphology of two analogous accumulation sites along the northern Adriatic adjoining coast: the 'Bacan island' (Venice Lagoon) and the Spit of Goro Lagoon (Po Delta). These two sites represent delicate ecosystems and are susceptible to different drivers being located close to the lagoon's inlet. The two tests sites support a great biodiversity and supply important resources, so the conservation of their habitats is necessary to maintain the ecosystem services provision. Evidence from previous studies highlights the role of climate, mostly winds and hydrology acting on sediment transport, but only few accounts for the role of vegetation in landform shaping and sediment stabilizing. In this study spatial trends of both vegetation cover/typology and sediment/soil distribution are implemented to obtain detailed classification from EO. By means of sub-pixel processing techniques (Spectral Mixing Analysis), classifications are analyzed in terms of spatial (Power law) and temporal (Empirical Orthogonal Functions) patterns, in order to find the fingerprint of spatial patterns of vegetation, sediments and very shallow waters and their variation over time. The application of a double step analysis from coarse to finer spatial resolution lead first to a biophysical cover map in term of vegetation typologies and cover percent, sediment typology and length of the different branches highlighting the mosaic of spatial pattern of vegetation, sediments and morphology. Then our results support the fact that the most frequent patch sizes, corresponding to the smallest vegetation patches as consistent with a power law relationship, are associated with the highest length values and specific sediments values; as the patch sizes become larger, and thus less frequent, the length next to patches decreases and reaches much lower values in relations to sediments classes. This indicates that at first, the formation of small vegetation patches increases flow resistance and facilitates the formation of new morphology; at the same time, when a threshold size is reached (due to patch growth or merging between adjacent patches), vegetation controls length of the different branches. In the framework of spatial self-organization, this method gives rise to a new approach to the study of landscape-forming processes, taking into account the prominent role of living organisms in shaping Earth's surface, in order to develop new instruments and tools that allow modular variation of spatial and temporal scales of observation (i.e. from local to regional; from seasonal to inter annual) that is mandatory for a valuable implementation of current management and conservation strategies (Integrated Coastal Zone Management).

Vegetation Coverage and Impervious Surface Area Estimated Based on the Estarfm Model and Remote Sensing Monitoring

NASA Astrophysics Data System (ADS)

Hu, Rongming; Wang, Shu; Guo, Jiao; Guo, Liankun

2018-04-01

Impervious surface area and vegetation coverage are important biophysical indicators of urban surface features which can be derived from medium-resolution images. However, remote sensing data obtained by a single sensor are easily affected by many factors such as weather conditions, and the spatial and temporal resolution can not meet the needs for soil erosion estimation. Therefore, the integrated multi-source remote sensing data are needed to carry out high spatio-temporal resolution vegetation coverage estimation. Two spatial and temporal vegetation coverage data and impervious data were obtained from MODIS and Landsat 8 remote sensing images. Based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), the vegetation coverage data of two scales were fused and the data of vegetation coverage fusion (ESTARFM FVC) and impervious layer with high spatiotemporal resolution (30 m, 8 day) were obtained. On this basis, the spatial variability of the seepage-free surface and the vegetation cover landscape in the study area was measured by means of statistics and spatial autocorrelation analysis. The results showed that: 1) ESTARFM FVC and impermeable surface have higher accuracy and can characterize the characteristics of the biophysical components covered by the earth's surface; 2) The average impervious surface proportion and the spatial configuration of each area are different, which are affected by natural conditions and urbanization. In the urban area of Xi'an, which has typical characteristics of spontaneous urbanization, landscapes are fragmented and have less spatial dependence.

Modelling of Space-Time Soil Moisture in Savannas and its Relation to Vegetation Patterns

NASA Astrophysics Data System (ADS)

Rodriguez-Iturbe, I.; Mohanty, B.; Chen, Z.

2017-12-01

A physically derived space-time representation of the soil moisture field is presented. It includes the incorporation of a "jitter" process acting over the space-time soil moisture field and accounting for the short distance heterogeneities in topography, soil, and vegetation characteristics. The modelling scheme allows for the representation of spatial random fluctuations of soil moisture at small spatial scales and reproduces quite well the space-time correlation structure of soil moisture from a field study in Oklahoma. It is shown that the islands of soil moisture above different thresholds have sizes which follow power distributions over an extended range of scales. A discussion is provided about the possible links of this feature with the observed power law distributions of the clusters of trees in savannas.

Spatial variability of soils in a seasonally dry tropical forest

NASA Astrophysics Data System (ADS)

Pulla, Sandeep; Riotte, Jean; Suresh, Hebbalalu; Dattaraja, Handanakere; Sukumar, Raman

2016-04-01

Soil structures communities of plants and soil organisms in tropical forests. Understanding the controls of soil spatial variability can therefore potentially inform efforts towards forest restoration. We studied the relationship between soils and lithology, topography, vegetation and fire in a seasonally dry tropical forest in southern India. We extensively sampled soil (available nutrients, Al, pH, and moisture), rocks, relief, woody vegetation, and spatial variation in fire burn frequency in a permanent 50-ha plot. Lower elevation soils tended to be less moist and were depleted in several nutrients and clay. The availability of several nutrients was, in turn, linked to whole-rock chemical composition differences since some lithologies were associated with higher elevations, while the others tended to dominate lower elevations. We suggest that local-scale topography in this region has been shaped by the spatial distribution of lithologies, which differ in their susceptibility to weathering. Nitrogen availability was uncorrelated with the presence of trees belonging to Fabaceae, a family associated with N-fixing species. No effect of burning on soil parameters could be discerned at this scale.

Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.

USGS Publications Warehouse

Shafer, Sarah; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model

PubMed Central

Shafer, Sarah L.; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas. PMID:26488750

A New Global LAI Product and Its Use for Terrestrial Carbon Cycle Estimation

NASA Astrophysics Data System (ADS)

Chen, J. M.; Liu, R.; Ju, W.; Liu, Y.

2014-12-01

For improving the estimation of the spatio-temporal dynamics of the terrestrial carbon cycle, a new time series of the leaf area index (LAI) is generated for the global land surface at 8 km resolution from 1981 to 2012 by combining AVHRR and MODIS satellite data. This product differs from existing LAI products in the following two aspects: (1) the non-random spatial distribution of leaves with the canopy is considered, and (2) the seasonal variation of the vegetation background is included. The non-randomness of the leaf spatial distribution in the canopy is considered using the second vegetation structural parameter named clumping index (CI), which quantifies the deviation of the leaf spatial distribution from the random case. Using the MODIS Bidirectional Reflectance Distribution Function product, a global map of CI is produced at 500 m resolution. In our LAI algorithm, CI is used to convert the effective LAI obtained from mono-angle remote sensing into the true LAI, otherwise LAI would be considerably underestimated. The vegetation background is soil in crop, grass and shrub but includes soil, grass, moss, and litter in forests. Through processing a large volume of MISR data from 2000 to 2010, monthly red and near-infrared reflectances of the vegetation background is mapped globally at 1 km resolution. This new LAI product has been validated extensively using ground-based LAI measurements distributed globally. In carbon cycle modeling, the use of CI in addition to LAI allows for accurate separation of sunlit and shaded leaves as an important step in terrestrial photosynthesis and respiration modeling. Carbon flux measurements over 100 sites over the globe are used to validate an ecosystem model named Boreal Ecosystem Productivity Simulator (BEPS). The validated model is run globally at 8 km resolution for the period from 1981 to 2012 using the LAI product and other spatial datasets. The modeled results suggest that changes in vegetation structure as quantified by LAI do not contribute significantly to the increasing trend in carbon sink over the last 32 years. The increases in atmospheric CO2 concentration and nitrogen deposition are found to be the major causes for the increases in plant productivity and carbon sink over the last 32 years.

Variation in soil enzyme activity as a function of vegetation amount, type, and spatial structure in fire-prone Mediterranean shrublands.

PubMed

Mayor, Ángeles G; Goirán, Silvana B; Vallejo, V Ramón; Bautista, Susana

2016-12-15

Fire-prone Mediterranean shrublands may be seriously threatened by land degradation due to progressive opening of the vegetation cover driven by increasing drought and fire recurrence. However, information about the consequences of this opening process for critical ecosystem functions is scant. In this work, we studied the influence of vegetation amount, type, and spatial pattern in the variation of extracellular soil enzyme activity (acid phosphatase, β-glucosidase, and urease) in fire-prone shrublands in eastern Spain. Soil was sampled in vegetation-patch and open-interpatch microsites in 15 shrubland sites affected by large wildfires in 1991. On average, the activities of the three enzymes were 1.5 (β-glucosidase and urease) to 1.7 (acid phosphatase) times higher in soils under vegetation patches than in adjacent interpatches. In addition, phosphatase activity for both microsites significantly decreased with the fragmentation of the vegetation. This result was attributed to a lower influence of roots -the main source of acid phosphatase- in the bigger interpatches of the sites with lower patch cover, and to feedbacks between vegetation pattern, redistribution of resources, and soil quality during post-fire vegetation dynamics. Phosphatase activity was also 1.2 times higher in patches of resprouter plants than in patches of non-resprouters, probably due to the faster post-fire recovery and older age of resprouter patches in these fire-prone ecosystems. The influence on the studied enzymes of topographic and climatic factors acting at the landscape scale was insignificant. According to our results, variations in the cover, pattern, and composition of vegetation patches may have profound impacts on soil enzyme activity and associated nutrient cycling processes in fire-prone Mediterranean shrublands, particularly in those related to phosphorus. Copyright © 2016 Elsevier B.V. All rights reserved.

Characterising Vegetation Structural and Functional Differences Across Australian Ecosystems From a Network of Terrestrial Laser Scanning Survey Sites and Airborne and Satellite Image Archives

NASA Astrophysics Data System (ADS)

Phinn, S. R.; Armston, J.; Scarth, P.; Johansen, K.; Schaefer, M.; Suarez, L.; Soto-Berelov, M.; Muir, J.; Woodgate, W.; Jones, S.; Held, A. A.

2015-12-01

Vegetation structural information is critical for environmental monitoring, management and compliance assessment. In this context we refer to vegetation structural properties as vertical, horizontal and volumetric dimensions, including: canopy height; amount and distribution of vegetation by height; foliage projective cover (FPC); leaf area index (LAI); and above ground biomass. Our aim was to determine if there were significant differences between vegetation structural properties across 11 ecosystem types in Australia as measured by terrestrial laser scanner (TLS) structure metrics. The ecosystems sampled included: mesophyll vineforest, wet-dry tropical savannah, mallee woodland, subtropical eucalypt forest, mulga woodland/grassland, wet eucalypt forest, dry eucalypt forest, tall and wet eucalypt forest, and desert grassland/shrublands. Canopy height, plant area-height profiles and LAI were calculated from consistently processed TLS data using Australia's Terrestrial Ecosystem Research Network's (TERN) Supersites by the TERN AusCover remote sensing field teams from 2012-2015. The Supersites were sampled using standardised field protocols within a core set of 1 ha plots as part of a 5 km x 5 km uniform area using a RIEGL-VZ400 waveform recording TLS. Four to seven scans were completed per plot, with one centre point and then at 25 m away from the centre point along transect lines at 0o, 60o and 240o. Individual foliage profiles were sensitive to spatial variation in the distribution of plant materials. Significant differences were visible between each of the vegetation communities assessed when aggregated to plot and ecosystem type scales. Several of the communities exhibited simple profiles with either grass and shrubs (e.g. desert grassland) or grass and trees (e.g. mallee woodland). Others had multiple vegetation forms at different heights, contributing to the profile (e.g. wet eucalypt forest). The TLS data provide significantly more detail about the relative vertical and horizontal distribution of plant materials. TLS data are providing a step change in satellite image based vegetation mapping, and refining our knowledge of vegetation structure and its phenological variability. Open access plot scale TLS measurements are available through the TERN Auscover data portal.

Vegetation cover in relation to socioeconomic factors in a tropical city assessed from sub-meter resolution imagery.

PubMed

Martinuzzi, Sebastián; Ramos-González, Olga M; Muñoz-Erickson, Tischa A; Locke, Dexter H; Lugo, Ariel E; Radeloff, Volker C

2018-04-01

Fine-scale information about urban vegetation and social-ecological relationships is crucial to inform both urban planning and ecological research, and high spatial resolution imagery is a valuable tool for assessing urban areas. However, urban ecology and remote sensing have largely focused on cities in temperate zones. Our goal was to characterize urban vegetation cover with sub-meter (<1 m) resolution aerial imagery, and identify social-ecological relationships of urban vegetation patterns in a tropical city, the San Juan Metropolitan Area, Puerto Rico. Our specific objectives were to (1) map vegetation cover using sub-meter spatial resolution (0.3-m) imagery, (2) quantify the amount of residential and non-residential vegetation, and (3) investigate the relationship between patterns of urban vegetation vs. socioeconomic and environmental factors. We found that 61% of the San Juan Metropolitan Area was green and that our combination of high spatial resolution imagery and object-based classification was highly successful for extracting vegetation cover in a moist tropical city (97% accuracy). In addition, simple spatial pattern analysis allowed us to separate residential from non-residential vegetation with 76% accuracy, and patterns of residential and non-residential vegetation varied greatly across the city. Both socioeconomic (e.g., population density, building age, detached homes) and environmental variables (e.g., topography) were important in explaining variations in vegetation cover in our spatial regression models. However, important socioeconomic drivers found in cities in temperate zones, such as income and home value, were not important in San Juan. Climatic and cultural differences between tropical and temperate cities may result in different social-ecological relationships. Our study provides novel information for local land use planners, highlights the value of high spatial resolution remote sensing data to advance ecological research and urban planning in tropical cities, and emphasizes the need for more studies in tropical cities. © 2017 by the Ecological Society of America.

Biological and climate factors co-regulated spatial-temporal dynamics of vegetation autumn phenology on the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zu, Jiaxing; Zhang, Yangjian; Huang, Ke; Liu, Yaojie; Chen, Ning; Cong, Nan

2018-07-01

Climate change is receiving mounting attentions from various fields and phenology is a commonly used indicator signaling vegetation responses to climate change. Previous phenology studies have mostly focused on vegetation greening-up and its climatic driving factors, while autumn phenology has been barely touched upon. In this study, vegetation phenological metrics were extracted from MODIS NDVI data and their temporal and spatial patterns were explored on the Tibetan Plateau (TP). The results showed that the start of season (SOS) has significantly earlier trend in the first decade, while the end of season (EOS) has slightly (not significant) earlier trend. In the spatial dimension, similar patterns were also identified. The SOS plays a more significant role in regulating vegetation growing season length than EOS does. The EOS and driving effects from each factor exhibited spatially heterogeneous patterns. Biological factor is the dominant factor regulating the spatial pattern of EOS, while climate factors control its inter-annual variation.

Dynamic Assessment on the Landscape Patterns and Spatio-temporal Change in the mainstream of Tarim River

NASA Astrophysics Data System (ADS)

Zhang, Hui; Xue, Lianqing; Yang, Changbing; Chen, Xinfang; Zhang, Luochen; Wei, Guanghui

2018-01-01

The Tarim River (TR), as the longest inland river at an arid area in China, is a typical regions of vegetation variation research and plays a crucial role in the sustainable development of regional ecological environment. In this paper, the newest dataset of MODND1M NDVI, at a resolution of 500m, were applied to calculate vegetation index in growing season during the period 2000-2015. Using a vegetation coverage index, a trend line analysis, and the local spatial autocorrelation analysis, this paper investigated the landscape patterns and spatio-temporal variation of vegetation coverage at regional and pixel scales over mainstream of the Tarim River, Xinjiang. The results showed that (1) The bare land area on both sides of Tarim River appeared to have a fluctuated downward trend and there were two obvious valley values in 2005 and 2012. (2) Spatially, the vegetation coverage improved areas is mostly distributed in upstream and the degraded areas is mainly distributed in the left bank of midstream and the end of Tarim River during 2000-2005. (3) The local spatial auto-correlation analysis revealed that vegetation coverage was spatially positive autocorrelated and spatial concentrated. The high-high self-related areas are mainly distributed in upstream, where vegetation cover are relatively good, and the low-low self-related areas are mostly with lower vegetation cover in the lower reaches of Tarim River.

Temporal-spatial distribution of American bison (Bison bison) in a tallgrass prairie fire mosaic

USGS Publications Warehouse

Schuler, K.L.; Leslie, David M.; Shaw, J.H.; Maichak, E.J.

2006-01-01

Fire and bison (Bison bison) are thought to be historically responsible for shaping prairie vegetation in North America. Interactions between temporal-spatial distributions of bison and prescribed burning protocols are important in current restoration of tallgrass prairies. We examined dynamics of bison distribution in a patch-burned tallgrass prairie in the south-central United States relative to bison group size and composition, and burn age and temporal distribution. Bison formed larger mixed groups during summer and smaller sexually segregated groups the rest of the year, and bison selected dormant-season burn patches in the 1st posture growing season most often during spring and summer. Large bison herds selecting recently burned areas resulted in seasonally variable and concentrated grazing pressure that may substantially alter site-specific vegetation. These dynamics must be considered when reintroducing bison and fire into tallgrass prairie because variable outcomes of floral richness and structural complexity are likely depending on temporal-spatial distribution of bison. ?? 2006 American Society of Mammalogists.

Carex sempervirens tussocks induce spatial heterogeneity in litter decomposition, but not in soil properties, in a subalpine grassland in the Central Alps

Treesearch

Fei-Hai Yu; Martin Schutz; Deborah S. Page-Dumroese; Bertil O. Krusi; Jakob Schneller; Otto Wildi; Anita C. Risch

2011-01-01

Tussocks of graminoids can induce spatial heterogeneity in soil properties in dry areas with discontinuous vegetation cover, but little is known about the situation in areas with continuous vegetation and no study has tested whether tussocks can induce spatial heterogeneity in litter decomposition. In a subalpine grassland in the Central Alps where vegetation cover is...

Aspect-related Vegetation Differences Amplify Soil Moisture Variability in Semiarid Landscapes

NASA Astrophysics Data System (ADS)

Yetemen, O.; Srivastava, A.; Kumari, N.; Saco, P. M.

2017-12-01

Soil moisture variability (SMV) in semiarid landscapes is affected by vegetation, soil texture, climate, aspect, and topography. The heterogeneity in vegetation cover that results from the effects of microclimate, terrain attributes (slope gradient, aspect, drainage area etc.), soil properties, and spatial variability in precipitation have been reported to act as the dominant factors modulating SMV in semiarid ecosystems. However, the role of hillslope aspect in SMV, though reported in many field studies, has not received the same degree of attention probably due to the lack of extensive large datasets. Numerical simulations can then be used to elucidate the contribution of aspect-driven vegetation patterns to this variability. In this work, we perform a sensitivity analysis to study on variables driving SMV using the CHILD landscape evolution model equipped with a spatially-distributed solar-radiation component that couples vegetation dynamics and surface hydrology. To explore how aspect-driven vegetation heterogeneity contributes to the SMV, CHILD was run using a range of parameters selected to reflect different scenarios (from uniform to heterogeneous vegetation cover). Throughout the simulations, the spatial distribution of soil moisture and vegetation cover are computed to estimate the corresponding coefficients of variation. Under the uniform spatial precipitation forcing and uniform soil properties, the factors affecting the spatial distribution of solar insolation are found to play a key role in the SMV through the emergence of aspect-driven vegetation patterns. Hence, factors such as catchment gradient, aspect, and latitude, define water stress and vegetation growth, and in turn affect the available soil moisture content. Interestingly, changes in soil properties (porosity, root depth, and pore-size distribution) over the domain are not as effective as the other factors. These findings show that the factors associated to aspect-related vegetation differences amplify the soil moisture variability of semi-arid landscapes.

Soil conservation through sediment trapping: A review

NASA Astrophysics Data System (ADS)

Mekonnen, Mulatie; Keesstra, Saskia; Baartman, Jantiene; Maroulis, Jerry; Stroosnijder, Leo

2014-05-01

Preventing the off-site effects of soil erosion is an essential part of good catchment management. Most efforts are in the form of on-site soil and water conservation measures. However, sediment trapping (ST) can be an alternative (or additional) measure to prevent the negative off-site effects of soil erosion. Therefore, not all efforts should focus solely on on-site soil conservation, but also on the safe routing of sediment-laden flows and on creating sites and conditions where sediment can be trapped, preferably in a cost effective or even profitable way. ST can be applied on-site (in-field) and off-site and involves both vegetative and structural measures. The main vegetative measures include grass strips, tree or bush buffers, grassed waterways and restoration of the waterways and their riparian zone; while structural measures include terraces, ponds and check dams. This paper provides a review of studies that have assessed the sediment trapping efficacy (STE) of such vegetative and structural measures. Vegetation type and integration of two or more measures (vegetative as well as structural) are important factors influencing STE. In this review, the STE of most measures was evaluated either individually or in such combinations. In real landscape situations, it is not only important to select the most efficient erosion control measures, but also to determine their optimum location in the catchment. Hence, there is a need for research that shows a more integrated determination of STE at the catchment scale. If integrated measures are implemented at the most appropriate spatial locations within a catchment where they can disconnect landscape units from each other, they will decrease runoff velocity and sediment transport and, subsequently, reduce downstream flooding and sedimentation problems. KEY WORDS: Integrated sediment trapping, sediment trapping efficacy, vegetative, structural, on-site and off-site measures.

Considerations for achieving cross-platform point cloud data fusion across different dryland ecosystem structural states

USDA-ARS?s Scientific Manuscript database

Dryland ecosystems undergo long periods of senescence punctuated by rapid growth following seasonal precipitation events. Remote sensing of vegetation dynamics which capture new growth as well as herbivory and disturbance require both high spatial and temporal resolution data acquired by various op...

Analysis of shifts in the spatial distribution of vegetation due to climate change

NASA Astrophysics Data System (ADS)

del Jesus, Manuel; Díez-Sierra, Javier; Rinaldo, Andrea; Rodríguez-Iturbe, Ignacio

2017-04-01

Climate change will modify the statistical regime of most climatological variables, inducing changes on average values and in the natural variability of environmental variables. These environmental variables may be used to explain the spatial distribution of functional types of vegetation in arid and semiarid watersheds through the use of plant optimization theories. Therefore, plant optimization theories may be used to approximate the response of the spatial distribution of vegetation to a changing climate. Predicting changes in these spatial distributions is important to understand how climate change may affect vegetated ecosystems, but it is also important for hydrological engineering applications where climate change effects on water availability are assessed. In this work, Maximum Entropy Production (MEP) is used as the plant optimization theory that describes the spatial distribution of functional types of vegetation. Current climatological conditions are obtained from direct observations from meteorological stations. Climate change effects are evaluated for different temporal horizons and different climate change scenarios using numerical model outputs from the CMIP5. Rainfall estimates are downscaled by means of a stochastic point process used to model rainfall. The study is carried out for the Rio Salado watershed, located within the Sevilleta LTER site, in New Mexico (USA). Results show the expected changes in the spatial distribution of vegetation and allow to evaluate the expected variability of the changes. The updated spatial distributions allow to evaluate the vegetated ecosystem health and its updated resilience. These results can then be used to inform the hydrological modeling part of climate change assessments analyzing water availability in arid and semiarid watersheds.

The complex roles of space and environment in structuring functional, taxonomic and phylogenetic beta diversity of frogs in the Atlantic Forest

PubMed Central

Luiz, Amom Mendes; Sawaya, Ricardo J.

2018-01-01

Ecological communities are complex entities that can be maintained and structured by niche-based processes such as environmental conditions, and spatial processes such as dispersal. Thus, diversity patterns may be shaped simultaneously at different spatial scales by very distinct processes. Herein we assess whether and how functional, taxonomic, and phylogenetic beta diversities of frog tadpoles are explained by environmental and/or spatial predictors. We implemented a distance–based redundancy analysis to explore variation in components of beta diversity explained by pure environmental and pure spatial predictors, as well as their interactions, at both fine and broad spatial scales. Our results indicated important but complex roles of spatial and environmental predictors in structuring phylogenetic, taxonomic and functional beta diversities. The pure fine-scales spatial fraction was more important in structuring all beta diversity components, especially to functional and taxonomical spatial turnover. Environmental variables such as canopy cover and vegetation structure were important predictors of all components, but especially to functional and taxonomic beta diversity. We emphasize that distinct factors related to environment and space are affecting distinct components of beta diversity in different ways. Although weaker, phylogenetic beta diversity, which is structured more on biogeographical scales, and thus can be represented by spatially structured processes, was more related to broad spatial processes than other components. However, selected fine-scale spatial predictors denoted negative autocorrelation, which may be revealing the existence of differences in unmeasured habitat variables among samples. Although overall important, local environmental-based processes explained better functional and taxonomic beta diversity, as these diversity components carry an important ecological value. We highlight the importance of assessing different components of diversity patterns at different scales by spatially explicit models in order to improve our understanding of community structure and help to unravel the complex nature of biodiversity. PMID:29672575

Soil Moisture fusion across scales using a multiscale nonstationary Spatial Hierarchical Model

NASA Astrophysics Data System (ADS)

Kathuria, D.; Mohanty, B.; Katzfuss, M.

2017-12-01

Soil moisture (SM) datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors, on the other hand, provide observations on a finer spatial scale (meter scale or less) but are sparsely available. SM is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables and these interactions change dynamically with footprint scales. Past literature has largely focused on the scale specific effect of these covariates on soil moisture. The present study proposes a robust Multiscale-Nonstationary Spatial Hierarchical Model (MN-SHM) which can assimilate SM from point to RS footprints. The spatial structure of SM across footprints is modeled by a class of scalable covariance functions whose nonstationary depends on atmospheric forcings (such as precipitation) and surface physical controls (such as topography, soil-texture and vegetation). The proposed model is applied to fuse point and airborne ( 1.5 km) SM data obtained during the SMAPVEX12 campaign in the Red River watershed in Southern Manitoba, Canada with SMOS ( 30km) data. It is observed that precipitation, soil-texture and vegetation are the dominant factors which affect the SM distribution across various footprint scales (750 m, 1.5 km, 3 km, 9 km,15 km and 30 km). We conclude that MN-SHM handles the change of support problems easily while retaining reasonable predictive accuracy across multiple spatial resolutions in the presence of surface heterogeneity. The MN-SHM can be considered as a complex non-stationary extension of traditional geostatistical prediction methods (such as Kriging) for fusing multi-platform multi-scale datasets.

Use of LANDSAT images of vegetation cover to estimate effective hydraulic properties of soils

NASA Technical Reports Server (NTRS)

Eagleson, Peter S.; Jasinski, Michael F.

1988-01-01

This work focuses on the characterization of natural, spatially variable, semivegetated landscapes using a linear, stochastic, canopy-soil reflectance model. A first application of the model was the investigation of the effects of subpixel and regional variability of scenes on the shape and structure of red-infrared scattergrams. Additionally, the model was used to investigate the inverse problem, the estimation of subpixel vegetation cover, given only the scattergrams of simulated satellite scale multispectral scenes. The major aspects of that work, including recent field investigations, are summarized.

Vegetation recovery assessment following large wildfires in the Mediterranean Basin

NASA Astrophysics Data System (ADS)

Bastos, A.; Gouveia, C. M.; Trigo, R. M.; DaCamara, C. C.

2012-04-01

Mediterranean ecosystems have evolved along with fire, adapting to quick recovering following wildfire events. However, vegetation species respond differently to the changes in fire regimes that have been observed in the past decades in the Mediterranean. These changes, which occurred mainly due to socio-economic and climatic changes, led to dramatic modifications of landscape composition and structure (Malkinson et al., 2011). Post-fire vegetation recovery depends on environmental factors such as landscape features and climatic variables and on specific plant traits; however it also depends on the differentiated response of each species to the characteristics of fire regimes, such as recurrence, severity and extent. The complexity of the interactions between these factors emphasizes the importance of assessing quantitatively post-fire recovery as well as the role of driving factors of regeneration over different regions in the Mediterranean. In 2006, Spain experienced the fire season with larger fires, restricted to a relatively small region of the province of Galicia, that represents more than 60% of total burned area of this fire season (92000ha out of 148827 ha). The 2007 fire season in Greece was remarkably severe, registering the highest value of burnt area (225734 ha) since 1980. Finally, in 2010 a very large wildfire of about 5000 ha occurred in Mount Carmel, Israel, with major social and environmental impacts. The work relies on monthly NDVI data from SPOT/VEGETATION at 1km spatial resolution over the period from September 1998 - August 2011 for Spain, Greece and Israel. Here we have applied the same sequential methodology developed at our laboratory, starting by the identification of very large burnt scars by means of a spatial cluster analysis followed by the application of the monoparametric model (Gouveia et al., 2010; Bastos et al., 2011) in order to study post-fire vegetation dynamics. Post-fire recovery times were estimated for burnt scars from each fire season considered in this study. The influence of driving factors such as pre-fire land-cover type and fire damage on vegetation recovery was assessed by means of a spatial analysis on recovery time fields. Finally, post-fire behaviour of vegetation over the selected regions and the role of the driving factors were compared. This work draws attention to the fact that the simple model applied by Bastos et al. (2011) to monitor vegetation recovery in Portugal following large wildfires is still applicable over other Mediterranean regions using coarse resolution remotely sensed data. Bastos A., Gouveia C., DaCamara C.C., and Trigo R.M.: Modelling post-fire vegetation recovery in Portugal. Biogeosciences, 8, 4559-4601, 2011. Gouveia C., DaCamara C.C. and Trigo R.M.: Post fire vegetation recovery in Portugal based on SPOT-VEGETATION data. Natural Hazards and Earth System Sciences, 10, 673-684, 2010. Malkinson D., Wittenberg, L., Beeri O. and Barzilai R.: Effects of repeated fires on the structure, composition, and dynamics of Mediterranean maquis: Short- and long-term perspectives. Ecosystems, 14, 478-488, 2011.

Disaggregating tree and grass phenology in tropical savannas

NASA Astrophysics Data System (ADS)

Zhou, Qiang

Savannas are mixed tree-grass systems and as one of the world's largest biomes represent an important component of the Earth system affecting water and energy balances, carbon sequestration and biodiversity as well as supporting large human populations. Savanna vegetation structure and its distribution, however, may change because of major anthropogenic disturbances from climate change, wildfire, agriculture, and livestock production. The overstory and understory may have different water use strategies, different nutrient requirements and have different responses to fire and climate variation. The accurate measurement of the spatial distribution and structure of the overstory and understory are essential for understanding the savanna ecosystem. This project developed a workflow for separating the dynamics of the overstory and understory fractional cover in savannas at the continental scale (Australia, South America, and Africa). Previous studies have successfully separated the phenology of Australian savanna vegetation into persistent and seasonal greenness using time series decomposition, and into fractions of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare soil (BS) using linear unmixing. This study combined these methods to separate the understory and overstory signal in both the green and senescent phenological stages using remotely sensed imagery from the MODIS (MODerate resolution Imaging Spectroradiometer) sensor. The methods and parameters were adjusted based on the vegetation variation. The workflow was first tested at the Australian site. Here the PV estimates for overstory and understory showed best performance, however NPV estimates exhibited spatial variation in validation relationships. At the South American site (Cerrado), an additional method based on frequency unmixing was developed to separate green vegetation components with similar phenology. When the decomposition and frequency methods were compared, the frequency method was better for extracting the green tree phenology, but the original decomposition method was better for retrieval of understory grass phenology. Both methods, however, were less accurate than in the Cerrado than in Australia due to intermingling and intergrading of grass and small woody components. Since African savanna trees are predominantly deciduous, the frequency method was combined with the linear unmixing of fractional cover to attempt to separate the relatively similar phenology of deciduous trees and seasonal grasses. The results for Africa revealed limitations associated with both methods. There was spatial and seasonal variation in the spectral indices used to unmix fractional cover resulting in poor validation for NPV in particular. The frequency analysis revealed significant phase variation indicative of different phenology, but these could not be clearly ascribed to separate grass and tree components. Overall findings indicate that site-specific variation and vegetation structure and composition, along with MODIS pixel resolution, and the simple vegetation index approach used was not robust across the different savanna biomes. The approach showed generally better performance for estimating PV fraction, and separating green phenology, but there were major inconsistencies, errors and biases in estimation of NPV and BS outside of the Australian savanna environment.

Exploring the role of trees in the evolution of meander bends: The Tagliamento River, Italy

NASA Astrophysics Data System (ADS)

Zen, Simone; Gurnell, Angela M.; Zolezzi, Guido; Surian, Nicola

2017-07-01

To date, the role of riparian trees in the formation of scroll bars, ridges, and swales during the evolution of meandering channels has been inferred largely from field observations with support from air photographs. In situ field observations are usually limited to relatively short periods of time, whereas the evolution of these morphological features may take decades. By combining field observations of inner bank morphology and overlying riparian woodland structure with a detailed historical analysis of airborne LiDAR data, panchromatic, and color images, we reconstruct the spatial and temporal evolution of the morphology and vegetation across four meander bends of the Tagliamento River, Italy. Specifically we reveal (i) the appearance of deposited trees and elongated vegetated patches on the inner bank of meander bends following flood events; (ii) temporal progression from deposited trees, through small to larger elongated vegetated patches (pioneer islands), to their coalescence into long, linear vegetated features that eventually become absorbed into the continuous vegetation cover of the riparian forest; and (iii) a spatial correspondence between the resulting scrolls and ridge and swale topography, and tree cover development and persistence. We provide a conceptual model of the mechanisms by which vegetation can contribute to the formation of sequence of ridges and swales on the convex bank of meander bends. We discuss how these insights into the biomorphological processes that control meander bends advance can inform modeling activities that aim to describe the lateral and vertical accretion of the floodplain during the evolution of vegetated river meanders.

Multiseasonal variables in digital image enhancements for geological applications

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Vitorello, I.; Almeidafilho, R.

1984-01-01

Examples of enhanced multiseasonal orbital imagery illustrate the influence of multiseasonal changes in their spatial and spectral attributes, and consequently in their application to structural geology and lithological discrimination. Shadow effects associated with appropriate solar elevation and azimuth effects enhance the spatial attributes but not the spectral. In this case, variations in illumination conditions should be minimized by selecting images with high solar elevation and by the use of techniques that minimize illumination conditions. Multiseasonal imagery should be used in the identification of spectral contrast changes of rock-soil-vegetation associations which can provide evidences of related lithological units and structural features. The extraction of maximum geological information requires, at least, a fall/winter and a spring/summer scene from which spatial, spectral and multiseasonal attributes can be adequately explored.

[Continuity and discontinuity of the geomerida: the bionomic and biotic aspects].

PubMed

Kafanov, A I

2005-01-01

The view of the spatial structure of the geomerida (Earth's life cover) as a continuum that prevails in modern phytocoenology is mostly determined by a physiognomic (landscape-bionomic) discrimination of vegetation components. In this connection, geography of life forms appears as subject of the landscapebionomic biogeography. In zoocoenology there is a tendency of synthesis of alternative concepts based on the assumption that there are no absolute continuum and absolute discontinuum in the organic nature. The problem of continuum and discontinuum of living cover being problem of scale aries from fractal structure of geomerida. This problem arises from fractal nature of the spatial structure of geomerida. The continuum mainly belongs to regularities of topological order. At regional and subregional scale the continuum of biochores is rather rare. The objective evidences of relative discontinuity of the living cover are determined by significant alterations of species diversity at the regional, subregional and even topological scale Alternatively to conventionally discriminated units in physionomically continuous vegetation, the same biotic complexes, represented as operational units of biogeographical and biocenological zoning, are distinguished repeatedly and independently by different researchers. An area occupied by certain flora (fauna, biota) could be considered as elementary unit of biotic diversity (elementary biotic complex).

Maximum entropy production, carbon assimilation, and the spatial organization of vegetation in river basins

PubMed Central

del Jesus, Manuel; Foti, Romano; Rinaldo, Andrea; Rodriguez-Iturbe, Ignacio

2012-01-01

The spatial organization of functional vegetation types in river basins is a major determinant of their runoff production, biodiversity, and ecosystem services. The optimization of different objective functions has been suggested to control the adaptive behavior of plants and ecosystems, often without a compelling justification. Maximum entropy production (MEP), rooted in thermodynamics principles, provides a tool to justify the choice of the objective function controlling vegetation organization. The application of MEP at the ecosystem scale results in maximum productivity (i.e., maximum canopy photosynthesis) as the thermodynamic limit toward which the organization of vegetation appears to evolve. Maximum productivity, which incorporates complex hydrologic feedbacks, allows us to reproduce the spatial macroscopic organization of functional types of vegetation in a thoroughly monitored river basin, without the need for a reductionist description of the underlying microscopic dynamics. The methodology incorporates the stochastic characteristics of precipitation and the associated soil moisture on a spatially disaggregated framework. Our results suggest that the spatial organization of functional vegetation types in river basins naturally evolves toward configurations corresponding to dynamically accessible local maxima of the maximum productivity of the ecosystem. PMID:23213227

Effects of topoclimatic complexity on the composition of woody plant communities.

PubMed

Oldfather, Meagan F; Britton, Matthew N; Papper, Prahlad D; Koontz, Michael J; Halbur, Michelle M; Dodge, Celeste; Flint, Alan L; Flint, Lorriane E; Ackerly, David D

2016-01-01

Topography can create substantial environmental variation at fine spatial scales. Shaped by slope, aspect, hill-position and elevation, topoclimate heterogeneity may increase ecological diversity, and act as a spatial buffer for vegetation responding to climate change. Strong links have been observed between climate heterogeneity and species diversity at broader scales, but the importance of topoclimate for woody vegetation across small spatial extents merits closer examination. We established woody vegetation monitoring plots in mixed evergreen-deciduous woodlands that spanned topoclimate gradients of a topographically heterogeneous landscape in northern California. We investigated the association between the structure of adult and regenerating size classes of woody vegetation and multidimensional topoclimate at a fine scale. We found a significant effect of topoclimate on both single-species distributions and community composition. Effects of topoclimate were evident in the regenerating size class for all dominant species (four Quercus spp., Umbellularia californica and Pseudotsuga menziesii) but only in two dominant species (Quercus agrifolia and Quercus garryana) for the adult size class. Adult abundance was correlated with water balance parameters (e.g. climatic water deficit) and recruit abundance was correlated with an interaction between the topoclimate parameters and conspecific adult abundance (likely reflecting local seed dispersal). However, in all cases, the topoclimate signal was weak. The magnitude of environmental variation across our study site may be small relative to the tolerance of long-lived woody species. Dispersal limitations, management practices and patchy disturbance regimes also may interact with topoclimate, weakening its influence on woody vegetation distributions. Our study supports the biological relevance of multidimensional topoclimate for mixed woodland communities, but highlights that this relationship might be mediated by interacting factors at local scales. Published by Oxford University Press on behalf of the Annals of Botany Company.

Effects of topoclimatic complexity on the composition of woody plant communities

PubMed Central

Oldfather, Meagan F.; Britton, Matthew N.; Papper, Prahlad D.; Koontz, Michael J.; Halbur, Michelle M.; Dodge, Celeste; Flint, Alan L.; Flint, Lorriane E.; Ackerly, David D.

2016-01-01

Topography can create substantial environmental variation at fine spatial scales. Shaped by slope, aspect, hill-position and elevation, topoclimate heterogeneity may increase ecological diversity, and act as a spatial buffer for vegetation responding to climate change. Strong links have been observed between climate heterogeneity and species diversity at broader scales, but the importance of topoclimate for woody vegetation across small spatial extents merits closer examination. We established woody vegetation monitoring plots in mixed evergreen-deciduous woodlands that spanned topoclimate gradients of a topographically heterogeneous landscape in northern California. We investigated the association between the structure of adult and regenerating size classes of woody vegetation and multidimensional topoclimate at a fine scale. We found a significant effect of topoclimate on both single-species distributions and community composition. Effects of topoclimate were evident in the regenerating size class for all dominant species (four Quercus spp., Umbellularia californica and Pseudotsuga menziesii) but only in two dominant species (Quercus agrifolia and Quercus garryana) for the adult size class. Adult abundance was correlated with water balance parameters (e.g. climatic water deficit) and recruit abundance was correlated with an interaction between the topoclimate parameters and conspecific adult abundance (likely reflecting local seed dispersal). However, in all cases, the topoclimate signal was weak. The magnitude of environmental variation across our study site may be small relative to the tolerance of long-lived woody species. Dispersal limitations, management practices and patchy disturbance regimes also may interact with topoclimate, weakening its influence on woody vegetation distributions. Our study supports the biological relevance of multidimensional topoclimate for mixed woodland communities, but highlights that this relationship might be mediated by interacting factors at local scales. PMID:27339048

Comparison of alternative spatial resolutions in the application of a spatially distributed biogeochemical model over complex terrain

USGS Publications Warehouse

Turner, D.P.; Dodson, R.; Marks, D.

1996-01-01

Spatially distributed biogeochemical models may be applied over grids at a range of spatial resolutions, however, evaluation of potential errors and loss of information at relatively coarse resolutions is rare. In this study, a georeferenced database at the 1-km spatial resolution was developed to initialize and drive a process-based model (Forest-BGC) of water and carbon balance over a gridded 54976 km2 area covering two river basins in mountainous western Oregon. Corresponding data sets were also prepared at 10-km and 50-km spatial resolutions using commonly employed aggregation schemes. Estimates were made at each grid cell for climate variables including daily solar radiation, air temperature, humidity, and precipitation. The topographic structure, water holding capacity, vegetation type and leaf area index were likewise estimated for initial conditions. The daily time series for the climatic drivers was developed from interpolations of meteorological station data for the water year 1990 (1 October 1989-30 September 1990). Model outputs at the 1-km resolution showed good agreement with observed patterns in runoff and productivity. The ranges for model inputs at the 10-km and 50-km resolutions tended to contract because of the smoothed topography. Estimates for mean evapotranspiration and runoff were relatively insensitive to changing the spatial resolution of the grid whereas estimates of mean annual net primary production varied by 11%. The designation of a vegetation type and leaf area at the 50-km resolution often subsumed significant heterogeneity in vegetation, and this factor accounted for much of the difference in the mean values for the carbon flux variables. Although area wide means for model outputs were generally similar across resolutions, difference maps often revealed large areas of disagreement. Relatively high spatial resolution analyses of biogeochemical cycling are desirable from several perspectives and may be particularly important in the study of the potential impacts of climate change.

Landscape-scale accessibility of livestock to tigers: implications of spatial grain for modeling predation risk to mitigate human-carnivore conflict.

PubMed

Miller, Jennifer R B; Jhala, Yadvendradev V; Jena, Jyotirmay; Schmitz, Oswald J

2015-03-01

Innovative conservation tools are greatly needed to reduce livelihood losses and wildlife declines resulting from human-carnivore conflict. Spatial risk modeling is an emerging method for assessing the spatial patterns of predator-prey interactions, with applications for mitigating carnivore attacks on livestock. Large carnivores that ambush prey attack and kill over small areas, requiring models at fine spatial grains to predict livestock depredation hot spots. To detect the best resolution for predicting where carnivores access livestock, we examined the spatial attributes associated with livestock killed by tigers in Kanha Tiger Reserve, India, using risk models generated at 20, 100, and 200-m spatial grains. We analyzed land-use, human presence, and vegetation structure variables at 138 kill sites and 439 random sites to identify key landscape attributes where livestock were vulnerable to tigers. Land-use and human presence variables contributed strongly to predation risk models, with most variables showing high relative importance (≥0.85) at all spatial grains. The risk of a tiger killing livestock increased near dense forests and near the boundary of the park core zone where human presence is restricted. Risk was nonlinearly related to human infrastructure and open vegetation, with the greatest risk occurring 1.2 km from roads, 1.1 km from villages, and 8.0 km from scrubland. Kill sites were characterized by denser, patchier, and more complex vegetation with lower visibility than random sites. Risk maps revealed high-risk hot spots inside of the core zone boundary and in several patches in the human-dominated buffer zone. Validation against known kills revealed predictive accuracy for only the 20 m model, the resolution best representing the kill stage of hunting for large carnivores that ambush prey, like the tiger. Results demonstrate that risk models developed at fine spatial grains can offer accurate guidance on landscape attributes livestock should avoid to minimize human-carnivore conflict.

Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model

NASA Astrophysics Data System (ADS)

Will, R. M.; Glenn, N. F.; Benner, S. G.; Pierce, J. L.; Spaete, L.; Li, A.

2015-12-01

Quantifying SOC (Soil Organic Carbon) storage in complex terrain is challenging due to high spatial variability. Generally, the challenge is met by transforming point data to the entire landscape using surrogate, spatially-distributed, variables like elevation or precipitation. In many ecosystems, remotely sensed information on above-ground vegetation (e.g. NDVI) is a good predictor of below-ground carbon stocks. In this project, we are attempting to improve this predictive method by incorporating LiDAR-derived vegetation indices. LiDAR provides a mechanism for improved characterization of aboveground vegetation by providing structural parameters such as vegetation height and biomass. In this study, a random forest model is used to predict SOC using a suite of LiDAR-derived vegetation indices as predictor variables. The Reynolds Creek Experimental Watershed (RCEW) is an ideal location for a study of this type since it encompasses a strong elevation/precipitation gradient that supports lower biomass sagebrush ecosystems at low elevations and forests with more biomass at higher elevations. Sagebrush ecosystems composed of Wyoming, Low and Mountain Sagebrush have SOC values ranging from .4 to 1% (top 30 cm), while higher biomass ecosystems composed of aspen, juniper and fir have SOC values approaching 4% (top 30 cm). Large differences in SOC have been observed between canopy and interspace locations and high resolution vegetation information is likely to explain plot scale variability in SOC. Mapping of the SOC reservoir will help identify underlying controls on SOC distribution and provide insight into which processes are most important in determining SOC in semi-arid mountainous regions. In addition, airborne LiDAR has the potential to characterize vegetation communities at a high resolution and could be a tool for improving estimates of SOC at larger scales.

Evaluating Climate Causation of Conflict in Darfur Using Multi-temporal, Multi-resolution Satellite Image Datasets With Novel Analyses

NASA Astrophysics Data System (ADS)

Brown, I.; Wennbom, M.

2013-12-01

Climate change, population growth and changes in traditional lifestyles have led to instabilities in traditional demarcations between neighboring ethic and religious groups in the Sahel region. This has resulted in a number of conflicts as groups resort to arms to settle disputes. Such disputes often centre on or are justified by competition for resources. The conflict in Darfur has been controversially explained by resource scarcity resulting from climate change. Here we analyse established methods of using satellite imagery to assess vegetation health in Darfur. Multi-decadal time series of observations are available using low spatial resolution visible-near infrared imagery. Typically normalized difference vegetation index (NDVI) analyses are produced to describe changes in vegetation ';greenness' or ';health'. Such approaches have been widely used to evaluate the long term development of vegetation in relation to climate variations across a wide range of environments from the Arctic to the Sahel. These datasets typically measure peak NDVI observed over a given interval and may introduce bias. It is furthermore unclear how the spatial organization of sparse vegetation may affect low resolution NDVI products. We develop and assess alternative measures of vegetation including descriptors of the growing season, wetness and resource availability. Expanding the range of parameters used in the analysis reduces our dependence on peak NDVI. Furthermore, these descriptors provide a better characterization of the growing season than the single NDVI measure. Using multi-sensor data we combine high temporal/moderate spatial resolution data with low temporal/high spatial resolution data to improve the spatial representativity of the observations and to provide improved spatial analysis of vegetation patterns. The approach places the high resolution observations in the NDVI context space using a longer time series of lower resolution imagery. The vegetation descriptors derived are evaluated using independent high spatial resolution datasets that reveal the pattern and health of vegetation at metre scales. We also use climate variables to support the interpretation of these data. We conclude that the spatio-temporal patterns in Darfur vegetation and climate datasets suggest that labelling the conflict a climate-change conflict is inaccurate and premature.

Evaluating the capacity of GF-4 satellite data for estimating fractional vegetation cover

NASA Astrophysics Data System (ADS)

Zhang, C.; Qin, Q.; Ren, H.; Zhang, T.; Sun, Y.

2016-12-01

Fractional vegetation cover (FVC) is a crucial parameter for many agricultural, environmental, meteorological and ecological applications, which is of great importance for studies on ecosystem structure and function. The Chinese GaoFen-4 (GF-4) geostationary satellite designed for the purpose of environmental and ecological observation was launched in December 29, 2015, and official use has been started by Chinese Government on June 13, 2016. Multi-spectral images with spatial resolution of 50 m and high temporal resolution, could be acquired by the sensor on GF-4 satellite on the 36000 km-altitude orbit. To take full advantage of the outstanding performance of GF-4 satellite, this study evaluated the capacity of GF-4 satellite data for monitoring FVC. To the best of our knowledge, this is the first research about estimating FVC from GF-4 satellite images. First, we developed a procedure for preprocessing GF-4 satellite data, including radiometric calibration and atmospheric correction, to acquire surface reflectance. Then single image and multi-temporal images were used for extracting the endmembers of vegetation and soil, respectively. After that, dimidiate pixel model and square model based on vegetation indices were used for estimating FVC. Finally, the estimation results were comparatively analyzed with FVC estimated by other existing sensors. The experimental results showed that satisfying accuracy of FVC estimation could be achieved from GF-4 satellite images using dimidiate pixel model and square model based on vegetation indices. What's more, the multi-temporal images increased the probability to find pure vegetation and soil endmembers, thus the characteristic of high temporal resolution of GF-4 satellite images improved the accuracy of FVC estimation. This study demonstrated the capacity of GF-4 satellite data for monitoring FVC. The conclusions reached by this study are significant for improving the accuracy and spatial-temporal resolution of existing FVC products, which provides a basis for the studies on ecosystem structure and function using remote sensing data acquired by GF-4 satellite.

Short-term effects of spring prescribed burning on the understory vegetation of a Pinushalepensis forest in Northeastern Spain.

PubMed

Fuentes, Laura; Duguy, Beatriz; Nadal-Sala, Daniel

2018-01-01

Since the 1970s, fire regimes have been modified in the Northern Mediterranean region due to profound landscape changes mostly driven by socioeconomic factors, such as rural abandonment and large-scale plantations. Both fuel accumulation and the increasing vegetation spatial continuity, combined with the expansion of the wildland-urban interface, have enhanced fire risk and the occurrence of large wildfires. This situation will likely worsen under the projected aridity increase resulting from climate change. Higher fire recurrences, in particular, are expected to cause changes in vegetation composition or structure and affect ecosystems' resilience to fire, which may lead to further land degradation. Prescribed burning is a common fuel reduction technique used for fire prevention, but for conservation and restoration purposes as well. It is still poorly accepted in the Mediterranean region since constrained by critical knowledge gaps about, in particular, its effects on the ecosystems (soil, vegetation). We studied the short-term (10months) effects on the understory vegetation of a spring prescribed burning conducted in a Pinushalepensis forest in Mediterranean climate (Northeastern Spain). Our results show that the understory plant community recovered after the burning without short term significant changes in either species richness, diversity, or floristic composition. Most vegetation structural characteristics were modified though. The burning strongly reduced shrub height, shrub and herbaceous percentage covers, and aerial shrub phytomass; especially its living fine fraction, thus resulting in a less flammable community. The treatment proved to be particularly effective for the short term control of Ulexparviflorus, a highly flammable seeder species. Moreover, the strong reduction of seeder shrubs frequency in relation to resprouters' likely promoted the resilience to fire of this plant community. From a fuel-oriented perspective, the burning caused a strong reduction of spatial continuity and surface fuel loads, leading to a less fire-prone fuel complex. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial vegetation patterns and neighborhood competition among woody plants in an East African savanna

USDA-ARS?s Scientific Manuscript database

The majority of research on savanna vegetation dynamics has focused on the coexistence of woody and herbaceous vegetation; interactions among woody plants in savannas are relatively poorly understood. We present data from a 10-year longitudinal study of spatially explicit growth patterns of woody ve...

Daily monitoring of vegetation conditions and evapotranspiration at field scale by fusing multi-satellite images

USDA-ARS?s Scientific Manuscript database

Vegetation monitoring requires frequent remote sensing observations. While imagery from coarse resolution sensors such as MODIS/VIIRS can provide daily observations, they lack spatial detail to capture surface features for vegetation monitoring. The medium spatial resolution (10-100m) sensors are su...

Spatial and Temporal Distribution of Non-Biting Midge Larvae Assemblages in Streams in a Mountainous Region in Southern Brazil

PubMed Central

Floss, Elzira Cecília Serafini; Secretti, Elisangela; Kotzian, Carla Bender; Spies, Marcia Regina; Pires, Mateus Marques

2013-01-01

The spatial and temporal structure of non-biting midge (Diptera: Chironomidae) larvae assemblages and some environmental factors that affect their distribution were analyzed in a montane river and its tributaries in a temperate climate region of southernmost Brazil. In total, 69 taxa were recorded after four seasonal samplings (winter, spring, summer, and autumn). The dominant taxa were Rheotanytarsus sp. 1, Rheotanytarsus sp. 2, Cricotopus sp. 2, and Polypedilum (Polypedilum) sp., although dominance varied among the four sampling sites. The variations in dominance, abundance, and richness among the different sites were affected by environmental characteristics, such as the presence of marginal vegetation and a heterogeneous substratum, and also by human activities. Strictly environmental factors, such as altitude, and factors related to annual weather patterns, such as mean temperature and precipitation, influenced the spatial and temporal distribution of certain taxa and the structure of faunal assemblages. The influence of the riparian vegetation and riverbed heterogeneity on the composition, richness, and abundance of the chironomid larvae assemblages indicates that human activities, such as deforestation and the construction of dams, constitute a serious threat to the conservation of these insects and to the fauna that depends on them for food. PMID:24784953

Effects of Topography-based Subgrid Structures on Land Surface Modeling

NASA Astrophysics Data System (ADS)

Tesfa, T. K.; Ruby, L.; Brunke, M.; Thornton, P. E.; Zeng, X.; Ghan, S. J.

2017-12-01

Topography has major control on land surface processes through its influence on atmospheric forcing, soil and vegetation properties, network topology and drainage area. Consequently, accurate climate and land surface simulations in mountainous regions cannot be achieved without considering the effects of topographic spatial heterogeneity. To test a computationally less expensive hyper-resolution land surface modeling approach, we developed topography-based landunits within a hierarchical subgrid spatial structure to improve representation of land surface processes in the ACME Land Model (ALM) with minimal increase in computational demand, while improving the ability to capture the spatial heterogeneity of atmospheric forcing and land cover influenced by topography. This study focuses on evaluation of the impacts of the new spatial structures on modeling land surface processes. As a first step, we compare ALM simulations with and without subgrid topography and driven by grid cell mean atmospheric forcing to isolate the impacts of the subgrid topography on the simulated land surface states and fluxes. Recognizing that subgrid topography also has important effects on atmospheric processes that control temperature, radiation, and precipitation, methods are being developed to downscale atmospheric forcings. Hence in the second step, the impacts of the subgrid topographic structure on land surface modeling will be evaluated by including spatial downscaling of the atmospheric forcings. Preliminary results on the atmospheric downscaling and the effects of the new spatial structures on the ALM simulations will be presented.

A morphometric analysis of vegetation patterns in dryland ecosystems

PubMed Central

Dekker, Stefan C.; Li, Mao; Mio, Washington; Punyasena, Surangi W.; Lenton, Timothy M.

2017-01-01

Vegetation in dryland ecosystems often forms remarkable spatial patterns. These range from regular bands of vegetation alternating with bare ground, to vegetated spots and labyrinths, to regular gaps of bare ground within an otherwise continuous expanse of vegetation. It has been suggested that spotted vegetation patterns could indicate that collapse into a bare ground state is imminent, and the morphology of spatial vegetation patterns, therefore, represents a potentially valuable source of information on the proximity of regime shifts in dryland ecosystems. In this paper, we have developed quantitative methods to characterize the morphology of spatial patterns in dryland vegetation. Our approach is based on algorithmic techniques that have been used to classify pollen grains on the basis of textural patterning, and involves constructing feature vectors to quantify the shapes formed by vegetation patterns. We have analysed images of patterned vegetation produced by a computational model and a small set of satellite images from South Kordofan (South Sudan), which illustrates that our methods are applicable to both simulated and real-world data. Our approach provides a means of quantifying patterns that are frequently described using qualitative terminology, and could be used to classify vegetation patterns in large-scale satellite surveys of dryland ecosystems. PMID:28386414

A morphometric analysis of vegetation patterns in dryland ecosystems.

PubMed

Mander, Luke; Dekker, Stefan C; Li, Mao; Mio, Washington; Punyasena, Surangi W; Lenton, Timothy M

2017-02-01

Vegetation in dryland ecosystems often forms remarkable spatial patterns. These range from regular bands of vegetation alternating with bare ground, to vegetated spots and labyrinths, to regular gaps of bare ground within an otherwise continuous expanse of vegetation. It has been suggested that spotted vegetation patterns could indicate that collapse into a bare ground state is imminent, and the morphology of spatial vegetation patterns, therefore, represents a potentially valuable source of information on the proximity of regime shifts in dryland ecosystems. In this paper, we have developed quantitative methods to characterize the morphology of spatial patterns in dryland vegetation. Our approach is based on algorithmic techniques that have been used to classify pollen grains on the basis of textural patterning, and involves constructing feature vectors to quantify the shapes formed by vegetation patterns. We have analysed images of patterned vegetation produced by a computational model and a small set of satellite images from South Kordofan (South Sudan), which illustrates that our methods are applicable to both simulated and real-world data. Our approach provides a means of quantifying patterns that are frequently described using qualitative terminology, and could be used to classify vegetation patterns in large-scale satellite surveys of dryland ecosystems.

A morphometric analysis of vegetation patterns in dryland ecosystems

NASA Astrophysics Data System (ADS)

Mander, Luke; Dekker, Stefan C.; Li, Mao; Mio, Washington; Punyasena, Surangi W.; Lenton, Timothy M.

2017-02-01

Vegetation in dryland ecosystems often forms remarkable spatial patterns. These range from regular bands of vegetation alternating with bare ground, to vegetated spots and labyrinths, to regular gaps of bare ground within an otherwise continuous expanse of vegetation. It has been suggested that spotted vegetation patterns could indicate that collapse into a bare ground state is imminent, and the morphology of spatial vegetation patterns, therefore, represents a potentially valuable source of information on the proximity of regime shifts in dryland ecosystems. In this paper, we have developed quantitative methods to characterize the morphology of spatial patterns in dryland vegetation. Our approach is based on algorithmic techniques that have been used to classify pollen grains on the basis of textural patterning, and involves constructing feature vectors to quantify the shapes formed by vegetation patterns. We have analysed images of patterned vegetation produced by a computational model and a small set of satellite images from South Kordofan (South Sudan), which illustrates that our methods are applicable to both simulated and real-world data. Our approach provides a means of quantifying patterns that are frequently described using qualitative terminology, and could be used to classify vegetation patterns in large-scale satellite surveys of dryland ecosystems.

Tundra landform and vegetation productivity trend maps for the Arctic Coastal Plain of northern Alaska

NASA Astrophysics Data System (ADS)

Lara, Mark J.; Nitze, Ingmar; Grosse, Guido; McGuire, A. David

2018-04-01

Arctic tundra landscapes are composed of a complex mosaic of patterned ground features, varying in soil moisture, vegetation composition, and surface hydrology over small spatial scales (10-100 m). The importance of microtopography and associated geomorphic landforms in influencing ecosystem structure and function is well founded, however, spatial data products describing local to regional scale distribution of patterned ground or polygonal tundra geomorphology are largely unavailable. Thus, our understanding of local impacts on regional scale processes (e.g., carbon dynamics) may be limited. We produced two key spatiotemporal datasets spanning the Arctic Coastal Plain of northern Alaska (~60,000 km2) to evaluate climate-geomorphological controls on arctic tundra productivity change, using (1) a novel 30 m classification of polygonal tundra geomorphology and (2) decadal-trends in surface greenness using the Landsat archive (1999-2014). These datasets can be easily integrated and adapted in an array of local to regional applications such as (1) upscaling plot-level measurements (e.g., carbon/energy fluxes), (2) mapping of soils, vegetation, or permafrost, and/or (3) initializing ecosystem biogeochemistry, hydrology, and/or habitat modeling.

Tundra landform and vegetation productivity trend maps for the Arctic Coastal Plain of northern Alaska.

PubMed

Lara, Mark J; Nitze, Ingmar; Grosse, Guido; McGuire, A David

2018-04-10

Arctic tundra landscapes are composed of a complex mosaic of patterned ground features, varying in soil moisture, vegetation composition, and surface hydrology over small spatial scales (10-100 m). The importance of microtopography and associated geomorphic landforms in influencing ecosystem structure and function is well founded, however, spatial data products describing local to regional scale distribution of patterned ground or polygonal tundra geomorphology are largely unavailable. Thus, our understanding of local impacts on regional scale processes (e.g., carbon dynamics) may be limited. We produced two key spatiotemporal datasets spanning the Arctic Coastal Plain of northern Alaska (~60,000 km 2 ) to evaluate climate-geomorphological controls on arctic tundra productivity change, using (1) a novel 30 m classification of polygonal tundra geomorphology and (2) decadal-trends in surface greenness using the Landsat archive (1999-2014). These datasets can be easily integrated and adapted in an array of local to regional applications such as (1) upscaling plot-level measurements (e.g., carbon/energy fluxes), (2) mapping of soils, vegetation, or permafrost, and/or (3) initializing ecosystem biogeochemistry, hydrology, and/or habitat modeling.

Drivers and feedbacks in spatial and temporal patterning of hydrology and vegetation in the Everglades wetlands

NASA Astrophysics Data System (ADS)

Miralles-Wilhelm, F.; Foti, R.; Rinaldo, A.; Rodriguez-Iturbe, I.; Del Jesus, M.

2013-05-01

Hosting a large variety of vegetal and animal species, many of which rare or endangered, wetlands are among the most rich and vulnerable ecosystems in the world. Throughout the past century, the growing climatic impact and the increasing anthropogenic pressure have seriously threatened their natural equilibrium and substantially deteriorated their ecosystems. For fragility, biodiversity and extension, the Everglades is probably one of the most iconic wetlands in the world. After decades of land seizing and exploitation following the southward march of development in Florida, awareness of the importance of the Everglades wetlands has recently risen, bringing it to the center of one of the largest and most ambitious restoration projects ever attempted. Wetlands equilibrium and biodiversity are crucially linked to the hydrologic regime. In the Everglades, hydroperiods (i.e. percent of time a site is inundated) exert a critical control in the creation of habitat niches for different plant species. However, the feedbacks between the hydrologic signature and the plant dynamics that ultimately yield the observed spatial vegetation patterns are unknown. We identify both the main hydrologic and local drivers of the vegetation species spatial configuration and use them within a robust modeling framework able to reproduce the vegetation structures currently observed in the Everglades. By including both exogenous (i.e. hydrologic) and endogenous (i.e. local interactions) forcings, we are able to describe the mechanisms yielding to the observed power law behavior of the cluster size distribution of vegetation species. Since power law clustering is often associated with self-organization and systems near critical transitions, these findings can be successfully used to quantitatively assess the impact of potential climatic shifts and the effect of habitat loss or deterioration due to human activity, and can assist policy makers in identifying case-specific ecosystems restoration and preservation measures.

Field validation of 1930s aerial photography: What are we missing?

USDA-ARS?s Scientific Manuscript database

Aerial photography from the 1930s serves as the earliest synoptic depiction of vegetation cover. We generated a spatially explicit database of shrub (Prosopis velutina) stand structure within two 1.8 ha field plots established in 1932 to address two questions: (1) What are the detection limits of p...

Historical fire regime and forest variability on two eastern Great Basin fire-sheds (USA)

Treesearch

Stanley G. Kitchen

2012-01-01

Proper management of naturally forested landscapes requires knowledge of key disturbance processes and their effects on species composition and structure. Spatially-intensive fire and forest histories provide valuable information about how fire and vegetation may vary and interact on heterogeneous landscapes. I constructed 800-year fire and tree recruitment...

Stand conditions associated with truffle abundance in western hemlock/Douglas-fir forests

Treesearch

Malcolm North; Joshua Greenberg

1998-01-01

Truffles are a staple food source for many forest small mammals yet the vegetation or soil conditions associated with truffle abundance are unknown. We examined the spatial distribution of forest structures, organic layer depth, root density, and two of the most common western North American truffles (Elaphomyces granulatus and Rhizopogon...

Use of a cable-based system for observing the heterogeneity of vegetation communities in arctic tundra

NASA Astrophysics Data System (ADS)

Ahrends, H. E.; Oberbauer, S. F.; Tweedie, C.; Hollister, R. D.

2010-12-01

Knowledge of changing tundra vegetation and its response to climate variability is critical for understanding the land-atmosphere-interactions for the Arctic and the global system. However, vegetation characteristics, such as phenology, structure and species composition, are characterized by an extreme heterogeneity at a small scale. Manual observations of these variables are highly time-consuming, labor intensive, subjective, and disturbing to the vegetation. In contrast, recently developed robotic systems (networked infomechanical systems, NIMS) allow for performing non-intrusive spatially integrated measurements of vegetation communities. Within the ITEX (International Tundra Experiment) AON (Arctic Observation Network) project we installed a cable-based sensor system, running over a transect of approximately 50 m length and 2 m width, at two long-term arctic research sites in Alaska. The trolley was initially equipped with instruments recording the distance to vegetation canopy, up- and downwelling short- and longwave radiation, air and surface temperature and spectral reflection. We aim to study the thermal and spectral response of the vegetation communities over a wide range of ecosystem types. We expect that automated observations, covering the spatial heterogeneity of vegetation and surface characteristics, can give a deeper insight in ecosystem functioning and vegetation response to climate. The data can be used for scaling up vegetation characteristics derived from manual measurements and for linking them to aircraft and satellite data and to carbon, water and surface energy budgets measured at the ecosystem scale. Sampling errors due to cable sag are correctable and effects of wind-driven movements can be offset by repeat measurements. First hand-pulled test measurements during summer 2010 show strong heterogeneity of the observation parameters and a variable spectral and thermal response of the plants within the transects. Differences support the importance of our approach for upscaling purposes and for a comprehensive understanding of the arctic biome.

Classifying and comparing spatial models of fire dynamics

Treesearch

Geoffrey J. Cary; Robert E. Keane; Mike D. Flannigan

2007-01-01

Wildland fire is a significant disturbance in many ecosystems worldwide and the interaction of fire with climate and vegetation over long time spans has major effects on vegetation dynamics, ecosystem carbon budgets, and patterns of biodiversity. Landscape-Fire-Succession Models (LFSMs) that simulate the linked processes of fire and vegetation development in a spatial...

Physically-based parameterization of spatially variable soil and vegetation using satellite multispectral data

NASA Technical Reports Server (NTRS)

Jasinski, Michael F.; Eagleson, Peter S.

1989-01-01

A stochastic-geometric landsurface reflectance model is formulated and tested for the parameterization of spatially variable vegetation and soil at subpixel scales using satellite multispectral images without ground truth. Landscapes are conceptualized as 3-D Lambertian reflecting surfaces consisting of plant canopies, represented by solid geometric figures, superposed on a flat soil background. A computer simulation program is developed to investigate image characteristics at various spatial aggregations representative of satellite observational scales, or pixels. The evolution of the shape and structure of the red-infrared space, or scattergram, of typical semivegetated scenes is investigated by sequentially introducing model variables into the simulation. The analytical moments of the total pixel reflectance, including the mean, variance, spatial covariance, and cross-spectral covariance, are derived in terms of the moments of the individual fractional cover and reflectance components. The moments are applied to the solution of the inverse problem: The estimation of subpixel landscape properties on a pixel-by-pixel basis, given only one multispectral image and limited assumptions on the structure of the landscape. The landsurface reflectance model and inversion technique are tested using actual aerial radiometric data collected over regularly spaced pecan trees, and using both aerial and LANDSAT Thematic Mapper data obtained over discontinuous, randomly spaced conifer canopies in a natural forested watershed. Different amounts of solar backscattered diffuse radiation are assumed and the sensitivity of the estimated landsurface parameters to those amounts is examined.

Using Vegetation Maps to Provide Information on Soil Distribution

NASA Astrophysics Data System (ADS)

José Ibáñez, Juan; Pérez-Gómez, Rufino; Brevik, Eric C.; Cerdà, Artemi

2016-04-01

Many different types of maps (geology, hydrology, soil, vegetation, etc.) are created to inventory natural resources. Each of these resources is mapped using a unique set of criteria, including scales and taxonomies. Past research has indicated that comparing the results of different but related maps (e.g., soil and geology maps) may aid in identifying deficiencies in those maps. Therefore, this study was undertaken in the Almería Province (Andalusia, Spain) to (i) compare the underlying map structures of soil and vegetation maps and (ii) to investigate if a vegetation map can provide useful soil information that was not shown on a soil map. To accomplish this soil and vegetation maps were imported into ArcGIS 10.1 for spatial analysis. Results of the spatial analysis were exported to Microsoft Excel worksheets for statistical analyses to evaluate fits to linear and power law regression models. Vegetative units were grouped according to the driving forces that determined their presence or absence (P/A): (i) climatophilous (climate is the only determinant of P/A) (ii); lithologic-climate (climate and parent material determine PNV P/A); and (iii) edaphophylous (soil features determine PNV P/A). The rank abundance plots for both the soil and vegetation maps conformed to Willis or Hollow Curves, meaning the underlying structures of both maps were the same. Edaphophylous map units, which represent 58.5% of the vegetation units in the study area, did not show a good correlation with the soil map. Further investigation revealed that 87% of the edaphohygrophylous units (which demand more soil water than is supplied by other soil types in the surrounding landscape) were found in ramblas, ephemeral riverbeds that are not typically classified and mapped as soils in modern systems, even though they meet the definition of soil given by the most commonly used and most modern soil taxonomic systems. Furthermore, these edaphophylous map units tend to be islands of biodiversity that are threatened by anthropogenic activity in the region. Therefore, this study revealed areas in Almería Province that need to be revisited and studied pedologically. The vegetation mapped in these areas and the soils that support it are key components of the earth's critical zone that must be studied, understood, and preserved.

Secondary dispersal driven by overland flow in drylands: Review and mechanistic model development.

PubMed

Thompson, Sally E; Assouline, Shmuel; Chen, Li; Trahktenbrot, Ana; Svoray, Tal; Katul, Gabriel G

2014-01-01

Seed dispersal alters gene flow, reproduction, migration and ultimately spatial organization of dryland ecosystems. Because many seeds in drylands lack adaptations for long-distance dispersal, seed transport by secondary processes such as tumbling in the wind or mobilization in overland flow plays a dominant role in determining where seeds ultimately germinate. Here, recent developments in modeling runoff generation in spatially complex dryland ecosystems are reviewed with the aim of proposing improvements to mechanistic modeling of seed dispersal processes. The objective is to develop a physically-based yet operational framework for determining seed dispersal due to surface runoff, a process that has gained recent experimental attention. A Buoyant OBject Coupled Eulerian - Lagrangian Closure model (BOB-CELC) is proposed to represent seed movement in shallow surface flows. The BOB-CELC is then employed to investigate the sensitivity of seed transport to landscape and storm properties and to the spatial configuration of vegetation patches interspersed within bare earth. The potential to simplify seed transport outcomes by considering the limiting behavior of multiple runoff events is briefly considered, as is the potential for developing highly mechanistic, spatially explicit models that link seed transport, vegetation structure and water movement across multiple generations of dryland plants.

High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision and hobbyist unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Dandois, J. P.; Ellis, E. C.

2013-12-01

High spatial resolution three-dimensional (3D) measurements of vegetation by remote sensing are advancing ecological research and environmental management. However, substantial economic and logistical costs limit this application, especially for observing phenological dynamics in ecosystem structure and spectral traits. Here we demonstrate a new aerial remote sensing system enabling routine and inexpensive aerial 3D measurements of canopy structure and spectral attributes, with properties similar to those of LIDAR, but with RGB (red-green-blue) spectral attributes for each point, enabling high frequency observations within a single growing season. This 'Ecosynth' methodology applies photogrammetric ''Structure from Motion'' computer vision algorithms to large sets of highly overlapping low altitude (< 130 m) aerial photographs acquired using off-the-shelf digital cameras mounted on an inexpensive (< USD$4000), lightweight (< 2 kg), hobbyist-grade unmanned aerial system (UAS). Ecosynth 3D point clouds with densities of 30 - 67 points m-2 were produced using commercial computer vision software from digital photographs acquired repeatedly by UAS over three 6.25 ha (250 m x 250 m) Temperate Deciduous forest sites in Maryland USA. Ecosynth canopy height maps (CHMs) were strong predictors of field-measured tree heights (R2 0.63 to 0.84) and were highly correlated with a LIDAR CHM (R 0.87) acquired 4 days earlier, though Ecosynth-based estimates of aboveground biomass densities included significant errors (31 - 36% of field-based estimates). Repeated scanning of a 0.25 ha forested area at six different times across a 16 month period revealed ecologically significant dynamics in canopy color at different heights and a structural shift upward in canopy density, as demonstrated by changes in vertical height profiles of point density and relative RGB brightness. Changes in canopy relative greenness were highly correlated (R2 = 0.88) with MODIS NDVI time series for the same area and vertical differences in canopy color revealed the early green up of the dominant canopy species, Liriodendron tulipifera, strong evidence that Ecosynth time series measurements capture vegetation structural and spectral dynamics at the spatial scale of individual trees. Observing canopy phenology in 3D at high temporal resolutions represents a breakthrough in forest ecology. Inexpensive user-deployed technologies for multispectral 3D scanning of vegetation at landscape scales (< 1 km2) heralds a new era of participatory remote sensing by field ecologists, community foresters and the interested public.

Monitoring Termite-Mediated Ecosystem Processes Using Moderate and High Resolution Satellite Imagery

NASA Astrophysics Data System (ADS)

Lind, B. M.; Hanan, N. P.

2016-12-01

Termites are considered dominant decomposers and prominent ecosystem engineers in the global tropics and they build some of the largest and architecturally most complex non-human-made structures in the world. Termite mounds significantly alter soil texture, structure, and nutrients, and have major implications for local hydrological dynamics, vegetation characteristics, and biological diversity. An understanding of how these processes change across large scales has been limited by our ability to detect termite mounds at high spatial resolutions. Our research develops methods to detect large termite mounds in savannas across extensive geographic areas using moderate and high resolution satellite imagery. We also investigate the effect of termite mounds on vegetation productivity using Landsat-8 maximum composite NDVI data as a proxy for production. Large termite mounds in arid and semi-arid Senegal generate highly reflective `mound scars' with diameters ranging from 10 m at minimum to greater than 30 m. As Sentinel-2 has several bands with 10 m resolution and Landsat-8 has improved calibration, higher radiometric resolution, 15 m spatial resolution (pansharpened), and improved contrast between vegetated and bare surfaces compared to previous Landsat missions, we found that the largest and most influential mounds in the landscape can be detected. Because mounds as small as 4 m in diameter are easily detected in high resolution imagery we used these data to validate detection results and quantify omission errors for smaller mounds.

Assessment of ASTER data for forest inventory in Canary Islands

NASA Astrophysics Data System (ADS)

Alonso-Benito, Alfonso; Arbelo, Manuel; Hernandez-Leal, Pedro A.; González-Calvo, Alejandro; Labrador Garcia, Mauricio

To understand and evaluate the forest structural attributes, forest inventories are conducted, which are costly and lengthy in time. Since the last 10-15 years there has been examining the possibility of using remote sensing data, to save costs and cheapen the process. One of the aims of SATELMAC, a project PCT-MAC 2007-2013 co-financing with FEDER funds, is to automate the forest inventory in Canary Islands using satellite images. In this study, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were used to estimate forest structure of the endemic vegetal specie, Pinus canariensis, located on the island of Tenerife (Spain). The forest structural attributes analyzed have been volume, basal area, stem per hectare and tree height. ASTER is an imaging instrument flying on Terra, a satellite launched in December 1999 as part of NASA's Earth Observing System. ASTER data were used because it have relatively high spatial resolution in the three visible and near-infrared bands (15 m) and in the six spectral bands (30 m) in the shortwave-IR region. To identify the vegetation index that is most suitable to use, about specific forest structural attributes in our study area, we assess the ability of different spectral indices: Normalized Difference Vegetation Index, Transformed Soil Adjusted Vegetation Index, Modified Soil adjusted Vegetation Index, Perpendicular Vegetation Index and Reduced Simple Ratio. The information provided by the ASTER data has been supplemented by the Third National Forest Inventory (III NFI) and field data. The results are analyzed statistically in order to see the degree of correlation (R2) and the mean square error (RMSE) of the values studied.

Stocking rate effects on spatial heterogeneity in vegetation cover in a grazing-resistant grassland

USDA-ARS?s Scientific Manuscript database

Spatial patterns in rangeland vegetation serve as indicators of rangeland condition and are an important component of wildlife habitat. We illustrate the use of very-large-scale aerial photography (VLSA) to quantify spatial patterns in bare soil of the northeastern Colorado shortgrass steppe. Using ...

Quasistationary areas of NDVI trend dynamics is a powerful research tool for studying spatial patterns of land vegetation

NASA Astrophysics Data System (ADS)

Shevyrnogov, Anatoly; Larko, Aleksandr

The most important task for humankind is to study and understand global processes on Earth. Large factual material on the dynamics of the optical spectral characteristics of the land surface has been accumulated in recent decades. This has been only made possible due to the use of satellite information. The development of satellite measurement technologies and new methods for pre-processing and interpretation of satellite data allowed the research adequate to the scale of the Earth. This adequacy includes the compliance of scale terrestrial objects to the scale of satellite measurements. Research is not limited by any latitude or longitude of the objects studied. The second most important quality is the adequacy of the technologies used to velocities of processes on Earth. This is enabled by long-term continuous satellite measurements at almost all latitudes. Effectiveness of this approach to the study of natural systems has been shown by the authors in ASR publications (AP Shevyrnogov, GS Vysotskaya, JI Gitelson, Quasistationary areas of chlorophyll concentration in the world ocean as observed satellite data Advances in Space Research, Volume 18, Issue 7, Pages 129-132, 1996), which reported a method for determining the ocean surface quasistationary zones. This approach allowed us to identify different types of phytopigment dynamics and the hydrological structure of the ocean. We proposed a similar approach for the study of land vegetation. In some aspects, it is similar to the previously published approach, despite the different nature of terrestrial and aquatic ecosystems. The results are based on the processing of satellite data from 1981 to 2006. Dynamics is the most interesting and important parameter of ecosystems, especially their trends. Therefore, it has been chosen for the analysis of spatial patterns of plant biota. The first results showed great heterogeneity of variances in nonlinear trends of the study areas of the Earth's surface. They corresponded to different natural systems. Various scales of temporal and spatial windows highlight different features of land vegetation. Methods for normalization of the initial information are also effective for highlighting the features of the spatial structure of vegetation. Thus, we have a powerful tool to analyze the spatial distribution and dynamics of terrestrial vegetation based on satellite data. This approach provides a great opportunity to get fundamental knowledge on the functioning of the biosphere. This is global warming, shifts in permafrost boundaries, global gas exchange, etc. It can be used for practical applications in various fields of human activity: forestry, environmental protection, agriculture, etc. We show the illustration of this method: the global maps of land surface dynamics of trends with different parameters of data processing.

Mitigating Uncertainty from Vegetation Spatial Complexity with Highly Portable Lidar

NASA Astrophysics Data System (ADS)

Paynter, I.; Schaaf, C.; Peri, F.; Saenz, E. J.; Genest, D.; Strahler, A. H.; Li, Z.

2015-12-01

To fully utilize the excellent spatial coverage and temporal resolution offered by satellite resources for estimating ecological variables, fine-scale observations are required for comparison, calibration and validation. Lidar instruments have proved effective in estimating the properties of vegetation components of ecosystems, but they are often challenged by occlusion, especially in structurally complex and spatially fragmented ecosystems such as tropical forests. Increasing the range of view angles, both horizontally and vertically, by increasing the number of scans, can mitigate occlusion. However these scans must occur within the window of temporal stability for the ecosystem and vegetation property being measured. The Compact Biomass Lidar (CBL) is a TLS optimized for portability and scanning speed, developed and operated by University of Massachusetts Boston. This 905nm wavelength scanner achieves an angular resolution of 0.25 degrees at a rate of 33 seconds per scan. The ability to acquire many scans within narrow windows of temporal stability for ecological variables has facilitated the more complete investigation of ecosystem structural characteristics, and their expression as a function of view angle. The lightweight CBL has facilitated the use of alternative deployment platforms including towers, trams and masts, allowing analysis of the vertical structure of ecosystems, even in highly enclosed environments such as the sub-canopy of tropical forests where aerial vehicles cannot currently operate. We will present results from view angle analyses of lidar surveys of tropical rainforest in La Selva, Costa Rica where the CBL was deployed at heights up to 10m in Carbono long-term research plots utilizing a portable mast, and on a 25m stationary tower; and temperate forest at Harvard Forest, Massachusetts, USA, where the CBL has been deployed biannually at long-term research plots of hardwood and hemlock, as well as at heights of up to 25m utilizing a stationary tower.

Waveform LiDAR processing: comparison of classic approaches and optimized Gold deconvolution to characterize vegetation structure and terrain elevation

NASA Astrophysics Data System (ADS)

Zhou, T.; Popescu, S. C.; Krause, K.

2016-12-01

Waveform Light Detection and Ranging (LiDAR) data have advantages over discrete-return LiDAR data in accurately characterizing vegetation structure. However, we lack a comprehensive understanding of waveform data processing approaches under different topography and vegetation conditions. The objective of this paper is to highlight a novel deconvolution algorithm, the Gold algorithm, for processing waveform LiDAR data with optimal deconvolution parameters. Further, we present a comparative study of waveform processing methods to provide insight into selecting an approach for a given combination of vegetation and terrain characteristics. We employed two waveform processing methods: 1) direct decomposition, 2) deconvolution and decomposition. In method two, we utilized two deconvolution algorithms - the Richardson Lucy (RL) algorithm and the Gold algorithm. The comprehensive and quantitative comparisons were conducted in terms of the number of detected echoes, position accuracy, the bias of the end products (such as digital terrain model (DTM) and canopy height model (CHM)) from discrete LiDAR data, along with parameter uncertainty for these end products obtained from different methods. This study was conducted at three study sites that include diverse ecological regions, vegetation and elevation gradients. Results demonstrate that two deconvolution algorithms are sensitive to the pre-processing steps of input data. The deconvolution and decomposition method is more capable of detecting hidden echoes with a lower false echo detection rate, especially for the Gold algorithm. Compared to the reference data, all approaches generate satisfactory accuracy assessment results with small mean spatial difference (<1.22 m for DTMs, < 0.77 m for CHMs) and root mean square error (RMSE) (<1.26 m for DTMs, < 1.93 m for CHMs). More specifically, the Gold algorithm is superior to others with smaller root mean square error (RMSE) (< 1.01m), while the direct decomposition approach works better in terms of the percentage of spatial difference within 0.5 and 1 m. The parameter uncertainty analysis demonstrates that the Gold algorithm outperforms other approaches in dense vegetation areas, with the smallest RMSE, and the RL algorithm performs better in sparse vegetation areas in terms of RMSE.

Ecogeomorphology of semiarid rangelands: understanding and quantifying rates and feedbacks to prevent landscape degradation.

NASA Astrophysics Data System (ADS)

Saco, Patricia; Azadi, Samira; Moreno-de las Heras, Mariano; Keesstra, Saskia

2017-04-01

In semiarid systems, hydrologic, geomorphic and ecological processes are tightly coupled through strong feedback mechanisms occurring across fine to coarse scales. These feedbacks have implications for equilibrium and resilience of the landscape and are particularly relevant for understanding the potential degradation effects of climate and anthropogenic pressures. The vegetation of these regions is sparse and often associated to the development and maintenance of spatially variable infiltration rates, with lower infiltration in the bare areas. These variable infiltration rates have been observed in many field studies and are responsible for the emergence of a runoff-runon system, and for the associated redistribution of water and sediments. We will present a modelling framework developed to understand the role of surface water connectivity in degradation processes in semiarid landscapes with patchy vegetation. Surface water connectivity in these systems is highly dynamic and emerges from non-linear feedbacks between vegetation patterns and the coevolving landforms. The model captures these feedbacks through the coupled nature of the processes included in the landform-vegetation modules. As increased surface runoff connectivity has been linked to degradation, we focus on evolving hydrologic connectivity patterns resulting from feedback effects and co-evolving structures. First, we will discuss some general results on the coevolution of semiarid rangelands, and the effects of varying abiotic and biotic conditions. Next we will present results in which we investigate changes in functional hydrologic connectivity, and the existence of tipping points as observed in several sites in Australia. These results are based on data from our recent studies along a precipitation gradient in the Mulga bioregion of Australia. The analysis from satellite images reveals a major role of surface connectivity on the spatial organization of patchy vegetation, suggesting that transitions on the distribution of vegetation leading to degradation are related to sharp variations on the landscape surface connectivity. Finally we will discuss results analysing the potential effect of soils depths on the coevolution of system structures and connectivity. The relevance and implications of these results for the successful reclamation of water-limited environments in which vegetation stability largely depends on the redistribution of the scarce water resources will be discussed.

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

NASA Technical Reports Server (NTRS)

Mcgwire, K.; Friedl, M.; Estes, J. E.

1993-01-01

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Simulating and mapping spatial complexity using multi-scale techniques

USGS Publications Warehouse

De Cola, L.

1994-01-01

A central problem in spatial analysis is the mapping of data for complex spatial fields using relatively simple data structures, such as those of a conventional GIS. This complexity can be measured using such indices as multi-scale variance, which reflects spatial autocorrelation, and multi-fractal dimension, which characterizes the values of fields. These indices are computed for three spatial processes: Gaussian noise, a simple mathematical function, and data for a random walk. Fractal analysis is then used to produce a vegetation map of the central region of California based on a satellite image. This analysis suggests that real world data lie on a continuum between the simple and the random, and that a major GIS challenge is the scientific representation and understanding of rapidly changing multi-scale fields. -Author

A methodology for investigating interdependencies between measured throughfall, meteorological variables and canopy structure on a small catchment.

NASA Astrophysics Data System (ADS)

Maurer, Thomas; Gustavos Trujillo Siliézar, Carlos; Oeser, Anne; Pohle, Ina; Hinz, Christoph

2016-04-01

In evolving initial landscapes, vegetation development depends on a variety of feedback effects. One of the less understood feedback loops is the interaction between throughfall and plant canopy development. The amount of throughfall is governed by the characteristics of the vegetation canopy, whereas vegetation pattern evolution may in turn depend on the spatio-temporal distribution of throughfall. Meteorological factors that may influence throughfall, while at the same time interacting with the canopy, are e.g. wind speed, wind direction and rainfall intensity. Our objective is to investigate how throughfall, vegetation canopy and meteorological variables interact in an exemplary eco-hydrological system in its initial development phase, in which the canopy is very heterogeneous and rapidly changing. For that purpose, we developed a methodological approach combining field methods, raster image analysis and multivariate statistics. The research area for this study is the Hühnerwasser ('Chicken Creek') catchment in Lower Lusatia, Brandenburg, Germany, where after eight years of succession, the spatial distribution of plant species is highly heterogeneous, leading to increasingly differentiated throughfall patterns. The constructed 6-ha catchment offers ideal conditions for our study due to the rapidly changing vegetation structure and the availability of complementary monitoring data. Throughfall data were obtained by 50 tipping bucket rain gauges arranged in two transects and connected via a wireless sensor network that cover the predominant vegetation types on the catchment (locust copses, dense sallow thorn bushes and reeds, base herbaceous and medium-rise small-reed vegetation, and open areas covered by moss and lichens). The spatial configuration of the vegetation canopy for each measurement site was described via digital image analysis of hemispheric photographs of the canopy using the ArcGIS Spatial Analyst, GapLight and ImageJ software. Meteorological data from two on-site weather stations (wind direction, wind speed, air temperature, air humidity, insolation, soil temperature, precipitation) were provided by the 'Research Platform Chicken Creek' (https://www.tu-cottbus.de/projekte/en/oekosysteme/startseite.html). Data were combined and multivariate statistical analysis (PCA, cluster analysis, regression trees) were conducted using the R-software to i) obtain statistical indices describing the relevant characteristics of the data and ii) to identify the determining factors for throughfall intensity. The methodology is currently tested and results will be presented. Preliminary evaluation of the image analysis approach showed only marginal, systematic deviation of results for the different software tools applied, which makes the developed workflow a viable tool for canopy characterization. Results from this study will have a broad spectrum of possible applications, for instance the development / calibration of rainfall interception models, the incorporation into eco-hydrological models, or to test the fault tolerance of wireless rainfall sensor networks.

Post-fire vegetation behaviour in large burnt scars from 2005 fire season in Spain

NASA Astrophysics Data System (ADS)

Bastos, A.; Gouveia, C. M.; DaCamara, C. C.; Trigo, R. M.

2012-04-01

Wildfires have a wide diversity of impacts on landscape which, in turn, depend on the interaction of fire regimes (e.g. intensity, extent, frequency) and the response of vegetation to them in short and long-terms. The increase in erosion rates and the loss of nutrients by runoff in the first months following the fire are among the major impacts of wildfires. A minimum of 30% of vegetation cover is enough to protect soils against erosion but vegetation may require a long period to reach this threshold after severe fires. Since erosion risk is strongly linked to vegetation recovery rates, post-fire vegetation monitoring becomes crucial in land management. Fire regimes in the Mediterranean have been changing in the past decades due to modifications in both socio-economic and climate patterns. Although many vegetation species in Mediterranean ecosystems are adapted to wildfires, changes in fire regime characteristics affect the ability of ecosystems to recover to their previous state. In Spain, fire is an important driver of changes in landscape composition, leading to dominance of shrubland following fire and to a major decrease of pine woodlands (Viedma et al., 2006). Remote sensing is a powerful tool in land management, allowing vegetation monitoring on large spatial scales for relatively long periods of time. In order to assess vegetation dynamics, monthly NDVI data from 1998-2009 from SPOT/VEGETATION at 1km spatial resolution over the Iberian Peninsula were used. This work focuses on 2005 fire season in Spain, which registered the highest amount of burnt area since 1994, with more than 188000 ha burnt. Burnt scars in this fire season were identified by cluster analysis. Post-fire vegetation recovery was assessed based on the monoparametric model developed by Gouveia et al. (2010) that was applied to four large scars located in different geographical settings with different land cover characteristics. While the two northern regions presented fast recovery, in the remaining areas (centre and south), vegetation recovered very slowly and irregularly. Four years following the fire, vegetation density in these two scars was still markedly below pre-fire levels. Spatial patterns of recovery times were assessed in order to evaluate the influence of physical factors such as fire damage, pre-fire vegetation density and land-cover type, in post-fire behaviour of vegetation for each scar. Pre-fire land-cover type raised as a key factor that may partially explain the differences observed, with shrublands and mixed forests recovering faster than coniferous. Gouveia C., DaCamara C.C. and Trigo R.M.: Post fire vegetation recovery in Portugal based on SPOT-VEGETATION data, Natural Hazards and Earth System Sciences, 10, 673-684, 2010. Viedma, O., Moreno, J.M. and Rieiro, I.: Interactions between land use/land cover change, forest fires and landscape structure in Sierra de Gredos (central Spain), Environmental Conservation, 33, 212-222, 2006.

Object-based vegetation classification with high resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Yu, Qian

Vegetation species are valuable indicators to understand the earth system. Information from mapping of vegetation species and community distribution at large scales provides important insight for studying the phenological (growth) cycles of vegetation and plant physiology. Such information plays an important role in land process modeling including climate, ecosystem and hydrological models. The rapidly growing remote sensing technology has increased its potential in vegetation species mapping. However, extracting information at a species level is still a challenging research topic. I proposed an effective method for extracting vegetation species distribution from remotely sensed data and investigated some ways for accuracy improvement. The study consists of three phases. Firstly, a statistical analysis was conducted to explore the spatial variation and class separability of vegetation as a function of image scale. This analysis aimed to confirm that high resolution imagery contains the information on spatial vegetation variation and these species classes can be potentially separable. The second phase was a major effort in advancing classification by proposing a method for extracting vegetation species from high spatial resolution remote sensing data. The proposed classification employs an object-based approach that integrates GIS and remote sensing data and explores the usefulness of ancillary information. The whole process includes image segmentation, feature generation and selection, and nearest neighbor classification. The third phase introduces a spatial regression model for evaluating the mapping quality from the above vegetation classification results. The effects of six categories of sample characteristics on the classification uncertainty are examined: topography, sample membership, sample density, spatial composition characteristics, training reliability and sample object features. This evaluation analysis answered several interesting scientific questions such as (1) whether the sample characteristics affect the classification accuracy and how significant if it does; (2) how much variance of classification uncertainty can be explained by above factors. This research is carried out on a hilly peninsular area in Mediterranean climate, Point Reyes National Seashore (PRNS) in Northern California. The area mainly consists of a heterogeneous, semi-natural broadleaf and conifer woodland, shrub land, and annual grassland. A detailed list of vegetation alliances is used in this study. Research results from the first phase indicates that vegetation spatial variation as reflected by the average local variance (ALV) keeps a high level of magnitude between 1 m and 4 m resolution. (Abstract shortened by UMI.)

Temporal and spatial structure in a daily wildfire-start data set from the western United States (198696)

USGS Publications Warehouse

Bartlein, P.J.; Hostetler, S.W.; Shafer, S.L.; Holman, J.O.; Solomon, A.M.

2008-01-01

The temporal and spatial structure of 332 404 daily fire-start records from the western United States for the period 1986 through 1996 is illustrated using several complimentary visualisation techniques. We supplement maps and time series plots with Hovmo??ller diagrams that reduce the spatial dimensionality of the daily data in order to reveal the underlying space?time structure. The mapped distributions of all lightning- and human-started fires during the 11-year interval show similar first-order patterns that reflect the broad-scale distribution of vegetation across the West and the annual cycle of climate. Lightning-started fires are concentrated in the summer half-year and occur in widespread outbreaks that last a few days and reflect coherent weather-related controls. In contrast, fires started by humans occur throughout the year and tend to be concentrated in regions surrounding large-population centres or intensive-agricultural areas. Although the primary controls of human-started fires are their location relative to burnable fuel and the level of human activity, spatially coherent, weather-related variations in their incidence can also be noted. ?? IAWF 2008.

Characterizing sub-arctic peatland vegeation using height estimates from structure from motion and an unmanned aerial system (UAS)

NASA Astrophysics Data System (ADS)

Palace, M. W.; DelGreco, J.; Herrick, C.; Sullivan, F.; Varner, R. K.

2017-12-01

The collapse of permafrost, due to thawing, changes landscape topography, hydrology and vegetation. Changes in plant species composition influence methane production pathways and methane emission rates. The complex spatial heterogeneity of vegetation composition across peatlands proves important in quantifying methane emissions. Effort to characterize vegetation across these permafrost peatlands has been conducted with varied success, with difficulty seen in estimating some cover types that are at opposite ends of the permafrost collapse transition, ie palsa/tall shrub and tall graminoid. This is because some of the species are the same (horsetail) and some of the species have similar structure (horsetail/Carex spp.). High resolution digital elevation maps, developed with airborne LIght Detection And Ranging (lidar) have provided insight into some wetland attributes, but lidar collection is costly and requires extensive data processing effort. Lidar information also lacks the spectral information that optical sensors provide. We used an inexpensive Unmanned Aerial Vehicle (UAV) with an optical sensor to image a mire in northern Sweden (Stordalen Mire) in 2015. We collected 700 overlapping images that were stitched together using Structure from Motion (SfM). SfM analysis also provided, due to parallax, the ability to develop a height map of vegetation. This height map was used, along with textural analysis, to develop an artificial neural network to predict five vegetation cover types. Using 200 training points, we found improvements in our prediction of these cover types. We suggest that using the digital height model from SfM provides useful information in remotely sensing vegetation across a permafrost collapsing region that exhibit resulting changes in vegetation composition. The ability to rapidly and inexpensively deploy such a UAV system provides the opportunity to examine multiple sites with limited personnel effort in remote areas.

Delineation of peatland lagg boundaries from airborne LiDAR

NASA Astrophysics Data System (ADS)

Langlois, Melanie N.; Richardson, Murray C.; Price, Jonathan S.

2017-09-01

In Canada, peatlands are the most common type of wetland, but boundary delineation in peatland complexes has received little attention in the scientific literature. Typically, peatland boundaries are mapped as crisp, absolute features, and the transitional lagg zone—the ecotone found between a raised bog and the surrounding mineral land—is often overlooked. In this study, we aim (1) to advance existing approaches for detecting and locating laggs and lagg boundaries using airborne LiDAR surveys and (2) to describe the spatial distribution of laggs around raised bog peatlands. Two contrasting spatial analytical approaches for lagg detection were tested using five LiDAR-derived topographic and vegetation indices: topography, vegetation height, topographic wetness index, the standard deviation of the vegetation's height (as a proxy for the complexity of the vegetation's structure), and local indices of elevation variance. Using a dissimilarity approach (edge-detection, split-moving window analysis), no one variable accurately depicted both the lagg-mineral land and bog-lagg boundaries. Some indicators were better at predicting the bog-lagg boundary (i.e., vegetation height) and others at finding the lagg-mineral land boundary (i.e., topography). Dissimilarity analysis reinforces the usefulness of derived variables (e.g., wetness indices) in locating laggs, especially for those with weak topographic and vegetation gradients. When the lagg was confined between the bog and the adjacent upland, it took a linear form, parallel to the peatland's edge and was easier to predict. When the adjacent mineral land was flat or sloping away from the peatland, the lagg was discontinuous and intermittent and more difficult to predict.

Analysis of vegetation recovery surrounding a restored wetland using the normalized difference infrared index (NDII) and normalized difference vegetation index (NDVI)

USGS Publications Warehouse

Wilson, Natalie R.; Norman, Laura

2018-01-01

Watershed restoration efforts seek to rejuvenate vegetation, biological diversity, and land productivity at Cienega San Bernardino, an important wetland in southeastern Arizona and northern Sonora, Mexico. Rock detention and earthen berm structures were built on the Cienega San Bernardino over the course of four decades, beginning in 1984 and continuing to the present. Previous research findings show that restoration supports and even increases vegetation health despite ongoing drought conditions in this arid watershed. However, the extent of restoration impacts is still unknown despite qualitative observations of improvement in surrounding vegetation amount and vigor. We analyzed spatial and temporal trends in vegetation greenness and soil moisture by applying the normalized difference vegetation index (NDVI) and normalized difference infrared index (NDII) to one dry summer season Landsat path/row from 1984 to 2016. The study area was divided into zones and spectral data for each zone was analyzed and compared with precipitation record using statistical measures including linear regression, Mann– Kendall test, and linear correlation. NDVI and NDII performed differently due to the presence of continued grazing and the effects of grazing on canopy cover; NDVI was better able to track changes in vegetation in areas without grazing while NDII was better at tracking changes in areas with continued grazing. Restoration impacts display higher greenness and vegetation water content levels, greater increases in greenness and water content through time, and a decoupling of vegetation greenness and water content from spring precipitation when compared to control sites in nearby tributary and upland areas. Our results confirm the potential of erosion control structures to affect areas up to 5 km downstream of restoration sites over time and to affect 1 km upstream of the sites.

The response of vegetation to geochemical conditions

NASA Technical Reports Server (NTRS)

Mouat, D. A.

1983-01-01

An understanding of the factors of vegetation response to changes in the geochemistry of the environment may give exploration geologists and other researchers an additional and effective tool for rock type discrimination. The factors of vegetation response can be grouped into three principal categories: structural or morphological factors, taxonomic factors which include indicator flora as well as vegetation assemblages, and spectral factors which represent the manner in which the vegetation interacts with electromagnetic radiation. The response of these factors over areas of anomalous mineralization is often unique and may be due to nutrient deficiencies and/or imbalances, toxicity and stress caused by anomalous mineral concentrations in the soil, low water retention, and plant competition. The successful use of geobotanical techniques results from the integration of the geobotanical observations with other techniques. The use of remote sensing in such a program must be predicated on those factors which can be discriminated within the constraints of the spatial, spectral, radiometric, and temporal resolutions of the sensing system and with appropriate analytical techniques.

Past and future effects of climate change on spatially heterogeneous vegetation activity in China

NASA Astrophysics Data System (ADS)

Gao, Jiangbo; Jiao, Kewei; Wu, Shaohong; Ma, Danyang; Zhao, Dongsheng; Yin, Yunhe; Dai, Erfu

2017-07-01

Climate change is a major driver of vegetation activity but its complex ecological relationships impede research efforts. In this study, the spatial distribution and dynamic characteristics of climate change effects on vegetation activity in China from the 1980s to the 2010s and from 2021 to 2050 were investigated using a geographically weighted regression (GWR) model. The GWR model was based on combined datasets of satellite vegetation index, climate observation and projection, and future vegetation productivity simulation. Our results revealed that the significantly positive precipitation-vegetation relationship was and will be mostly distributed in North China. However, the regions with temperature-dominated distribution of vegetation activity were and will be mainly located in South China. Due to the varying climate features and vegetation cover, the spatial correlation between vegetation activity and climate change may be altered. There will be different dominant climatic factors for vegetation activity distribution in some regions such as Northwest China, and even opposite correlations in Northeast China. Additionally, the response of vegetation activity to precipitation will move southward in the next three decades. In contrast, although the high warming rate will restrain the vegetation activity, precipitation variability could modify hydrothermal conditions for vegetation activity. This observation is exemplified in the projected future enhancement of vegetation activity in the Tibetan Plateau and weakened vegetation activity in East and Middle China. Furthermore, the vegetation in most parts of North China may adapt to an arid environment, whereas in many southern areas, vegetation will be repressed by water shortage in the future.

Developing a global mixed-canopy, height-variable vegetation structure dataset for estimating global vegetation albedo by a clumped canopy radiative transfer scheme in the NASA Ent Terrestrial Biosphere Model and GISS GCM

NASA Astrophysics Data System (ADS)

Montes, Carlo; Kiang, Nancy Y.; Ni-Meister, Wenge; Yang, Wenze; Schaaf, Crystal; Aleinov, Igor; Jonas, Jeffrey A.; Zhao, Feng; Yao, Tian; Wang, Zhuosen; Sun, Qingsong; Carrer, Dominique

2016-04-01

Processes determining biosphere-atmosphere coupling are strongly influenced by vegetation structure. Thus, ecosystem carbon sequestration and evapotranspiration affecting global carbon and water balances will depend upon the spatial extent of vegetation, its vertical structure, and its physiological variability. To represent this globally, Dynamic Global Vegetation Models (DGVMs) coupled to General Circulation Models (GCMs) make use of satellite and/or model-based vegetation classifications often composed by homogeneous communities. This work aims at developing a new Global Vegetation Structure Dataset (GVSD) by incorporating varying vegetation heights for mixed plant communities to be used as boundary conditions to the Analytical Clumped Two-Stream (ACTS) canopy radiative transfer scheme (Ni-Meister et al., 2010) incorporated into the NASA Ent Terrestrial Biosphere Model (TBM), the DGVM coupled to the NASA Goddard Institute for Space Studies (GISS) GCM. Information sources about land surface and vegetation characteristics obtained from a number of earth observation platforms and algorithms include the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover and plant functional types (PFTs) (Friedl et al., 2010), soil albedo derived from MODIS (Carrer et al., 2014), along with vegetation height from the Geoscience Laser Altimeter System (GLAS) on board ICESat (Ice, Cloud, and land Elevation Satellite) (Simard et al., 2011; Tang et al., 2014). Three widely used Leaf Area Index (LAI) products are compared as input to the GVSD and ACTS forcing in terms of vegetation albedo: Global Data Sets of Vegetation (LAI)3g (Zhu et al. 2013), Beijing Normal University LAI (Yuan et al., 2011), and MODIS MOD15A2H product (Yang et al., 2006). Further PFT partitioning is performed according to a climate classification utilizing the Climate Research Unit (CRU; Harris et al., 2013) and the NOAA Global Precipitation Climatology Centre (GPCC; Scheider et al., 2014) data. Final products are a GVSD consisting of mixed plant communities (e.g. mixed forests, savannas, mixed PFTs) following the Ecosystem Demography model (Moorcroft et al., 2001) approach represented by multi-cohort community patches at the sub-grid level of the GCM, which are ensembles of identical individuals whose differences are represented by PFTs, canopy height, density and vegetation structure sensitivity to allometric parameters. The performance of the Ent TBM in estimating VIS-NIR vegetation albedo by the new GVSD and ACTS is assessed first by comparison against the previous GISS GCM vegetation classification and prescribed Lambertian albedoes of Matthews (1984), and secondly, against MODIS global estimations and FLUXNET site-scale observations. Ultimately, this GVSD will serve as a template for community data sets, and be used as boundary conditions to the Ent TBM for prediction of biomass, carbon balances and GISS GCM climate.

Mapping Successional Stages in a Wet Tropical Forest Using Landsat ETM+ and Forest Inventory Data

NASA Technical Reports Server (NTRS)

Goncalves, Fabio G.; Yatskov, Mikhail; dos Santos, Joao Roberto; Treuhaft, Robert N.; Law, Beverly E.

2010-01-01

In this study, we test whether an existing classification technique based on the integration of Landsat ETM+ and forest inventory data enables detailed characterization of successional stages in a wet tropical forest site. The specific objectives were: (1) to map forest age classes across the La Selva Biological Station in Costa Rica; and (2) to quantify uncertainties in the proposed approach in relation to field data and existing vegetation maps. Although significant relationships between vegetation height entropy (a surrogate for forest age) and ETM+ data were detected, the classification scheme tested in this study was not suitable for characterizing spatial variation in age at La Selva, as evidenced by the error matrix and the low Kappa coefficient (12.9%). Factors affecting the performance of the classification at this particular study site include the smooth transition in vegetation structure between intermediate and advanced successional stages, and the low sensitivity of NDVI to variations in vertical structure at high biomass levels.

Producing Science-Ready Radar Datasets for the Retrieval of Forest Structure Parameters from Backscatter: Correcting for Terrain Topography and Changes in Vegetation Reflectivity

NASA Technical Reports Server (NTRS)

Simard, M.; Riel, Bryan; Hensley, S.; Lavalle, Marco

2011-01-01

Radar backscatter data contain both geometric and radiometric distortions due to underlying topography and the radar viewing geometry. Our objective is to develop a radiometric correction algorithm specific to the UAVSAR system configuration that would improve retrieval of forest structure parameters. UAVSAR is an airborne Lband radar capable of repeat?pass interferometry producing images with a spatial resolution of 5m. It is characterized by an electronically steerable antenna to compensate for aircraft attitude. Thus, the computation of viewing angles (i.e. look, incidence and projection) must include aircraft attitude angles (i.e. yaw, pitch and roll) in addition to the antenna steering angle. In this presentation, we address two components of radiometric correction: area projection and vegetation reflectivity. The first correction is applied by normalization of the radar backscatter by the local ground area illuminated by the radar beam. The second is a correction due to changes in vegetation reflectivity with viewing geometry.

FATE-HD: A spatially and temporally explicit integrated model for predicting vegetation structure and diversity at regional scale

PubMed Central

Isabelle, Boulangeat; Damien, Georges; Wilfried, Thuiller

2014-01-01

During the last decade, despite strenuous efforts to develop new models and compare different approaches, few conclusions have been drawn on their ability to provide robust biodiversity projections in an environmental change context. The recurring suggestions are that models should explicitly (i) include spatiotemporal dynamics; (ii) consider multiple species in interactions; and (iii) account for the processes shaping biodiversity distribution. This paper presents a biodiversity model (FATE-HD) that meets this challenge at regional scale by combining phenomenological and process-based approaches and using well-defined plant functional groups. FATE-HD has been tested and validated in a French National Park, demonstrating its ability to simulate vegetation dynamics, structure and diversity in response to disturbances and climate change. The analysis demonstrated the importance of considering biotic interactions, spatio-temporal dynamics, and disturbances in addition to abiotic drivers to simulate vegetation dynamics. The distribution of pioneer trees was particularly improved, as were all undergrowth functional groups. PMID:24214499

Meteorological factors associated with abundance of airborne fungal spores over natural vegetation

NASA Astrophysics Data System (ADS)

Crandall, Sharifa G.; Gilbert, Gregory S.

2017-08-01

The abundance of airborne fungal spores in agricultural and urban settings increases with greater air temperature, relative humidity, or precipitation. The same meteorological factors that affect temporal patterns in spore abundance in managed environments also vary spatially across natural habitats in association with differences in vegetation structure. Here we investigated how temporal and spatial variation in aerial spore abundance is affected by abiotic (weather) and biotic (vegetation) factors as a foundation for predicting how fungi may respond to changes in weather and land-use patterns. We measured the phenology of airborne fungal spores across a mosaic of naturally occurring vegetation types at different time scales to describe (1) how spore abundance changes over time, (2) which local meteorological variables are good predictors for airborne spore density, and (3) whether spore abundance differs across vegetation types. Using an air volumetric vacuum sampler, we collected spore samples at 3-h intervals over a 120-h period in a mixed-evergreen forest and coastal prairie to measure diurnal, nocturnal, and total airborne spore abundance across vegetation types. Spore samples were also collected at weekly and monthly intervals in mixed-evergreen forest, redwood forest, and maritime chaparral vegetation types from 12 field sites across two years. We found greater airborne spore densities during the wetter winter months compared to the drier summer months. Mean total spore abundance in the mixed-evergreen forest was twice than in the coastal prairie, but there were no significant differences in total airborne spore abundance among mixed-evergreen forest, redwood forest, and maritime chaparral vegetation types. Weekly and monthly peaks in airborne spore abundance corresponded with rain events and peaks in soil moisture. Overall, temporal patterns in meteorological factors were much more important in determining airborne fungal spore abundance than the vegetation type. This suggests that overall patterns of fungal spore dynamics may be predictable across heterogeneous landscapes based on local weather patterns.

Bird Communities and Environmental Correlates in Southern Oregon and Northern California, USA.

PubMed

Stephens, Jaime L; Dinger, Eric C; Alexander, John D; Mohren, Sean R; Ralph, C John; Sarr, Daniel A

2016-01-01

We examined avian community ecology in the Klamath Ecoregion and determined that individual bird species co-exist spatially to form 29 statistically distinguishable bird groups. We identified climate, geography, and vegetation metrics that are correlated with these 29 bird groups at three scales: Klamath Ecoregion, vegetation formation (agriculture, conifer, mixed conifer/hardwood, shrubland), and National Park Service unit. Two climate variables (breeding season mean temperature and temperature range) and one geography variable (elevation) were correlated at all scales, suggesting that for some vegetation formations and park units there is sufficient variation in climate and geography to be an important driver of bird communities, a level of variation we expected only at the broader scale. We found vegetation to be important at all scales, with coarse metrics (environmental site potential and existing vegetation formation) meaningful across all scales and structural vegetation patterns (e.g. succession, disturbance) important only at the scale of vegetation formation or park unit. Additionally, we examined how well six National Park Service units represent bird communities in the broader Klamath Ecoregion. Park units are inclusive of most bird communities with the exception of the oak woodland community; mature conifer forests are well represented, primarily associated with conifer canopy and lacking multi-layered structure. Identifying environmental factors that shape bird communities at three scales within this region is important; such insights can inform local and regional land management decisions necessary to ensure bird conservation in this globally significant region.

Bird Communities and Environmental Correlates in Southern Oregon and Northern California, USA

PubMed Central

Dinger, Eric C.; Alexander, John D.; Mohren, Sean R.; Ralph, C. John; Sarr, Daniel A.

2016-01-01

We examined avian community ecology in the Klamath Ecoregion and determined that individual bird species co-exist spatially to form 29 statistically distinguishable bird groups. We identified climate, geography, and vegetation metrics that are correlated with these 29 bird groups at three scales: Klamath Ecoregion, vegetation formation (agriculture, conifer, mixed conifer/hardwood, shrubland), and National Park Service unit. Two climate variables (breeding season mean temperature and temperature range) and one geography variable (elevation) were correlated at all scales, suggesting that for some vegetation formations and park units there is sufficient variation in climate and geography to be an important driver of bird communities, a level of variation we expected only at the broader scale. We found vegetation to be important at all scales, with coarse metrics (environmental site potential and existing vegetation formation) meaningful across all scales and structural vegetation patterns (e.g. succession, disturbance) important only at the scale of vegetation formation or park unit. Additionally, we examined how well six National Park Service units represent bird communities in the broader Klamath Ecoregion. Park units are inclusive of most bird communities with the exception of the oak woodland community; mature conifer forests are well represented, primarily associated with conifer canopy and lacking multi-layered structure. Identifying environmental factors that shape bird communities at three scales within this region is important; such insights can inform local and regional land management decisions necessary to ensure bird conservation in this globally significant region. PMID:27732625

Spatial statistical analysis of tree deaths using airborne digital imagery

NASA Astrophysics Data System (ADS)

Chang, Ya-Mei; Baddeley, Adrian; Wallace, Jeremy; Canci, Michael

2013-04-01

High resolution digital airborne imagery offers unprecedented opportunities for observation and monitoring of vegetation, providing the potential to identify, locate and track individual vegetation objects over time. Analytical tools are required to quantify relevant information. In this paper, locations of trees over a large area of native woodland vegetation were identified using morphological image analysis techniques. Methods of spatial point process statistics were then applied to estimate the spatially-varying tree death risk, and to show that it is significantly non-uniform. [Tree deaths over the area were detected in our previous work (Wallace et al., 2008).] The study area is a major source of ground water for the city of Perth, and the work was motivated by the need to understand and quantify vegetation changes in the context of water extraction and drying climate. The influence of hydrological variables on tree death risk was investigated using spatial statistics (graphical exploratory methods, spatial point pattern modelling and diagnostics).

Implementation of a Time Series Analysis for the Assessment of the Role of Climate Variability in a Post-Disturbance Savanna System

NASA Astrophysics Data System (ADS)

Gibbes, C.; Southworth, J.; Waylen, P. R.

2013-05-01

How do climate variability and climate change influence vegetation cover and vegetation change in savannas? A landscape scale investigation of the effect of changes in precipitation on vegetation is undertaken through the employment of a time series analysis. The multi-national study region is located within the Kavango-Zambezi region, and is delineated by the Okavango, Kwando, and Zambezi watersheds. A mean-variance time-series analysis quantifies vegetation dynamics and characterizes vegetation response to climate. The spatially explicit approach used to quantify the persistence of vegetation productivity permits the extraction of information regarding long term climate-landscape dynamics. Results show a pattern of reduced mean annual precipitation and increased precipitation variability across key social and ecological areas within the study region. Despite decreased mean annual precipitation since the mid to late 1970's vegetation trends predominantly indicate increasing biomass. The limited areas which have diminished vegetative cover relate to specific vegetation types, and are associated with declines in precipitation variability. Results indicate that in addition to short term changes in vegetation cover, long term trends in productive biomass are apparent, relate to spatial differences in precipitation variability, and potentially represent shifts vegetation composition. This work highlights the importance of time-series analyses for examining climate-vegetation linkages in a spatially explicit manner within a highly vulnerable region of the world.

Small-scale variation in ecosystem CO2 fluxes in an alpine meadow depends on plant biomass and species richness.

PubMed

Hirota, Mitsuru; Zhang, Pengcheng; Gu, Song; Shen, Haihua; Kuriyama, Takeo; Li, Yingnian; Tang, Yanhong

2010-07-01

Characterizing the spatial variation in the CO2 flux at both large and small scales is essential for precise estimation of an ecosystem's CO2 sink strength. However, little is known about small-scale CO2 flux variations in an ecosystem. We explored these variations in a Kobresia meadow ecosystem on the Qinghai-Tibetan plateau in relation to spatial variability in species composition and biomass. We established 14 points and measured net ecosystem production (NEP), gross primary production (GPP), and ecosystem respiration (Re) in relation to vegetation biomass, species richness, and environmental variables at each point, using an automated chamber system during the 2005 growing season. Mean light-saturated NEP and GPP were 30.3 and 40.5 micromol CO2 m(-2) s(-1) [coefficient of variation (CV), 42.7 and 29.4], respectively. Mean Re at 20 degrees C soil temperature, Re(20), was -10.9 micromol CO2 m(-2) s(-1) (CV, 27.3). Re(20) was positively correlated with vegetation biomass. GPP(max) was positively correlated with species richness, but 2 of the 14 points were outliers. Vegetation biomass was the main determinant of spatial variation of Re, whereas species richness mainly affected that of GPP, probably reflecting the complexity of canopy structure and light partitioning in this small grassland patch.

Secondary forest regeneration on degraded tropical lands: the role of plantations as ‘foster ecosystems’

Treesearch

John A. Parrotta

1993-01-01

Forest plantations established on degraded sites can accelerate natural succession through their effects on vegetation structure, microclimate, and soils. Spatial and temporal patterns of secondary forest species regeneration were studied in permanent quadrats in Albizia lebbek planta1ion plots and control areas at a degraded coastal pasture in...

Composition, biomass and structure of mangroves within the Zambezi River Delta

Treesearch

Carl C. Trettin; Christina E. Stringer; Stan Zarnoch

2015-01-01

We used a stratified random sampling design to inventory the mangrove vegetation within the Zambezi River Delta, Mozambique, to provide a basis for estimating biomass pools. We used canopy height, derived from remote sensing data, to stratify the inventory area, and then applied a spatial decision support system to objectively allocate sample plots among five...

Abundance and production of riparian trees in the lowland floodplain of the Queets River, Washington.

Treesearch

Estelle V. Balian; Robert J. Naiman

2005-01-01

Riparian zones associated with alluvial rivers are spatially dynamic, forming distinct vegetative mosaics that exhibit sharp contrasts in structure and processes related to the underlying biophysical template. The productivity of riparian plants, especially trees, influences streamside community characteristics as, well as the forms and fluxes of organic matter to...

Snow-covered Landsat time series stacks improve automated disturbance mapping accuracy in forested landscapes

Treesearch

Kirk M. Stueve; Ian W. Housman; Patrick L. Zimmerman; Mark D. Nelson; Jeremy B. Webb; Charles H. Perry; Robert A. Chastain; Dale D. Gormanson; Chengquan Huang; Sean P. Healey; Warren B. Cohen

2011-01-01

Accurate landscape-scale maps of forests and associated disturbances are critical to augment studies on biodiversity, ecosystem services, and the carbon cycle, especially in terms of understanding how the spatial and temporal complexities of damage sustained from disturbances influence forest structure and function. Vegetation change tracker (VCT) is a highly automated...

Coastal vegetation and its influence on the 2004 tsunami event

NASA Astrophysics Data System (ADS)

Laso Bayas, J. C.; Marohn, C.; Dercon, G.; Dewi, S.; Piepho, H. P.; Joshi, L.; van Noordwijk, M.; Cadisch, G.

2012-04-01

A tsunami event has several effects once it reaches the shore. Infrastructure damage and casualties are two of its most dire consequences. The intensity of these damages is related to the wave force, which in turn is mostly determined by seaquake intensity and offshore properties. Nevertheless, once on land, the energy of the wave is attenuated by gravity (elevation) and friction (land cover). Despite being promoted as 'bio-shields' against wave impact, tree-belts lack quantitative evidence of their performance in such extreme events, and have been criticized for creating a false sense of security. We have studied some of the land uses in sites affected by the 2004 tsunami event, especially in coastal areas close to the coast of Indonesia, more specifically in the west coast of Aceh, Sumatra. Using transects perpendicular to the coast we analyzed the influence of coastal vegetation, particularly cultivated trees, on the impact of the 2004 tsunami. We developed a spatial statistical model that uses a land cover roughness coefficient to account for the resistance offered by different land uses to the wave advance. The coefficient was built using satellite imagery, land cover maps, land use characteristics such as stem diameter, height, and planting density, as well as a literature review. The spatial generalized linear mixed models used determined that while distance to coast was the dominant determinant of impact (casualties and infrastructure damage), the existing coastal vegetation in front of settlements also significantly reduced casualties by an average of 5%. Despite this positive effect of coastal vegetation in front of a settlement, we also found out that dense vegetation behind villages endangered human lives and increased structural damage. We believe that possibly debris carried by the backwash may have contributed to these dissimilar effects of land cover. The models developed in Indonesia are currently being adapted and tested for the effects that the same tsunami event caused in the Seychelles, where the intensity of the wave was a tenth of that in Aceh. On the Seychelles, our current work suggests that no direct effect of coastal vegetation existed. At the same time, our results indicate that vegetation maintained dunes seemed to offer a decrease of the probability of structural damage. We believe that instead of advocating for or against tree belts, a sustainable and effective coastal risk management should be promoted. This should include smart planning for the location (relative to the sea) of settlements but also consider the possible roles of coastal vegetation, as determined by its spatial arrangement. Overall, for any of these planning measures to be sustainable, coastal vegetation must be regarded as an important livelihood provider rather than just as a bio-shield. Consequently, it should be adapted to local customs as well as provide tangible short and mid-term benefits for local communities.

Analyzing landscape changes in the Bafa Lake Nature Park of Turkey using remote sensing and landscape structure metrics.

PubMed

Esbah, Hayriye; Deniz, Bulent; Kara, Baris; Kesgin, Birsen

2010-06-01

Bafa Lake Nature Park is one of Turkey's most important legally protected areas. This study aimed at analyzing spatial change in the park environment by using object-based classification technique and landscape structure metrics. SPOT 2X (1994) and ASTER (2005) images are the primary research materials. Results show that artificial surfaces, low maqui, garrigue, and moderately high maqui covers have increased and coniferous forests, arable lands, permanent crop, and high maqui covers have decreased; coniferous forest, high maqui, grassland, and saline areas are in a disappearance stage of the land transformation; and the landscape pattern is more fragmented outside the park boundaries. The management actions should support ongoing vegetation regeneration, mitigate transformation of vegetation structure to less dense and discontinuous cover, control the dynamics at the agricultural-natural landscape interface, and concentrate on relatively low but steady increase of artificial surfaces.

Representation of vegetation by continental data sets derived from NOAA-AVHRR data

NASA Technical Reports Server (NTRS)

Justice, C. O.; Townshend, J. R. G.; Kalb, V. L.

1991-01-01

Images of the normalized difference vegetation index (NDVI) are examined with specific attention given to the effect of spatial scales on the understanding of surface phenomena. A scale variance analysis is conducted on NDVI annual and seasonal images of Africa taken from 1987 NOAA-AVHRR data at spatial scales ranging from 8-512 km. The scales at which spatial variation takes place are determined and the relative magnitude of the variations are considered. Substantial differences are demonstrated, notably an increase in spatial variation with coarsening spatial resolution. Different responses in scale variance as a function of spatial resolution are noted in an analysis of maximum value composites for February and September; the difference is most marked in areas with very seasonal vegetation. The spatial variation at different scales is attributed to different factors, and methods involving the averaging of areas of transition and surface heterogeneity can oversimplify surface conditions. The spatial characteristics and the temporal variability of areas should be considered to accurately apply satellite data to global models.

On the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements.

PubMed

Li, Zhan; Schaefer, Michael; Strahler, Alan; Schaaf, Crystal; Jupp, David

2018-04-06

The Dual-Wavelength Echidna Lidar (DWEL), a full waveform terrestrial laser scanner (TLS), has been used to scan a variety of forested and agricultural environments. From these scanning campaigns, we summarize the benefits and challenges given by DWEL's novel coaxial dual-wavelength scanning technology, particularly for the three-dimensional (3D) classification of vegetation elements. Simultaneous scanning at both 1064 nm and 1548 nm by DWEL instruments provides a new spectral dimension to TLS data that joins the 3D spatial dimension of lidar as an information source. Our point cloud classification algorithm explores the utilization of both spectral and spatial attributes of individual points from DWEL scans and highlights the strengths and weaknesses of each attribute domain. The spectral and spatial attributes for vegetation element classification each perform better in different parts of vegetation (canopy interior, fine branches, coarse trunks, etc.) and under different vegetation conditions (dead or live, leaf-on or leaf-off, water content, etc.). These environmental characteristics of vegetation, convolved with the lidar instrument specifications and lidar data quality, result in the actual capabilities of spectral and spatial attributes to classify vegetation elements in 3D space. The spectral and spatial information domains thus complement each other in the classification process. The joint use of both not only enhances the classification accuracy but also reduces its variance across the multiple vegetation types we have examined, highlighting the value of the DWEL as a new source of 3D spectral information. Wider deployment of the DWEL instruments is in practice currently held back by challenges in instrument development and the demands of data processing required by coaxial dual- or multi-wavelength scanning. But the simultaneous 3D acquisition of both spectral and spatial features, offered by new multispectral scanning instruments such as the DWEL, opens doors to study biophysical and biochemical properties of forested and agricultural ecosystems at more detailed scales.

Gold - A novel deconvolution algorithm with optimization for waveform LiDAR processing

NASA Astrophysics Data System (ADS)

Zhou, Tan; Popescu, Sorin C.; Krause, Keith; Sheridan, Ryan D.; Putman, Eric

2017-07-01

Waveform Light Detection and Ranging (LiDAR) data have advantages over discrete-return LiDAR data in accurately characterizing vegetation structure. However, we lack a comprehensive understanding of waveform data processing approaches under different topography and vegetation conditions. The objective of this paper is to highlight a novel deconvolution algorithm, the Gold algorithm, for processing waveform LiDAR data with optimal deconvolution parameters. Further, we present a comparative study of waveform processing methods to provide insight into selecting an approach for a given combination of vegetation and terrain characteristics. We employed two waveform processing methods: (1) direct decomposition, (2) deconvolution and decomposition. In method two, we utilized two deconvolution algorithms - the Richardson-Lucy (RL) algorithm and the Gold algorithm. The comprehensive and quantitative comparisons were conducted in terms of the number of detected echoes, position accuracy, the bias of the end products (such as digital terrain model (DTM) and canopy height model (CHM)) from the corresponding reference data, along with parameter uncertainty for these end products obtained from different methods. This study was conducted at three study sites that include diverse ecological regions, vegetation and elevation gradients. Results demonstrate that two deconvolution algorithms are sensitive to the pre-processing steps of input data. The deconvolution and decomposition method is more capable of detecting hidden echoes with a lower false echo detection rate, especially for the Gold algorithm. Compared to the reference data, all approaches generate satisfactory accuracy assessment results with small mean spatial difference (<1.22 m for DTMs, <0.77 m for CHMs) and root mean square error (RMSE) (<1.26 m for DTMs, <1.93 m for CHMs). More specifically, the Gold algorithm is superior to others with smaller root mean square error (RMSE) (<1.01 m), while the direct decomposition approach works better in terms of the percentage of spatial difference within 0.5 and 1 m. The parameter uncertainty analysis demonstrates that the Gold algorithm outperforms other approaches in dense vegetation areas, with the smallest RMSE, and the RL algorithm performs better in sparse vegetation areas in terms of RMSE. Additionally, the high level of uncertainty occurs more on areas with high slope and high vegetation. This study provides an alternative and innovative approach for waveform processing that will benefit high fidelity processing of waveform LiDAR data to characterize vegetation structures.

Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

NASA Astrophysics Data System (ADS)

Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

2017-03-01

Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

Estimation of Spatial Trends in LAI in Heterogeneous Semi-arid Ecosystems using Full Waveform Lidar

NASA Astrophysics Data System (ADS)

Glenn, N. F.; Ilangakoon, N.; Spaete, L.; Dashti, H.

2017-12-01

Leaf area index (LAI) is a key structural trait that is defined by the plant functional type (PFT) and controlled by prevailing climate- and human-driven ecosystem stresses. Estimates of LAI using remote sensing techniques are limited by the uncertainties of vegetation inter and intra-gap fraction estimates; this is especially the case in sparse, low stature vegetated ecosystems. Small footprint full waveform lidar digitizes the total amount of return energy with the direction information as a near continuous waveform at a high vertical resolution (1 ns). Thus waveform lidar provides additional data matrices to capture vegetation gaps as well as PFTs that can be used to constrain the uncertainties of LAI estimates. In this study, we calculated a radiometrically calibrated full waveform parameter called backscatter cross section, along with other data matrices from the waveform to estimate vegetation gaps across plots (10 m x 10 m) in a semi-arid ecosystem in the western US. The LAI was then estimated using empirical relationships with directional gap fraction. Full waveform-derived gap fraction based LAI showed a high correlation with field observed shrub LAI (R2 = 0.66, RMSE = 0.24) compared to discrete return lidar based LAI (R2 = 0.01, RMSE = 0.5). The data matrices derived from full waveform lidar classified a number of deciduous and evergreen tree species, shrub species, and bare ground with an overall accuracy of 89% at 10 m. A similar analysis was performed at 1m with overall accuracy of 80%. The next step is to use these relationships to map the PFTs LAI at 10 m spatial scale across the larger study regions. The results show the exciting potential of full waveform lidar to identify plant functional types and LAI in low-stature vegetation dominated semi-arid ecosystems, an ecosystem in which many other remote sensing techniques fail. These results can be used to assess ecosystem state, habitat suitability as well as to constrain model uncertainties in vegetation dynamic models with a combination of other remote sensing techniques. Multi-spatial resolution (1 m and 10 m) studies provide basic information on the applicability and detection thresholds of future global satellite sensors designed at coarser spatial resolutions (e.g. GEDI, ICESat-2) in semi-arid ecosystems.

Advanced NASA Earth Science Mission Concept for Vegetation 3D Structure, Biomass and Disturbance

NASA Technical Reports Server (NTRS)

Ranson, K. Jon

2007-01-01

Carbon in forest canopies represents about 85% of the total carbon in the Earth's aboveground biomass (Olson et al., 1983). A major source of uncertainty in global carbon budgets derives from large errors in the current estimates of these carbon stocks (IPCC, 2001). The magnitudes and distributions of terrestrial carbon storage along with changes in sources and sinks for atmospheric C02 due to land use change remain the most significant uncertainties in Earth's carbon budget. These uncertainties severely limit accurate terrestrial carbon accounting; our ability to evaluate terrestrial carbon management schemes; and the veracity of atmospheric C02 projections in response to further fossil fuel combustion and other human activities. Measurements of vegetation three-dimensional (3D) structural characteristics over the Earth's land surface are needed to estimate biomass and carbon stocks and to quantify biomass recovery following disturbance. These measurements include vegetation height, the vertical profile of canopy elements (i.e., leaves, stems, branches), andlor the volume scattering of canopy elements. They are critical for reducing uncertainties in the global carbon budget. Disturbance by natural phenomena, such as fire or wind, as well as by human activities, such as forest harvest, and subsequent recovery, complicate the quantification of carbon storage and release. The resulting spatial and temporal heterogeneity of terrestrial biomass and carbon in vegetation make it very difficult to estimate terrestrial carbon stocks and quantify their dynamics. Vegetation height profiles and disturbance recovery patterns are also required to assess ecosystem health and characterize habitat. The three-dimensional structure of vegetation provides habitats for many species and is a control on biodiversity. Canopy height and structure influence habitat use and specialization, two fundamental processes that modify species richness and abundance across ecosystems. Accurate and consistent 3D measurements of forest structure at the landscape scale are needed for assessing impacts to animal habitats and biodiversity following disturbance.

Recovery of forest structure and spectral properties after selective logging in lowland Bolivia.

PubMed

Broadbent, Eben N; Zarin, Daniel J; Asner, Gregory P; Peña-Claros, Marielos; Cooper, Amanda; Littell, Ramon

2006-06-01

Effective monitoring of selective logging from remotely sensed data requires an understanding of the spatial and temporal thresholds that constrain the utility of those data, as well as the structural and ecological characteristics of forest disturbances that are responsible for those constraints. Here we assess those thresholds and characteristics within the context of selective logging in the Bolivian Amazon. Our study combined field measurements of the spatial and temporal dynamics of felling gaps and skid trails ranging from <1 to 19 months following reduced-impact logging in a forest in lowland Bolivia with remote-sensing measurements from simultaneous monthly ASTER satellite overpasses. A probabilistic spectral mixture model (AutoMCU) was used to derive per-pixel fractional cover estimates of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and soil. Results were compared with the normalized difference in vegetation index (NDVI). The forest studied had considerably lower basal area and harvest volumes than logged sites in the Brazilian Amazon where similar remote-sensing analyses have been performed. Nonetheless, individual felling-gap area was positively correlated with canopy openness, percentage liana coverage, rates of vegetation regrowth, and height of remnant NPV. Both liana growth and NPV occurred primarily in the crown zone of the felling gap, whereas exposed soil was limited to the trunk zone of the gap. In felling gaps >400 m2, NDVI, and the PV and NPV fractions, were distinguishable from unlogged forest values for up to six months after logging; felling gaps <400 m2 were distinguishable for up to three months after harvest, but we were entirely unable to distinguish skid trails from our analysis of the spectral data.

Near ground level sensing for spatial analysis of vegetation

NASA Technical Reports Server (NTRS)

Sauer, Tom; Rasure, John; Gage, Charlie

1991-01-01

Measured changes in vegetation indicate the dynamics of ecological processes and can identify the impacts from disturbances. Traditional methods of vegetation analysis tend to be slow because they are labor intensive; as a result, these methods are often confined to small local area measurements. Scientists need new algorithms and instruments that will allow them to efficiently study environmental dynamics across a range of different spatial scales. A new methodology that addresses this problem is presented. This methodology includes the acquisition, processing, and presentation of near ground level image data and its corresponding spatial characteristics. The systematic approach taken encompasses a feature extraction process, a supervised and unsupervised classification process, and a region labeling process yielding spatial information.

What are hot and what are not in an urban landscape: quantifying and explaining the land surface temperature pattern in Beijing, China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuang, Wenhui; Liu, Yue; Dou, Yinyin

Understanding how landscape components affect the urban heat islands is crucial for urban ecological planning and sustainable development. The purpose of this research was to quantify the spatial pattern of land surface temperatures (LSTs) and associated heat fluxes in relation to land-cover types in Beijing, China, using portable infrared thermometers, thermal infrared imagers, and the moderate resolution imaging spectroradiometer. The spatial differences and the relationships between LSTs and the hierarchical landscape structure were analyzed with in situ observations of surface radiation and heat fluxes. Large LST differences were found among various land-use/land-cover types, urban structures, and building materials. Within themore » urban area, the mean LST of urban impervious surfaces was about 6–12°C higher than that of the urban green space. LSTs of built-up areas were on average 3–6°C higher than LSTs of rural areas. The observations for surface radiation and heat fluxes indicated that the differences were caused by different fractions of sensible heat or latent heat flux in net radiation. LSTs decreased with increasing elevation and normalized difference vegetation index. Variations in building materials and urban structure significantly influenced the spatial pattern of LSTs in urban areas. By contrast, elevation and vegetation cover are the major determinants of the LST pattern in rural areas. In summary, to alleviate urban heat island intensity, urban planners and policy makers should pay special attention to the selection of appropriate building materials, the reasonable arrangement of urban structures, and the rational design of landscape components.« less

What are hot and what are not in an urban landscape: quantifying and explaining the land surface temperature pattern in Beijing, China

DOE PAGES

Kuang, Wenhui; Liu, Yue; Dou, Yinyin; ...

2014-12-06

Understanding how landscape components affect the urban heat islands is crucial for urban ecological planning and sustainable development. The purpose of this research was to quantify the spatial pattern of land surface temperatures (LSTs) and associated heat fluxes in relation to land-cover types in Beijing, China, using portable infrared thermometers, thermal infrared imagers, and the moderate resolution imaging spectroradiometer. The spatial differences and the relationships between LSTs and the hierarchical landscape structure were analyzed with in situ observations of surface radiation and heat fluxes. Large LST differences were found among various land-use/land-cover types, urban structures, and building materials. Within themore » urban area, the mean LST of urban impervious surfaces was about 6–12°C higher than that of the urban green space. LSTs of built-up areas were on average 3–6°C higher than LSTs of rural areas. The observations for surface radiation and heat fluxes indicated that the differences were caused by different fractions of sensible heat or latent heat flux in net radiation. LSTs decreased with increasing elevation and normalized difference vegetation index. Variations in building materials and urban structure significantly influenced the spatial pattern of LSTs in urban areas. By contrast, elevation and vegetation cover are the major determinants of the LST pattern in rural areas. In summary, to alleviate urban heat island intensity, urban planners and policy makers should pay special attention to the selection of appropriate building materials, the reasonable arrangement of urban structures, and the rational design of landscape components.« less

City 2020+

NASA Astrophysics Data System (ADS)

Schneider, C.; Buttstädt, M.; Merbitz, H.; Sachsen, T.; Ketzler, G.; Michael, S.; Klemme, M.; Dott, W.; Selle, K.; Hofmeister, H.

2010-09-01

This research initiative CITY 2020+ assesses the risks and opportunities for residents in urban built environments under projected demographic and climate change for the year 2020 and beyond, using the City of Aachen as a case study. CITY 2020+ develops scenarios, options and tools for planning and developing sustainable future city structures. We investigate how urban environment, political structure and residential behavior can best be adapted, with attention to the interactions among structural, political, and sociological configurations and with their consequences on human health. Demographers project that in the EU-25-States by 2050, approximately 30% of the population will be over age 65. Also by 2050, average tem¬peratures are projected to rise by 1 to 2 K. Combined, Europe can expect enhanced thermal stress and higher levels of particulate matter. CITY 2020+ amongst other sub-projects includes research project dealing with (1) a micro-scale assessment of blockages to low-level cold-air drainage flow into the city centre by vegetation and building structures, (2) a detailed analysis of the change of probability density functions related to the occurrence of heat waves during summer and the spatial and temporal structure of the urban heat island (UHI) (3) a meso-scale analysis of particulate matter (PM) concentrations depending on topography, local meteorological conditions and synoptic-scale weather patterns. First results will be presented specifically from sub-projects related to vegetation barriers within cold air drainage, the assessment of the UHI and the temporal and spatial pattern of PM loadings in the city centre. The analysis of the cold air drainage flow is investigated in two consecutive years with a clearing of vegetation stands in the beginning of the second year early in 2010. The spatial pattern of the UHI and its possible enhancement by climate change is addressed employing a unique setup using GPS devices and temperature probes fixed to several public transport units running all across the city. This is accompanied by an analysis of probability density functions (PDF) for heat waves based on recent climate data and climate projections. A dense net of 40 PM measurement sites is operated in order to obtain the spatial pattern of PM concentration as depending on meteorological condition and location. It is lined out how this climate related sub-projects interact with investigations on social networks, governance issues, buildings structure development and health outcome. Related to the later the chemical composition of PM is analyzed in more detail and related to the spatial patterns of health deficiencies. At a later stage City2020+ will propose new strategies based on cooperation from the fields of medicine, geography, sociology, history, civil engineering, and architecture for adapting the city for future needs. The Project CITY 2020+ is part of the interdisciplinary Project House HumTec (Human Sciences and Technology) at RWTH Aachen University funded by the Excellence Initiative of the German federal and state governments through the Deutsche Forschungsgemeinschaft (German Research Foundation, DFG).

Linking imaging spectroscopy and trait data to better understand spatial and temporal variability in functional traits

NASA Astrophysics Data System (ADS)

Townsend, Philip; Kruger, Eric; Wang, Zhihui; Singh, Aditya

2017-04-01

Imaging spectroscopy exhibits great potential for mapping foliar functional traits that are impractical or expensive to regularly measure on the ground, and are essentially impossible to characterize comprehensively across space. Specifically, the high information content in spectroscopic data enables us to identify narrow spectral feature that are associated with vegetation primary and secondary biochemistry (nutrients, pigments, defensive compounds), leaf structure (e.g., leaf mass per area), canopy structure, and physiological capacity. Ultimately, knowledge of the variability in such traits is critical to understanding vegetation productivity, as well as responses to climatic variability, disturbances, pests and pathogens. The great challenge to the use of imaging spectroscopy to supplement trait databases is the development of trait retrieval approaches that are broadly applicable within and between ecosystem types. Here, we outline how we are using the US National Ecological Observatory Network (NEON) to prototype the scaling and comparison of trait distributions derived from field measurements and imagery. We find that algorithms to map traits from imagery are robust across ecosystem types, when controlling for physiognomy and vegetation percent cover, and that among all vegetation types, the chemometric algorithms utilize similar features for mapping of traits.

Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops

NASA Astrophysics Data System (ADS)

Kross, Angela; McNairn, Heather; Lapen, David; Sunohara, Mark; Champagne, Catherine

2015-02-01

Leaf area index (LAI) and biomass are important indicators of crop development and the availability of this information during the growing season can support farmer decision making processes. This study demonstrates the applicability of RapidEye multi-spectral data for estimation of LAI and biomass of two crop types (corn and soybean) with different canopy structure, leaf structure and photosynthetic pathways. The advantages of Rapid Eye in terms of increased temporal resolution (∼daily), high spatial resolution (∼5 m) and enhanced spectral information (includes red-edge band) are explored as an individual sensor and as part of a multi-sensor constellation. Seven vegetation indices based on combinations of reflectance in green, red, red-edge and near infrared bands were derived from RapidEye imagery between 2011 and 2013. LAI and biomass data were collected during the same period for calibration and validation of the relationships between vegetation indices and LAI and dry above-ground biomass. Most indices showed sensitivity to LAI from emergence to 8 m2/m2. The normalized difference vegetation index (NDVI), the red-edge NDVI and the green NDVI were insensitive to crop type and had coefficients of variations (CV) ranging between 19 and 27%; and coefficients of determination ranging between 86 and 88%. The NDVI performed best for the estimation of dry leaf biomass (CV = 27% and r2 = 090) and was also insensitive to crop type. The red-edge indices did not show any significant improvement in LAI and biomass estimation over traditional multispectral indices. Cumulative vegetation indices showed strong performance for estimation of total dry above-ground biomass, especially for corn (CV ≤ 20%). This study demonstrated that continuous crop LAI monitoring over time and space at the field level can be achieved using a combination of RapidEye, Landsat and SPOT data and sensor-dependant best-fit functions. This approach eliminates/reduces the need for reflectance resampling, VIs inter-calibration and spatial resampling.

On modeling the organization of landscapes and vegetation patterns controlled by solar radiation

NASA Astrophysics Data System (ADS)

Istanbulluoglu, E.; Yetemen, O.

2014-12-01

Solar radiation is a critical driver of ecohydrologic processes and vegetation dynamics. Patterns of runoff generation and vegetation dictate landscape geomorphic response. Distinct patterns in the organization of soil moisture, vegetation type, and landscape morphology have been documented in close relation to aspect in a range of climates. Within catchments, from north to south facing slopes, studies have shown ecotone shifts from forest to shrub species, and steep diffusion-dominated landforms to fluvial landforms. Over the long term differential evolution of ecohydrology and geomorphology leads to observed asymmetric structure in the planform of channel network and valley morphology. In this talk we present examples of coupled modeling of ecohydrology and geomorphology driven by solar radiation. In a cellular automata model of vegetation dynamics we will first show how plants organize in north and south facing slopes and how biodiversity changes with elevation. When vegetation-erosion feedbacks are coupled emergent properties of the coupled system are observed in the modeled elevation and vegetation fields. Integrating processes at a range of temporal and spatial scales, coupled models of ecohydrologic and geomorphic dynamics enable examination of global change impacts on landscapes and ecosystems.

Scaling effect of fraction of vegetation cover retrieved by algorithms based on linear mixture model

NASA Astrophysics Data System (ADS)

Obata, Kenta; Miura, Munenori; Yoshioka, Hiroki

2010-08-01

Differences in spatial resolution among sensors have been a source of error among satellite data products, known as a scaling effect. This study investigates the mechanism of the scaling effect on fraction of vegetation cover retrieved by a linear mixture model which employs NDVI as one of the constraints. The scaling effect is induced by the differences in texture, and the differences between the true endmember spectra and the endmember spectra assumed during retrievals. A mechanism of the scaling effect was analyzed by focusing on the monotonic behavior of spatially averaged FVC as a function of spatial resolution. The number of endmember is limited into two to proceed the investigation analytically. Although the spatially-averaged NDVI varies monotonically along with spatial resolution, the corresponding FVC values does not always vary monotonically. The conditions under which the averaged FVC varies monotonically for a certain sequence of spatial resolutions, were derived analytically. The increasing and decreasing trend of monotonic behavior can be predicted from the true and assumed endmember spectra of vegetation and non-vegetation classes regardless the distributions of the vegetation class within a fixed area. The results imply that the scaling effect on FVC is more complicated than that on NDVI, since, unlike NDVI, FVC becomes non-monotonic under a certain condition determined by the true and assumed endmember spectra.

Modeling spatial patterns of soil respiration in maize fields from vegetation and soil property factors with the use of remote sensing and geographical information system.

PubMed

Huang, Ni; Wang, Li; Guo, Yiqiang; Hao, Pengyu; Niu, Zheng

2014-01-01

To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m(-2) s(-1). The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China.

Modeling Spatial Patterns of Soil Respiration in Maize Fields from Vegetation and Soil Property Factors with the Use of Remote Sensing and Geographical Information System

PubMed Central

Huang, Ni; Wang, Li; Guo, Yiqiang; Hao, Pengyu; Niu, Zheng

2014-01-01

To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m−2 s−1. The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China. PMID:25157827

Topographic, meteorologic, and canopy controls on the scaling characteristics of the spatial distribution of snow depth fields

Treesearch

Ernesto Trujillo; Jorge A. Ramirez; Kelly J. Elder

2007-01-01

In this study, LIDAR snow depths, bare ground elevations (topography), and elevations filtered to the top of vegetation (topography + vegetation) in five 1-km2 areas are used to determine whether the spatial distribution of snow depth exhibits scale invariance, and the control that vegetation, topography, and winds exert on such behavior. The one-dimensional and mean...

Integration of GIS, Geostatistics, and 3-D Technology to Assess the Spatial Distribution of Soil Moisture

NASA Technical Reports Server (NTRS)

Betts, M.; Tsegaye, T.; Tadesse, W.; Coleman, T. L.; Fahsi, A.

1998-01-01

The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.

Providing a Spatial Context for Crop Insurance in Ethiopia: Multiscale Comparisons of Vegetation Metrics in Tigray

NASA Astrophysics Data System (ADS)

Mann, B. F.; Small, C.

2014-12-01

Weather-based index insurance projects are rapidly expanding across the developing world. Many of these projects use satellite-based observations to detect extreme weather events, which inform and trigger payouts to smallholder farmers. While most index insurance programs use precipitation measurements to determine payouts, the use of remotely sensed observations of vegetation is currently being explored. In order to use vegetation indices as a basis for payouts, it is necessary to establish a consistent relationship between the vegetation index and the health and abundance of agriculture on the ground. The accuracy with which remotely sensed vegetation indices can detect changes in agriculture depends on both the spatial scale of the agriculture and the spatial resolution of the sensor. This study analyzes the relationship between meter and decameter scale vegetation fraction estimates derived from linear spectral mixture models with a more commonly used vegetation index (NDVI, EVI) at hectometer spatial scales. In addition, the analysis incorporates land cover/land use field observations collected in Tigray Ethiopia in July 2013. . It also tests the flexibility and utility of a standardized spectral mixture model in which land cover is represented as continuous fields of rock and soil substrate (S), vegetation (V) and dark surfaces (D; water, shadow). This analysis found strong linear relationships with vegetation metrics at 1.6-meter, 30-meter and 250-meter resolutions across spectrally diverse subsets of Tigray, Ethiopia and significantly correlated relationships using the Spearman's rho statistic. The observed linear scaling has positive implications for future use of moderate resolution vegetation indices in similar landscapes; especially index insurance projects that are scaling up across the developing world using remotely-sensed environmental information.

Historical and contemporary geographic data reveal complex spatial and temporal responses of vegetation to climate and land stewardship

USGS Publications Warehouse

Villarreal, Miguel L.; Norman, Laura M.; Webb, Robert H.; Turner, Raymond M.

2013-01-01

Vegetation and land-cover changes are not always directional but follow complex trajectories over space and time, driven by changing anthropogenic and abiotic conditions. We present a multi-observational approach to land-change analysis that addresses the complex geographic and temporal variability of vegetation changes related to climate and land use. Using land-ownership data as a proxy for land-use practices, multitemporal land-cover maps, and repeat photography dating to the late 19th century, we examine changing spatial and temporal distributions of two vegetation types with high conservation value in the southwestern United States: grasslands and riparian vegetation. In contrast to many reported vegetation changes, notably shrub encroachment in desert grasslands, we found an overall increase in grassland area and decline of xeroriparian and riparian vegetation. These observed change patterns were neither temporally directional nor spatially uniform over the landscape. Historical data suggest that long-term vegetation changes coincide with broad climate fluctuations while fine-scale patterns are determined by land-management practices. In some cases, restoration and active management appear to weaken the effects of climate on vegetation; therefore, if land managers in this region act in accord with on-going directional changes, the current drought and associated ecological reorganization may provide an opportunity to achieve desired restoration endpoints.

Tundra landform and vegetation productivity trend maps for the Arctic Coastal Plain of northern Alaska

PubMed Central

Lara, Mark J.; Nitze, Ingmar; Grosse, Guido; McGuire, A. David

2018-01-01

Arctic tundra landscapes are composed of a complex mosaic of patterned ground features, varying in soil moisture, vegetation composition, and surface hydrology over small spatial scales (10–100 m). The importance of microtopography and associated geomorphic landforms in influencing ecosystem structure and function is well founded, however, spatial data products describing local to regional scale distribution of patterned ground or polygonal tundra geomorphology are largely unavailable. Thus, our understanding of local impacts on regional scale processes (e.g., carbon dynamics) may be limited. We produced two key spatiotemporal datasets spanning the Arctic Coastal Plain of northern Alaska (~60,000 km2) to evaluate climate-geomorphological controls on arctic tundra productivity change, using (1) a novel 30 m classification of polygonal tundra geomorphology and (2) decadal-trends in surface greenness using the Landsat archive (1999–2014). These datasets can be easily integrated and adapted in an array of local to regional applications such as (1) upscaling plot-level measurements (e.g., carbon/energy fluxes), (2) mapping of soils, vegetation, or permafrost, and/or (3) initializing ecosystem biogeochemistry, hydrology, and/or habitat modeling. PMID:29633984

Tundra landform and vegetation productivity trend maps for the Arctic Coastal Plain of northern Alaska

USGS Publications Warehouse

Lara, Mark J.; Nitze, Ingmar; Grosse, Guido; McGuire, A. David

2018-01-01

Arctic tundra landscapes are composed of a complex mosaic of patterned ground features, varying in soil moisture, vegetation composition, and surface hydrology over small spatial scales (10–100 m). The importance of microtopography and associated geomorphic landforms in influencing ecosystem structure and function is well founded, however, spatial data products describing local to regional scale distribution of patterned ground or polygonal tundra geomorphology are largely unavailable. Thus, our understanding of local impacts on regional scale processes (e.g., carbon dynamics) may be limited. We produced two key spatiotemporal datasets spanning the Arctic Coastal Plain of northern Alaska (~60,000 km2) to evaluate climate-geomorphological controls on arctic tundra productivity change, using (1) a novel 30 m classification of polygonal tundra geomorphology and (2) decadal-trends in surface greenness using the Landsat archive (1999–2014). These datasets can be easily integrated and adapted in an array of local to regional applications such as (1) upscaling plot-level measurements (e.g., carbon/energy fluxes), (2) mapping of soils, vegetation, or permafrost, and/or (3) initializing ecosystem biogeochemistry, hydrology, and/or habitat modeling.

Identifying western yellow-billed cuckoo breeding habitat with a dual modelling approach

USGS Publications Warehouse

Johnson, Matthew J.; Hatten, James R.; Holmes, Jennifer A.; Shafroth, Patrick B.

2017-01-01

The western population of the yellow-billed cuckoo (Coccyzus americanus) was recently listed as threatened under the federal Endangered Species Act. Yellow-billed cuckoo conservation efforts require the identification of features and area requirements associated with high quality, riparian forest habitat at spatial scales that range from nest microhabitat to landscape, as well as lower-suitability areas that can be enhanced or restored. Spatially explicit models inform conservation efforts by increasing ecological understanding of a target species, especially at landscape scales. Previous yellow-billed cuckoo modelling efforts derived plant-community maps from aerial photography, an expensive and oftentimes inconsistent approach. Satellite models can remotely map vegetation features (e.g., vegetation density, heterogeneity in vegetation density or structure) across large areas with near perfect repeatability, but they usually cannot identify plant communities. We used aerial photos and satellite imagery, and a hierarchical spatial scale approach, to identify yellow-billed cuckoo breeding habitat along the Lower Colorado River and its tributaries. Aerial-photo and satellite models identified several key features associated with yellow-billed cuckoo breeding locations: (1) a 4.5 ha core area of dense cottonwood-willow vegetation, (2) a large native, heterogeneously dense forest (72 ha) around the core area, and (3) moderately rough topography. The odds of yellow-billed cuckoo occurrence decreased rapidly as the amount of tamarisk cover increased or when cottonwood-willow vegetation was limited. We achieved model accuracies of 75–80% in the project area the following year after updating the imagery and location data. The two model types had very similar probability maps, largely predicting the same areas as high quality habitat. While each model provided unique information, a dual-modelling approach provided a more complete picture of yellow-billed cuckoo habitat requirements and will be useful for management and conservation activities.

Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 1; Theory

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Schull, Mitchell A.; Samanta, Arindam; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramakrishna R.; Knyazikhin, Yuri; Myneni, Ranga B.

2008-01-01

The generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher information content). Implementation of this approach indicates good consistency in LAI values retrieved from NDVI (AVHRRmode) and spectral BRF (MODIS-mode). Specific details of the implementation and evaluation of the derived products are detailed in the second part of this two-paper series.

High-Resolution Urban Greenery Mapping for Micro-Climate Modelling Based on 3d City Models

NASA Astrophysics Data System (ADS)

Hofierka, J.; Gallay, M.; Kaňuk, J.; Šupinský, J.; Šašak, J.

2017-10-01

Urban greenery has various positive micro-climate effects including mitigation of heat islands. The primary root of heat islands in cities is in absorption of solar radiation by the mass of building structures, roads and other solid materials. The absorbed heat is subsequently re-radiated into the surroundings and increases ambient temperatures. The vegetation can stop and absorb most of incoming solar radiation mostly via the photosynthesis and evapotranspiration process. However, vegetation in mild climate of Europe manifests considerable annual seasonality which can also contribute to the seasonal change in the cooling effect of the vegetation on the urban climate. Modern methods of high-resolution mapping and new generations of sensors have brought opportunity to record the dynamics of urban greenery in a high resolution in spatial, spectral, and temporal domains. In this paper, we use the case study of the city of Košice in Eastern Slovakia to demonstrate the methodology of 3D mapping and modelling the urban greenery during one vegetation season in 2016. The purpose of this monitoring is to capture 3D effects of urban greenery on spatial distribution of solar radiation in urban environment. Terrestrial laser scanning was conducted on four selected sites within Košice in ultra-high spatial resolution. The entire study area, which included these four smaller sites, comprised 4 km2 of the central part of the city was flown within a single airborne lidar and photogrammetric mission to capture the upper parts of buildings and vegetation. The acquired airborne data were used to generate a 3D city model and the time series of terrestrial lidar data were integrated with the 3D city model. The results show that the terrestrial and airborne laser scanning techniques can be effectively used to monitor seasonal changes in foliage of trees in order to assess the transmissivity of the canopy for microclimate modelling.

Monitoring landscape change for LANDFIRE using multi-temporal satellite imagery and ancillary data

Treesearch

James E. Vogelmann; Jay R. Kost; Brian Tolk; Stephen Howard; Karen Short; Xuexia Chen; Chengquan Huang; Kari Pabst; Matthew G. Rollins

2011-01-01

LANDFIRE is a large interagency project designed to provide nationwide spatial data for fire management applications. As part of the effort, many 2000 vintage Landsat Thematic Mapper and Enhanced Thematic Mapper plus data sets were used in conjunction with a large volume of field information to generate detailed vegetation type and structure data sets for the entire...

Historical fire and vegetation dynamics in dry forests of the interior Pacific Northwest, USA, and relationships to northern spotted owl (Strix occidentalis caurina) habitat conservation

Treesearch

Rebecca S.H. Kennedy; Michael C. Wimberly

2009-01-01

Regional conservation planning frequently relies on general assumptions about historical disturbance regimes to inform decisions about landscape restoration, reserve allocations, and landscape management. Spatially explicit simulations of landscape dynamics provide quantitative estimates of landscape structure and allow for the testing of alternative scenarios. We used...

Discriminating disturbance from natural variation with LiDAR in semi-arid forests in the southwestern USA

Treesearch

T. L. Swetnam; A. M. Lynch; D. A. Falk; S. R. Yool; D. P. Guertin

2015-01-01

Discriminating amongst spatial configurations and climax size of trees in forests along varying physical gradients from time since last disturbance is a significant component of applied forest management. Understanding what has led to the existing vegetation’s structure has important implications for monitoring succession and eco-hydrological interactions within the...

Mapping forest canopy gaps using air-photo interpretation and ground surveys

USGS Publications Warehouse

Fox, T.J.; Knutson, M.G.; Hines, R.K.

2000-01-01

Canopy gaps are important structural components of forested habitats for many wildlife species. Recent improvements in the spatial accuracy of geographic information system tools facilitate accurate mapping of small canopy features such as gaps. We compared canopy-gap maps generated using ground survey methods with those derived from air-photo interpretation. We found that maps created from high-resolution air photos were more accurate than those created from ground surveys. Errors of omission were 25.6% for the ground-survey method and 4.7% for the air-photo method. One variable of inter est in songbird research is the distance from nests to gap edges. Distances from real and simulated nests to gap edges were longer using the ground-survey maps versus the air-photo maps, indicating that gap omission could potentially bias the assessment of spatial relationships. If research or management goals require location and size of canopy gaps and specific information about vegetation structure, we recommend a 2-fold approach. First, canopy gaps can be located and the perimeters defined using 1:15,000-scale or larger aerial photographs and the methods we describe. Mapped gaps can then be field-surveyed to obtain detailed vegetation data.

The Flora Mission for Ecosystem Composition, Disturbance and Productivity

NASA Technical Reports Server (NTRS)

Asner, Gregory P.; Knox, Robert G.; Green, Robert O.; Ungar, Stephen G.

2005-01-01

Global land use and climate variability alter ecosystem conditions - including structure, function, and biological diversity - at a pace that requires unambiguous observations from satellite vantage points. Current global measurements are limited to general land cover, some disturbances, vegetation leaf area index, and canopy energy absorption. Flora is a pathfinding mission that provides new measurements of ecosystem structure, function, and diversity to understand the spatial and temporal dynamics of human and natural disturbances, and the biogeochemical and physiological responses of ecosystems to disturbance. The mission relies upon high-fidelity imaging spectroscopy to deliver full optical spectrum measurements (400-2500 nm) of the global land surface on a monthly time step at 45 meter spatial resolution for three years. The Flora measurement objectives are: (i) fractional cover of biological materials, (ii) canopy water content, (iii) vegetation pigments and light-use efficiency, (iv) plant functional types, (v) fire fuel load and fuel moisture content, and (vi) disturbance occurrence, type and intensity. These measurements are made using a multi-parameter, spectroscopic analysis approach afforded by observation of the full optical spectrum. Combining these measurements, along with additional observations from multispectral sensors, Flora will far advance global studies and models of ecosystem dynamics and change.

Synergy of VSWIR and LiDAR for Ecosystem Structure, Biomass, and Canopy Diversity

NASA Technical Reports Server (NTRS)

Cook, Bruce D.; Asner, Gregory P.

2010-01-01

This slide presentation reviews the use of Visible ShortWave InfraRed (VSWIR) Imaging Spectrometer and LiDAR to study ecosystem structure, biomass and canopy diversity. It is shown that the biophysical data from LiDAR and biochemical information from hyperspectral remote sensing provides complementary data for: (1) describing spatial patterns of vegetation and biodiversity, (2) characterizing relationships between ecosystem form and function, and (3) detecting natural and human induced change that affects the biogeochemical cycles.

A Numerical Study of Atmospheric Perturbations Induced by Heat From a Wildland Fire: Sensitivity to Vertical Canopy Structure and Heat Source Strength

NASA Astrophysics Data System (ADS)

Kiefer, Michael T.; Zhong, Shiyuan; Heilman, Warren E.; Charney, Joseph J.; Bian, Xindi

2018-03-01

An improved understanding of atmospheric perturbations within and above a forest during a wildland fire has relevance to many aspects of wildland fires including fire spread, smoke transport and dispersion, and tree mortality. In this study, the ARPS-CANOPY model, a version of the Advanced Regional Prediction System (ARPS) model with a canopy parameterization, is utilized in a series of idealized numerical experiments to investigate the influence of vertical canopy structure on the atmospheric response to a stationary sensible heat flux at the ground ("fire heat flux"), broadly consistent in magnitude with the sensible heat flux from a low-intensity surface fire. Five vertical canopy structures are combined with five fire heat flux magnitudes to yield a matrix of 25 simulations. Analyses of the fire-heat-flux-perturbed u component of the wind, vertical velocity, kinetic energy, and temperature show that the spatial pattern and magnitude of the perturbations are sensitive to vertical canopy structure. Both vertical velocity and kinetic energy exhibit an increasing trend with increasing fire heat flux that is stronger for cases with some amount of overstory vegetation than cases with exclusively understory vegetation. A weaker trend in cases with exclusively understory vegetation indicates a damping of the atmospheric response to the sensible heat from a surface fire when vegetation is most concentrated near the surface. More generally, the results presented in this study suggest that canopy morphology should be considered when applying the results of a fire-atmosphere interaction study conducted in one type of forest to other forests with different canopy structures.

Species diversity of remnant calcareous grasslands in south eastern Germany depends on litter cover and landscape structure

NASA Astrophysics Data System (ADS)

Huber, Stephanie; Huber, Birgit; Stahl, Silvia; Schmid, Christoph; Reisch, Christoph

2017-08-01

Species diversity depends on, often interfering, multiple ecological drivers. Comprehensive approaches are hence needed to understand the mechanisms determining species diversity. In this study, we analysed the impact of vegetation structure, soil properties and fragmentation on the plant species diversity of remnant calcareous grasslands, therefore, in a comparative approach. We determined plant species diversity of 18 calcareous grasslands in south eastern Germany including all species and grassland specialists separately. Furthermore, we analysed the spatial structure of the grasslands as a result of fragmentation during the last 150 years (habitat area, distance to the nearest calcareous grassland and connectivity in 1830 and 2013). We also collected data concerning the vegetation structure (height of the vegetation, cover of bare soil, grass and litter) and the soil properties (content of phosphorous and potassium, ratio of carbon and nitrogen) of the grassland patches. Data were analysed using Bayesian multiple regressions. We observed a habitat loss of nearly 80% and increasing isolation between grasslands since 1830. In the Bayesian multiple regressions the species diversity of the studied grasslands depended negatively on cover of litter and to a lower degree on the distance to the nearest calcareous grassland in 2013, whereas soil properties had no significant impact. Our study supports the observation that vegetation structure, which strongly depends on land use, is often more important for the species richness of calcareous grasslands than fragmentation or soil properties. Even small and isolated grasslands may, therefore, contribute significantly to the conservation of species diversity, when they are still grazed.

Modeling landscape evapotranspiration by integrating land surface phenology and a water balance algorithm

USGS Publications Warehouse

Senay, Gabriel B.

2008-01-01

The main objective of this study is to present an improved modeling technique called Vegetation ET (VegET) that integrates commonly used water balance algorithms with remotely sensed Land Surface Phenology (LSP) parameter to conduct operational vegetation water balance modeling of rainfed systems at the LSP’s spatial scale using readily available global data sets. Evaluation of the VegET model was conducted using Flux Tower data and two-year simulation for the conterminous US. The VegET model is capable of estimating actual evapotranspiration (ETa) of rainfed crops and other vegetation types at the spatial resolution of the LSP on a daily basis, replacing the need to estimate crop- and region-specific crop coefficients.

[Spatial pattern of forest biomass and its influencing factors in the Great Xing'an Mountains, Heilongjiang Province, China].

PubMed

Wang, Xiao-Li; Chang, Yu; Chen, Hong-Wei; Hu, Yuan-Man; Jiao, Lin-Lin; Feng, Yu-Ting; Wu, Wen; Wu, Hai-Feng

2014-04-01

Based on field inventory data and vegetation index EVI (enhanced vegetation index), the spatial pattern of the forest biomass in the Great Xing'an Mountains, Heilongjiang Province was quantitatively analyzed. Using the spatial analysis and statistics tools in ArcGIS software, the impacts of climatic zone, elevation, slope, aspect and vegetation type on the spatial pattern of forest biomass were explored. The results showed that the forest biomass in the Great Xing'an Mountains was 350 Tg and spatially aggregated with great increasing potentials. Forest biomass density in the cold temperate humid zone (64.02 t x hm(-2)) was higher than that in the temperate humid zone (60.26 t x hm(-2)). The biomass density of each vegetation type was in the order of mixed coniferous forest (65.13 t x hm(-2)) > spruce-fir forest (63.92 t x hm(-2)) > Pinus pumila-Larix gmelinii forest (63.79 t x hm(-2)) > Pinus sylvestris var. mongolica forest (61.97 t x hm(-2)) > Larix gmelinii forest (61.40 t x hm(-2)) > deciduous broadleaf forest (58.96 t x hm(-2)). With the increasing elevation and slope, the forest biomass density first decreased and then increased. The forest biomass density in the shady slopes was greater than that in the sunny slopes. The spatial pattern of forest biomass in the Great Xing' an Mountains exhibited a heterogeneous pattern due to the variation of climatic zone, vegetation type and topographical factor. This spatial heterogeneity needs to be accounted when evaluating forest biomass at regional scales.

Effects of spatial heterogeneity on butterfly species richness in Rocky Mountain National Park, CO, USA

USGS Publications Warehouse

Kumar, S.; Simonson, S.E.; Stohlgren, T.J.

2009-01-01

We investigated butterfly responses to plot-level characteristics (plant species richness, vegetation height, and range in NDVI [normalized difference vegetation index]) and spatial heterogeneity in topography and landscape patterns (composition and configuration) at multiple spatial scales. Stratified random sampling was used to collect data on butterfly species richness from seventy-six 20 ?? 50 m plots. The plant species richness and average vegetation height data were collected from 76 modified-Whittaker plots overlaid on 76 butterfly plots. Spatial heterogeneity around sample plots was quantified by measuring topographic variables and landscape metrics at eight spatial extents (radii of 300, 600 to 2,400 m). The number of butterfly species recorded was strongly positively correlated with plant species richness, proportion of shrubland and mean patch size of shrubland. Patterns in butterfly species richness were negatively correlated with other variables including mean patch size, average vegetation height, elevation, and range in NDVI. The best predictive model selected using Akaike's Information Criterion corrected for small sample size (AICc), explained 62% of the variation in butterfly species richness at the 2,100 m spatial extent. Average vegetation height and mean patch size were among the best predictors of butterfly species richness. The models that included plot-level information and topographic variables explained relatively less variation in butterfly species richness, and were improved significantly after including landscape metrics. Our results suggest that spatial heterogeneity greatly influences patterns in butterfly species richness, and that it should be explicitly considered in conservation and management actions. ?? 2008 Springer Science+Business Media B.V.

Small wash functions and effects of their disturbance on vegetation of a Mojave Desert bajada

NASA Astrophysics Data System (ADS)

Sandquist, D. R.; Bedford, D.; Macias, M.; Miller, D. M.; Newlander, A.; Schwinning, S.

2011-12-01

The extensive network of small washes and channels that pervades most desert bajadas usually represents only a small proportion of the bajada's spatial area and are usually devoid of vegetation. However, these channels may be the most important geomorphic feature influencing vegetation properties and processes in arid lands. To evaluate the functional influence of small channels on the vegetation of a Mojave Desert bajada, we conducted a series of observations and experiments across a ~100 year old linear disturbance (railroad and parallel road) that disrupts the natural flow path of the channel network. In areas below the railroad where flow has been either increased due to channel diversion and coalescence through culverts, or cut off due to diversion, plant community structure and cover has changed relative to undisturbed areas. Plant physiological responses to simulated runoff experiments, conducted in active (undisturbed) and inactive (cut-off) channels, revealed subtle differences that, when compounded through time, are likely to contribute to these shifts in vegetation. Measurements of water potential on the two dominant plant species, Larrea tridentata and Ambrosia dumosa, indicate that Larrea within 3 m of a channel, and Ambrosia within 2 m, access water from the channel. However, the water potential responses were less pronounced, shorter in duration and more variable for plants adjacent to inactive channels than for those near active channels. Stomatal conductance and sap-flow measurements on Larrea corroborated these findings, suggesting that root patterns and functions associated with channels are altered when water flow is reduced or eliminated over extended periods of time. These findings indicate that disturbance of small desert washes and channels can lead to vegetation shifts through time with consequences that are not yet fully understood. Small desert washes and channels may represent a minor spatial component of the vast bajada landscape, but runoff and higher infiltration rates, coupled with the breadth of their spatial influence on adjacent plants, suggests that these modest geomorphic features may have a disproportionate impact on plant function and community properties in arid ecosystems.

Spatio-temporal development of vegetation die-off in a submerging coastal marsh

USGS Publications Warehouse

Schepers, Lennert; Kirwan, Matthew; Guntenspergen, Glenn R.; Temmerman, Stijn

2017-01-01

In several places around the world, coastal marsh vegetation is converting to open water through the formation of pools. This is concerning, as vegetation die-off is expected to reduce the marshes' capacity to adapt to sea level rise by vegetation-induced sediment accretion. Quantitative analyses of the spatial and temporal development of marsh vegetation die-off are scarce, although these are needed to understand the bio-geomorphic feedback effects of vegetation die-off on flow, erosion, and sedimentation. In this study, we quantified the spatial and temporal development of marsh vegetation die-off with aerial images from 1938 to 2010 in a submerging coastal marsh along the Blackwater River (Maryland, U.S.A). Our results indicate that die-off begins with conversion of marsh vegetation into bare open water pools that are relatively far (> 75 m) from tidal channels. As vegetation die-off continues, pools expand, and new pools emerge at shorter and shorter distances from channels. Consequently larger pools are found at larger distances from the channels. Our results suggest that the size of the pools and possibly the connection of pools with the tidal channel system have important bio-geomorphic implications and aggravate marsh deterioration. Moreover, we found that the temporal development of vegetation die-off in moderately degraded marshes is similar as the spatial die-off development along a present-day gradient, which indicates that the contemporary die-off gradient might be considered a chronosequence that offers a unique opportunity to study vegetation die-off processes.

Remote Sensing of Wildland Fire-Induced Risk Assessment at the Community Level.

PubMed

Ahmed, M Razu; Rahaman, Khan Rubayet; Hassan, Quazi K

2018-05-15

Wildland fires are some of the critical natural hazards that pose a significant threat to the communities located in the vicinity of forested/vegetated areas. In this paper, our overall objective was to study the structural damages due to the 2016 Horse River Fire (HRF) that happened in Fort McMurray (Alberta, Canada) by employing primarily very high spatial resolution optical satellite data, i.e., WorldView-2. Thus, our activities included the: (i) estimation of the structural damages; and (ii) delineation of the wildland-urban interface (WUI) and its associated buffers at certain intervals, and their utilization in assessing potential risks. Our proposed method of remote sensing-based estimates of the number of structural damages was compared with the ground-based information available from the Planning and Development Recovery Committee Task Force of Regional Municipality of Wood Buffalo (RMWB); and found a strong linear relationship (i.e., r² value of 0.97 with a slope of 0.97). Upon delineating the WUI and its associated buffer zones at 10 m, 30 m, 50 m, 70 m and 100 m distances; we found existence of vegetation within the 30 m buffers from the WUI for all of the damaged structures. In addition, we noticed that the relevant authorities had removed vegetation in some areas between 30 m and 70 m buffers from the WUI, which was proven to be effective in order to protect the structures in the adjacent communities. Furthermore, we mapped the wildland fire-induced vulnerable areas upon considering the WUI and its associated buffers. Our analysis revealed that approximately 30% of the areas within the buffer zones of 10 m and 30 m were vulnerable due to the presence of vegetation; in which, approximately 7% were burned during the 2016 HRF event that led the structural damages. Consequently, we suggest to remove the existing vegetation within these critical zones and also monitor the region at a regular interval in order to reduce the wildland fire-induced risk.

Does the spatial arrangement of vegetation and anthropogenic land cover features matter? Case studies of urban warming and cooling in Phoenix and Las Vegas

NASA Astrophysics Data System (ADS)

Myint, S. W.; Zheng, B.; Fan, C.; Kaplan, S.; Brazel, A.; Middel, A.; Smith, M.

2014-12-01

While the relationship between fractional cover of anthropogenic and vegetation features and the urban heat island has been well studied, the effect of spatial arrangements (e.g., clustered, dispersed) of these features on urban warming or cooling are not well understood. The goal of this study is to examine if and how spatial configuration of land cover features influence land surface temperatures (LST) in urban areas. This study focuses on Phoenix, AZ and Las Vegas, NV that have undergone dramatic urban expansion. The data used to classify detailed urban land cover types include Geoeye-1 (Las Vegas) and QuickBird (Phoenix). The Geoeye-1 image (3 m resolution) was acquired on October 12, 2011 and the QuickBird image (2.4 m resolution) was taken on May 29, 2007. Classification was performed using object based image analysis (OBIA). We employed a spatial autocorrelation approach (i.e., Moran's I) that measures the spatial dependence of a point to its neighboring points and describes how clustered or dispersed points are arranged in space. We used Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data acquired over Phoenix (daytime on June 10, 2011 and nighttime on October 17, 2011) and Las Vegas (daytime on July 6, 2005 and nighttime on August 27, 2005) to examine daytime and nighttime LST with regards to the spatial arrangement of anthropogenic and vegetation features. We spatially correlate Moran's I values of each land cover per surface temperature, and develop regression models. The spatial configuration of grass and trees shows strong negative correlations with LST, implying that clustered vegetation lowers surface temperatures more effectively. In contrast, a clustered spatial arrangement of anthropogenic land-cover features, especially impervious surfaces, significantly elevates surface temperatures. Results from this study suggest that the spatial configuration of anthropogenic and vegetation features influence urban warming and cooling.

Hydroclimatic Controls on the Means and Variability of Vegetation Phenology and Carbon Uptake

NASA Technical Reports Server (NTRS)

Koster, Randal Dean; Walker, Gregory K.; Collatz, George J.; Thornton, Peter E.

2013-01-01

Long-term, global offline (land-only) simulations with a dynamic vegetation phenology model are used to examine the control of hydroclimate over vegetation-related quantities. First, with a control simulation, the model is shown to capture successfully (though with some bias) key observed relationships between hydroclimate and the spatial and temporal variations of phenological expression. In subsequent simulations, the model shows that: (i) the global spatial variation of seasonal phenological maxima is controlled mostly by hydroclimate, irrespective of distributions in vegetation type, (ii) the occurrence of high interannual moisture-related phenological variability in grassland areas is determined by hydroclimate rather than by the specific properties of grassland, and (iii) hydroclimatic means and variability have a corresponding impact on the spatial and temporal distributions of gross primary productivity (GPP).

Time series evaluation of landscape dynamics using annual Landsat imagery and spatial statistical modeling: Evidence from the Phoenix metropolitan region

NASA Astrophysics Data System (ADS)

Fan, Chao; Myint, Soe W.; Rey, Sergio J.; Li, Wenwen

2017-06-01

Urbanization is a natural and social process involving simultaneous changes to the Earth's land systems, energy flow, demographics, and the economy. Understanding the spatiotemporal pattern of urbanization is increasingly important for policy formulation, decision making, and natural resource management. A combination of satellite remote sensing and patch-based models has been widely adopted to characterize landscape changes at various spatial and temporal scales. Nevertheless, the validity of this type of framework in identifying long-term changes, especially subtle or gradual land modifications is seriously challenged. In this paper, we integrate annual image time series, continuous spatial indices, and non-parametric trend analysis into a spatiotemporal study of landscape dynamics over the Phoenix metropolitan area from 1991 to 2010. We harness local indicators of spatial dependence and modified Mann-Kendall test to describe the monotonic trends in the quantity and spatial arrangement of two important land use land cover types: vegetation and built-up areas. Results suggest that declines in vegetation and increases in built-up areas are the two prevalent types of changes across the region. Vegetation increases mostly occur at the outskirts where new residential areas are developed from natural desert. A sizable proportion of vegetation declines and built-up increases are seen in the central and southeast part. Extensive land conversion from agricultural fields into urban land use is one important driver of vegetation declines. The xeriscaping practice also contributes to part of vegetation loss and an increasingly heterogeneous landscape. The quantitative framework proposed in this study provides a pathway to effective landscape mapping and change monitoring from a spatial statistical perspective.

Effects of decreasing resolution on spectral and spatial information content in an agricultural area. [Pottawatmie study site, Iowa and Nebraska

NASA Technical Reports Server (NTRS)

1983-01-01

The effects of decreasing spatial resolution from 6 1/4 miles square to 50 miles square are described. The effects of increases in cell size is studied on; the mean and variance of spectral data; spatial trends; and vegetative index numbers. Information content changes on cadastral, vegetal, soil, water and physiographic information are summarized.

Spatial Genetic Structure and Clonal Diversity in an Alpine Population of Salix herbacea (Salicaceae)

PubMed Central

Reisch, Christoph; Schurm, Sophia; Poschlod, Peter

2007-01-01

Background and Aims Many alpine plant species combine clonal and sexual reproduction to minimize the risks of flowering and seed production in high mountain regions. The spatial genetic structure and diversity of these alpine species is strongly affected by different clonal strategies (phalanx or guerrilla) and the proportion of generative and vegetative reproduction. Methods The clonal structure of the alpine plant species Salix herbacea was investigated in a 3 × 3 m plot of an alpine meadow using microsatellite (simple sequence repeat; SSR) analysis. The data obtained were compared with the results of a random amplified polymorphic DNA (RAPD) analysis. Key Results SSR analysis, based on three loci and 16 alleles, revealed 24 different genotypes and a proportion of distinguishable genotypes of 0·18. Six SSR clones were found consisting of at least five samples, 17 clones consisting of more than two samples and seven single genotypes. Mean clone size comprising at least five samples was 0·96 m2, and spatial autocorrelation analysis showed strong similarity of samples up to 130 cm. RAPD analysis revealed a higher level of clonal diversity but a comparable number of larger clones and a similar spatial structure. Conclusions The spatial genetic structure as well as the occurrence of single genotypes revealed in this study suggests both clonal and sexual propagation and repeated seedling recruitment in established populations of S. herbacea and is thus suggestive of a relaxed phalanx strategy. PMID:17242040

Spatial effects of aboveground biomass on soil ecological parameters and trace gas fluxes in a savannah ecosystem of Mount Kilimanjaro

NASA Astrophysics Data System (ADS)

Becker, Joscha; Gütlein, Adrian; Sierra Cornejo, Natalia; Kiese, Ralf; Hertel, Dietrich; Kuzyakov, Yakov

2015-04-01

The savannah biome is a hotspot for biodiversity and wildlife conservation in Africa and recently got in the focus of research on carbon sequestration. Savannah ecosystems are under strong pressure from climate and land-use change, especially around populous areas like the Mt. Kilimanjaro region. Savannah vegetation in this area consists of grassland with isolated trees and is therefore characterized by high spatial variation of canopy cover, aboveground biomass and root structure. Canopy structure is known to affect microclimate, throughfall and evapotranspiration and thereby controls soil moisture conditions. Consequently, the canopy structure is a major regulator for soil ecological parameters and soil-atmospheric trace gas exchange (CO2, N2O, CH4) in water limited environments. The spatial distribution of these parameters and the connection between above and belowground processes are important to understand and predict ecosystem changes and estimate its vulnerability. Our objective was to determine trends and changes of soil parameters and relate their spatial variability to the vegetation structure. We chose three trees from each of the two most dominant species (Acacia nilotica and Balanites aegyptiaca) in our research area. For each tree, we selected transects with nine sampling points of the same relative distances to the stem. Distances were calculated in relation to the crown radius. At these each sampling point a soil core was taken and separated in 0-10 cm and 10-30 cm depth. We measured soil carbon (C) and nitrogen (N) storage, microbial biomass carbon C and N, soil respiration as well as root biomass and -density, soil temperature and soil water content. Each tree was characterized by crown spread, leaf area index and basal area. Preliminary results show that C and N stocks decreased about 50% with depth independently of distance to the tree. Soil water content under the tree crown increased with depth while it decreased under grass cover. Microbial Biomass C and N in the upper 10 cm decreased with distance (C: r²=0.22, p<0.001; N: r²=0.3, p<0.001) as well as total soil respiration. This decrease was affected by tree size but independent from tree species. We conclude that savannah ecosystems exhibit a large spatial variability of soil parameters within the upper horizons which is strongly depend on the structure of aboveground biomass.

Effects of spatial resolution and landscape structure on land cover characterization

NASA Astrophysics Data System (ADS)

Yang, Wenli

This dissertation addressed problems in scaling, problems that are among the main challenges in remote sensing. The principal objective of the research was to investigate the effects of changing spatial scale on the representation of land cover. A second objective was to determine the relationship between such effects, characteristics of landscape structure and scaling procedures. Four research issues related to spatial scaling were examined. They included: (1) the upscaling of Normalized Difference Vegetation Index (NDVI); (2) the effects of spatial scale on indices of landscape structure; (3) the representation of land cover databases at different spatial scales; and (4) the relationships between landscape indices and land cover area estimations. The overall bias resulting from non-linearity of NDVI in relation to spatial resolution is generally insignificant as compared to other factors such as influences of aerosols and water vapor. The bias is, however, related to land surface characteristics. Significant errors may be introduced in heterogeneous areas where different land cover types exhibit strong spectral contrast. Spatially upscaled SPOT and TM NDVIs have information content comparable with the AVHRR-derived NDVI. Indices of landscape structure and spatial resolution are generally related, but the exact forms of the relationships are subject to changes in other factors including the basic patch unit constituting a landscape and the proportional area of foreground land cover under consideration. The extent of agreement between spatially aggregated coarse resolution land cover datasets and full resolution datasets changes with the properties of the original datasets, including the pixel size and class definition. There are close relationships between landscape structure and class areas estimated from spatially aggregated land cover databases. The relationships, however, do not permit extension from one area to another. Inversion calibration across different geographic/ecological areas is, therefore, not feasible. Different rules govern the land cover area changes across resolutions when different upscaling methods are used. Special attention should be given to comparison between land cover maps derived using different methods.

The effects of biotic and abiotic factors on the spatial heterogeneity of alpine grassland vegetation at a small scale on the Qinghai-Tibet Plateau (QTP), China.

PubMed

Wen, Lu; Dong, Shi Kui; Li, Yuan Yuan; Sherman, Ruth; Shi, Jian Jun; Liu, De Mei; Wang, Yan Long; Ma, Yu Shou; Zhu, Lei

2013-10-01

Understanding the complex effects of biotic and abiotic factors on the composition of vegetation is very important for developing and implementing strategies for promoting sustainable grassland development. The vegetation-disturbance-environment relationship was examined in degraded alpine grasslands in the headwater areas of three rivers on the Qinghai-Tibet Plateau in this study. The investigated hypotheses were that (1) the heterogeneity of the vegetation of the alpine grassland is due to a combination of biotic and abiotic factors and that (2) at a small scale, biotic factors are more important for the distribution of alpine vegetation. On this basis, four transects were set along altitudinal gradients from 3,770 to 3,890 m on a sunny slope, and four parallel transects were set along altitudinal gradients on a shady slope in alpine grasslands in Guoluo Prefecture of Qinghai Province, China. It was found that biological disturbances were the major forces driving the spatial heterogeneity of the alpine grassland vegetation and abiotic factors were of secondary importance. Heavy grazing and intensive rat activity resulted in increases in unpalatable and poisonous weeds and decreased fine forages in the form of sedges, forbs, and grasses in the vegetation composition. Habitat degradation associated with biological disturbances significantly affected the spatial variation of the alpine grassland vegetation, i.e., more pioneer plants of poisonous or unpalatable weed species, such as Ligularia virgaurea and Euphorbia fischeriana, were found in bare patches. Environmental/abiotic factors were less important than biological disturbances in affecting the spatial distribution of the alpine grassland vegetation at a small scale. It was concluded that rat control and light grazing should be applied first in implementing restoration strategies. The primary vegetation in lightly grazed and less rat-damaged sites should be regarded as a reference for devising vegetation restoration measures in alpine pastoral regions.

Ecosystem Impacts of Woody Encroachment In Texas: A Spatial Analysis Using AVIRIS

NASA Technical Reports Server (NTRS)

Martin, Roberta E.; Asner, Gregory P.

2004-01-01

Woody encroachment, the increase of woody plant density relative to herbaceous vegetation, has been documented in drylands of Texas as well as worldwide (Archer 1994, Harrington and Harman 1995, Moleele et al. 2002). Over-grazing, fire suppression and climate change are implicated in the shift from open grasslands to ecosystems now populated by trees and shrubs (Scholes and Archer 1997, Archer et al. 2001), such as Prosopis glandulosa var. glandulosa (honey mesquite) in north Texas (Teague et al. 1997, Ansley et al. 2001, Asner et al. 2003a). Several studies have examined changes in ecosystem properties accompanying woody vegetation encroachment in the Southwest U.S., with research focused on increases in plant and soil carbon (C) and nitrogen (N) stores (Hoffman and Jackson 2000, Asner et al. 2003a), isotopic shifts in these pools (Boutton 1999, Archer et al. 2001), and increases in N cycling rates (Rundel et al. 1982, Hibbard et al. 2001). However, little is known regarding the impact of woody encroachment on N trace gas emissions from dryland regions such as Texas. NOx is produced in the soil during the processes of nitrification and denitrification (Firestone and Davidson 1989). The total N efflux from soils is most directly influenced by the internal cycling of N, which at a regionalscale, is controlled by the inputs and availability of N from vegetation via litterfall and subsequent decomposition (Robertson et al. 1989). Although plot-scale studies are critical to understanding controls over N oxide emissions, regionalization of the measurements is impeded by spatial variation in the factors contributing most to N cycling processes: soil properties (affecting soil moisture regimes and N stocks) and vegetation cover (affecting litter inputs and N uptake). While broad patterns in ecosystem structure and vegetation composition co-vary with general patterns of trace gas emissions (Matson 1997), there is no easily measured index of N availability that can be applied for regional-scale studies of N oxide fluxes. Remote sensing is arguably the only approach available to develop a spatially-explicit understanding of ecosystem processes. More specifically, remotely detectable spatial patterns in the distal controls over soil N properties, such as vegetation cover, land use and soil type (Robertson et al. 1989), should be exploited for regional studies of N oxide emissions. The woody encroachment phenomenon provides an opportunity to test the strength of the relationship between N oxide emissions and those factors controlling the fluxes that can be remotely measured. If such linkages can be firmly established, and if the spatial pattern of distal controls is relevant, then the combination of field measurements and remote sensing offers to improve regional-scale N oxide estimates. The paper presents the utility of linking field based sampling of soil NOx emissions with very high resolution remote sensing estimates of woody vegetation cover from the NASA AVIRIS, Airborne Visible-Infrared Imaging Spectrometer (Green et al. 1998, Asner and Green 2001) and automated spectral mixture analysis (Asner and Lobell 2000, Asner and Heidebrecht 2002) that provide a means to spatially extrapolate soil NOx emissions to the regional scale.

Influence of coastal vegetation on the 2004 tsunami wave impact in west Aceh

PubMed Central

Laso Bayas, Juan Carlos; Marohn, Carsten; Dercon, Gerd; Dewi, Sonya; Piepho, Hans Peter; Joshi, Laxman; van Noordwijk, Meine; Cadisch, Georg

2011-01-01

In a tsunami event human casualties and infrastructure damage are determined predominantly by seaquake intensity and offshore properties. On land, wave energy is attenuated by gravitation (elevation) and friction (land cover). Tree belts have been promoted as “bioshields” against wave impact. However, given the lack of quantitative evidence of their performance in such extreme events, tree belts have been criticized for creating a false sense of security. This study used 180 transects perpendicular to over 100 km on the west coast of Aceh, Indonesia to analyze the influence of coastal vegetation, particularly cultivated trees, on the impact of the 2004 tsunami. Satellite imagery; land cover maps; land use characteristics; stem diameter, height, and planting density; and a literature review were used to develop a land cover roughness coefficient accounting for the resistance offered by different land uses to the wave advance. Applying a spatial generalized linear mixed model, we found that while distance to coast was the dominant determinant of impact (casualties and infrastructure damage), the existing coastal vegetation in front of settlements also significantly reduced casualties by an average of 5%. In contrast, dense vegetation behind villages endangered human lives and increased structural damage. Debris carried by the backwash may have contributed to these dissimilar effects of land cover. For sustainable and effective coastal risk management, location of settlements is essential, while the protective potential of coastal vegetation, as determined by its spatial arrangement, should be regarded as an important livelihood provider rather than just as a bioshield. PMID:22065751

Correlation between the habitats productivity and species richness (amphibians and reptiles) in Portugal through remote sensed data

NASA Astrophysics Data System (ADS)

Teodoro, A. C.; Sillero, N.; Alves, S.; Duarte, L.

2013-10-01

Several biogeographic theories propose that the species richness depends on the structure and ecosystems diversity. The habitat productivity, a surrogate for these variables, can be evaluated through satellite imagery, namely using vegetation indexes (e.g. NDVI). We analyzed the correlation between species richness (from the Portuguese Atlas of Amphibians and Reptiles) and NDVI (from Landsat, MODIS, and Vegetation images). The species richness database contains more than 80000 records, collected from bibliographic sources (at 1 or 10 km of spatial resolution) and fieldwork sampling stations (recorded with GPS devices). Several study areas were chosen for Landsat images (three subsets), and all Portugal for MODIS and Vegetation images. The Landsat subareas had different climatic and habitat characteristics, located in the north, center and south of Portugal. Different species richness datasets were used depending on the image spatial resolution: data with metric resolution were used for Landsat, and with 1 km resolution, for MODIS and Vegetation images. The NDVI indexes and all the images were calculated/processed in an open source software (Quantum GIS). Several plug-ins were applied in order to automatize several procedures. We did not find any correlation between the species richness of amphibians and reptiles (not even after separating both groups by species of Atlantic and Mediterranean affinity) and the NDVI calculated with Landsat, MODIS and Vegetation images. Our results may fail to find a relationship because as the species richness is not correlated with only one variable (NDVI), and thus other environmental variables must be considered.

Multivariate ordination identifies vegetation types associated with spider conservation in brassica crops

PubMed Central

Saqib, Hafiz Sohaib Ahmed; You, Minsheng

2017-01-01

Conservation biological control emphasizes natural and other non-crop vegetation as a source of natural enemies to focal crops. There is an unmet need for better methods to identify the types of vegetation that are optimal to support specific natural enemies that may colonize the crops. Here we explore the commonality of the spider assemblage—considering abundance and diversity (H)—in brassica crops with that of adjacent non-crop and non-brassica crop vegetation. We employ spatial-based multivariate ordination approaches, hierarchical clustering and spatial eigenvector analysis. The small-scale mixed cropping and high disturbance frequency of southern Chinese vegetation farming offered a setting to test the role of alternate vegetation for spider conservation. Our findings indicate that spider families differ markedly in occurrence with respect to vegetation type. Grassy field margins, non-crop vegetation, taro and sweetpotato harbour spider morphospecies and functional groups that are also present in brassica crops. In contrast, pumpkin and litchi contain spiders not found in brassicas, and so may have little benefit for conservation biological control services for brassicas. Our findings also illustrate the utility of advanced statistical approaches for identifying spatial relationships between natural enemies and the land uses most likely to offer alternative habitats for conservation biological control efforts that generates testable hypotheses for future studies. PMID:29085741

Disturbance Impacts on Thermal Hot Spots and Hot Moments at the Peatland-Atmosphere Interface

NASA Astrophysics Data System (ADS)

Leonard, R. M.; Kettridge, N.; Devito, K. J.; Petrone, R. M.; Mendoza, C. A.; Waddington, J. M.; Krause, S.

2018-01-01

Soil-surface temperature acts as a master variable driving nonlinear terrestrial ecohydrological, biogeochemical, and micrometeorological processes, inducing short-lived or spatially isolated extremes across heterogeneous landscape surfaces. However, subcanopy soil-surface temperatures have been, to date, characterized through isolated, spatially discrete measurements. Using spatially complex forested northern peatlands as an exemplar ecosystem, we explore the high-resolution spatiotemporal thermal behavior of this critical interface and its response to disturbances by using Fiber-Optic Distributed Temperature Sensing. Soil-surface thermal patterning was identified from 1.9 million temperature measurements under undisturbed, trees removed and vascular subcanopy removed conditions. Removing layers of the structurally diverse vegetation canopy not only increased mean temperatures but it shifted the spatial and temporal distribution, range, and longevity of thermal hot spots and hot moments. We argue that linking hot spots and/or hot moments with spatially variable ecosystem processes and feedbacks is key for predicting ecosystem function and resilience.

Combining high fidelity simulations and real data for improved small-footprint waveform lidar assessment of vegetation structure (Invited)

NASA Astrophysics Data System (ADS)

van Aardt, J. A.; Wu, J.; Asner, G. P.

2010-12-01

Our understanding of vegetation complexity and biodiversity, from a remote sensing perspective, has evolved from 2D species diversity to also include 3D vegetation structural diversity. Attempts at using image-based approaches for structural assessment have met with reasonable success, but 3D remote sensing technologies, such as radar and light detection and ranging (lidar), are arguably more adept at sensing vegetation structure. While radar-derived structure metrics tend to break down at high biomass levels, novel waveform lidar systems present us with new opportunities for detailed and scalable structural characterization of vegetation. These sensors digitize the entire backscattered energy profile at high spatial and vertical resolutions and often at off-nadir angles. Research teams at Rochester Institute of Technology (RIT) and Carnegie Institution for Science have been using airborne data from the Carnegie Airborne Observatory (CAO) to assess vegetation structure and variation in savanna ecosystems in and around the Kruger National Park, South Africa. It quickly became evident that (i) pre-processing of small-footprint waveform data is a critical step prior to testing scientific hypotheses, (ii) a number of assumptions of how vegetation structure is expressed in these 3D signals need to be evaluated, and very importantly (iii) we need to re-evaluate our linkages between coarse in-field measurements, e.g., volume, biomass, leaf area index (LAI), and metrics derived from waveform lidar. Research has progressed to the stage where we have evaluated various pre-processing steps, e.g., convolution via the Wiener filter, Richardson-Lucy, and non-negative least squares algorithms, and the coupling of waveform voxels to tree structure in a simulation environment. This was done in the MODTRAN-based Digital Imaging and Remote Sensing Image Generation (DIRSIG) simulation environment, developed at RIT. We generated "truth" cross-section datasets of detailed virtual trees in this environment and evaluated inversion approaches to tree structure estimation. Various outgoing pulse widths, tree structures, and a noise component were included as part of the simulation effort. Results, for example, have shown that the Richardson-Lucy algorithm outperforms other approaches in terms of retrieval of known structural information, that our assumption regarding the position of the ground surface needs re-evaluation, and has shed light on herbaceous biomass and waveform interactions and the impact of outgoing pulse width on assessments. These efforts have gone a long way in providing a solid foundation for analysis and interpretation of actual waveform data from the savanna study area. We expect that newfound knowledge with respect to waveform-target interactions from these simulations will also aid efforts to reconstruct 3D trees from real data and better describe associated structural diversity. Results will be presented at the conference.

Biomass Increases Go under Cover: Woody Vegetation Dynamics in South African Rangelands

PubMed Central

Mograbi, Penelope J.; Knapp, David E.; Martin, Roberta E.; Main, Russell

2015-01-01

Woody biomass dynamics are an expression of ecosystem function, yet biomass estimates do not provide information on the spatial distribution of woody vegetation within the vertical vegetation subcanopy. We demonstrate the ability of airborne light detection and ranging (LiDAR) to measure aboveground biomass and subcanopy structure, as an explanatory tool to unravel vegetation dynamics in structurally heterogeneous landscapes. We sampled three communal rangelands in Bushbuckridge, South Africa, utilised by rural communities for fuelwood harvesting. Woody biomass estimates ranged between 9 Mg ha-1 on gabbro geology sites to 27 Mg ha-1 on granitic geology sites. Despite predictions of woodland depletion due to unsustainable fuelwood extraction in previous studies, biomass in all the communal rangelands increased between 2008 and 2012. Annual biomass productivity estimates (10–14% p.a.) were higher than previous estimates of 4% and likely a significant contributor to the previous underestimations of modelled biomass supply. We show that biomass increases are attributable to growth of vegetation <5 m in height, and that, in the high wood extraction rangeland, 79% of the changes in the vertical vegetation subcanopy are gains in the 1-3m height class. The higher the wood extraction pressure on the rangelands, the greater the biomass increases in the low height classes within the subcanopy, likely a strong resprouting response to intensive harvesting. Yet, fuelwood shortages are still occurring, as evidenced by the losses in the tall tree height class in the high extraction rangeland. Loss of large trees and gain in subcanopy shrubs could result in a structurally simple landscape with reduced functional capacity. This research demonstrates that intensive harvesting can, paradoxically, increase biomass and this has implications for the sustainability of ecosystem service provision. The structural implications of biomass increases in communal rangelands could be misinterpreted as woodland recovery in the absence of three-dimensional, subcanopy information. PMID:25969985

Vegetation function and non-uniqueness of the hydrological response

NASA Astrophysics Data System (ADS)

Ivanov, V. Y.; Fatichi, S.; Kampf, S. K.; Caporali, E.

2012-04-01

Through local moisture uptake vegetation exerts seasonal and longer-term impacts on the watershed hydrological response. However, the role of vegetation may go beyond the conventionally implied and well-understood "sink" function in the basin soil moisture storage equation. We argue that vegetation function imposes a "homogenizing" effect on pre-event soil moisture spatial storage, decreasing the likelihood that a rainfall event will result in a topographically-driven redistribution of soil water and the consequent formation of variable source areas. In combination with vegetation temporal dynamics, this may lead to the non-uniqueness of the hydrological response with respect to the mean basin wetness. This study designs a set of relevant numerical experiments carried out with two physically-based models; one of the models, HYDRUS, resolves variably saturated subsurface flow using a fully three-dimensional formulation, while the other model, tRIBS+VEGGIE, uses a one-dimensional formulation applied in a quasi-three-dimensional framework in combination with the model of vegetation dynamics. We demonstrate that (1) vegetation function modifies spatial heterogeneity in moisture spatial storage by imposing different degrees of subsurface flow connectivity; explore mechanistically (2) how and why a basin with the same mean soil moisture can have distinctly different spatial soil moisture distributions; and demonstrate (2) how these distinct moisture distributions result in a hysteretic runoff response to precipitation. Furthermore, the study argues that near-surface soil moisture is an insufficient indicator of the initial moisture state of a catchment with the implication of its limited effect on hydrological predictability.

Image and in situ data integration to derive sawgrass density for surface flow modelling in the Everglades, Florida, USA

USGS Publications Warehouse

Jones, J.W.

2000-01-01

The US Geological Survey is building models of the Florida Everglades to be used in managing south Florida surface water flows for habitat restoration and maintenance. Because of the low gradients in the Everglades, vegetation structural characteristics are very important and greatly influence surface water flow and distribution. Vegetation density is being evaluated as an index of surface resistance to flow. Digital multispectral videography (DMSV) has been captured over several sites just before field collection of vegetation data. Linear regression has been used to establish a relationship between normalized difference vegetation index (NDVI) values computed from the DMSV and field-collected biomass and density estimates. Spatial analysis applied to the DMSV data indicates that thematic mapper (TM) resolution is at the limit required to capture land surface heterogeneity. The TM data collected close to the time of the DMSV will be used to derive a regional sawgrass density map.

Image and in situ data integration to derive sawgrass density for surface flow modelling in the Everglades, Florida, USA

USGS Publications Warehouse

Jones, J.W.

2001-01-01

The US Geological Survey is building models of the Florida Everglades to be used in managing south Florida surface water flows for habitat restoration and maintenance. Because of the low gradients in the Everglades, vegetation structural characteristics are very important and greatly influence surface water flow and distribution. Vegetation density is being evaluated as an index of surface resistance to flow. Digital multispectral videography (DMSV) has been captured over several sites just before field collection of vegetation data. Linear regression has been used to establish a relationship between normalized difference vegetation index (NDVI) values computed from the DMSV and field-collected biomass and density estimates. Spatial analysis applied to the DMSV data indicates that thematic mapper (TM) resolution is at the limit required to capture land surface heterogeneity. The TM data collected close to the time of the DMSV will be used to derive a regional sawgrass density map.

Phenological dynamics of arctic tundra vegetation and its implications on satellite imagery interpretation

NASA Astrophysics Data System (ADS)

Juutinen, Sari; Aurela, Mika; Mikola, Juha; Räsänen, Aleksi; Virtanen, Tarmo

2016-04-01

Remote sensing is a key methodology when monitoring the responses of arctic ecosystems to climatic warming. The short growing season and rapid vegetation development, however, set demands to the timing of image acquisition in the arctic. We used multispectral very high spatial resolution satellite images to study the effect of vegetation phenology on the spectral reflectance and image interpretation in the low arctic tundra in coastal Siberia (Tiksi, 71°35'39"N, 128°53'17"E). The study site mainly consists of peatlands, tussock, dwarf shrub, and grass tundra, and stony areas with some lichen and shrub patches. We tested the hypotheses that (1) plant phenology is responsive to the interannual weather variation and (2) the phenological state of vegetation has an impact on satellite image interpretation and the ability to distinguish between the plant communities. We used an empirical transfer function with temperature sums as drivers to reconstruct daily leaf area index (LAI) for the different plant communities for years 2005, and 2010-2014 based on measured LAI development in summer 2014. Satellite images, taken during growing seasons, were acquired for two years having late and early spring, and short and long growing season, respectively. LAI dynamics showed considerable interannual variation due to weather variation, and particularly the relative contribution of graminoid dominated communities was sensitive to these phenology shifts. We have also analyzed the differences in the reflectance values between the two satellite images taking account the LAI dynamics. These results will increase our understanding of the pitfalls that may arise from the timing of image acquisition when interpreting the vegetation structure in a heterogeneous tundra landscape. Very high spatial resolution multispectral images are available at reasonable cost, but not in high temporal resolution, which may lead to compromises when matching ground truth and the imagery. On the other hand, to identify existing plant communities, high resolution images are needed due fragmented nature of tundra vegetation communities. Temporal differences in the phenology among different plant functional types may also obscure the image interpretations when using spatially low resolution images in heterogeneous landscapes. Phenological features of plant communities should be acknowledged, when plant functional or community type based classifications are used in models to estimate global greenhouse gas emissions and when monitoring changes in vegetation are monitored, for example to indicate permafrost thawing or changes in growing season lengths.

Effects Of Spatial Variability In Marshes On Coastal Erosion Under Storm Conditions

NASA Astrophysics Data System (ADS)

Lunghino, B.; Suckale, J.; Fringer, O. B.; Maldonado, S.; Ferreira, C.; Marras, S.; Mandel, T.

2016-12-01

To quantify the contribution of marshes in protecting coastlines, engineers and planners need to evaluate how variability in marsh characteristics and storm conditions affect erosion in the inundation zone. Previous studies show that spatial patterns in marshes significantly affect flow and sediment transport under normal tidal conditions [1, 2]. This study investigates the effect of spatial variability on floodplain sediment transport under a range of extreme hydrodynamic conditions that occur during storm events. We model the hydrodynamics of storm surge conditions on an idealized coastal floodplain by solving the 2D shallow water equations. We approximate the effect of vegetation on hydrodynamics as a constant drag coefficient. The model calculates suspended sediment transport with the advection-diffusion equation and updates morphology with erosional and depositional fluxes. We conduct numerical experiments in which we vary both the scale of the storm event and the spatial patterns of vegetation and evaluate the impact on erosion and deposition on the floodplain. We find that the alongshore extent of the vegetation is the primary control on the net volume of sediment eroded. Scour occurs in narrow channels between vegetated areas, but this does not significantly alter the net volume of sediment transported. Deposition occurs in vegetated areas under the full range of flow velocities we test. These results suggest that resolving all variability in vegetation is not necessary to quantify net sediment transport volumes at the floodplain scale. Increasing the scale of the storm event does not alter the role of spatial variability. References [1] Meire, D. W., Kondziolka, J. M., and Nepf, H. M. Interaction between neighboring vegetation patches: Impact on flow and deposition. Water Resources Research 50, 5 (2014), 3809-3825. [2] Temmerman, S., Bouma, T., Govers, G., Wang, Z., De Vries, M., and Her- man, P. Impact of vegetation on flow routing and sedimentation patterns: Three-dimensional modeling for a tidal marsh. Journal of Geophysical Research: Earth Surface 110, F4 (2005).

Do ecohydrology and community dynamics feed back to banded-ecosystem structure and productivity?

NASA Astrophysics Data System (ADS)

Callegaro, Chiara; Ursino, Nadia

2016-04-01

Mixed communities including grass, shrubs and trees are often reported to populate self-organized vegetation patterns. Patterns of survey data suggest that species diversity and complementarity strengthen the dynamics of banded environments. Resource scarcity and local facilitation trigger self organization, whereas coexistence of multiple species in vegetated self-organizing patches, implying competition for water and nutrients and favorable reproduction sites, is made possible by differing adaptation strategies. Mixed community spatial self-organization has so far received relatively little attention, compared with local net facilitation of isolated species. We assumed that soil moisture availability is a proxy for the environmental niche of plant species according to Ursino and Callegaro (2016). Our modelling effort was focused on niche differentiation of coexisting species within a tiger bush type ecosystem. By minimal numerical modelling and stability analysis we try to answer a few open scientific questions: Is there an adaptation strategy that increases biodiversity and ecosystem functioning? Does specific adaptation to environmental niches influence the structure of self-organizing vegetation pattern? What specific niche distribution along the environmental gradient gives the highest global productivity?

Stability of spatial distributions of stink bugs, boll injury, and NDVI in cotton

USDA-ARS?s Scientific Manuscript database

A two-year study was conducted to determine the degree of aggregation of thrips, stink bugs, and aphids in cotton, Gossypium hirsutum L., and their spatial association with soil apparent electrical conductivity (ECa), a multispectral vegetation index (Normalized Difference Vegetation Index [NDVI]), ...

Formation of banded vegetation patterns resulted from interactions between sediment deposition and vegetation growth.

PubMed

Huang, Tousheng; Zhang, Huayong; Dai, Liming; Cong, Xuebing; Ma, Shengnan

2018-03-01

This research investigates the formation of banded vegetation patterns on hillslopes affected by interactions between sediment deposition and vegetation growth. The following two perspectives in the formation of these patterns are taken into consideration: (a) increased sediment deposition from plant interception, and (b) reduced plant biomass caused by sediment accumulation. A spatial model is proposed to describe how the interactions between sediment deposition and vegetation growth promote self-organization of banded vegetation patterns. Based on theoretical and numerical analyses of the proposed spatial model, vegetation bands can result from a Turing instability mechanism. The banded vegetation patterns obtained in this research resemble patterns reported in the literature. Moreover, measured by sediment dynamics, the variation of hillslope landform can be described. The model predicts how treads on hillslopes evolve with the banded patterns. Thus, we provide a quantitative interpretation for coevolution of vegetation patterns and landforms under effects of sediment redistribution. Copyright © 2018. Published by Elsevier Masson SAS.

Remotely Sensed Northern Vegetation Response to Changing Climate: Growing Season and Productivity Perspective

NASA Technical Reports Server (NTRS)

Ganguly, S.; Park, Taejin; Choi, Sungho; Bi, Jian; Knyazikhin, Yuri; Myneni, Ranga

2016-01-01

Vegetation growing season and maximum photosynthetic state determine spatiotemporal variability of seasonal total gross primary productivity of vegetation. Recent warming induced impacts accelerate shifts on growing season and physiological status over Northern vegetated land. Thus, understanding and quantifying these changes are very important. Here, we first investigate how vegetation growing season and maximum photosynthesis state are evolved and how such components contribute on inter-annual variation of seasonal total gross primary productivity. Furthermore, seasonally different response of northern vegetation to changing temperature and water availability is also investigated. We utilized both long-term remotely sensed data to extract larger scale growing season metrics (growing season start, end and duration) and productivity (i.e., growing season summed vegetation index, GSSVI) for answering these questions. We find that regionally diverged growing season shift and maximum photosynthetic state contribute differently characterized productivity inter-annual variability and trend. Also seasonally different response of vegetation gives different view of spatially varying interaction between vegetation and climate. These results highlight spatially and temporally varying vegetation dynamics and are reflective of biome-specific responses of northern vegetation to changing climate.

Evaluating Hyperspectral Imaging of Wetland Vegetation as a Tool for Detecting Estuarine Nutrient Enrichment

DTIC Science & Technology

2008-05-01

the vegetation’s uptake of water column nutrients produces a spectral response; and 3) the spectral and spatial resolutions ...analysis. This allowed us to evaluate these assumptions at the landscape level, by using the high spectral and spatial resolution of the hyperspectral... spatial resolution (2.5 m pixels) HyMap hyperspectral imagery of the entire wetland. After using a hand-held spectrometer to characterize

Modeling broad-scale patterns of avian species richness across the Midwestern United States with measures of satellite image texture

Treesearch

Patrick D. Culbert; Volker C. Radeloff; Veronique St-Louis; Curtis H. Flather; Chadwick D. Rittenhouse; Thomas P. Albright; Anna M. Pidgeon

2012-01-01

Avian biodiversity is threatened, and in order to prioritize limited conservation resources and conduct effective conservation planning a better understanding of avian species richness patterns is needed. The use of image texture measures, as a proxy for the spatial structure of land cover and vegetation, has proven useful in explaining patterns of avian abundance and...

Soil heterogeneity in Mojave Desert shrublands: Biotic and abiotic processes

NASA Astrophysics Data System (ADS)

Caldwell, Todd G.; Young, Michael H.; McDonald, Eric V.; Zhu, Jianting

2012-09-01

Geological and ecological processes play critical roles in the evolution of desert piedmonts. Feedback between fast cyclic biotic and slow cumulative pedogenic processes on arid alluvial fan systems results in a heterogeneous landscape of interspace and canopy microsites. Defining the spatial extent between these processes will allow a better connection to ecosystem service and climate change. We use a soil chronosequence in the Mojave Desert and high spatial resolution infiltrometer measurements along transects radiating from canopies of perennial shrubs to assess the extent of biotic and abiotic processes and the heterogeneity of soil properties in arid shrublands. Results showed higher saturated conductivity under vegetation regardless of surface age, but it was more conspicuous on older, developed soils. At proximal locations to the shrub, bulk density, soil structure grade, silt, and clay content significantly increased radially from the canopy, while sand and organic material decreased. Soil properties at distal locations 2-5 times the canopy radius had no significant spatial correlation. The extent of the biotic influence of the shrub was 1.34 ± 0.32 times the canopy radius. Hydraulic properties were weakly correlated in space, but 75% of the variance could be attributed to sand content, soil structure grade, mean-particle diameter, and soil organic material, none of which are exclusively biotic or abiotic. The fast cyclic biotic processes occurring under vegetation are clearly overprinted on slow cumulative abiotic processes, resulting in the deterministic variability observed at the plant scale.

Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, D.A.; Green, R.O.; Adams, J.B.

1997-12-01

Little research has focused on the use of imaging spectrometry for change detection. In this paper, the authors apply Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data to the monitoring of seasonal changes in atmospheric water vapor, liquid water, and surface cover in the vicinity of the Jasper Ridge, CA, for three dates in 1992. Apparent surface reflectance was retrieved and water vapor and liquid water mapped by using a radiative-transfer-based inversion that accounts for spatially variable atmospheres. Spectral mixture analysis (SMA) was used to model reflectance data as mixtures of green vegetation (GV), nonphotosynthetic vegetation (NPV), soil, and shade. Temporal andmore » spatial patterns in endmember fractions and liquid water were compared to the normalized difference vegetation index (NDVI). The reflectance retrieval algorithm was tested by using a temporally invariant target.« less

Resilience Through Disturbance: Effects of Wildfire on Vegetation and Water Balance in the Sierra Nevadas

NASA Astrophysics Data System (ADS)

Boisrame, G. F. S.; Thompson, S. E.; Stephens, S.; Collins, B.; Tague, N.

2015-12-01

A century of fire suppression in the Western United States has drastically altered the historically fire-adapated ecology in California's Sierra Nevada Mountains. Fire suppression is understood to have increased the forest cover, as well as the stem density, canopy cover and water demand of montane forests, reducing resilience of the forests to drought, and increasing the risk of catastrophic fire by drying the landscape and increasing fuel loads. The potential to reverse these trends by re-introducing fire into the Sierra Nevada is highly promising, but the likely effects on vegetation structure and water balance are poorly quantified. The Illilouette Creek Basin in Yosemite National Park represents a unique experiment in the Sierra Nevada, in which managers have moved from fire suppression to allowing a near-natural fire regime to prevail since 1972. Changes in vegetation structure in the Illilouette since the restoration of natural burning provides a unique opportunity to examine how frequent, mixed severity fires can reshape the Sierra Nevada landscape. We characterize these changes from 1969 to the present using a combination of Landsat products and high-resolution aerial imagery. We describe how the landscape structure has changed in terms of vegetation composition and its spatial organization, and explore the drivers of different post-fire vegetation type transitions (e.g. forest to shrubland vs. forest to meadow). By upscaling field data using vegetation maps and Landsat wetness indices, we explore how these vegetation transitions have impacted the water balance of the Illilouette Creek Basin, potentially increasing its resilience in the face of drought, climate change, and catastrophic fire. In a region that is adapted to frequent disturbance from fire, this work helps us understand how allowing such natural disturbances to take place can increase the sustainability of diverse landscapes in the long term.

Spatial patterns in vegetation fires in the Indian region.

PubMed

Vadrevu, Krishna Prasad; Badarinath, K V S; Anuradha, Eaturu

2008-12-01

In this study, we used fire count datasets derived from Along Track Scanning Radiometer (ATSR) satellite to characterize spatial patterns in fire occurrences across highly diverse geographical, vegetation and topographic gradients in the Indian region. For characterizing the spatial patterns of fire occurrences, observed fire point patterns were tested against the hypothesis of a complete spatial random (CSR) pattern using three different techniques, the quadrat analysis, nearest neighbor analysis and Ripley's K function. Hierarchical nearest neighboring technique was used to depict the 'hotspots' of fire incidents. Of the different states, highest fire counts were recorded in Madhya Pradesh (14.77%) followed by Gujarat (10.86%), Maharastra (9.92%), Mizoram (7.66%), Jharkhand (6.41%), etc. With respect to the vegetation categories, highest number of fires were recorded in agricultural regions (40.26%) followed by tropical moist deciduous vegetation (12.72), dry deciduous vegetation (11.40%), abandoned slash and burn secondary forests (9.04%), tropical montane forests (8.07%) followed by others. Analysis of fire counts based on elevation and slope range suggested that maximum number of fires occurred in low and medium elevation types and in very low to low-slope categories. Results from three different spatial techniques for spatial pattern suggested clustered pattern in fire events compared to CSR. Most importantly, results from Ripley's K statistic suggested that fire events are highly clustered at a lag-distance of 125 miles. Hierarchical nearest neighboring clustering technique identified significant clusters of fire 'hotspots' in different states in northeast and central India. The implications of these results in fire management and mitigation were discussed. Also, this study highlights the potential of spatial point pattern statistics in environmental monitoring and assessment studies with special reference to fire events in the Indian region.

Species Richness Responses to Structural or Compositional Habitat Diversity between and within Grassland Patches: A Multi-Taxon Approach

PubMed Central

Lengyel, Szabolcs; Déri, Eszter; Magura, Tibor

2016-01-01

Habitat diversity (spatial heterogeneity within and between habitat patches in a landscape, HD) is often invoked as a driver of species diversity at small spatial scales. However, the effect of HD on species richness (SR) of multiple taxa is not well understood. We quantified HD and SR in a wet-dry gradient of open grassland habitats in Hortobágy National Park (E-Hungary) and tested the effect of compositional and structural factors of HD on SR of flowering plants, orthopterans, true bugs, spiders, ground beetles and birds. Our dataset on 434 grassland species (170 plants, 264 animals) showed that the wet-dry gradient (compositional HD at the between-patch scale) was primarily related to SR in orthopterans, ground-dwelling arthropods, and all animals combined. The patchiness, or plant association richness, of the vegetation (compositional HD at the within-patch scale) was related to SR of vegetation-dwelling arthropods, whereas vegetation height (structural HD at the within-patch scale) was related to SR of ground-dwelling arthropods and birds. Patch area was related to SR only in birds, whereas management (grazing, mowing, none) was related to SR of plants and true bugs. All relationships between HD and SR were positive, indicating increasing SR with increasing HD. However, total SR was not related to HD because different taxa showed similar positive responses to different HD variables. Our findings, therefore, show that even though HD positively influences SR in a wide range of grassland taxa, each taxon responds to different compositional or structural measures of HD, resulting in the lack of a consistent relationship between HD and SR when taxon responses are pooled. The idiosyncratic responses shown here exemplify the difficulties in detecting general HD-SR relationships over multiple taxa. Our results also suggest that management and restoration aimed specifically to sustain or increase the diversity of habitats are required to conserve biodiversity in complex landscapes. PMID:26901569

Spatial patterns of vegetation biomass and soil organic carbon acquired from airborne lidar and hyperspectral imagery at Reynolds Creek Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Will, R. M.; Li, A.; Glenn, N. F.; Benner, S. G.; Spaete, L.; Ilangakoon, N. T.

2015-12-01

Soil organic carbon distribution and the factors influencing this distribution are important for understanding carbon stores, vegetation dynamics, and the overall carbon cycle. Linking soil organic carbon (SOC) with aboveground vegetation biomass may provide a method to better understand SOC distribution in semiarid ecosystems. The Reynolds Creek Critical Zone Observatory (RC CZO) in Idaho, USA, is approximately 240 square kilometers and is situated in the semiarid Great Basin of the sagebrush-steppe ecosystem. Full waveform airborne lidar data and Next-Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-ng) collected in 2014 across the RC CZO are used to map vegetation biomass and SOC and then explore the relationships between them. Vegetation biomass is estimated by identifying vegetation species, and quantifying distribution and structure with lidar and integrating the field-measured biomass. Spectral data from AVIRIS-ng are used to differentiate non-photosynthetic vegetation (NPV) and soil, which are commonly confused in semiarid ecosystems. The information from lidar and AVIRIS-ng are then used to predict SOC by partial least squares regression (PLSR). An uncertainty analysis is provided, demonstrating the applicability of these approaches to improving our understanding of the distribution and patterns of SOC across the landscape.

Contrasting patterns of fine-scale herb layer species composition in temperate forests

NASA Astrophysics Data System (ADS)

Chudomelová, Markéta; Zelený, David; Li, Ching-Feng

2017-04-01

Although being well described at the landscape level, patterns in species composition of forest herb layer are rarely studied at smaller scales. Here, we examined fine-scale environmental determinants and spatial structures of herb layer communities in thermophilous oak- and hornbeam dominated forests of the south-eastern part of the Czech Republic. Species composition of herb layer vegetation and environmental variables were recorded within a fixed grid of 2 × 2 m subplots regularly distributed within 1-ha quadrate plots in three forest stands. For each site, environmental models best explaining species composition were constructed using constrained ordination analysis. Spatial eigenvector mapping was used to model and account for spatial structures in community variation. Mean Ellenberg indicator values calculated for each subplot were used for ecological interpretation of spatially structured residual variation. The amount of variation explained by environmental and spatial models as well as the selection of variables with the best explanatory power differed among sites. As an important environmental factor, relative elevation was common to all three sites, while pH and canopy openness were shared by two sites. Both environmental and community variation was mostly coarse-scaled, as was the spatially structured portion of residual variation. When corrected for bias due to spatial autocorrelation, those environmental factors with already weak explanatory power lost their significance. Only a weak evidence of possibly omitted environmental predictor was found for autocorrelated residuals of site models using mean Ellenberg indicator values. Community structure was determined by different factors at different sites. The relative importance of environmental filtering vs. spatial processes was also site specific, implying that results of fine-scale studies tend to be shaped by local conditions. Contrary to expectations based on other studies, overall dominance of spatial processes at fine scale has not been detected. Ecologists should keep this in mind when making generalizations about community dynamics.

Modeling evapotranspiration based on plant hydraulic theory can predict spatial variability across an elevation gradient and link to biogeochemical fluxes

NASA Astrophysics Data System (ADS)

Mackay, D. S.; Frank, J.; Reed, D.; Whitehouse, F.; Ewers, B. E.; Pendall, E.; Massman, W. J.; Sperry, J. S.

2012-04-01

In woody plant systems transpiration is often the dominant component of total evapotranspiration, and so it is key to understanding water and energy cycles. Moreover, transpiration is tightly coupled to carbon and nutrient fluxes, and so it is also vital to understanding spatial variability of biogeochemical fluxes. However, the spatial variability of transpiration and its links to biogeochemical fluxes, within- and among-ecosystems, has been a challenge to constrain because of complex feedbacks between physical and biological controls. Plant hydraulics provides an emerging theory with the rigor needed to develop testable hypotheses and build useful models for scaling these coupled fluxes from individual plants to regional scales. This theory predicts that vegetative controls over water, energy, carbon, and nutrient fluxes can be determined from the limitation of plant water transport through the soil-xylem-stomata pathway. Limits to plant water transport can be predicted from measurable plant structure and function (e.g., vulnerability to cavitation). We present a next-generation coupled transpiration-biogeochemistry model based on this emerging theory. The model, TREEScav, is capable of predicting transpiration, along with carbon and nutrient flows, constrained by plant structure and function. The model incorporates tightly coupled mechanisms of the demand and supply of water through the soil-xylem-stomata system, with the feedbacks to photosynthesis and utilizable carbohydrates. The model is evaluated by testing it against transpiration and carbon flux data along an elevation gradient of woody plants comprising sagebrush steppe, mid-elevation lodgepole pine forests, and subalpine spruce/fir forests in the Rocky Mountains. The model accurately predicts transpiration and carbon fluxes as measured from gas exchange, sap flux, and eddy covariance towers. The results of this work demonstrate that credible spatial predictions of transpiration and related biogeochemical fluxes will be possible at regional scales using relatively easily obtained vegetation structural and functional information.

Toward daily monitoring of vegetation conditions at field scale through fusing data from multiple sensors

USDA-ARS?s Scientific Manuscript database

Vegetation monitoring requires remote sensing data at fine spatial and temporal resolution. While imagery from coarse resolution sensors such as MODIS/VIIRS can provide daily observations, they lack spatial detail to capture surface features for crop and rangeland monitoring. The Landsat satellite s...

Can Process Understanding Help Elucidate The Structure Of The Critical Zone? Comparing Process-Based Soil Formation Models With Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Peña, A.; Laguna, A.; Giráldez, J. V.

2017-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties in the critical zone. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of traditional digital soil mapping versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

Seasonal and spatial variations in fish and macrocrustacean assemblage structure in Mad Island Marsh estuary, Texas

NASA Astrophysics Data System (ADS)

Akin, S.; Winemiller, K. O.; Gelwick, F. P.

2003-05-01

Fish and macrocrustacean assemblage structure was analyzed along an estuarine gradient at Mad Island Marsh (MIM), Matagorda Bay, TX, during March 1998-August 1999. Eight estuarine-dependent fish species accounted for 94% of the individual fishes collected, and three species accounted for 96% of macrocrustacean abundance. Consistent with evidence from other Gulf of Mexico estuarine studies, species richness and abundance were highest during late spring and summer, and lowest during winter and early spring. Sites near the bay supported the most individuals and species. Associations between fish abundance and environmental variables were examined with canonical correspondence analysis. The dominant gradient was associated with water depth and distance from the bay. The secondary gradient reflected seasonal variation and was associated with temperature, salinity, dissolved oxygen, and vegetation cover. At the scales examined, estuarine biota responded to seasonal variation more than spatial variation. Estuarine-dependent species dominated the fauna and were common throughout the open waters of the shallow lake during winter-early spring when water temperature and salinity were low and dissolved oxygen high. During summer-early fall, sub-optimal environmental conditions (high temperature, low DO) in upper reaches accounted for strong spatial variation in assemblage composition. Small estuarine-resident fishes and the blue crab ( Callinectes sapidus) were common in warm, shallow, vegetated inland sites during summer-fall. Estuarine-dependent species were common at deeper, more saline locations near the bay during this period. During summer, freshwater species, such as gizzard shad ( Dorosoma cepedianum) and gars ( Lepisosteus spp.), were positively associated with water depth and proximity to the bay. The distribution and abundance of fishes in MIM appear to result from the combined effects of endogenous, seasonal patterns of reproduction and migration operating on large spatial scales, and species-specific response to local environmental variation.

Carbon stock and carbon turnover in boreal and temperate forests - Integration of remote sensing data and global vegetation models

NASA Astrophysics Data System (ADS)

Thurner, Martin; Beer, Christian; Carvalhais, Nuno; Forkel, Matthias; Tito Rademacher, Tim; Santoro, Maurizio; Tum, Markus; Schmullius, Christiane

2016-04-01

Long-term vegetation dynamics are one of the key uncertainties of the carbon cycle. There are large differences in simulated vegetation carbon stocks and fluxes including productivity, respiration and carbon turnover between global vegetation models. Especially the implementation of climate-related mortality processes, for instance drought, fire, frost or insect effects, is often lacking or insufficient in current models and their importance at global scale is highly uncertain. These shortcomings have been due to the lack of spatially extensive information on vegetation carbon stocks, which cannot be provided by inventory data alone. Instead, we recently have been able to estimate northern boreal and temperate forest carbon stocks based on radar remote sensing data. Our spatially explicit product (0.01° resolution) shows strong agreement to inventory-based estimates at a regional scale and allows for a spatial evaluation of carbon stocks and dynamics simulated by global vegetation models. By combining this state-of-the-art biomass product and NPP datasets originating from remote sensing, we are able to study the relation between carbon turnover rate and a set of climate indices in northern boreal and temperate forests along spatial gradients. We observe an increasing turnover rate with colder winter temperatures and longer winters in boreal forests, suggesting frost damage and the trade-off between frost adaptation and growth being important mortality processes in this ecosystem. In contrast, turnover rate increases with climatic conditions favouring drought and insect outbreaks in temperate forests. Investigated global vegetation models from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT, are able to reproduce observation-based spatial climate - turnover rate relationships only to a limited extent. While most of the models compare relatively well in terms of NPP, simulated vegetation carbon stocks are severely biased compared to our biomass dataset. Current limitations lead to considerable uncertainties in the estimated vegetation carbon turnover, contributing substantially to the forest feedback to climate change. Our results are the basis for improving mortality concepts in models and estimating their impact on the land carbon balance.

Heterogeneous environments shape invader impacts: integrating environmental, structural and functional effects by isoscapes and remote sensing.

PubMed

Hellmann, Christine; Große-Stoltenberg, André; Thiele, Jan; Oldeland, Jens; Werner, Christiane

2017-06-23

Spatial heterogeneity of ecosystems crucially influences plant performance, while in return plant feedbacks on their environment may increase heterogeneous patterns. This is of particular relevance for exotic plant invaders that transform native ecosystems, yet, approaches integrating geospatial information of environmental heterogeneity and plant-plant interaction are lacking. Here, we combined remotely sensed information of site topography and vegetation cover with a functional tracer of the N cycle, δ 15 N. Based on the case study of the invasion of an N 2 -fixing acacia in a nutrient-poor dune ecosystem, we present the first model that can successfully predict (R 2  = 0.6) small-scale spatial variation of foliar δ 15 N in a non-fixing native species from observed geospatial data. Thereby, the generalized additive mixed model revealed modulating effects of heterogeneous environments on invader impacts. Hence, linking remote sensing techniques with tracers of biological processes will advance our understanding of the dynamics and functioning of spatially structured heterogeneous systems from small to large spatial scales.

Assimilation of Leaf and Canopy Spectroscopic Data to Improve the Representation of Vegetation Dynamics in Terrestrial Ecosystem Models

NASA Astrophysics Data System (ADS)

Serbin, S. P.; Dietze, M.; Desai, A. R.; LeBauer, D.; Viskari, T.; Kooper, R.; McHenry, K. G.; Townsend, P. A.

2013-12-01

The ability to seamlessly integrate information on vegetation structure and function across a continuum of scales, from field to satellite observations, greatly enhances our ability to understand how terrestrial vegetation-atmosphere interactions change over time and in response to disturbances. In particular, terrestrial ecosystem models require detailed information on ecosystem states and canopy properties in order to properly simulate the fluxes of carbon (C), water and energy from the land to the atmosphere as well as address the vulnerability of ecosystems to environmental and other perturbations. Over the last several decades the amount of available data to constrain ecological predictions has increased substantially, resulting in a progressively data-rich era for global change research. In particular remote sensing data, specifically optical data (leaf and canopy), offers the potential for an important and direct data constraint on ecosystem model projections of C and energy fluxes. Here we highlight the utility of coupling information provided through the Ecosystem Spectral Information System (EcoSIS) with complex process models through the Predictive Ecosystem Analyzer (PEcAn; http://www.pecanproject.org/) eco-informatics framework as a means to improve the description of canopy optical properties, vegetation composition, and modeled radiation balance. We also present this an efficient approach for understanding and correcting implicit assumptions and model structural deficiencies. We first illustrate the challenges and issues in adequately characterizing ecosystem fluxes with the Ecosystem Demography model (ED2, Medvigy et al., 2009) due to improper parameterization of leaf and canopy properties, as well as assumptions describing radiative transfer within the canopy. ED2 is especially relevant to these efforts because it contains a sophisticated structure for scaling ecological processes across a range of spatial scales: from the tree-level (demography, physiology) to the distribution of stands across a landscape, which allows for the direct use of remotely sensed data at the appropriate spatial scale. A sensitivity analysis is employed within PEcAn to illustrate the influence of ED2 parameterizations on modeled C and energy fluxes for a northern temperate forest ecosystem as an example of the need for more detailed information on leaf and canopy optical properties. We then demonstrate a data assimilation approach to synthesize spectral data contained within EcoSIS in order to update model parameterizations across key vegetation plant functional types, as well as a means to update vegetation state information (i.e. composition, LAI) and improve the description of radiation transfer through model structural updates. A better understanding of the radiation balance of ecosystems will improve regional and global scale C and energy balance projections.

Solving Large-scale Spatial Optimization Problems in Water Resources Management through Spatial Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Wang, J.; Cai, X.

2007-12-01

A water resources system can be defined as a large-scale spatial system, within which distributed ecological system interacts with the stream network and ground water system. Water resources management, the causative factors and hence the solutions to be developed have a significant spatial dimension. This motivates a modeling analysis of water resources management within a spatial analytical framework, where data is usually geo- referenced and in the form of a map. One of the important functions of Geographic information systems (GIS) is to identify spatial patterns of environmental variables. The role of spatial patterns in water resources management has been well established in the literature particularly regarding how to design better spatial patterns for satisfying the designated objectives of water resources management. Evolutionary algorithms (EA) have been demonstrated to be successful in solving complex optimization models for water resources management due to its flexibility to incorporate complex simulation models in the optimal search procedure. The idea of combining GIS and EA motivates the development and application of spatial evolutionary algorithms (SEA). SEA assimilates spatial information into EA, and even changes the representation and operators of EA. In an EA used for water resources management, the mathematical optimization model should be modified to account the spatial patterns; however, spatial patterns are usually implicit, and it is difficult to impose appropriate patterns to spatial data. Also it is difficult to express complex spatial patterns by explicit constraints included in the EA. The GIS can help identify the spatial linkages and correlations based on the spatial knowledge of the problem. These linkages are incorporated in the fitness function for the preference of the compatible vegetation distribution. Unlike a regular GA for spatial models, the SEA employs a special hierarchical hyper-population and spatial genetic operators to represent spatial variables in a more efficient way. The hyper-population consists of a set of populations, which correspond to the spatial distributions of the individual agents (organisms). Furthermore spatial crossover and mutation operators are designed in accordance with the tree representation and then applied to both organisms and populations. This study applies the SEA to a specific problem of water resources management- maximizing the riparian vegetation coverage in accordance with the distributed groundwater system in an arid region. The vegetation coverage is impacted greatly by the nonlinear feedbacks and interactions between vegetation and groundwater and the spatial variability of groundwater. The SEA is applied to search for an optimal vegetation configuration compatible to the groundwater flow. The results from this example demonstrate the effectiveness of the SEA. Extension of the algorithm for other water resources management problems is discussed.

Vegetation Cover Analysis in Shaanxi Province of China Based on Grid Pixel Ternd Analysis and Stability Evaluation

NASA Astrophysics Data System (ADS)

Yue, H.; Liu, Y.

2018-04-01

As a key factor affecting the biogeochemical cycle of human existence, terrestrial vegetation is vulnerable to natural environment and human activities, with obvious temporal and spatial characteristics. The change of vegetation cover will affect the ecological balance and environmental quality to a great extent. Therefore, the research on the causes and influencing factors of vegetation cover has become the focus of attention of scholars at home and abroad. In the evolution of human activities and natural environment, the vegetation coverage in Shaanxi has changed accordingly. Using MODIS/NDVI 2000-2014 time series data, using the method of raster pixel trend analysis, stability evaluation, rescaled range analysis and correlation analysis, the climatic factors in Shaanxi province were studied in the near 15 years vegetation spatial and temporal variation and influence of vegetation NDVI changes. The results show that NDVI in Shaanxi province in the near 15 years increased by 0.081, the increase of NDVI in Northern Shaanxi was obvious, and negative growth was found in some areas of Guanzhong, southern Shaanxi NDVI overall still maintained at a high level; the trend of vegetation change in Shaanxi province has obvious spatial differences, most of the province is a slight tendency to improve vegetation, there are many obvious improvement areas in Northern Shaanxi Province. Guanzhong area vegetation area decreased, the small range of variation of vegetation in Shaanxi province; the most stable areas are mainly concentrated in the southern, southern Yanan, Yulin, Xi'an area of Weinan changed greatly; Shaanxi Province in recent 15 a, the temperature and precipitation have shown an increasing trend, and the vegetation NDVI is more closely related to the average annual rainfall, with increase of 0.48 °C/10 years and 69.5 mm per year.

[Effects of landscape and vegetation structure on the diversity of phyllostomid bats (Chiroptera: Phyllostomidae) in Oaxaca, Mexico].

PubMed

García-García, José Luis; Santos-Moreno, Antonio

2014-03-01

The tropical forest fragmentation is known to affect the spatial structure of the landscape and habitat. These alterations can modify the attributes of bat assemblages, however, this phenomenon has been little studied and understood. In this work we evaluated the structure of landscape (i.e. composition and configuration) and vegetation, and its relationship with assemblage- and population-level characteristics of phyllostomid bats in a tropical rainforest of Southeastern Mexico. For this, we previously selected 12 sites located in continuous and fragmented forests, where bats were captured using mist nets during a two years sampling effort (144 nights). Bats relative abundance, species richness (diversity of order 0, 0D), Shannon diversity index (1D) and Simpson index (2D) were evaluated in all sites, and their relationship with seven measures of landscape structure and seven measures of vegetation structure was described using a Hierarchical Partitioning Analysis. A total of 1 840 individuals of 29 species of phyllostomid bats were captured in this period. Differences in the assemblages were manifested only in the relative abundance and not in the richness of the species. The assemblages of fragmented forest exhibited greater variation in species composition and a greater abundance of frugivorous and nectarivorous bats in comparison with the assemblages of continuous forest. The landscape configuration was related to the assemblage- and population-level attributes, contrasting with previous studies where the composition was a key element. At habitat level, tree density and canopy cover determined the abundance of bats. Nectarivorous and frugivorous bats were mostly found in disturbed vegetation landscapes, primarily due to landscape configuration (e.g. edge density). This phenomenon could be a response to the availability of food in primary and intermediate successional stages, which are characterized by an abundance of food value.

Savanna Vegetation Dynamics and their Influence on Landscape-Scale C, N, and P Biogeochemistry

NASA Astrophysics Data System (ADS)

Boutton, T. W.; Zhou, Y.; Wu, X. B.; Hyodo, A.

2017-12-01

Soil carbon (C), nitrogen (N) and phosphorus (P) cycles are strongly interlinked and controlled through biological processes, and the P cycle is further controlled through geochemical processes. In grasslands, savannas, and other dryland ecosystems throughout the world, woody plant encroachment often modifies soil C, N, and P stores, although it remains unknown if these three elements change proportionally in response to this vegetation change. We evaluated proportional changes and spatial patterns of soil organic C (SOC), total N (TN), and total P (TP) following woody encroachment by taking spatially-explicit soil cores to a depth of 1.2 m across a subtropical savanna landscape which has undergone encroachment by trees and shrubs during the past century in the Rio Grande Plains, USA. SOC and TN were coupled with respect to increasing magnitudes and spatial patterns along the soil profile following woody encroachment. In contrast, TP increased slower than SOC and TN in surface soils, but faster in subsurface soils. Spatial patterns of TP strongly resembled those of vegetation cover throughout the soil profile, but differed from those of SOC and TN, especially in deeper portions of the profile. The encroachment of woody plants into this P-limited ecosystem resulted in the accumulation of proportionally less soil P compared to C and N in surface soils; however, proportionally more P accrued in deeper portions of the profile beneath woody patches where alkaline soil pH and high carbonate concentrations would favor precipitation of P as relatively insoluble calcium phosphates. Structural equation models (SEM) showed that fine root density explained the greatest proportion of variation in SOC, TN, and TP in the surface soil. In deeper portions of the profile, SEM showed that silt and clay explained much of the variation in SOC and TN, while soil pH strongly controlled TP. This imbalanced relationship highlights that the relative importance of biotic vs. abiotic mechanisms controlling C and N vs. P accumulation following vegetation change may vary with depth in the profile. Our findings suggest that efforts to incorporate the effects of land cover changes into coupled climate-biogeochemical models should attempt to represent C-N-P imbalances that may arise following vegetation change.

Cubesats and drones: bridging the spatio-temporal divide for enhanced earth observation

NASA Astrophysics Data System (ADS)

McCabe, M. F.; Aragon, B.; Parkes, S. D.; Mascaro, J.; Houborg, R.

2017-12-01

In just the last few years, a range of advances in remote sensing technologies have enabled an unprecedented opportunity in earth observation. Parallel developments in cubesats and unmanned aerial vehicles (UAVs) have overcome one of the outstanding challenges in observing the land surface: the provision of timely retrievals at a spatial resolution that is sufficiently detailed to make field-level decisions. Planet cubesats have revolutionized observing capacity through their objective of near daily global retrieval. These nano-satellite systems provide high resolution (approx. 3 m) retrievals in red-green-blue and near-infrared wavelengths, offering capacity to develop vegetation metrics for both hydrological and precision agricultural applications. Apart from satellite based advances, nearer to earth technology is being exploited for a range of observation needs. UAVs provide an adaptable platform from which a variety of sensing systems can be deployed. Combinations of optical, thermal, multi- and hyper-spectral systems allow for the estimation of a range of land surface variables, including vegetation structure, vegetation health, land surface temperature and evaporation. Here we explore some of these exciting developments in the context of agricultural hydrology, providing examples of cubesat and UAV imagery that has been used to inform upon crop health and water use. An investigation of the spatial and temporal advantage of these complementary systems is undertaken, with examples of multi-day high-resolution vegetation dynamics from cubesats presented alongside diurnal-cycle responses derived from multiple within-day UAV flights.

Evaluation of Vertical Lacunarity Profiles in Forested Areas Using Airborne Laser Scanning Point Clouds

NASA Astrophysics Data System (ADS)

Székely, B.; Kania, A.; Standovár, T.; Heilmeier, H.

2016-06-01

The horizontal variation and vertical layering of the vegetation are important properties of the canopy structure determining the habitat; three-dimensional (3D) distribution of objects (shrub layers, understory vegetation, etc.) is related to the environmental factors (e.g., illumination, visibility). It has been shown that gaps in forests, mosaic-like structures are essential to biodiversity; various methods have been introduced to quantify this property. As the distribution of gaps in the vegetation is a multi-scale phenomenon, in order to capture it in its entirety, scale-independent methods are preferred; one of these is the calculation of lacunarity. We used Airborne Laser Scanning point clouds measured over a forest plantation situated in a former floodplain. The flat topographic relief ensured that the tree growth is independent of the topographic effects. The tree pattern in the plantation crops provided various quasi-regular and irregular patterns, as well as various ages of the stands. The point clouds were voxelized and layers of voxels were considered as images for two-dimensional input. These images calculated for a certain vicinity of reference points were taken as images for the computation of lacunarity curves, providing a stack of lacunarity curves for each reference points. These sets of curves have been compared to reveal spatial changes of this property. As the dynamic range of the lacunarity values is very large, the natural logarithms of the values were considered. Logarithms of lacunarity functions show canopy-related variations, we analysed these variations along transects. The spatial variation can be related to forest properties and ecology-specific aspects.

Predictive modeling of hazardous waste landfill total above-ground biomass using passive optical and LIDAR remotely sensed data

NASA Astrophysics Data System (ADS)

Hadley, Brian Christopher

This dissertation assessed remotely sensed data and geospatial modeling technique(s) to map the spatial distribution of total above-ground biomass present on the surface of the Savannah River National Laboratory's (SRNL) Mixed Waste Management Facility (MWMF) hazardous waste landfill. Ordinary least squares (OLS) regression, regression kriging, and tree-structured regression were employed to model the empirical relationship between in-situ measured Bahia (Paspalum notatum Flugge) and Centipede [Eremochloa ophiuroides (Munro) Hack.] grass biomass against an assortment of explanatory variables extracted from fine spatial resolution passive optical and LIDAR remotely sensed data. Explanatory variables included: (1) discrete channels of visible, near-infrared (NIR), and short-wave infrared (SWIR) reflectance, (2) spectral vegetation indices (SVI), (3) spectral mixture analysis (SMA) modeled fractions, (4) narrow-band derivative-based vegetation indices, and (5) LIDAR derived topographic variables (i.e. elevation, slope, and aspect). Results showed that a linear combination of the first- (1DZ_DGVI), second- (2DZ_DGVI), and third-derivative of green vegetation indices (3DZ_DGVI) calculated from hyperspectral data recorded over the 400--960 nm wavelengths of the electromagnetic spectrum explained the largest percentage of statistical variation (R2 = 0.5184) in the total above-ground biomass measurements. In general, the topographic variables did not correlate well with the MWMF biomass data, accounting for less than five percent of the statistical variation. It was concluded that tree-structured regression represented the optimum geospatial modeling technique due to a combination of model performance and efficiency/flexibility factors.

Interactions among hydrogeomorphology, vegetation, and nutrient biogeochemistry in floodplain ecosystems

USGS Publications Warehouse

Noe, G.B.; Shroder, John F.

2013-01-01

Hydrogeomorphic, vegetative, and biogeochemical processes interact in floodplains resulting in great complexity that provides opportunities to better understand linkages among physical and biological processes in ecosystems. Floodplains and their associated river systems are structured by four-dimensional gradients of hydrogeomorphology: longitudinal, lateral, vertical, and temporal components. These four dimensions create dynamic hydrologic and geomorphologic mosaics that have a large imprint on the vegetation and nutrient biogeochemistry of floodplains. Plant physiology, population dynamics, community structure, and productivity are all very responsive to floodplain hydrogeomorphology. The strength of this relationship between vegetation and hydrogeomorphology is evident in the use of vegetation as an indicator of hydrogeomorphic processes. However, vegetation also influences hydrogeomorphology by modifying hydraulics and sediment entrainment and deposition that typically stabilize geomorphic patterns. Nitrogen and phosphorus biogeochemistry commonly influence plant productivity and community composition, although productivity is not limited by nutrient availability in all floodplains. Conversely, vegetation influences nutrient biogeochemistry through direct uptake and storage as well as production of organic matter that regulates microbial biogeochemical processes. The biogeochemistries of nitrogen and phosphorus cycling are very sensitive to spatial and temporal variation in hydrogeomorphology, in particular floodplain wetness and sedimentation. The least-studied interaction is the direct effect of biogeochemistry on hydrogeomorphology, but the control of nutrient availability over organic matter decomposition and thus soil permeability and elevation is likely important. Biogeochemistry also has the more documented but indirect control of hydrogeomorphology through regulation of plant biomass. In summary, the defining characteristics of floodplain ecosystems are determined by the many interactions among physical and biological processes. Conservation and restoration of the valuable ecosystem services that floodplains provide depend on improved understanding and predictive models of interactive system controls and behavior.

Interactions among hydrogeomorphology, vegetation, and nutrient biogeochemistry in floodplain ecosystems

USGS Publications Warehouse

Noe, G.B.

2013-01-01

Hydrogeomorphic, vegetative, and biogeochemical processes interact in floodplains resulting in great complexity that provides opportunities to better understand linkages among physical and biological processes in ecosystems. Floodplains and their associated river systems are structured by four dimensional gradients of hydrogeomorphology: longitudinal, lateral, vertical, and temporal components. These four dimensions create dynamic hydrologic and geomorphologic mosaics that have a large imprint on the vegetation and nutrient biogeochemistry of floodplains. Plant physiology, population dynamics, community structure, and productivity are all very responsive to floodplain hydrogeomorphology. The strength of this relationship between vegetation and hydrogeomorphology is evident in the use of vegetation as an indicator of hydrogeomorphic processes. However, vegetation also influences hydrogeomorphology by modifying hydraulics and sediment entrainment and deposition that typically stabilize geomorphic patterns. Nitrogen and phosphorus biogeochemistry commonly influence plant productivity and community composition, although productivity is not limited by nutrient availability in all floodplains. Conversely, vegetation influences nutrient biogeochemistry through direct uptake and storage as well as production of organic matter that regulates microbial biogeochemical processes. The biogeochemistries of nitrogen and phosphorus cycling are very sensitive to spatial and temporal variation in hydrogeomorphology, in particular floodplain wetness and sedimentation. The least studied interaction is the direct effect of biogeochemistry on hydrogeomorphology, but the control of nutrient availability over organic matter decomposition and thus soil permeability and elevation is likely important. Biogeochemistry also has the more documented but indirect control of hydrogeomorphology through regulation of plant biomass. In summary, the defining characteristics of floodplain ecosystems are determined by the many interactions among physical and biological processes. Conservation and restoration of the valuable ecosystem services that floodplains provide depends on improved understanding and predictive models of interactive system controls and behavior.

Woody-Herbaceous Species Coexistence in Mulga Hillslopes: Modelling Structure and Function

NASA Astrophysics Data System (ADS)

Soltanjalili, M. J.; Saco, P. M.; Willgoose, G. R.

2016-12-01

The fundamental processes underlying the coexistence of woody and herbaceous species in arid and semi-arid areas have been a topic of intense research during the last few decades. Experimental and modelling studies have both supported and disputed alternative hypotheses explaining this phenomenon. Vegetation models including the key processes that drive coexistence can be used to understand vegetation pattern dynamics and structure under current climate conditions, and to predict changes under future conditions. Here we present work done towards linking the observations to modelling. The model captures woody-herbaceous coexistence along a rainfall gradient characteristic of typical conditions on Mulga ecosystems in Australia. The dynamic vegetation model simulates the spatial dynamics of overland flow, soil moisture and vegetation growth of two species. It incorporates key mechanisms for coexistence and pattern formation, including facilitation by evaporation reduction through shading, and infiltration feedbacks, local and non-local seed dispersal, competition for water uptake. Model outcomes, obtained including diflerent mechanisms, are qualitatively compared to typical vegetation cover patterns in the Australian Mulga bioregion where bush fire is very infrequent and the fate of vegetation cover is mostly determined by intra- and interspecies interactions. Through these comparisons, and by drawing on the large number of recent studies that have delivered new insights into the dynamics of such ecosystems, we identify main mechanisms that need an improved representation in the dynamic vegetation models. We show that a realistic parameterization of the model leads to results which are aligned with the observations reported in the literature. At the lower end of the rainfall gradient woody species coexist with herbaceous species within a sparse banded pattern, while at higher rainfall woody species tend to dominate the landscape.

Combining ground-based measurements and satellite-based spectral vegetation indices to track biomass accumulation in post-fire chaparral

NASA Astrophysics Data System (ADS)

Uyeda, K. A.; Stow, D. A.; Roberts, D. A.; Riggan, P. J.

2015-12-01

Multi-temporal satellite imagery can provide valuable information on patterns of vegetation growth over large spatial extents and long time periods, but corresponding ground-referenced biomass information is often difficult to acquire, especially at an annual scale. In this study, I test the relationship between annual biomass estimated using shrub growth rings and metrics of seasonal growth derived from Moderate Resolution Imaging Spectroradiometer (MODIS) spectral vegetation indices (SVIs) for a small area of southern California chaparral to evaluate the potential for mapping biomass at larger spatial extents. The site had most recently burned in 2002, and annual biomass accumulation measurements were available from years 5 - 11 post-fire. I tested metrics of seasonal growth using six SVIs (Normalized Difference Vegetation Index, Enhanced Vegetation Index, Soil Adjusted Vegetation Index, Normalized Difference Water Index, Normalized Difference Infrared Index 6, and Vegetation Atmospherically Resistant Index). While additional research would be required to determine which of these metrics and SVIs are most promising over larger spatial extents, several of the seasonal growth metrics/ SVI combinations have a very strong relationship with annual biomass, and all SVIs have a strong relationship with annual biomass for at least one of the seasonal growth metrics.

Primary Productivity and Precipitation-Use Efficiency in Temperate Grassland in the Loess Plateau of China

PubMed Central

Jia, Xiaoxu; Xie, Baoni; Shao, Ming’an; Zhao, Chunlei

2015-01-01

Clarifying spatial variations in aboveground net primary productivity (ANPP) and precipitation-use efficiency (PUE) of grasslands is critical for effective prediction of the response of terrestrial ecosystem carbon and water cycle to future climate change. Though the combination use of remote sensing products and in situ ANPP measurements, we quantified the effects of climatic [mean annual precipitation (MAP) and precipitation seasonal distribution (PSD)], biotic [leaf area index (LAI)] and abiotic [slope gradient, aspect, soil water storage (SWS) and other soil physical properties] factors on the spatial variations in ANPP and PUE across different grassland types (i.e., meadow steppe, typical steppe and desert steppe) in the Loess Plateau. Based on the study, ANPP increased exponentially with MAP for the entire temperate grassland; suggesting that PUE increased with increasing MAP. Also PSD had a significant effect on ANPP and PUE; where more even PSD favored higher ANPP and PUE. Then MAP, more than PSD, explained spatial variations in typical steppe and desert steppe. However, PSD was the dominant driving factor of spatial variations in ANPP of meadow steppe. This suggested that in terms of spatial variations in ANPP of meadow steppe, change in PSD due to climate change was more important than that in total annual precipitation. LAI explained 78% of spatial PUE in the entire Loess Plateau temperate grassland. As such, LAI was the primary driving factor of spatial variations in PUE. Although the effect of SWS on ANPP and PUE was significant, it was nonetheless less than that of precipitation and vegetation. We therefore concluded that changes in vegetation structure and consequently in LAI and/or altered pattern of seasonal distribution of rainfall due to global climate change could significantly influence ecosystem carbon and water cycle in temperate grasslands. PMID:26295954

Primary Productivity and Precipitation-Use Efficiency in Temperate Grassland in the Loess Plateau of China.

PubMed

Jia, Xiaoxu; Xie, Baoni; Shao, Ming'an; Zhao, Chunlei

2015-01-01

Clarifying spatial variations in aboveground net primary productivity (ANPP) and precipitation-use efficiency (PUE) of grasslands is critical for effective prediction of the response of terrestrial ecosystem carbon and water cycle to future climate change. Though the combination use of remote sensing products and in situ ANPP measurements, we quantified the effects of climatic [mean annual precipitation (MAP) and precipitation seasonal distribution (PSD)], biotic [leaf area index (LAI)] and abiotic [slope gradient, aspect, soil water storage (SWS) and other soil physical properties] factors on the spatial variations in ANPP and PUE across different grassland types (i.e., meadow steppe, typical steppe and desert steppe) in the Loess Plateau. Based on the study, ANPP increased exponentially with MAP for the entire temperate grassland; suggesting that PUE increased with increasing MAP. Also PSD had a significant effect on ANPP and PUE; where more even PSD favored higher ANPP and PUE. Then MAP, more than PSD, explained spatial variations in typical steppe and desert steppe. However, PSD was the dominant driving factor of spatial variations in ANPP of meadow steppe. This suggested that in terms of spatial variations in ANPP of meadow steppe, change in PSD due to climate change was more important than that in total annual precipitation. LAI explained 78% of spatial PUE in the entire Loess Plateau temperate grassland. As such, LAI was the primary driving factor of spatial variations in PUE. Although the effect of SWS on ANPP and PUE was significant, it was nonetheless less than that of precipitation and vegetation. We therefore concluded that changes in vegetation structure and consequently in LAI and/or altered pattern of seasonal distribution of rainfall due to global climate change could significantly influence ecosystem carbon and water cycle in temperate grasslands.

Comparison of Topographic Effects between the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI)

NASA Astrophysics Data System (ADS)

Matsushita, B.; Yang, W.; Chen, J.; Onda, Y.

2007-12-01

Vegetation indices play an important role in monitoring variations in vegetation. The Enhanced Vegetation Index (EVI) proposed by the MODIS Land Discipline Group and the Normalized Difference Vegetation Index (NDVI) are both global-based vegetation indices aimed at providing consistent spatial and temporal information regarding global vegetation. However, many environmental factors such as atmospheric conditions and soil background may produce errors in these indices. The topographic effect is another very important factor, especially when the indices are used in areas of rough terrain. In this paper, we analyzed differences in the topographic effect between the EVI and the NDVI based on a non-Lambertian model and using two airborne-based images with a spatial resolution of 1.5m acquired from a mountainous area covered by a homogeneous Japanese cypress plantation. The results indicate that the soil adjustment factor "L" in the EVI makes it more sensitive to topographic conditions than is the NDVI. Based on these results, we strongly recommend that the topographic effect be removed from the EVI--as well as from other vegetation indices that similarly include a term without a band ratio format (e.g., the PVI and SAVI)--when these indices are used in conjunction with a high spatial resolution image of an area of rough terrain, where the topographic effect on the vegetarian indices having only a band ratio format (e.g., the NDVI) can usually be ignored.

Monitoring vegetation dynamics with medium resolution MODIS-EVI time series at sub-regional scale in southern Africa

NASA Astrophysics Data System (ADS)

Dubovyk, Olena; Landmann, Tobias; Erasmus, Barend F. N.; Tewes, Andreas; Schellberg, Jürgen

2015-06-01

Currently there is a lack of knowledge on spatio-temporal patterns of land surface dynamics at medium spatial scale in southern Africa, even though this information is essential for better understanding of ecosystem response to climatic variability and human-induced land transformations. In this study, we analysed vegetation dynamics across a large area in southern Africa using the 14-years (2000-2013) of medium spatial resolution (250 m) MODIS-EVI time-series data. Specifically, we investigated temporal changes in the time series of key phenometrics including overall greenness, peak and timing of annual greenness over the monitoring period and study region. In order to specifically capture spatial and per pixel vegetation changes over time, we calculated trends in these phenometrics using a robust trend analysis method. The results showed that interannual vegetation dynamics followed precipitation patterns with clearly differentiated seasonality. The earliest peak greenness during 2000-2013 occurred at the end of January in the year 2000 and the latest peak greenness was observed at the mid of March in 2012. Specifically spatial patterns of long-term vegetation trends allowed mapping areas of (i) decrease or increase in overall greenness, (ii) decrease or increase of peak greenness, and (iii) shifts in timing of occurrence of peak greenness over the 14-year monitoring period. The observed vegetation decline in the study area was mainly attributed to human-induced factors. The obtained information is useful to guide selection of field sites for detailed vegetation studies and land rehabilitation interventions and serve as an input for a range of land surface models.

Canopy reflectance modelling of semiarid vegetation

NASA Technical Reports Server (NTRS)

Franklin, Janet

1994-01-01

Three different types of remote sensing algorithms for estimating vegetation amount and other land surface biophysical parameters were tested for semiarid environments. These included statistical linear models, the Li-Strahler geometric-optical canopy model, and linear spectral mixture analysis. The two study areas were the National Science Foundation's Jornada Long Term Ecological Research site near Las Cruces, NM, in the northern Chihuahuan desert, and the HAPEX-Sahel site near Niamey, Niger, in West Africa, comprising semiarid rangeland and subtropical crop land. The statistical approach (simple and multiple regression) resulted in high correlations between SPOT satellite spectral reflectance and shrub and grass cover, although these correlations varied with the spatial scale of aggregation of the measurements. The Li-Strahler model produced estimated of shrub size and density for both study sites with large standard errors. In the Jornada, the estimates were accurate enough to be useful for characterizing structural differences among three shrub strata. In Niger, the range of shrub cover and size in short-fallow shrublands is so low that the necessity of spatially distributed estimation of shrub size and density is questionable. Spectral mixture analysis of multiscale, multitemporal, multispectral radiometer data and imagery for Niger showed a positive relationship between fractions of spectral endmembers and surface parameters of interest including soil cover, vegetation cover, and leaf area index.

Effects of distance from cattle water developments on grassland birds

USGS Publications Warehouse

Fontaine, A.L.; Kennedy, P.L.; Johnson, D.H.

2004-01-01

Many North American grassland bird populations appear to be declining, which may be due to changes in grazing regimes on their breeding areas. Establishment of water developments and confining cattle (Bos taurus L.) to small pastures often minimizes spatial heterogeneity of cattle forage consumption, which may lead to uniformity in vegetative structure. This increased uniformity may provide suitable habitat for some bird species but not others. We assessed how cattle use, vegetative structure, and bird population densities varied with increasing distance from water developments (0DS800 m) on the Little Missouri National Grassland (LMNG) in North Dakota. Lark buntings (Calamospiza melancorys Stejneger), which are typically associated with low vegetative cover, decreased with increasing distance from water developments. Horned larks (Eremophila alpestris L.), also a low-cover associate, followed a similar but weaker trend. Densities of another low-cover associate as well as moderate- and high-cover associates were not related to distance from water. Vegetative height-density and litter depth increased by 50 and 112%, respectively, while cowpie cover and structural variability decreased by 51 and 24%, respectively, with distance from water. Confidence interval overlap was common among all measures, showing substantial variability among study sites. Our results indicate cattle use is higher closer to water developments, and this pattern may positively affect the densities of lark buntings and horned larks. The absence of density gradients in the other bird species may be due to the paucity of locations > 800 m from water on the LMNG.

Effects of distance from cattle water developments on grassland birds

USGS Publications Warehouse

Fontaine, A.L.; Kennedy, P.L.; Johnson, D.H.

2004-01-01

Many North American grassland bird populations appear to be declining, which may be due to changes in grazing regimes on their breeding areas. Establishment of water developments and confining cattle (Bos taurus L.) to small pastures often minimizes spatial heterogeneity of cattle forage consumption, which may lead to uniformity in vegetative structure. This increased uniformity may provide suitable habitat for some bird species but not others. We assessed how cattle use, vegetative structure, and bird population densities varied with increasing distance from water developments (0-800 m) on the Little Missouri National Grassland (LMNG) in North Dakota. Lark buntings (Calamospiza melancorys Stejneger), which are typically associated with low vegetative cover, decreased with increasing distance from water developments. Horned larks (Eremophila alpestris L.), also a low-cover associate, followed a similar but weaker trend. Densities of another low-cover associate as well as moderate- and high-cover associates were not related to distance from water. Vegetative height-density and litter depth increased by 50 and 112%, respectively, while cowpie cover and structural variability decreased by 51 and 24%, respectively, with distance from water. Confidence interval overlap was common among all measures, showing substantial variability among study sites. Our results indicate cattle use is higher closer to water developments, and this pattern may positively affect the densities of lark buntings and horned larks. The absence of density gradients in the other bird species may be due to the paucity of locations > 800 m from water on the LMNG.

Influence of climate variability, fire and phosphorus limitation on vegetation structure and dynamics of the Amazon-Cerrado border

NASA Astrophysics Data System (ADS)

Ane Dionizio, Emily; Heil Costa, Marcos; de Almeida Castanho, Andrea D.; Ferreira Pires, Gabrielle; Schwantes Marimon, Beatriz; Hur Marimon-Junior, Ben; Lenza, Eddie; Martins Pimenta, Fernando; Yang, Xiaojuan; Jain, Atul K.

2018-02-01

Climate, fire and soil nutrient limitation are important elements that affect vegetation dynamics in areas of the forest-savanna transition. In this paper, we use the dynamic vegetation model INLAND to evaluate the influence of interannual climate variability, fire and phosphorus (P) limitation on Amazon-Cerrado transitional vegetation structure and dynamics. We assess how each environmental factor affects net primary production, leaf area index and aboveground biomass (AGB), and compare the AGB simulations to an observed AGB map. We used two climate data sets (monthly average climate for 1961-1990 and interannual climate variability for 1948-2008), two data sets of total soil P content (one based on regional field measurements and one based on global data), and the INLAND fire module. Our results show that the inclusion of interannual climate variability, P limitation and fire occurrence each contribute to simulating vegetation types that more closely match observations. These effects are spatially heterogeneous and synergistic. In terms of magnitude, the effect of fire is strongest and is the main driver of vegetation changes along the transition. Phosphorus limitation, in turn, has a stronger effect on transitional ecosystem dynamics than interannual climate variability does. Overall, INLAND typically simulates more than 80 % of the AGB variability in the transition zone. However, the AGB in many places is clearly not well simulated, indicating that important soil and physiological factors in the Amazon-Cerrado border region, such as lithology, water table depth, carbon allocation strategies and mortality rates, still need to be included in the model.

Equine Grazing in Managed Subalpine Wetlands: Effects on Arthropods and Plant Structure as a Function of Habitat

NASA Astrophysics Data System (ADS)

Holmquist, Jeffrey G.; Schmidt-Gengenbach, Jutta; Haultain, Sylvia A.

2013-12-01

Grazing management necessarily emphasizes the most spatially extensive vegetation assemblages, but landscapes are mosaics, often with more mesic vegetation types embedded within a matrix of drier vegetation. Our primary objective was to contrast effects of equine grazing on both subalpine vegetation structure and associated arthropods in a drier reed grass ( Calamagrostis muiriana) dominated habitat versus a wetter, more productive sedge habitat ( Carex utriculata). A second objective was to compare reed grass and sedge as habitats for fauna, irrespective of grazing. All work was done in Sequoia National Park (CA, USA), where detailed, long-term records of stock management were available. We sampled paired grazed and control wet meadows that contained both habitats. There were moderate negative effects of grazing on vegetation, and effects were greater in sedge than in reed grass. Conversely, negative grazing effects on arthropods, albeit limited, were greater in the drier reed grass, possibly due to microhabitat differences. The differing effects on plants and animals as a function of habitat emphasize the importance of considering both flora and fauna, as well as multiple habitat types, when making management decisions. Sedge supported twice the overall arthropod abundance of reed grass as well as greater diversity; hemipteran and dipteran taxa were particularly abundant in sedge. Given the greater grazing effects on sedge vegetation, greater habitat provision for terrestrial arthropods, and value as aquatic arthropod habitat, the wetter sedge assemblage is worthy of additional consideration by managers when planning for grazing and other aspects of land usage.

Limbic hyperconnectivity in the vegetative state.

PubMed

Di Perri, Carol; Bastianello, Stefano; Bartsch, Andreas J; Pistarini, Caterina; Maggioni, Giorgio; Magrassi, Lorenzo; Imberti, Roberto; Pichiecchio, Anna; Vitali, Paolo; Laureys, Steven; Di Salle, Francesco

2013-10-15

To investigate functional connectivity between the default mode network (DMN) and other networks in disorders of consciousness. We analyzed MRI data from 11 patients in a vegetative state and 7 patients in a minimally conscious state along with age- and sex-matched healthy control subjects. MRI data analysis included nonlinear spatial normalization to compensate for disease-related anatomical distortions. We studied brain connectivity data from resting-state MRI temporal series, combining noninferential (independent component analysis) and inferential (seed-based general linear model) methods. In DMN hypoconnectivity conditions, a patient's DMN functional connectivity shifts and paradoxically increases in limbic structures, including the orbitofrontal cortex, insula, hypothalamus, and the ventral tegmental area. Concurrently with DMN hypoconnectivity, we report limbic hyperconnectivity in patients in vegetative and minimally conscious states. This hyperconnectivity may reflect the persistent engagement of residual neural activity in self-reinforcing neural loops, which, in turn, could disrupt normal patterns of connectivity.

From Patterns to Function in Living Systems: Dryland Ecosystems as a Case Study

NASA Astrophysics Data System (ADS)

Meron, Ehud

2018-03-01

Spatial patterns are ubiquitous in animate matter. Besides their intricate structure and beauty they generally play functional roles. The capacity of living systems to remain functional in changing environments is a question of utmost importance, but its intimate relationship to pattern formation is largely unexplored. Here, we address this relationship using dryland vegetation as a case study. Following a brief introduction to pattern-formation theory, we describe a mathematical model that captures several mechanisms of vegetation pattern formation and discuss ecological contexts that showcase different mechanisms. Using this model, we unravel the different vegetation patterns that keep dryland ecosystems viable along the rainfall gradient, identify multistability ranges where fronts separating domains of alternative stable states exist, and highlight the roles of front dynamics in mitigating or reversing desertification. The utility of satellite images in testing model predictions is discussed. An outlook on outstanding open problems concludes this paper.

Simulation Based Exploration of Critical Zone Dynamics in Intensively Managed Landscapes

NASA Astrophysics Data System (ADS)

Kumar, P.

2017-12-01

The advent of high-resolution measurements of topographic and (vertical) vegetation features using areal LiDAR are enabling us to resolve micro-scale ( 1m) landscape structural characteristics over large areas. Availability of hyperspectral measurements is further augmenting these LiDAR data by enabling the biogeochemical characterization of vegetation and soils at unprecedented spatial resolutions ( 1-10m). Such data have opened up novel opportunities for modeling Critical Zone processes and exploring questions that were not possible before. We show how an integrated 3-D model at 1m grid resolution can enable us to resolve micro-topographic and ecological dynamics and their control on hydrologic and biogeochemical processes over large areas. We address the computational challenge of such detailed modeling by exploiting hybrid CPU and GPU computing technologies. We show results of moisture, biogeochemical, and vegetation dynamics from studies in the Critical Zone Observatory for Intensively managed Landscapes (IMLCZO) in the Midwestern United States.

Conspecific and Heterospecific Plant Densities at Small-Scale Can Drive Plant-Pollinator Interactions

PubMed Central

Janovský, Zdeněk; Mikát, Michael; Hadrava, Jiří; Horčičková, Eva; Kmecová, Kateřina; Požárová, Doubravka; Smyčka, Jan; Herben, Tomáš

2013-01-01

Generalist pollinators are important in many habitats, but little research has been done on small-scale spatial variation in interactions between them and the plants that they visit. Here, using a spatially explicit approach, we examined whether multiple species of flowering plants occurring within a single meadow showed spatial structure in their generalist pollinator assemblages. We report the results for eight plant species for which at least 200 individual visits were recorded. We found that for all of these species, the proportions of their general pollinator assemblages accounted for by particular functional groups showed spatial heterogeneity at the scale of tens of metres. This heterogeneity was connected either with no or only subtle changes of vegetation and flowering species composition. In five of these species, differences in conspecific plant density influenced the pollinator communities (with greater dominance of main pollinators at low-conspecific plant densities). The density of heterospecific plant individuals influenced the pollinator spectrum in one case. Our results indicate that the picture of plant-pollinator interactions provided by averaging data within large plots may be misleading and that within-site spatial heterogeneity should be accounted for in terms of sampling effort allocation and analysis. Moreover, spatially structured plant-pollinator interactions may have important ecological and evolutionary consequences, especially for plant population biology. PMID:24204818

Detecting vegetation cover change on the summit of Cadillac Mountain using multi-temporal remote sensing datasets: 1979, 2001, and 2007.

PubMed

Kim, Min-Kook; Daigle, John J

2011-09-01

This study examines the efficacy of management strategies implemented in 2000 to reduce visitor-induced vegetation impact and enhance vegetation recovery at the summit loop trail on Cadillac Mountain at Acadia National Park, Maine. Using single-spectral high-resolution remote sensing datasets captured in 1979, 2001, and 2007, pre-classification change detection analysis techniques were applied to measure fractional vegetation cover changes between the time periods. This popular sub-alpine summit with low-lying vegetation and attractive granite outcroppings experiences dispersed visitor use away from the designated trail, so three pre-defined spatial scales (small, 0-30 m; medium, 0-60 m; and large, 0-90 m) were examined in the vicinity of the summit loop trail with visitor use (experimental site) and a site chosen nearby in a relatively pristine undisturbed area (control site) with similar spatial scales. Results reveal significant changes in terms of rates of vegetation impact between 1979 and 2001 extending out to 90 m from the summit loop trail with no management at the site. No significant differences were detected among three spatial zones (inner, 0-30 m; middle, 30-60 m; and outer, 60-90 m) at the experimental site, but all were significantly higher rates of impact compared to similar spatial scales at the control site (all p < 0.001). In contrast, significant changes in rates of recovery between 2001 and 2007 were observed in the medium and large spatial scales at the experimental site under management as compared to the control site (all p < 0.05). Also during this later period a higher rate of recovery was observed in the outer zone as compared to the inner zone at the experimental site (p < 0.05). The overall study results suggest a trend in the desired direction for the site and visitor management strategies designed to reduce vegetation impact and enhance vegetation recovery at the summit loop trail of Cadillac Mountain since 2000. However, the vegetation recovery has been rather minimal and did not reach the level of cover observed during the 1979 time period. In addition, the advantages and some limitations of using remote sensing technologies are discussed in detecting vegetation change in this setting and potential application to other recreation settings.

Topography-mediated controls on local vegetation phenology estimated from MODIS vegetation index

Treesearch

Taehee Hwang; Conghe Song; James Vose; Lawrence Band

2011-01-01

Forest canopy phenology is an important constraint on annual water and carbon budgets, and responds to regional interannual climate variation. In steep terrain, there are complex spatial variations in phenology due to topographic influences on microclimate, community composition, and available soil moisture. In this study, we investigate spatial patterns of phenology...

Changes in Species Diversity Patterns and Spatial Heterogeneity during the Secondary Succession of Grassland Vegetation on the Loess Plateau, China.

PubMed

Sun, Caili; Chai, Zongzheng; Liu, Guobin; Xue, Sha

2017-01-01

Analyzing the dynamic patterns of species diversity and spatial heterogeneity of vegetation in grasslands during secondary succession could help with the maintenance and management of these ecosystems. Here, we evaluated the influence of secondary succession on grassland plant diversity and spatial heterogeneity of abandoned croplands on the Loess Plateau (China) during four phases of recovery: 1-5, 5-10, 10-20, and 20-30 years. The species composition and dominance of the grassland vegetation changed markedly during secondary succession and formed a clear successional series, with the species assemblage dominated by Artemisia capillaris → Heteropappus altaicus→ A. sacrorum . The diversity pattern was one of low-high-low, with diversity peaking in the 10-20 year phase, thus corresponding to a hump-backed model in which maximum diversity occurring at the intermediate stages. A spatially aggregated pattern prevailed throughout the entire period of grassland recovery; this was likely linked to the dispersal properties of herbaceous plants and to high habitat heterogeneity. We conclude that natural succession was conducive to the successful recovery of native vegetation. From a management perspective, native pioneer tree species should be introduced about 20 years after abandoning croplands to accelerate the natural succession of grassland vegetation.

Changes in Species Diversity Patterns and Spatial Heterogeneity during the Secondary Succession of Grassland Vegetation on the Loess Plateau, China

PubMed Central

Sun, Caili; Chai, Zongzheng; Liu, Guobin; Xue, Sha

2017-01-01

Analyzing the dynamic patterns of species diversity and spatial heterogeneity of vegetation in grasslands during secondary succession could help with the maintenance and management of these ecosystems. Here, we evaluated the influence of secondary succession on grassland plant diversity and spatial heterogeneity of abandoned croplands on the Loess Plateau (China) during four phases of recovery: 1–5, 5–10, 10–20, and 20–30 years. The species composition and dominance of the grassland vegetation changed markedly during secondary succession and formed a clear successional series, with the species assemblage dominated by Artemisia capillaris→ Heteropappus altaicus→ A. sacrorum. The diversity pattern was one of low–high–low, with diversity peaking in the 10–20 year phase, thus corresponding to a hump-backed model in which maximum diversity occurring at the intermediate stages. A spatially aggregated pattern prevailed throughout the entire period of grassland recovery; this was likely linked to the dispersal properties of herbaceous plants and to high habitat heterogeneity. We conclude that natural succession was conducive to the successful recovery of native vegetation. From a management perspective, native pioneer tree species should be introduced about 20 years after abandoning croplands to accelerate the natural succession of grassland vegetation. PMID:28900433

Climate-biomes, pedo-biomes and pyro-biomes: which world view explains the tropical forest - savanna boundary in South America?

NASA Astrophysics Data System (ADS)

Langan, Liam; Higgins, Steven; Scheiter, Simon

2015-04-01

Elucidating the drivers of broad vegetation formations improves our understanding of earth system functioning. The biome, defined primarily by the dominance of a particular growth strategy, is commonly employed to group vegetation into similar units. Predicting tropical forest and savanna biome boundaries in South America has proven difficult. Process based DGVMs (Dynamic global vegetation models) are our best tool to simulate vegetation patterns, make predictions for future changes and test theory, however, many DGVMs fail to accurately simulate the spatial distribution or indeed presence of the South American savanna biome which can result in large differences in modelled ecosystem structural properties. Evidence suggests fire plays a significant role in mediating these forest and savanna biome boundaries, however, fire alone does not appear to be sufficient to predict these boundaries in South America using DGVMs hinting at the presence of one or more missing environmental factors. We hypothesise that soil depth, which affects plant available water by determining maximum storage potential and influences temporal availability, may be one of these missing environmental factors. To test our hypothesis we use a novel vegetation model, the aDGVM2. This model has been specifically designed to allow plant trait strategies, constrained by trade-offs between traits, evolve based on the abiotic and biotic conditions where the resulting community trait suites are emergent properties of model dynamics. Furthermore it considers root biomass in multiple soil layers and therefore allows the consideration of alternative rooting strategies, which in turn allows us to explore in more detail the role of soil hydraulic factors in controlling biome boundary distributions. We find that changes in soil depth, interacting with fire, affect the relative dominance of tree and grass strategies and thus the presence and spatial distribution of forest and savanna biomes in South America. Using the ISRIC-WISE soil depth dataset we show that applying spatially variable soil depth, in contrast to globally fixed soil depth, improves the accuracy with which we predict the South American savanna biome distribution when compared to multiple contemporary biome maps and that the emergence of the savanna biome results in markedly different ecosystem structural properties such as tree height, tree cover and above ground biomass. Many of these areas are capable of supporting forest and savanna biome states and have been deemed bi-stable areas, we show that, in these bi-stable areas the emergent tree community trait suite differs markedly between forest and savanna biome states.

Agriculture, forestry, range, and soils, chapter 2, part C

NASA Technical Reports Server (NTRS)

1975-01-01

The feasibility of using microwave systems in agriculture, forestry, range, and soil moisture measurements was studied. Theory and preliminary results show the feasibility of measuring moisture status in the soil. For vegetational resources, crop identification for inventory and for yield and production estimates is most feasible. Apart from moisture- and water-related phenomena, microwave systems are also used to record structural and spatial data related to crops and forests.

Identifying and Prioritizing Greater Sage-Grouse Nesting and Brood-Rearing Habitat for Conservation in Human-Modified Landscapes

PubMed Central

Dzialak, Matthew R.; Olson, Chad V.; Harju, Seth M.; Webb, Stephen L.; Mudd, James P.; Winstead, Jeffrey B.; Hayden-Wing, L.D.

2011-01-01

Background Balancing animal conservation and human use of the landscape is an ongoing scientific and practical challenge throughout the world. We investigated reproductive success in female greater sage-grouse (Centrocercus urophasianus) relative to seasonal patterns of resource selection, with the larger goal of developing a spatially-explicit framework for managing human activity and sage-grouse conservation at the landscape level. Methodology/Principal Findings We integrated field-observation, Global Positioning Systems telemetry, and statistical modeling to quantify the spatial pattern of occurrence and risk during nesting and brood-rearing. We linked occurrence and risk models to provide spatially-explicit indices of habitat-performance relationships. As part of the analysis, we offer novel biological information on resource selection during egg-laying, incubation, and night. The spatial pattern of occurrence during all reproductive phases was driven largely by selection or avoidance of terrain features and vegetation, with little variation explained by anthropogenic features. Specifically, sage-grouse consistently avoided rough terrain, selected for moderate shrub cover at the patch level (within 90 m2), and selected for mesic habitat in mid and late brood-rearing phases. In contrast, risk of nest and brood failure was structured by proximity to anthropogenic features including natural gas wells and human-created mesic areas, as well as vegetation features such as shrub cover. Conclusions/Significance Risk in this and perhaps other human-modified landscapes is a top-down (i.e., human-mediated) process that would most effectively be minimized by developing a better understanding of specific mechanisms (e.g., predator subsidization) driving observed patterns, and using habitat-performance indices such as those developed herein for spatially-explicit guidance of conservation intervention. Working under the hypothesis that industrial activity structures risk by enhancing predator abundance or effectiveness, we offer specific recommendations for maintaining high-performance habitat and reducing low-performance habitat, particularly relative to the nesting phase, by managing key high-risk anthropogenic features such as industrial infrastructure and water developments. PMID:22022587

Relationships between aquatic vegetation and water turbidity: A field survey across seasons and spatial scales

PubMed Central

Austin, Åsa N.; Hansen, Joakim P.; Donadi, Serena; Eklöf, Johan S.

2017-01-01

Field surveys often show that high water turbidity limits cover of aquatic vegetation, while many small-scale experiments show that vegetation can reduce turbidity by decreasing water flow, stabilizing sediments, and competing with phytoplankton for nutrients. Here we bridged these two views by exploring the direction and strength of causal relationships between aquatic vegetation and turbidity across seasons (spring and late summer) and spatial scales (local and regional), using causal modeling based on data from a field survey along the central Swedish Baltic Sea coast. The two best-fitting regional-scale models both suggested that in spring, high cover of vegetation reduces water turbidity. In summer, the relationships differed between the two models; in the first model high vegetation cover reduced turbidity; while in the second model reduction of summer turbidity by high vegetation cover in spring had a positive effect on summer vegetation which suggests a positive feedback of vegetation on itself. Nitrogen load had a positive effect on turbidity in both seasons, which was comparable in strength to the effect of vegetation on turbidity. To assess whether the effect of vegetation was primarily caused by sediment stabilization or a reduction of phytoplankton, we also tested models where turbidity was replaced by phytoplankton fluorescence or sediment-driven turbidity. The best-fitting regional-scale models suggested that high sediment-driven turbidity in spring reduces vegetation cover in summer, which in turn has a negative effect on sediment-driven turbidity in summer, indicating a potential positive feedback of sediment-driven turbidity on itself. Using data at the local scale, few relationships were significant, likely due to the influence of unmeasured variables and/or spatial heterogeneity. In summary, causal modeling based on data from a large-scale field survey suggested that aquatic vegetation can reduce turbidity at regional scales, and that high vegetation cover vs. high sediment-driven turbidity may represent two self-enhancing, alternative states of shallow bay ecosystems. PMID:28854185

Relationships between aquatic vegetation and water turbidity: A field survey across seasons and spatial scales.

PubMed

Austin, Åsa N; Hansen, Joakim P; Donadi, Serena; Eklöf, Johan S

2017-01-01

Field surveys often show that high water turbidity limits cover of aquatic vegetation, while many small-scale experiments show that vegetation can reduce turbidity by decreasing water flow, stabilizing sediments, and competing with phytoplankton for nutrients. Here we bridged these two views by exploring the direction and strength of causal relationships between aquatic vegetation and turbidity across seasons (spring and late summer) and spatial scales (local and regional), using causal modeling based on data from a field survey along the central Swedish Baltic Sea coast. The two best-fitting regional-scale models both suggested that in spring, high cover of vegetation reduces water turbidity. In summer, the relationships differed between the two models; in the first model high vegetation cover reduced turbidity; while in the second model reduction of summer turbidity by high vegetation cover in spring had a positive effect on summer vegetation which suggests a positive feedback of vegetation on itself. Nitrogen load had a positive effect on turbidity in both seasons, which was comparable in strength to the effect of vegetation on turbidity. To assess whether the effect of vegetation was primarily caused by sediment stabilization or a reduction of phytoplankton, we also tested models where turbidity was replaced by phytoplankton fluorescence or sediment-driven turbidity. The best-fitting regional-scale models suggested that high sediment-driven turbidity in spring reduces vegetation cover in summer, which in turn has a negative effect on sediment-driven turbidity in summer, indicating a potential positive feedback of sediment-driven turbidity on itself. Using data at the local scale, few relationships were significant, likely due to the influence of unmeasured variables and/or spatial heterogeneity. In summary, causal modeling based on data from a large-scale field survey suggested that aquatic vegetation can reduce turbidity at regional scales, and that high vegetation cover vs. high sediment-driven turbidity may represent two self-enhancing, alternative states of shallow bay ecosystems.

Development of indicators of vegetation recovery based on time series analysis of SPOT Vegetation data

NASA Astrophysics Data System (ADS)

Lhermitte, S.; Tips, M.; Verbesselt, J.; Jonckheere, I.; Van Aardt, J.; Coppin, Pol

2005-10-01

Large-scale wild fires have direct impacts on natural ecosystems and play a major role in the vegetation ecology and carbon budget. Accurate methods for describing post-fire development of vegetation are therefore essential for the understanding and monitoring of terrestrial ecosystems. Time series analysis of satellite imagery offers the potential to quantify these parameters with spatial and temporal accuracy. Current research focuses on the potential of time series analysis of SPOT Vegetation S10 data (1999-2001) to quantify the vegetation recovery of large-scale burns detected in the framework of GBA2000. The objective of this study was to provide quantitative estimates of the spatio-temporal variation of vegetation recovery based on remote sensing indicators. Southern Africa was used as a pilot study area, given the availability of ground and satellite data. An automated technique was developed to extract consistent indicators of vegetation recovery from the SPOT-VGT time series. Reference areas were used to quantify the vegetation regrowth by means of Regeneration Indices (RI). Two kinds of recovery indicators (time and value- based) were tested for RI's of NDVI, SR, SAVI, NDWI, and pure band information. The effects of vegetation structure and temporal fire regime features on the recovery indicators were subsequently analyzed. Statistical analyses were conducted to assess whether the recovery indicators were different for different vegetation types and dependent on timing of the burning season. Results highlighted the importance of appropriate reference areas and the importance of correct normalization of the SPOT-VGT data.

Large scale pre-rain vegetation green up across Africa.

PubMed

Adole, Tracy; Dash, Jadunandan; Atkinson, Peter M

2018-05-16

Information on the response of vegetation to different environmental drivers, including rainfall, forms a critical input to ecosystem models. Currently, such models are run based on parameters that, in some cases, are either assumed or lack supporting evidence (e.g., that vegetation growth across Africa is rainfall-driven). A limited number of studies have reported that the onset of rain across Africa does not fully explain the onset of vegetation growth, for example, drawing on the observation of pre-rain flush effects in some parts of Africa. The spatial extent of this pre-rain green-up effect, however, remains unknown, leaving a large gap in our understanding that may bias ecosystem modelling. This paper provides the most comprehensive spatial assessment to-date of the magnitude and frequency of the different patterns of phenology response to rainfall across Africa, and for different vegetation types. To define the relations between phenology and rainfall, we investigated the spatial variation in the difference, in number of days, between the start of rainy season (SRS) and start of vegetation growing season (SOS); and between the end of rainy season (ERS) and end of vegetation growing season (EOS). We reveal a much more extensive spread of pre-rain green-up over Africa than previously reported, with pre-rain green-up being the norm rather than the exception. We also show the relative sparsity of post-rain green-up, confined largely to the Sudano-Sahel region. While the pre-rain green-up phenomenon is well documented, its large spatial extent was not anticipated. Our results, thus, contrast with the widely held view that rainfall drives the onset and end of the vegetation growing season across Africa. Our findings point to a much more nuanced role of rainfall in Africa's vegetation growth cycle than previously thought, specifically as one of a set of several drivers, with important implications for ecosystem modelling. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Severity of climate change dictates the direction of biophysical feedbacks of vegetation change to Arctic climate

NASA Astrophysics Data System (ADS)

Zhang, Wenxin; Jansson, Christer; Miller, Paul; Smith, Ben; Samuelsson, Patrick

2014-05-01

Vegetation-climate feedbacks induced by vegetation dynamics under climate change alter biophysical properties of the land surface that regulate energy and water exchange with the atmosphere. Simulations with Earth System Models applied at global scale suggest that the current warming in the Arctic has been amplified, with large contributions from positive feedbacks, dominated by the effect of reduced surface albedo as an increased distribution, cover and taller stature of trees and shrubs mask underlying snow, darkening the surface. However, these models generally employ simplified representation of vegetation dynamics and structure and a coarse grid resolution, overlooking local or regional scale details determined by diverse vegetation composition and landscape heterogeneity. In this study, we perform simulations using an advanced regional coupled vegetation-climate model (RCA-GUESS) applied at high resolution (0.44×0.44° ) over the Arctic Coordinated Regional Climate Downscaling Experiment (CORDEX-Arctic) domain. The climate component (RCA4) is forced with lateral boundary conditions from EC-EARTH CMIP5 simulations for three representative concentration pathways (RCP 2.6, 4.5, 8.5). Vegetation-climate response is simulated by the individual-based dynamic vegetation model (LPJ-GUESS), accounting for phenology, physiology, demography and resource competition of individual-based vegetation, and feeding variations of leaf area index and vegetative cover fraction back to the climate component, thereby adjusting surface properties and surface energy fluxes. The simulated 2m air temperature, precipitation, vegetation distribution and carbon budget for the present period has been evaluated in another paper. The purpose of this study is to elucidate the spatial and temporal characteristics of the biophysical feedbacks arising from vegetation shifts in response to different CO2 concentration pathways and their associated climate change. Our results indicate that the albedo feedback dominates simulated warming in spring in all three scenarios, while in summer, evapotranspiration feedback, governing the partitioning of the return energy flux from the surface to the atmosphere into latent and sensible heat, exerts evaporative cooling effects, the magnitude of which depends on the severity of climate change, in turn driven by the underlying GHG emissions pathway, resulting in shift in the sign of net biophysical at higher levels of warming. Spatially, western Siberia is identified as the most susceptible location, experiencing the potential to reverse biophysical feedbacks in all seasons. We further analyze how the pattern of vegetation shifts triggers different signs of net effects of biophysical feedbacks.

Soil erosion and sediment yield and their relationships with vegetation cover in upper stream of the Yellow River.

PubMed

Ouyang, Wei; Hao, Fanghua; Skidmore, Andrew K; Toxopeus, A G

2010-12-15

Soil erosion is a significant concern when considering regional environmental protection, especially in the Yellow River Basin in China. This study evaluated the temporal-spatial interaction of land cover status with soil erosion characteristics in the Longliu Catchment of China, using the Soil and Water Assessment Tool (SWAT) model. SWAT is a physical hydrological model which uses the RUSLE equation as a sediment algorithm. Considering the spatial and temporal scale of the relationship between soil erosion and sediment yield, simulations were undertaken at monthly and annual temporal scales and basin and sub-basin spatial scales. The corresponding temporal and spatial Normalized Difference Vegetation Index (NDVI) information was summarized from MODIS data, which can integrate regional land cover and climatic features. The SWAT simulation revealed that the annual soil erosion and sediment yield showed similar spatial distribution patterns, but the monthly variation fluctuated significantly. The monthly basin soil erosion varied from almost no erosion load to 3.92 t/ha and the maximum monthly sediment yield was 47,540 tones. The inter-annual simulation focused on the spatial difference and relationship with the corresponding vegetation NDVI value for every sub-basin. It is concluded that, for this continental monsoon climate basin, the higher NDVI vegetation zones prevented sediment transport, but at the same time they also contributed considerable soil erosion. The monthly basin soil erosion and sediment yield both correlated with NDVI, and the determination coefficients of their exponential correlation model were 0.446 and 0.426, respectively. The relationships between soil erosion and sediment yield with vegetation NDVI indicated that the vegetation status has a significant impact on sediment formation and transport. The findings can be used to develop soil erosion conservation programs for the study area. Copyright © 2010 Elsevier B.V. All rights reserved.

Vegetation spatial variability and its effect on vegetation indices

NASA Technical Reports Server (NTRS)

Ormsby, J. P.; Choudhury, B. J.; Owe, M.

1987-01-01

Landsat MSS data were used to simulate low resolution satellite data, such as NOAA AVHRR, to quantify the fractional vegetation cover within a pixel and relate the fractional cover to the normalized difference vegetation index (NDVI) and the simple ratio (SR). The MSS data were converted to radiances from which the NDVI and SR values for the simulated pixels were determined. Each simulated pixel was divided into clusters using an unsupervised classification program. Spatial and spectral analysis provided a means of combining clusters representing similar surface characteristics into vegetated and non-vegetated areas. Analysis showed an average error of 12.7 per cent in determining these areas. NDVI values less than 0.3 represented fractional vegetated areas of 5 per cent or less, while a value of 0.7 or higher represented fractional vegetated areas greater than 80 per cent. Regression analysis showed a strong linear relation between fractional vegetation area and the NDVI and SR values; correlation values were 0.89 and 0.95 respectively. The range of NDVI values calculated from the MSS data agrees well with field studies.

Using the Gravity Model to Estimate the Spatial Spread of Vector-Borne Diseases

PubMed Central

Barrios, José Miguel; Verstraeten, Willem W.; Maes, Piet; Aerts, Jean-Marie; Farifteh, Jamshid; Coppin, Pol

2012-01-01

The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the physical habitat of pathogens’ vectors and/or hosts, and urban areas, thus humans. This study implements the concept behind gravity models in the spatial spread of two vector-borne diseases, nephropathia epidemica and Lyme borreliosis, based on current knowledge on the transmission mechanism of these diseases. Two sources of information on vegetated systems were tested: the CORINE land cover map and MODIS NDVI. The size of vegetated areas near urban centers and a local indicator of occupation-related exposure were found significant predictors of disease risk. Both the land cover map and the space-borne dataset were suited yet not equivalent input sources to locate and measure vegetated areas of importance for disease spread. The overall results point at the compatibility of the gravity model concept and the spatial spread of vector-borne diseases. PMID:23202882

Using the gravity model to estimate the spatial spread of vector-borne diseases.

PubMed

Barrios, José Miguel; Verstraeten, Willem W; Maes, Piet; Aerts, Jean-Marie; Farifteh, Jamshid; Coppin, Pol

2012-11-30

The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the physical habitat of pathogens’ vectors and/or hosts, and urban areas, thus humans. This study implements the concept behind gravity models in the spatial spread of two vector-borne diseases, nephropathia epidemica and Lyme borreliosis, based on current knowledge on the transmission mechanism of these diseases. Two sources of information on vegetated systems were tested: the CORINE land cover map and MODIS NDVI. The size of vegetated areas near urban centers and a local indicator of occupation-related exposure were found significant predictors of disease risk. Both the land cover map and the space-borne dataset were suited yet not equivalent input sources to locate and measure vegetated areas of importance for disease spread. The overall results point at the compatibility of the gravity model concept and the spatial spread of vector-borne diseases.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).

PubMed

Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PubMed Central

Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858

Integration of airborne optical and thermal imagery for archaeological subsurface structures detection: the Arpi case study (Italy)

NASA Astrophysics Data System (ADS)

Bassani, C.; Cavalli, R. M.; Fasulli, L.; Palombo, A.; Pascucci, S.; Santini, F.; Pignatti, S.

2009-04-01

The application of Remote Sensing data for detecting subsurface structures is becoming a remarkable tool for the archaeological observations to be combined with the near surface geophysics [1, 2]. As matter of fact, different satellite and airborne sensors have been used for archaeological applications, such as the identification of spectral anomalies (i.e. marks) related to the buried remnants within archaeological sites, and the management and protection of archaeological sites [3, 5]. The dominant factors that affect the spectral detectability of marks related to manmade archaeological structures are: (1) the spectral contrast between the target and background materials, (2) the proportion of the target on the surface (relative to the background), (3) the imaging system characteristics being used (i.e. bands, instrument noise and pixel size), and (4) the conditions under which the surface is being imaged (i.e. illumination and atmospheric conditions) [4]. In this context, just few airborne hyperspectral sensors were applied for cultural heritage studies, among them the AVIRIS (Airborne Visible/Infrared Imaging Spectrometer), the CASI (Compact Airborne Spectrographic Imager), the HyMAP (Hyperspectral MAPping) and the MIVIS (Multispectral Infrared and Visible Imaging Spectrometer). Therefore, the application of high spatial/spectral resolution imagery arise the question on which is the trade off between high spectral and spatial resolution imagery for archaeological applications and which spectral region is optimal for the detection of subsurface structures. This paper points out the most suitable spectral information useful to evaluate the image capability in terms of spectral anomaly detection of subsurface archaeological structures in different land cover contexts. In this study, we assess the capability of MIVIS and CASI reflectances and of ATM and MIVIS emissivities (Table 1) for subsurface archaeological prospection in different sites of the Arpi archaeological area (southern Italy). We identify, for the selected sites, three main land cover overlying the buried structures: (a) photosynthetic (i.e. green low vegetation), (b) non-photosynthetic vegetation (i.e. yellow, dry low vegetation), and (c) dry bare soil. Afterwards, we analyse the spectral regions showing an inherent potential for the archaeological detection as a function of the land cover characteristics. The classified land cover units have been used in a spectral mixture analysis to assess the land cover fractional abundance surfacing the buried structures (i.e. mark-background system). The classification and unmixing results for the CASI, MIVIS and ATM remote sensing data processing showed a good accordance both in the land cover units and in the subsurface structures identification. The integrated analysis of the unmixing results for the three sensors allowed us to establish that for the land cover characterized by green and dry vegetation (occurrence higher than 75%), the visible and near infrared (VNIR) spectral regions better enhance the buried man-made structures. In particular, if the structures are covered by more than 75% of vegetation the two most promising wavelengths for their detection are the chlorophyll peak at 0.56 m (Visible region) and the red edge region (0.67 to 0.72 m; NIR region). This result confirms that the variation induced by the subsurface structures (e.g., stone walls, tile concentrations, pavements near the surface, road networks) to the natural vegetation growth and/or colour (i.e., for different stress factors) is primarily detectable by the chlorophyll peak and the red edge region applied for the vegetation stress detection. Whereas, if dry soils cover the structures (occurrence higher than 75%), both the VNIR and thermal infrared (TIR) regions are suitable to detect the subsurface structures. This work demonstrates that airborne reflectances and emissivities data, even though at different spatial/spectral resolutions and acquisition time represent an effective and rapid tool to detect subsurface structures within different land cover contexts. As concluding results, this study reveals that the airborne multi/hyperspectral image processing can be an effective and cost-efficient tool to perform a preliminary analysis of those areas where large cultural heritage assets prioritising and localizing the sites where to apply near surface geophysics surveys. Spectral Region Spectral Resolution ( m )Spectral Range ( m) Spatial Resolution (m)IFOV (deg) ATM VIS-NIR SWIR-TIR (tot 12 ch) variable from 24 to 3100 0.42 - 1150 2 0.143 CASI VNIR (48 ch.) 0.01 0.40-0.94 2 0.115 MIVIS VNIR (28ch.) 0.02 (VIS) 0.05 (NIR) 0.43-0.83 (VIS) 1.15-1.55 (NIR) 6 - 7 0.115 SWIR (64ch.) 0.09 1.983-2.478 TIR (10ch.) 0.34-0.54 8.180-12.700 Table 1. Characteristics of airborne sensors used for the Arpi test area. 1 References 2 [1] Beck, A., Philip, G., Abdulkarim, M. and Donoghue, D., 2007. Evaluation of Corona and Ikonos high resolution satellite imagery for archaeological prospection in western Syria. Antiquity, 81: 161-175. 3 [2] Altaweel, M., 2005. The Use of ASTER Satellite Imagery in Archaeological Contexts. Archaeological Prospection, 12: 151- 166. 4 [3] Cavalli, R.M.; Colosi, F.; Palombo, A.; Pignatti, S.; Poscolieri, M. Remote hyperspectral imagery as a support to archaeological prospection. J. of Cultural Heritage 2007, 8, 272-283. 5 [4] Kucukkaya, A.G. Photogrammetry and remote sensing in archaeology. J. Quant. Spectrosc. Radiat. Transfer 2004, 97(1-3), 83-97. [5] Rowlands, A.; Sarris, A. Detection of exposed and subsurface archaeological remains using multi-sensor remote sensing. J. of Archaeological Science 2007, 34, 795-803.

Measurement of Ecosystem Metabolism across Climatic and Vegetation Gradients in California

NASA Astrophysics Data System (ADS)

DuBois, S.; Serbin, S.; Desai, A. R.; Kruger, E.; Kingdon, C.; Goulden, M.; Townsend, P. A.

2013-12-01

Terrestrial ecosystem models require information on vegetation structure, phenology, demographics, biochemistry, radiation properties, and physiology in order to accurately simulate the responses of ecosystem functioning to global change and disturbances. These models generally depend on a small number of intensive, fine-scaled point-based measurements from eddy covariance towers, detailed vegetation surveys, literature values, and site-scale data assimilation techniques to improve model calibration. However, the limited geographic and/or temporal scope of measurements can lead to inadequate model generalizations of modeled carbon (C), water, and energy fluxes across broad regions and relevant time periods. Remote sensing approaches, particularly imaging spectroscopy (IS) and thermal infrared (TIR) data, have the potential to provide the broad-scale spatial and temporal dynamics in many important vegetation properties related to ecosystem functioning. As part of the ongoing NASA HyspIRI Airborne Campaign (http://hyspiri.jpl.nasa.gov/airborne) we are assessing the potential of IS+TIR to generate spatially explicit estimates of two important parameters characterizing plant photosynthetic capacity: the maximum rate of CO2 carboxylation by RuBisCo (Vcmax), and the maximum rate of electron transport required for the regeneration of RuBP needed in Calvin Cycle processes (Jmax). These estimates are based on recent evidence that both properties can be predicted at the leaf level using spectroscopy techniques (Ainsworth et al. 2013 [http://tinyurl.com/n5xnzjg]; Serbin et al. 2012 [http://tinyurl.com/mhocmlz]). It follows that estimation of these variables from remotely sensed IS+TIR (i.e. AVIRIS & MASTER) could facilitate the prediction of seasonal C assimilation across large areas using data from the anticipated HyspIRI satellite mission. Our research focuses on two climate-elevation transects in California, which span a vegetation gradient from coastal sage and chaparral to oak woodlands and closed-canopy coniferous forests, as well as agro-ecosystems located throughout the Central and Imperial Valleys. We are also comparing remotely sensed estimates of ecosystem photosynthetic capacity with C flux data from a series of 10 eddy covariance towers. Results from the 2013 field season highlight the large range in sampled vegetation structure, optical properties (i.e. reflectance and transmittance) and physiology (i.e. Vcmax, Jmax, and cholorphyll fluorescence). Using approaches similar to Serbin et al. (2012) we have confirmed the ability of spectroscopy to estimate Vcmax and Jmax across these diverse and structurally complex vegetation types. Ecosystem products, such as gross primary productivity, estimated from flux towers highlight the relationship between climatic parameters and vegetation productivity. Multiple data-years allow this relationship to be examined under various climatic forcings including drought and heat stress. Based on these preliminary results, our next step is to scale leaf-level information to AVIRIS footprints using radiative transfer and statistical modeling approaches with ecosystem modeling in order to assess the IS data products against flux tower observations.

Topography and vegetation as predictors of snow water equivalent across the alpine treeline ecotone at Lee Ridge, Glacier National Park, Montana, U.S.A.

USGS Publications Warehouse

Geddes, C.A.; Brown, D.G.; Fagre, D.B.

2005-01-01

We derived and implemented two spatial models of May snow water equivalent (SWE) at Lee Ridge in Glacier National Park, Montana. We used the models to test the hypothesis that vegetation structure is a control on snow redistribution at the alpine treeline ecotone (ATE). The statistical models were derived using stepwise and "best" subsets regression techniques. The first model was derived from field measurements of SWE, topography, and vegetation taken at 27 sample points. The second model was derived using GIS-based measures of topography and vegetation. Both the field- (R² = 0.93) and GIS-based models (R² = 0.69) of May SWE included the following variables: site type (based on vegetation), elevation, maximum slope, and general slope aspect. Site type was identified as the most important predictor of SWE in both models, accounting for 74.0% and 29.5% of the variation, respectively. The GIS-based model was applied to create a predictive map of SWE across Lee Ridge, predicting little snow accumulation on the top of the ridge where vegetation is scarce. The GIS model failed in large depressions, including ephemeral stream channels. The models supported the hypothesis that upright vegetation has a positive effect on accumulation of SWE above and beyond the effects of topography. Vegetation, therefore, creates a positive feedback in which it modifies its, environment and could affect the ability of additional vegetation to become established.

Validating LiDAR Derived Estimates of Canopy Height, Structure and Fractional Cover in Riparian Areas: A Comparison of Leaf-on and Leaf-off LiDAR Data

NASA Astrophysics Data System (ADS)

Wasser, L. A.; Chasmer, L. E.; Taylor, A.; Day, R.

2010-12-01

Characterization of riparian buffers is integral to understanding the landscape scale impacts of disturbance on wildlife and aquatic ecosystems. Riparian buffers may be characterized using in situ plot sampling or via high resolution remote sensing. Field measurements are time-consuming and may not cover a broad range of ecosystem types. Further, spectral remote sensing methods introduce a compromise between spatial resolution (grain) and area extent. Airborne LiDAR can be used to continuously map and characterize riparian vegetation structure and composition due to the three-dimensional reflectance of laser pulses within and below the canopy, understory and at the ground surface. The distance between reflections (or ‘returns’) allows for detection of narrow buffer corridors at the landscape scale. There is a need to compare leaf-off and leaf-on surveyed LiDAR data with in situ measurements to assess accuracy in landscape scale analysis. These comparisons are particularly important considering increased availability of leaf-off surveyed LiDAR datasets. And given this increased availability, differences between leaf-on and leaf-off derived LiDAR metrics are largely unknown for riparian vegetation of varying composition and structure. This study compares the effectiveness of leaf-on and leaf-off LiDAR in characterizing riparian buffers of varying structure and composition as compared to field measurements. Field measurements were used to validate LiDAR derived metrics. Vegetation height, canopy cover, density and overstory and understory species composition were recorded in 80 random plots of varying vegetation type, density and structure within a Pennsylvania watershed (-77.841, 40.818). Plot data were compared with LiDAR data collected during leaf on and leaf off conditions to determine 1) accuracy of LiDAR derived metrics compared to field measures and 2) differences between leaf-on and leaf-off LiDAR metrics. Results illustrate that differences exist between metrics derived from leaf on and leaf-off surveyed LiDAR. There is greater variability between the two datasets within taller deciduous and mixed (conifer and deciduous) vegetation compared to shorter deciduous and mixed vegetation. Differences decrease as stand density increases for both mixed and deciduous forests. LiDAR derived canopy height is more sensitive to understory vegetation as stand density decreases making measurement of understory vegetation in the field important in the validation process. Finally, while leaf-on LiDAR is often preferred for vegetation analysis, results suggest that leaf-off LiDAR may be sufficient to categorize vegetation into height classes to be used for landscape scale habitat models.

Uav Photogrammetry for Mapping and Monitoring of Northern Permafrost Landscapes

NASA Astrophysics Data System (ADS)

Fraser, R. H.; Olthof, I.; Maloley, M.; Fernandes, R.; Prevost, C.; van der Sluijs, J.

2015-08-01

Northern environments are changing in response to recent climate warming, resource development, and natural disturbances. The Arctic climate has warmed by 2-3°C since the 1950's, causing a range of cryospheric changes including declines in sea ice extent, snow cover duration, and glacier mass, and warming permafrost. The terrestrial Arctic has also undergone significant temperature-driven changes in the form of increased thermokarst, larger tundra fires, and enhanced shrub growth. Monitoring these changes to inform land managers and decision makers is challenging due to the vast spatial extents involved and difficult access. Environmental monitoring in Canada's North is often based on local-scale measurements derived from aerial reconnaissance and photography, and ecological, hydrologic, and geologic sampling and surveying. Satellite remote sensing can provide a complementary tool for more spatially comprehensive monitoring but at coarser spatial resolutions. Satellite remote sensing has been used to map Arctic landscape changes related to vegetation productivity, lake expansion and drainage, glacier retreat, thermokarst, and wildfire activity. However, a current limitation with existing satellite-based techniques is the measurement gap between field measurements and high resolution satellite imagery. Bridging this gap is important for scaling up field measurements to landscape levels, and validating and calibrating satellite-based analyses. This gap can be filled to a certain extent using helicopter or fixed-wing aerial surveys, but at a cost that is often prohibitive. Unmanned aerial vehicle (UAV) technology has only recently progressed to the point where it can provide an inexpensive and efficient means of capturing imagery at this middle scale of measurement with detail that is adequate to interpret Arctic vegetation (i.e. 1-5 cm) and coverage that can be directly related to satellite imagery (1-10 km2). Unlike satellite measurements, UAVs permit frequent surveys (e.g. for monitoring vegetation phenology, fires, and hydrology), are not constrained by repeat cycle or cloud cover, can be rapidly deployed following a significant event, and are better suited than manned aircraft for mapping small areas. UAVs are becoming more common for agriculture, law enforcement, and marketing, but their use in the Arctic is still rare and represents untapped technology for northern mapping, monitoring, and environmental research. We are conducting surveys over a range of sensitive or changing northern landscapes using a variety of UAV multicopter platforms and small sensors. Survey targets include retrogressive thaw slumps, tundra shrub vegetation, recently burned vegetation, road infrastructure, and snow. Working with scientific partners involved in northern monitoring programs (NWT CIMP, CHARS, NASA ABOVE, NRCan-GSC) we are investigating the advantages, challenges, and best practices for acquiring high resolution imagery from multicopters to create detailed orthomosaics and co-registered 3D terrain models. Colour and multispectral orthomosaics are being integrated with field measurements and satellite imagery to conduct spatial scaling of environmental parameters. Highly detailed digital terrain models derived using structure from motion (SfM) photogrammetry are being applied to measure thaw slump morphology and change, snow depth, tundra vegetation structure, and surface condition of road infrastructure. These surveys and monitoring applications demonstrate that UAV-based photogrammetry is poised to make a rapid contribution to a wide range of northern monitoring and research applications.

Localized extinction of an arboreal desert lizard caused by habitat fragmentation

USGS Publications Warehouse

Munguia-Vega, Adrian; Rodriguez-Estrella, Ricardo; Shaw, William W.; Culver, Melanie

2013-01-01

We adopted a species’ perspective for predicting extinction risk in a small, endemic, and strictly scansorial lizard (Urosaurus nigricaudus), in an old (∼60 year) and highly fragmented (8% habitat remaining) agricultural landscape from the Sonoran Desert, Mexico. We genotyped 10 microsatellite loci in 280 individuals from 11 populations in fragmented and continuous habitat. Individual dispersal was restricted to less than 400 m, according to analyses of spatial autocorrelation and spatially explicit Bayesian assignment methods. Within this scale, continuous areas and narrow washes with native vegetation allowed high levels of gene flow over tens of kilometers. In the absence of the native vegetation, cleared areas and highways were identified as partial barriers. In contrast, outside the scale of dispersal, cleared areas behaved as complete barriers, and surveys corroborated the species went extinct after a few decades in all small (less than 45 ha), isolated habitat fragments. No evidence for significant loss of genetic diversity was found, but results suggested fragmentation increased the spatial scale of movements, relatedness, genetic structure, and potentially affected sex-biased dispersal. A plausible threshold of individual dispersal predicted only 23% of all fragments in the landscape were linked with migration from continuous habitat, while complete barriers isolated the majority of fragments. Our study suggested limited dispersal, coupled with an inability to use a homogeneous and hostile matrix without vegetation and shade, could result in frequent time-delayed extinctions of small ectotherms in highly fragmented desert landscapes, particularly considering an increase in the risk of overheating and a decrease in dispersal potential induced by global warming.

Salt lakes of La Mancha (Central Spain): A hot spot for tiger beetle (Carabidae, Cicindelinae) species diversity

PubMed Central

Rodríguez-Flores, Paula C.; Gutiérrez-Rodríguez, Jorge; Aguirre-Ruiz, Ernesto F.; García-París, Mario

2016-01-01

Abstract The tiger beetle assemblage of the wetlands of La Mancha (central Spain) comprises nine species: Calomera littoralis littoralis, Cephalota maura maura, Cephalota circumdata imperialis, Cephalota dulcinea, Cicindela campestris campestris, Cicindela maroccana, Cylindera paludosa, Lophyra flexuosa flexuosa, and Myriochila melancholica melancholica. This assemblage represents the largest concentration of tiger beetles in a single 1º latitude / longitude square in Europe. General patterns of spatial and temporal segregation among species are discussed based on observations of 1462 specimens registered during an observation period of one year, from April to August. The different species of Cicindelini appear to be distributed over space and time, with little overlapping among them. Three sets of species replace each other phenologically as the season goes on. Most of the species occupy drying or dried salt lakes and salt marshes, with sparse vegetation cover. Spatial segregation is marked in terms of substrate and vegetation use. Calomera littoralis and Myriochila melancholica have been observed mainly on wet soils; Cephalota circumdata on dry open saline flats; Cephalota dulcinea and Cylindera paludosa in granulated substrates with typical halophytic vegetation; Cephalota maura is often present in man-modified areas. Cephalota circumdata and Cephalota dulcinea are included as species of special interest in the list of protected species in Castilla–La Mancha. Conservation problems for the Cicindelini assemblage arise from agricultural activities and inadequate use of sport vehicles. Attempts at restoring the original habitat, supressing old semi-industrial structures, may affect the spatial heterogeneity of the lakes, and have an effect on Cicindelinae diversity. PMID:27006617

Scale - dependent effects on the surface energy fluxes modelling in Iberian oak-savanna (dehesa) using the Two-Source Energy Balance (TSEB)

NASA Astrophysics Data System (ADS)

Andreu, Ana; Nieto, Hector; Gómez-Giráldez, Pedro; González-Dugo, Maria P.

2017-04-01

Iberian semi-arid oak-savannas (dehesas) are complex ecosystems where bare soil and different layers of vegetation (grass/scrubs/trees) are distributed following heterogeneous patterns. An assumption of the two source energy balance models is that the effective source/sink for turbulent flux exchange at the surface(canopy/soil) is described by a bulk radiometric surface temperature (TRAD) and resistance. Therefore, the agreement of the TRAD used as an input to these models, with the "bulk" concept (determined by the spatial resolution), will influence the final energy fluxes estimations. The representativeness of the field-ground measurements, the spatial resolution of sensors, the averaging and the up-scaling of TRAD and the ecosystem vegetation parameters, will be crucial for the precision of the results, more than in homogeneous landscapes. The aim of this study is to analyze the scale-effects derived from TSEB application, comparing the observed energy fluxes and the estimated ones obtained from multiple TRAD data sources of different nature: tree/grass/soil ground-based observations, tower footprint, hyperspectral reflectance imagery acquired with an airborne platform, medium (Landsat) and low spatial resolution satellite data (Sentinel 3, MODIS), and how the up-scaling of the vegetation structural characteristics contribute to the discrepancies. The study area selected for this purpose is a dehesa site (Santa Clotilde, Cordoba), which present canopy mosaics (oak, annual grasses and bushes) differing in phenology, physiology and functioning, and bare soil, all of them influencing the turbulent and radiative exchanges.

Integrating satellite remote sensing data and field data to predict rangeland structural indicators at the continental scale

NASA Astrophysics Data System (ADS)

Zhang, J.; Okin, G.

2016-12-01

Rangelands provide a variety of important ecosystem goods and services across drylands globally. They are also the most important emitters of dust across the globe. Field data collection based on points does not represent spatially continuous information about surface variables and, given the vast size of the world's rangelands, cannot cover even a small fraction of their area. Remote sensing is potentially a labor- and time-saving method to observe important rangeland vegetation variables at both temporal and spatial scales. Information on vegetation cover, bare gap size, and plant height provide key rangeland vegetation variables in arid and semiarid rangelands, in part because they strongly impact dust emission and determine wildlife habitat characteristics. This study reports on relationships between remote sensing in the reflected solar spectrum and field measures related to these three variables, and shows how these relationships can be extended to produce spatially and temporally continuous datasets coupled with quantitative estimates of error. Field data for this study included over 3,800 Assessment, Inventory, and Monitoring (AIM) measurements on Bureau of Land Management (BLM) lands throughout the western US. Remote sensing data were derived from MODIS nadir BRDF-adjusted reflectance (NBAR) and Landsat 8 OLI surface reflectance. Normalized bare gap size, total foliar cover, herbaceous cover and herbaceous height exhibit the greatest predictability from remote sensing variables with physically-reasonable relationships between remote sensing variables and field measures. Data fields produced using these relationships across the western US exhibit good agreement with independent high-resolution imagery.

Electrical resistivity surveys to understand vegetation-water interlinkages in a northern latitude headwater catchment

NASA Astrophysics Data System (ADS)

Soulsby, C.; Dick, J.; Tetzlaff, D.; Bradford, J.

2016-12-01

The role of vegetation on the partitioning of precipitation, and the subsequent storage and release of water within the landscape is poorly understood. In particular, the relationship between vegetation and soil moisture is complex and reciprocal. The role of soil moisture as the primary source of water to plants may affect vegetation distribution. In turn, the structure of vegetation canopies may regulate water partitioning into interception, throughfall and steam flow. Such spatial differences in the inputs, together with complex patterns of water uptake from highly distributed root networks can create marked heterogeneity in soil moisture dynamics at small scales. Here, we present a study combining 3D and 2D ERT surveys with soil moisture measurements in a 3.2km upland catchment in the Scottish Highlands to understand influences of different vegetation types on spatio-temporal dynamics in soil moisture. The study focussed on one year of fortnightly ERT surveys to investigate plant-soil-water interactions within the root zone in podzolic soils. Locations were selected in both forest stands of 15m high Scots pine (Pinus sylvestris) and non-forest locations dominated by heather (Calluna vulgaris) shrubs (<0.5m high). These dominant species are typical of forest and non-forest vegetation communities in the Scottish Highlands. Results showed differences in the soil moisture dynamics under the different vegetation types, with heterogeneous patterns in the forested site mainly correlated with canopy cover and mirroring interception losses, with pronounced wetting cycles of the soil surrounding the bole of trees as a consequence of stem flow. Temporal variability in the forested site was greater, probably due to the interception, and increased evapotranspiration losses relative to the heather site, with drying typically being focussed on the areas around the trees, and reflecting the amount of water uptake. Moisture changes in the heather site were fairly heterogeneous are related to micro-topographic affects, lower interception ( 30% compared with 45%) and a smaller microclimatic effect of the canopy which serves to create greater fluctuations in soil moisture. Our results confirm the value in using geophysics to spatially elucidate subsurface plant-soil-water interactions.

Characterizing Climate Controls on Vegetation Seasonality in the North American Southwest

NASA Astrophysics Data System (ADS)

Fish, M. A.; Cook, B.; Smerdon, J. E.; Seager, R.; Williams, P.

2014-12-01

The North American Southwest, which extends from Colorado to southern Mexico and California to eastern Texas, encompasses a diversity of climates, elevations, and ecosystems. This region is expected to experience significant climatic change, and associated impacts, in the coming decades. To better understand the spatiotemporal variability of vegetation in the Southwest and the expected climatic controls on timing and spatial extend of vegetation growth, we compared GIMMS normalized difference vegetation index (NDVI, 1981-2011) against temperature and precipitation data. Spatial variations in vegetation seasonality and the timing of peak NDVI are linked to spatial variability in the precipitation regimes across the Southwest. Regions with spring NDVI peaks are dominated by winter precipitation, while late summer and fall peaks are in regions with significant summer precipitation driven by the North American Monsoon. Inter-annual variability in peak NDVI is positively correlated with precipitation and negatively correlated with temperature, with the largest correlation coefficients at one-month lags. The only significant long-term trends in NDVI are for northern Mexico, where agricultural productivity has been increasing over the last 30 years.

Remote sensing data with the conditional latin hypercube sampling and geostatistical approach to delineate landscape changes induced by large chronological physical disturbances.

PubMed

Lin, Yu-Pin; Chu, Hone-Jay; Wang, Cheng-Long; Yu, Hsiao-Hsuan; Wang, Yung-Chieh

2009-01-01

This study applies variogram analyses of normalized difference vegetation index (NDVI) images derived from SPOT HRV images obtained before and after the ChiChi earthquake in the Chenyulan watershed, Taiwan, as well as images after four large typhoons, to delineate the spatial patterns, spatial structures and spatial variability of landscapes caused by these large disturbances. The conditional Latin hypercube sampling approach was applied to select samples from multiple NDVI images. Kriging and sequential Gaussian simulation with sufficient samples were then used to generate maps of NDVI images. The variography of NDVI image results demonstrate that spatial patterns of disturbed landscapes were successfully delineated by variogram analysis in study areas. The high-magnitude Chi-Chi earthquake created spatial landscape variations in the study area. After the earthquake, the cumulative impacts of typhoons on landscape patterns depended on the magnitudes and paths of typhoons, but were not always evident in the spatiotemporal variability of landscapes in the study area. The statistics and spatial structures of multiple NDVI images were captured by 3,000 samples from 62,500 grids in the NDVI images. Kriging and sequential Gaussian simulation with the 3,000 samples effectively reproduced spatial patterns of NDVI images. However, the proposed approach, which integrates the conditional Latin hypercube sampling approach, variogram, kriging and sequential Gaussian simulation in remotely sensed images, efficiently monitors, samples and maps the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial variability and heterogeneity.

Environmental drivers of spatial patterns of topsoil nitrogen and phosphorus under monsoon conditions in a complex terrain of South Korea

PubMed Central

Choi, Kwanghun; Spohn, Marie; Park, Soo Jin; Huwe, Bernd; Ließ, Mareike

2017-01-01

Nitrogen (N) and phosphorus (P) in topsoils are critical for plant nutrition. Relatively little is known about the spatial patterns of N and P in the organic layer of mountainous landscapes. Therefore, the spatial distributions of N and P in both the organic layer and the A horizon were analyzed using a light detection and ranging (LiDAR) digital elevation model and vegetation metrics. The objective of the study was to analyze the effect of vegetation and topography on the spatial patterns of N and P in a small watershed covered by forest in South Korea. Soil samples were collected using the conditioned latin hypercube method. LiDAR vegetation metrics, the normalized difference vegetation index (NDVI), and terrain parameters were derived as predictors. Spatial explicit predictions of N/P ratios were obtained using a random forest with uncertainty analysis. We tested different strategies of model validation (repeated 2-fold to 20-fold and leave-one-out cross validation). Repeated 10-fold cross validation was selected for model validation due to the comparatively high accuracy and low variance of prediction. Surface curvature was the best predictor of P contents in the organic layer and in the A horizon, while LiDAR vegetation metrics and NDVI were important predictors of N in the organic layer. N/P ratios increased with surface curvature and were higher on the convex upper slope than on the concave lower slope. This was due to P enrichment of the soil on the lower slope and a more even spatial distribution of N. Our digital soil maps showed that the topsoils on the upper slopes contained relatively little P. These findings are critical for understanding N and P dynamics in mountainous ecosystems. PMID:28837590

[Evaluation on environmental quality of heavy metals in soils and vegetables based on geostatistics and GIS].

PubMed

Xie, Zheng-miao; Li, Jing; Wang, Bi-ling; Chen, Jian-jun

2006-10-01

Contents of heavy metals (Pb, Zn, Cd, Cu) in soils and vegetables from Dongguan town in Shangyu city, China were studied using geostatistical analysis and GIS technique to evaluate environmental quality. Based on the evaluation criteria, the distribution of the spatial variability of heavy metals in soil-vegetable system was mapped and analyzed. The results showed that the distribution of soil heavy metals in a large number of soil samples in Dongguan town was asymmetric. The contents of Zn and Cu were lower than those of Cd and Pb. The concentrations distribution of Pb, Zn, Cd and Cu in soils and vegetables were different in spatial variability. There was a close relationship between total and available contents of heavy metals in soil. The contents of Pb and Cd in green vegetables were higher than those of Zn and Cu and exceeded the national sanitation standards for vegetables.

Monitoring tropical vegetation succession with LANDSAT data

NASA Technical Reports Server (NTRS)

Robinson, V. B. (Principal Investigator)

1983-01-01

The shadowing problem, which is endemic to the use of LANDSAT in tropical areas, and the ability to model changes over space and through time are problems to be addressed when monitoring tropical vegetation succession. Application of a trend surface analysis model to major land cover classes in a mountainous region of the Phillipines shows that the spatial modeling of radiance values can provide a useful approach to tropical rain forest succession monitoring. Results indicate shadowing effects may be due primarily to local variations in the spectral responses. These variations can be compensated for through the decomposition of the spatial variation in both elevation and MSS data. Using the model to estimate both elevation and spectral terrain surface as a posteriori inputs in the classification process leads to improved classification accuracy for vegetation of cover of this type. Spatial patterns depicted by the MSS data reflect the measurement of responses to spatial processes acting at several scales.

Multi-scale spatial controls of understory vegetation in Douglas-fir–western hemlock forests of western Oregon, USA

Treesearch

Julia I. Burton; Lisa M. Ganio; Klaus J. Puettmann

2014-01-01

Forest understory vegetation is influenced by broad-scale variation in climate, intermediate scale variation in topography, disturbance and neighborhood interactions. However, little is known about how these multi-scale controls interact to influence observed spatial patterns. We examined relationships between the aggregated cover of understory plant species (%...

Phenology and trend indicators derived from spatially dynamic bi-weekly satellite imagery to support ecosystem monitoring

Treesearch

Barron J. Orr; Grant M. Casady; Daniel G. Tuttle; Willem J. D. van Leeuwen; Laura E. Baker; Colleen I. McDonald; Stuart E. Marsh

2005-01-01

Ground-based ecosystem monitoring presents some practical challenges to natural resource managers and ecologists tasked with assessing vegetation dynamics across large areas through time. RangeView (http://rangeview.arizona.edu) provides online access to spatially and temporally explicit biweekly vegetation indices derived from satellite data. It also permits side-by-...

Development of coarse-scale spatial data for wildland fire and fuel management

Treesearch

Kirsten M. Schmidt; James P. Menakis; Colin C. Hardy; Wendall J. Hann; David L. Bunnell

2002-01-01

We produced seven coarse-scale, 1-km2 resolution, spatial data layers for the conterminous United States to support national-level fire planning and risk assessments. Four of these layers were developed to evaluate ecological conditions and risk to ecosystem components: Potential Natural Vegetation Groups, a layer of climax vegetation types representing site...

On Variability in Satellite Terrestrial Chlorophyll Fluorescence Measurements: Relationships with Phenology and Ecosystem-Atmosphere Carbon Exchange, Vegetation Structure, Clouds, and Sun-Satellite Geometry

NASA Astrophysics Data System (ADS)

Joiner, J.; Yoshida, Y.; Guanter, L.; Zhang, Y.; Vasilkov, A. P.; Schaefer, K. M.; Huemmrich, K. F.; Middleton, E.; Koehler, P.; Jung, M.; Tucker, C. J.; Lyapustin, A.; Wang, Y.; Frankenberg, C.; Berry, J. A.; Koster, R. D.; Reichle, R. H.; Lee, J. E.; Kawa, S. R.; Collatz, G. J.; Walker, G. K.; Van der Tol, C.

2014-12-01

Over the past several years, there have been several breakthroughs in our ability to detect the very small fluorescence emitted by chlorophyll in vegetation globally from space. There are now multiple instruments in space capable of measuring this signal at varying temporal and spatial resolutions. We will review the state-of-the-art with respect to these relatively new satellite measurements and ongoing studies that examine the relationships with photosynthesis. Now that we have a data record spanning more than seven years, we can examine variations due to seasonal carbon uptake, interannual variability, land-use changes, and water and temperature stress. In addition, we examine how clouds and satellite viewing geometry impact the signal. We compare and contrast these variations with those from popular vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), related to the potential photosynthesis as well as with measurements from flux tower gas exchange measurements and other model-based estimates of Global Primary Productivity (GPP). Vegetation fluorescence can be simulated in global vegetation models as well as with 1D canopy radiative transport models. We will describe how the satellite fluorescence data are being used to evaluate and potentially improve these models.

The effect of short ground vegetation on terrestrial laser scans at a local scale

NASA Astrophysics Data System (ADS)

Fan, Lei; Powrie, William; Smethurst, Joel; Atkinson, Peter M.; Einstein, Herbert

2014-09-01

Terrestrial laser scanning (TLS) can record a large amount of accurate topographical information with a high spatial accuracy over a relatively short period of time. These features suggest it is a useful tool for topographical survey and surface deformation detection. However, the use of TLS to survey a terrain surface is still challenging in the presence of dense ground vegetation. The bare ground surface may not be illuminated due to signal occlusion caused by vegetation. This paper investigates vegetation-induced elevation error in TLS surveys at a local scale and its spatial pattern. An open, relatively flat area vegetated with dense grass was surveyed repeatedly under several scan conditions. A total station was used to establish an accurate representation of the bare ground surface. Local-highest-point and local-lowest-point filters were applied to the point clouds acquired for deriving vegetation height and vegetation-induced elevation error, respectively. The effects of various factors (for example, vegetation height, edge effects, incidence angle, scan resolution and location) on the error caused by vegetation are discussed. The results are of use in the planning and interpretation of TLS surveys of vegetated areas.

Analyzing the Velocity of Vegetation Phenology Over the Tibetan Plateau Using Gimms NDVI3g Data

NASA Astrophysics Data System (ADS)

Zhou, Y. K.

2018-05-01

Global environmental change is rapidly altering the dynamics of terrestrial vegetation, and phenology is a classic proxy to detect the response of vegetation to the changes. On the Tibetan Plateau, the earlier spring and delayed autumn vegetation phenology is widely reported. Remotely sensed NDVI can serve as a good data source for vegetation phenology study. Here GIMMS NDVI3g data was used to detect vegetation phenology status on the Tibetan Plateau. The spatial and temporal gradients are combined to depict the velocity of vegetation expanding process. This velocity index represents the instantaneous local velocity along the Earth's surface needed to maintain constant vegetation condition. This study found that NDVI velocity show a complex spatial pattern. A considerable number of regions display a later starting of growing season (SOS) and earlier end of growing season (EOS) reflected by the velocity change, particularly in the central part of the plateau. Nearly 74 % vegetation experienced a shortened growing season length. Totally, the magnitude of the phenology velocity is at a small level that reveals there is not a significant variation of vegetation phenology under the climate change context.

Modelling spatial and temporal vegetation variability with the Climate Constrained Vegetation Index: evidence of CO2 fertilisation and of water stress in continental interiors

NASA Astrophysics Data System (ADS)

Los, S. O.

2015-06-01

A model was developed to simulate spatial, seasonal and interannual variations in vegetation in response to temperature, precipitation and atmospheric CO2 concentrations; the model addresses shortcomings in current implementations. The model uses the minimum of 12 temperature and precipitation constraint functions to simulate NDVI. Functions vary based on the Köppen-Trewartha climate classification to take adaptations of vegetation to climate into account. The simulated NDVI, referred to as the climate constrained vegetation index (CCVI), captured the spatial variability (0.82 < r <0.87), seasonal variability (median r = 0.83) and interannual variability (median global r = 0.24) in NDVI. The CCVI simulated the effects of adverse climate on vegetation during the 1984 drought in the Sahel and during dust bowls of the 1930s and 1950s in the Great Plains in North America. A global CO2 fertilisation effect was found in NDVI data, similar in magnitude to that of earlier estimates (8 % for the 20th century). This effect increased linearly with simple ratio, a transformation of the NDVI. Three CCVI scenarios, based on climate simulations using the representative concentration pathway RCP4.5, showed a greater sensitivity of vegetation towards precipitation in Northern Hemisphere mid latitudes than is currently implemented in climate models. This higher sensitivity is of importance to assess the impact of climate variability on vegetation, in particular on agricultural productivity.

Remote Sensing of Wildland Fire-Induced Risk Assessment at the Community Level

PubMed Central

Hassan, Quazi K.

2018-01-01

Wildland fires are some of the critical natural hazards that pose a significant threat to the communities located in the vicinity of forested/vegetated areas. In this paper, our overall objective was to study the structural damages due to the 2016 Horse River Fire (HRF) that happened in Fort McMurray (Alberta, Canada) by employing primarily very high spatial resolution optical satellite data, i.e., WorldView-2. Thus, our activities included the: (i) estimation of the structural damages; and (ii) delineation of the wildland-urban interface (WUI) and its associated buffers at certain intervals, and their utilization in assessing potential risks. Our proposed method of remote sensing-based estimates of the number of structural damages was compared with the ground-based information available from the Planning and Development Recovery Committee Task Force of Regional Municipality of Wood Buffalo (RMWB); and found a strong linear relationship (i.e., r2 value of 0.97 with a slope of 0.97). Upon delineating the WUI and its associated buffer zones at 10 m, 30 m, 50 m, 70 m and 100 m distances; we found existence of vegetation within the 30 m buffers from the WUI for all of the damaged structures. In addition, we noticed that the relevant authorities had removed vegetation in some areas between 30 m and 70 m buffers from the WUI, which was proven to be effective in order to protect the structures in the adjacent communities. Furthermore, we mapped the wildland fire-induced vulnerable areas upon considering the WUI and its associated buffers. Our analysis revealed that approximately 30% of the areas within the buffer zones of 10 m and 30 m were vulnerable due to the presence of vegetation; in which, approximately 7% were burned during the 2016 HRF event that led the structural damages. Consequently, we suggest to remove the existing vegetation within these critical zones and also monitor the region at a regular interval in order to reduce the wildland fire-induced risk. PMID:29762504

Negative plant soil feedback explaining ring formation in clonal plants.

PubMed

Cartenì, Fabrizio; Marasco, Addolorata; Bonanomi, Giuliano; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco

2012-11-21

Ring shaped patches of clonal plants have been reported in different environments, but the mechanisms underlying such pattern formation are still poorly explained. Water depletion in the inner tussocks zone has been proposed as a possible cause, although ring patterns have been also observed in ecosystems without limiting water conditions. In this work, a spatially explicit model is presented in order to investigate the role of negative plant-soil feedback as an additional explanation for ring formation. The model describes the dynamics of the plant biomass in the presence of toxicity produced by the decomposition of accumulated litter in the soil. Our model qualitatively reproduces the emergence of ring patterns of a single clonal plant species during colonisation of a bare substrate. The model admits two homogeneous stationary solutions representing bare soil and uniform vegetation cover which depend only on the ratio between the biomass death and growth rates. Moreover, differently from other plant spatial patterns models, but in agreement with real field observations of vegetation dynamics, we demonstrated that the pattern dynamics always lead to spatially homogeneous vegetation covers without creation of stable Turing patterns. Analytical results show that ring formation is a function of two main components, the plant specific susceptibility to toxic compounds released in the soil by the accumulated litter and the decay rate of these same compounds, depending on environmental conditions. These components act at the same time and their respective intensities can give rise to the different ring structures observed in nature, ranging from slight reductions of biomass in patch centres, to the appearance of marked rings with bare inner zones, as well as the occurrence of ephemeral waves of plant cover. Our results highlight the potential role of plant-soil negative feedback depending on decomposition processes for the development of transient vegetation patterns. Copyright © 2012 Elsevier Ltd. All rights reserved.

Analyzing millet price regimes and market performance in Niger with remote sensing data

NASA Astrophysics Data System (ADS)

Essam, Timothy Michael

This dissertation concerns the analysis of staple food prices and market performance in Niger using remotely sensed vegetation indices in the form of normalized differenced vegetation index (NDVI). By exploiting the link between weather-related vegetation production conditions, which serve as a proxy for spatially explicit millet yields and thus millet availability, this study analyzes the potential causal links between NDVI outcomes and millet market performance and presents an empirical approach for predicting changes in market performance based on NDVI outcomes. Overall, the thesis finds that inter-market price spreads and levels of market integration can be reasonably explained by deviations in vegetation index outcomes from the growing season. Negative (positive) NDVI shocks are associated with better (worse) than expected market performance as measured by converging inter-market price spreads. As the number of markets affected by negatively abnormal vegetation production conditions in the same month of the growing season increases, inter-market price dispersion declines. Positive NDVI shocks, however, do not mirror this pattern in terms of the magnitude of inter-market price divergence. Market integration is also found to be linked to vegetation index outcomes as below (above) average NDVI outcomes result in more integrated (segmented) markets. Climate change and food security policies and interventions should be guided by these findings and account for dynamic relationships among market structures and vegetation production outcomes.

Monitoring structural breaks in vegetation dynamics of the nature reserve Königsbrücker Heide

NASA Astrophysics Data System (ADS)

Wessollek, Christine; Karrasch, Pierre

2017-10-01

Nowadays remote sensing is a well-established method and technique of providing data. The current development shows the availability of systems with very high geometric resolution for the monitoring of vegetation. At the same time, however, the value of temporally high-resolution data is underestimated, particularly in applications focusing on the detection of short-term changes. These can be natural processes like natural disasters as well as changes caused by anthropogenic interventions. These include economic activities such as forestry, agriculture or mining but also processes which are intended to convert previously used areas into natural or near-natural surfaces. The K¨onigsbr¨ucker Heide is a former military training site located about 30 km north of the Saxon state capitol Dresden. After the withdrawal of the Soviet forces in 1992 and after nearly 100 years of military use this site was declared as nature reserve in 1996. The management of the whole protection area is implemented in three different management zone. Based on MODIS-NDVI time series between 2000 and 2016 different developments are apparent in the nature development zone and the zone of controlled succession. Nevertheless, the analyses also show that short-term changes, so called breaks in the vegetation development cannot be described using linear trend models. The complete understanding of vegetation trends is only given if discontinuities in vegetation development are considered. Structural breaks in the NDVI time series can be found simultaneously in the whole study area. Hence it can be assumed that these breaks have a more natural character, caused for example by climatic conditions like temperature or precipitation. Otherwise, especially in the zone of controlled succession structural breaks can be detected which cannot be traced back to natural conditions. Final analyses of the spatial distribution of breakpoints as well as their frequency depending on the respective protection zone allow a detailed view to vegetation development in the K¨onigsbr¨ucker Heide.

Spatiotemporal diversity, structure and trophic guilds of insect assemblages in a semi-arid Sabkha ecosystem

PubMed Central

Menasria, Taha; Neffar, Souad; Chafaa, Smail; Bradai, Lyès; Chaibi, Rachid; Mekahlia, Mohamed Nacer; Bendjoudi, Djamel; Si Bachir, Abdelkrim

2015-01-01

The current study highlights some knowledge on the diversity and structure of insect communities and trophic groups living in Sabkha Djendli (semi-arid area of Northeastern Algeria). The entomofauna was monthly sampled from March to November 2006 using pitfall traps at eight sites located at the vicinity of the Sabkha. Structural and diversity parameters (species richness, Shannon index, evenness) were measured for both insect orders and trophic guilds. The canonical correspondence analysis (CCA) was applied to determine how vegetation parameters (species richness and cover) influence spatial and seasonal fluctuations of insect assemblages. The catches totalled 434 insect individuals classified into 75 species, 62 genera, 31 families and 7 orders, of which Coleoptera and Hymenoptera were the most abundant and constant over seasons and study stations. Spring and autumn presented the highest values of diversity parameters. Individual-based Chao-1 species richness estimator indicated 126 species for the total individuals captured in the Sabkha. Based on catch abundances, the structure of functional trophic groups was predators (37.3%), saprophages (26.7%), phytophages (20.5%), polyphages (10.8%), coprophages (4.6%); whereas in terms of numbers of species, they can be classified as phytophages (40%), predators (25.3%), polyphages (13.3%), saprophages (12%), coprophages (9.3%). The CCA demonstrated that phytophages and saprophages as well as Coleoptera and Orthoptera were positively correlated with the two parameters of vegetation, especially in spring and summer. While the abundance of coprophages was positively correlated with species richness of plants, polyphage density was positively associated with vegetation cover. The insect community showed high taxonomic and functional diversity that is closely related to diversity and vegetation cover in different stations of the wetland and seasons. PMID:25825682

Compositing MODIS Terra and Aqua 250m daily surface reflectance data sets for vegetation monitoring

USDA-ARS?s Scientific Manuscript database

Remote sensing based vegetation Indices have been proven valuable in providing a spatially complete view of crop’s vegetation condition, which also manifests the impact of the disastrous events such as massive flood and drought. VegScape, a web GIS application for crop vegetation condition monitorin...

Coupled topographic and vegetation patterns in coastal dunes: Remote sensing observations and ecomorphodynamic implications

NASA Astrophysics Data System (ADS)

Yousefi Lalimi, F.; Silvestri, S.; Moore, L. J.; Marani, M.

2017-01-01

Vegetation plays a key role in stabilizing coastal dunes and barrier islands by mediating sand transport, deposition, and erosion. Dune topography, in turn, affects vegetation growth, by determining local environmental conditions. However, our understanding of vegetation and dune topography as coupled and spatially extensive dynamical systems is limited. Here we develop and use remote sensing analyses to quantitatively characterize coastal dune ecotopographic patterns by simultaneously identifying the spatial distribution of topographic elevation and vegetation biomass. Lidar-derived leaf area index and hyperspectral-derived normalized difference vegetation index patterns yield vegetation distributions at the whole-system scale which are in agreement with each other and with field observations. Lidar-derived concurrent quantifications of biomass and topography show that plants more favorably develop on the landward side of the foredune crest and that the foredune crestline marks the position of an ecotone, which is interpreted as the result of a sheltering effect sharply changing local environmental conditions. We conclude that the position of the foredune crestline is a chief ecomorphodynamic feature resulting from the two-way interaction between vegetation and topography.

30-year Dynamics of Terrestrial Vegetation Activity and the Relationship with Climatologies

NASA Astrophysics Data System (ADS)

de Jong, R.; Schaepman, M. E.; Furrer, R.; de Bruin, S.; Verburg, P. H.

2013-12-01

The climate governs the seasonal activity of terrestrial vegetation while humankind influences it. The relative role of these drivers in changing vegetation activity is crucial information for accurate modeling of vegetation and climate dynamics and for adaptation and mitigation strategies. Disentangling the two, however, is an ongoing scientific challenge, because of limited data availability, mainly regarding non-climatic drivers, and complex biosphere-atmosphere feedback mechanisms. Here, we contribute to this quest by modeling the spatial relationship between climatologies and changes in global vegetation activity (de Jong et al., 2013a). Vegetation activity is commonly quantified using remotely sensed vegetation indices (VI). Extensive reports on temporal trends over the past decades in time series of such indices can be found in literature, including the detection of shifts (de Jong et al., 2013b), which may be related to climate (e.g. Zhao & Running, 2010). However, little remains known about the exact processes underlying vegetation change at large spatial scales. Depending on eco-region, three climatologies potentially constrain plant growth (Churkina and Running, 1998). In the humid mid-latitudes, for example, temperature is the largest influencing factor; in (semi) arid regions it is the availability of water and in the tropics incident solar radiation. Based on this logic, we developed a mixed-effect model to relate changes in these climatologies to changes in vegetation activity and to quantify the spatial process underlying the other drivers, including human land use. Little over 50% of the spatial variation in vegetation change could be attributed to changes in climatologies; conspicuously, many of the global ';greening' trends and the ';browning' hotspots in Argentina and Australia. Browning hotspots in the non-climatic component were especially located in subequatorial Africa (e.g. parts of Zimbabwe and Tanzania), where human drivers may be responsible. Indications for browning under warming conditions were found in some boreal regions. These results are examples of relationships we can find within readily available datasets, without a-priori information, and may be used as indicator for drivers of biospheric change. Churkina G, Running SW (1998) Contrasting climatic controls on the estimated productivity of global terrestrial biomes. Ecosystems, 1, 206-215 de Jong R, Schaepman ME, Furrer R, De Bruin S, Verburg PH (2013a) Spatial relationship between climatologies and changes in global vegetation activity. Global Change Biology, 19, 1953-1964 de Jong, R, Verbesselt, J, Zeileis, A, & Schaepman, ME (2013b) Shifts in Global Vegetation Activity Trends. Remote Sensing, 5, 1117-1133 Zhao M, Running SW (2010) Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009. Science, 329, 940-943

Phenomapping of rangelands in South Africa using time series of RapidEye data

NASA Astrophysics Data System (ADS)

Parplies, André; Dubovyk, Olena; Tewes, Andreas; Mund, Jan-Peter; Schellberg, Jürgen

2016-12-01

Phenomapping is an approach which allows the derivation of spatial patterns of vegetation phenology and rangeland productivity based on time series of vegetation indices. In our study, we propose a new spatial mapping approach which combines phenometrics derived from high resolution (HR) satellite time series with spatial logistic regression modeling to discriminate land management systems in rangelands. From the RapidEye time series for selected rangelands in South Africa, we calculated bi-weekly noise reduced Normalized Difference Vegetation Index (NDVI) images. For the growing season of 2011⿿2012, we further derived principal phenology metrics such as start, end and length of growing season and related phenological variables such as amplitude, left derivative and small integral of the NDVI curve. We then mapped these phenometrics across two different tenure systems, communal and commercial, at the very detailed spatial resolution of 5 m. The result of a binary logistic regression (BLR) has shown that the amplitude and the left derivative of the NDVI curve were statistically significant. These indicators are useful to discriminate commercial from communal rangeland systems. We conclude that phenomapping combined with spatial modeling is a powerful tool that allows efficient aggregation of phenology and productivity metrics for spatially explicit analysis of the relationships of crop phenology with site conditions and management. This approach has particular potential for disaggregated and patchy environments such as in farming systems in semi-arid South Africa, where phenology varies considerably among and within years. Further, we see a strong perspective for phenomapping to support spatially explicit modelling of vegetation.

Islands of biogeodiversity in arid lands on a polygons map study: Detecting scale invariance patterns from natural resources maps.

PubMed

Ibáñez, J J; Pérez-Gómez, R; Brevik, Eric C; Cerdà, A

2016-12-15

Many maps (geology, hydrology, soil, vegetation, etc.) are created to inventory natural resources. Each of these resources is mapped using a unique set of criteria, including scales and taxonomies. Past research indicates that comparing results of related maps (e.g., soil and geology maps) may aid in identifying mapping deficiencies. Therefore, this study was undertaken in Almeria Province, Spain to (i) compare the underlying map structures of soil and vegetation maps and (ii) investigate if a vegetation map can provide useful soil information that was not shown on a soil map. Soil and vegetation maps were imported into ArcGIS 10.1 for spatial analysis, and results then exported to Microsoft Excel worksheets for statistical analyses to evaluate fits to linear and power law regression models. Vegetative units were grouped according to the driving forces that determined their presence or absence: (i) climatophilous (ii) lithologic-climate; and (iii) edaphophylous. The rank abundance plots for both the soil and vegetation maps conformed to Willis or Hollow Curves, meaning the underlying structures of both maps were the same. Edaphophylous map units, which represent 58.5% of the vegetation units in the study area, did not show a good correlation with the soil map. Further investigation revealed that 87% of the edaphohygrophilous units were found in ramblas, ephemeral riverbeds that are not typically classified and mapped as soils in modern systems, even though they meet the definition of soil given by the most commonly used and most modern soil taxonomic systems. Furthermore, these edaphophylous map units tend to be islands of biodiversity that are threatened by anthropogenic activity in the region. Therefore, this study revealed areas that need to be revisited and studied pedologically. The vegetation mapped in these areas and the soils that support it are key components of the earth's critical zone that must be studied, understood, and preserved. Copyright © 2016 Elsevier B.V. All rights reserved.

Using multi-scale sampling and spatial cross-correlation to investigate patterns of plant species richness

USGS Publications Warehouse

Kalkhan, M.A.; Stohlgren, T.J.

2000-01-01

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, IYZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m2) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m2 subplots within each of the 1000 m2 plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balance

NASA Astrophysics Data System (ADS)

Tang, G.; Bartlein, P. J.

2012-01-01

Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p < 0.01) in the Everglades of Florida over the years 1996-2001. The modeled monthly soil moisture for Illinois of the US agrees well (R2 = 0.79, p < 0.01) with the observed over the years 1984-2001. The modeled monthly stream flow for most 12 major rivers in the US is consistent R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficients >0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

Transition from Connected to Fragmented Vegetation across an Environmental Gradient: Scaling Laws in Ecotone Geometry.

PubMed

Gastner, Michael T; Oborny, Beata; Zimmermann, D K; Pruessner, Gunnar

2009-07-01

A change in the environmental conditions across space-for example, altitude or latitude-can cause significant changes in the density of a vegetation type and, consequently, in spatial connectivity. We use spatially explicit simulations to study the transition from connected to fragmented vegetation. A static (gradient percolation) model is compared to dynamic (gradient contact process) models. Connectivity is characterized from the perspective of various species that use this vegetation type for habitat and differ in dispersal or migration range, that is, "step length" across the landscape. The boundary of connected vegetation delineated by a particular step length is termed the " hull edge." We found that for every step length and for every gradient, the hull edge is a fractal with dimension 7/4. The result is the same for different spatial models, suggesting that there are universal laws in ecotone geometry. To demonstrate that the model is applicable to real data, a hull edge of fractal dimension 7/4 is shown on a satellite image of a piñon-juniper woodland on a hillside. We propose to use the hull edge to define the boundary of a vegetation type unambiguously. This offers a new tool for detecting a shift of the boundary due to a climate change.

In the hot seat : Insolation and ENSO controls on vegetation productivity in tropical Africa inferred from NDVI

NASA Astrophysics Data System (ADS)

Ivory, S.; Russell, J. L.; Cohen, A. S.

2010-12-01

Threats to tropical biodiversity with serious and costly implications for both ecosystems and human well-being in Africa have led the IPCC to classify this region as vulnerable to negative impacts from climate change. Yet little is known about how vegetation communities respond to altered patterns of rainfall and evaporation. Paleoclimate records within the tropics can help answer questions about how vegetation response to climate forcing changes over time. However, sparse spatial extent of records and uncertainty surrounding the climate-vegetation relationship complicate these insights. Understanding the climatic mechanisms involved in landscape change at all temporal scales creates the need for quantitative constraints of the modern relationship between climatic controls, hydrology, and vegetation. Though modern observational data can help elucidate this relationship, low resolution and complicated rainfall/vegetation associations make them less than ideal. Satellite data of vegetation productivity (NDVI) with continuous high-resolution spatial coverage provides a robust and elegant tool for identifying the link between global and regional controls and vegetation. We use regression analyses of variables either previously proposed or potentially important in regulating Afro-tropical vegetation (insolation, out-going long-wave radiation, geopotential height, Southern Oscillation Index, Indian Ocean Dipole, Indian Monsoon precipitation, sea-level pressure, surface wind, sea-surface temperature) on continuous, time-varying spatial fields of 8km NDVI for sub-Saharan Africa. These analyses show the importance of global atmospheric controls in producing regional intra-annual and inter-annual vegetation variability. Dipole patterns emerge primarily correlated with both the seasonal and inter-annual extent of the Intertropical Convergence Zone (ITCZ). Inter-annual ITCZ variability drives patterns in African vegetation resulting from the effect of insolation anomalies and ENSO events on atmospheric circulation rather than sea surface temperatures or teleconnections to mid/high latitudes. Global controls on tropical atmospheric circulation regulate vegetation throughout sub-Saharan Africa on many time scales through alteration of dry season length and moisture convergence, rather than precipitation amount.

Detecting changes in water limitation in the West using integrated ecosystem modeling approaches

NASA Astrophysics Data System (ADS)

Poulter, B.; Hoy, J.; Emmett, K.; Cross, M.; Maneta, M. P.; Al-Chokhachy, R.

2016-12-01

Water in the western United States is the critical currency for determining a range of ecosystem services, such as wildlife habitat, carbon sequestration, and timber and water resources for an expanding human population. The current generation of catchment models trades a detailed representation of hydrologic processes for a generalization of vegetation processes and thus ignores many land-surface feedbacks that are driven by physiological responses to atmospheric CO2 and changes in vegetation structure following disturbance and climate change. Here we demonstrate how catchment scale modeling can better couple vegetation dynamics and disturbance processes to reconstruct historic streamflow, stream temperature and vegetation greening for the Greater Yellowstone Ecosystem. Using a new catchment routing model coupled to the LPJ-GUESS dynamic global vegetation model, simulations are made at 1 km spatial resolution using two different climate products. Decreased winter snowpack has led to increasing spring runoff and declines in summertime slow, and increasing the likelihood that stream temperature exceeds thresholds for cold-water fish growth. Since the mid-1980s, vegetation greening is projected by both the model and detected from space-borne normalized difference vegetation index observations. These greening trends are superimposed on a landscape matrix defined by frequent disturbance and intensive land management, making the climate and CO2 fingerprint difficult to discern. Integrating dynamical vegetation models with in-situ and spaceborne measurements to understand and interpret catchment-scale trends in water availability has potential to better disentangle historical climate, CO2, and human drivers and their ecosystem consequences.

A non-parametric, supervised classification of vegetation types on the Kaibab National Forest using decision trees

Treesearch

Suzanne M. Joy; R. M. Reich; Richard T. Reynolds

2003-01-01

Traditional land classification techniques for large areas that use Landsat Thematic Mapper (TM) imagery are typically limited to the fixed spatial resolution of the sensors (30m). However, the study of some ecological processes requires land cover classifications at finer spatial resolutions. We model forest vegetation types on the Kaibab National Forest (KNF) in...

Variation in nutrient characteristics of surface soils from the Luquillo Experimental Forest of Puerto Rico: A multivariate perspective.

Treesearch

S. B. Cox; M. R. Willig; F. N. Scatena

2002-01-01

We assessed the effects of landscape features (vegetation type and topography), season, and spatial hierarchy on the nutrient content of surface soils in the Luquillo Experimental Forest (LEF) of Puerto Rico. Considerable spatial variation characterized the soils of the LEF, and differences between replicate sites within each combination of vegetation type (tabonuco vs...

Selection of fire-created snags at two spatial scales by cavity-nesting birds

Treesearch

Victoria A. Saab; Ree Brannon; Jonathan Dudley; Larry Donohoo; Dave Vanderzanden; Vicky Johnson; Henry Lachowski

2002-01-01

We examined the use of snag stands by seven species of cavity-nesting birds from 1994-1998. Selection of snags was studied in logged and unlogged burned forests at two spatial scales: microhabitat (local vegetation characteristics) and landscape (composition and patterning of surrounding vegetation types). We modeled nest occurrence at the landscape scale by using...

Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels

PubMed Central

Van de Voorde, Tim; Vlaeminck, Jeroen; Canters, Frank

2008-01-01

Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city's inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP) at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing. PMID:27879914

Using High Resolution Remote Sensing Images to Investigate Hydrologic Connectivity and Degradation Thresholds along a Precipitation Gradient in Semiarid Australia

NASA Astrophysics Data System (ADS)

Azadi, S.; Saco, P. M.; Moreno-de las Heras, M.; Willgoose, G. R.

2016-12-01

Arid and semiarid landscapes are particularly sensitive to climatic and anthropogenic disturbances. Previous work has identified that these landscapes are prone to undergo critical degradation thresholds above which rehabilitation is difficult to achieve. This threshold behaviour is tightly linked to the overland flow redistribution and an increase in hydrologic connectivity associated with the climatic or anthropogenic disturbances. In fact, disturbances (such as wildfire, overgrazing or harvesting activities) can disrupt the spatial structure of vegetation, increase landscape hydrologic connectivity, trigger erosion and produce a substantial loss of water. All these effects can eventually affect ecosystem functionality (e.g. Rainfall Use Efficiency). In this study, we explore the impact of degradation processes induced by vegetation disturbances (mostly due to grazing pressure) on ecosystem functionality and connectivity along a precipitation gradient (250 mm to 490 mm annual average rainfall) using a combination of remote sensing observations and Digital Elevation Model data. The sites were carefully selected in the Mulga landscapes bioregion (New South Wales, Queensland) and in sites of the Northern Territory in Australia, which display similar vegetation characteristics and good quality rainfall information. Vegetation patterns and the percent of fractional cover were obtained from high resolution remote sensing images (IKONOS, QuickBird and Pleiades). We computed rainfall use efficiency and precipitation marginal response using local precipitation data and MODIS vegetation indices. We estimated mean Flowlength as an indicator of structural hydrologic connectivity using vegetation binary maps and digital elevation models. We compared the trends for several sites along the precipitation gradient, and found that disturbances substantially increase hydrologic connectivity following a threshold behaviour that affects landscape functionality. Though this threshold behaviour is found in all sites, the plots in higher rainfall landscapes show evidence of higher resilience.

The Contribution of Vegetation and Landscape Configuration for Predicting Environmental Change Impacts on Iberian Birds

PubMed Central

Triviño, Maria; Thuiller, Wilfried; Cabeza, Mar; Hickler, Thomas; Araújo, Miguel B.

2011-01-01

Although climate is known to be one of the key factors determining animal species distributions amongst others, projections of global change impacts on their distributions often rely on bioclimatic envelope models. Vegetation structure and landscape configuration are also key determinants of distributions, but they are rarely considered in such assessments. We explore the consequences of using simulated vegetation structure and composition as well as its associated landscape configuration in models projecting global change effects on Iberian bird species distributions. Both present-day and future distributions were modelled for 168 bird species using two ensemble forecasting methods: Random Forests (RF) and Boosted Regression Trees (BRT). For each species, several models were created, differing in the predictor variables used (climate, vegetation, and landscape configuration). Discrimination ability of each model in the present-day was then tested with four commonly used evaluation methods (AUC, TSS, specificity and sensitivity). The different sets of predictor variables yielded similar spatial patterns for well-modelled species, but the future projections diverged for poorly-modelled species. Models using all predictor variables were not significantly better than models fitted with climate variables alone for ca. 50% of the cases. Moreover, models fitted with climate data were always better than models fitted with landscape configuration variables, and vegetation variables were found to correlate with bird species distributions in 26–40% of the cases with BRT, and in 1–18% of the cases with RF. We conclude that improvements from including vegetation and its landscape configuration variables in comparison with climate only variables might not always be as great as expected for future projections of Iberian bird species. PMID:22216263

Informal urban green-space: comparison of quantity and characteristics in Brisbane, Australia and Sapporo, Japan.

PubMed

Rupprecht, Christoph D D; Byrne, Jason A

2014-01-01

Informal urban green-space (IGS) such as vacant lots, brownfields and street or railway verges is receiving growing attention from urban scholars. Research has shown IGS can provide recreational space for residents and habitat for flora and fauna, yet we know little about the quantity, spatial distribution, vegetation structure or accessibility of IGS. We also lack a commonly accepted definition of IGS and a method that can be used for its rapid quantitative assessment. This paper advances a definition and typology of IGS that has potential for global application. Based on this definition, IGS land use percentage in central Brisbane, Australia and Sapporo, Japan was systematically surveyed in a 10×10 km grid containing 121 sampling sites of 2,500 m2 per city, drawing on data recorded in the field and aerial photography. Spatial distribution, vegetation structure and accessibility of IGS were also analyzed. We found approximately 6.3% of the surveyed urban area in Brisbane and 4.8% in Sapporo consisted of IGS, a non-significant difference. The street verge IGS type (80.4% of all IGS) dominated in Brisbane, while lots (42.2%) and gaps (19.2%) were the two largest IGS types in Sapporo. IGS was widely distributed throughout both survey areas. Vegetation structure showed higher tree cover in Brisbane, but higher herb cover in Sapporo. In both cities over 80% of IGS was accessible or partly accessible. The amount of IGS we found suggests it could play a more important role than previously assumed for residents' recreation and nature experience as well as for fauna and flora, because it substantially increased the amount of potentially available greenspace in addition to parks and conservation greenspace. We argue that IGS has potential for recreation and conservation, but poses some challenges to urban planning. To address these challenges, we propose some directions for future research.

Informal Urban Green-Space: Comparison of Quantity and Characteristics in Brisbane, Australia and Sapporo, Japan

PubMed Central

Rupprecht, Christoph D. D.; Byrne, Jason A.

2014-01-01

Informal urban green-space (IGS) such as vacant lots, brownfields and street or railway verges is receiving growing attention from urban scholars. Research has shown IGS can provide recreational space for residents and habitat for flora and fauna, yet we know little about the quantity, spatial distribution, vegetation structure or accessibility of IGS. We also lack a commonly accepted definition of IGS and a method that can be used for its rapid quantitative assessment. This paper advances a definition and typology of IGS that has potential for global application. Based on this definition, IGS land use percentage in central Brisbane, Australia and Sapporo, Japan was systematically surveyed in a 10×10 km grid containing 121 sampling sites of 2,500 m2 per city, drawing on data recorded in the field and aerial photography. Spatial distribution, vegetation structure and accessibility of IGS were also analyzed. We found approximately 6.3% of the surveyed urban area in Brisbane and 4.8% in Sapporo consisted of IGS, a non-significant difference. The street verge IGS type (80.4% of all IGS) dominated in Brisbane, while lots (42.2%) and gaps (19.2%) were the two largest IGS types in Sapporo. IGS was widely distributed throughout both survey areas. Vegetation structure showed higher tree cover in Brisbane, but higher herb cover in Sapporo. In both cities over 80% of IGS was accessible or partly accessible. The amount of IGS we found suggests it could play a more important role than previously assumed for residents' recreation and nature experience as well as for fauna and flora, because it substantially increased the amount of potentially available greenspace in addition to parks and conservation greenspace. We argue that IGS has potential for recreation and conservation, but poses some challenges to urban planning. To address these challenges, we propose some directions for future research. PMID:24941046

Quantifying Structural and Compositional Changes in Forest Cover in NW Yunnan, China

NASA Astrophysics Data System (ADS)

Hakkenberg, C.

2012-12-01

NW Yunnan, China is a region renowned for high levels of biodiversity, endemism and genetically distinct refugial plant populations. It is also a focal area for China's national reforestation efforts like the Natural Forest Protection Program (NFPP), intended to control erosion in the Upper Yangtze watershed. As part of a larger project to investigate the role of reforestation programs in facilitating the emergence of increasingly species-rich forest communities on a previously degraded and depauperate land mosaic in montane SW China, this study uses a series of Landsat TM images to quantify the spatial pattern and rate of structural and compositional change in forests recovering from medium to large-scale disturbances in the area over the past 25 years. Beyond the fundamental need to assess the outcomes of one of the world's largest reforestation programs, this research offers approaches to confronting two critical methodological issues: (1) techniques for characterizing subtle changes in the nature of vegetation cover, and (2) reducing change detection uncertainty due to persistent cloud cover and shadow. To address difficulties in accurately assessing the structure and composition of vegetative regrowth, a biophysical model was parameterized with over 300 ground-truthed canopy cover assessment points to determine pattern and rate of long-term vegetation changes. To combat pervasive shadow and cloud cover, an interactive generalized additive model (GAM) model based on topographic and spatial predictors was used to overcome some of the constraints of satellite image analysis in Himalayan regions characterized by extreme topography and extensive cloud cover during the summer monsoon. The change detection is assessed for accuracy using ground-truthed observations in a variety of forest cover types and topographic positions. Results indicate effectiveness in reducing the areal extent of unclassified regions and increasing total change detection accuracy. In addition to quantifying forest cover change in this section of NW Yunnan, the analysis attempts to qualify that change - distinguishing among distinct disturbance histories and post-recovery successional pathways.

Discovery of fairy circles in Australia supports self-organization theory

PubMed Central

Getzin, Stephan; Yizhaq, Hezi; Bell, Bronwyn; Erickson, Todd E.; Postle, Anthony C.; Katra, Itzhak; Tzuk, Omer; Zelnik, Yuval R.; Wiegand, Kerstin; Wiegand, Thorsten; Meron, Ehud

2016-01-01

Vegetation gap patterns in arid grasslands, such as the “fairy circles” of Namibia, are one of nature’s greatest mysteries and subject to a lively debate on their origin. They are characterized by small-scale hexagonal ordering of circular bare-soil gaps that persists uniformly in the landscape scale to form a homogeneous distribution. Pattern-formation theory predicts that such highly ordered gap patterns should be found also in other water-limited systems across the globe, even if the mechanisms of their formation are different. Here we report that so far unknown fairy circles with the same spatial structure exist 10,000 km away from Namibia in the remote outback of Australia. Combining fieldwork, remote sensing, spatial pattern analysis, and process-based mathematical modeling, we demonstrate that these patterns emerge by self-organization, with no correlation with termite activity; the driving mechanism is a positive biomass–water feedback associated with water runoff and biomass-dependent infiltration rates. The remarkable match between the patterns of Australian and Namibian fairy circles and model results indicate that both patterns emerge from a nonuniform stationary instability, supporting a central universality principle of pattern-formation theory. Applied to the context of dryland vegetation, this principle predicts that different systems that go through the same instability type will show similar vegetation patterns even if the feedback mechanisms and resulting soil–water distributions are different, as we indeed found by comparing the Australian and the Namibian fairy-circle ecosystems. These results suggest that biomass–water feedbacks and resultant vegetation gap patterns are likely more common in remote drylands than is currently known. PMID:26976567

Spatially explicit feedbacks between seagrass meadow structure, sediment and light: Habitat suitability for seagrass growth

USGS Publications Warehouse

Carr, Joel; D'Odorico, Paul; McGlathery, Karen; Wiberg, Patricia L.

2016-01-01

In shallow coastal bays where nutrient loading and riverine inputs are low, turbidity, and the consequent light environment are controlled by resuspension of bed sediments due to wind-waves and tidal currents. High sediment resuspension and low light environments can limit benthic primary productivity; however, both currents and waves are affected by the presence of benthic plants such as seagrass. This feedback between the presence of benthic primary producers such as seagrass and the consequent light environment has been predicted to induce bistable dynamics locally. However, these vegetated areas influence a larger area than they footprint, including a barren adjacent downstream area which exhibits reduced shear stresses. Here we explore through modeling how the patchy structure of seagrass meadows on a landscape may affect sediment resuspension and the consequent light environment due to the presence of this sheltered region. Heterogeneous vegetation covers comprising a mosaic of randomly distributed patches were generated to investigate the effect of patch modified hydrodynamics. Actual cover of vegetation on the landscape was used to facilitate comparisons across landscape realizations. Hourly wave and current shear stresses on the landscape along with suspended sediment concentration and light attenuation characteristics were then calculated and spatially averaged to examine how actual cover and mean water depth affect the bulk sediment and light environment. The results indicate that an effective cover, which incorporates the sheltering area, has important controls on the distributions of shear stress, suspended sediment, light environment, and consequent seagrass habitat suitability. Interestingly, an optimal habitat occurs within a depth range where, if actual cover is reduced past some threshold, the bulk light environment would no longer favor seagrass growth.

Wolf Creek Research Basin Cold REgion Process Studies - 1992-2003

NASA Astrophysics Data System (ADS)

Janowicz, R.; Hedstrom, N.; Pomeroy, J.; Granger, R.; Carey, S.

2004-12-01

The development of hydrological models in northern regions are complicated by cold region processes. Sparse vegetation influences snowpack accumulation, redistribution and melt, frozen ground effects infiltration and runoff and cold soils in the summer effect evapotranspiration rates. Situated in the upper Yukon River watershed, the 195 km2 Wolf Creek Research Basin was instrumented in 1992 to calibrate hydrologic flow models, and has since evolved into a comprehensive study of cold region processes and linkages, contributing significantly to hydrological and climate change modelling. Studies include those of precipitation distribution, snowpack accumulation and redistribution, energy balance, snowmelt infiltration, and water balance. Studies of the spatial variability of hydrometeorological data demonstrate the importance of physical parameters on their distribution and control on runoff processes. Many studies have also identified the complex interaction of several of the physical parameters, including topography, vegetation and frozen ground (seasonal or permafrost) as important. They also show that there is a fundamental, underlying spatial structure to the watershed that must be adequately represented in parameterization schemes for scaling and watershed modelling. The specific results of numerous studies are presented.

Space-time modeling of soil moisture

NASA Astrophysics Data System (ADS)

Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio

2017-11-01

A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.

Plant species coalition groups of Zion National Park: An individualistic, floristic alternative to vegetation classification

Treesearch

Jeffrey E. Ott; Stewart C. Sanderson; E. Durant McArthur

2015-01-01

Vegetation surveys at Zion National Park (Zion), Utah, have contributed to our understanding of plant community patterns and their relationship to environmental factors. Previous authors used vegetation plot data to characterize vegetation types at Zion following conventional procedures that emphasize spatial discreteness and dominant species. We developed and applied...

Understanding relationships between morphology and ecosystem structure in a shallow tidal basins of Venice lagoon

NASA Astrophysics Data System (ADS)

Giuseppina Persichillo, Maria; Taramelli, Andrea; Valentini, Emiliana; Filipponi, Federico; Meisina, Claudia; Zucca, Francesco

2014-05-01

Coastal wetlands represent complex ecosystems prone to continue fluctuation of their internal equilibrium. They are valuable natural resources characterized by the continue interactions between geomorphological and biological components. Their adaptation to changing conditions is highly dependent on the rate and extent of spatial and temporal processes and their responses are still poorly understood. According to this, the vulnerability assessment to natural and human made hazard have became fundamental to analyse the resilience of these areas, their ability to cope with the impacts from externally driven forces or the efforts needed to minimize the impacts (Gitay et al., 2011). The objective of this research is to develop a comprehensive and replicable method through the application of Multi-Source data analysis, based on the integration of Earth Observation data and field survey, to analyse a shallow tidal basin of salt marshes, located in the northern part of the Venice lagoon. The study site is characterised by relatively elevated areas colonized by halophytic vegetation, and tidal flats, with not vegetated areas, characterized by lower elevations. Sub-pixel processing techniques (Spectral Mixing Analysis - SMA) were used to analyse the spatial distribution of both vegetation and sediments typology. Furthermore the classifications were assayed in terms of spatial (Power law) and temporal (Empirical Orthogonal Functions) patterns, in order to find the main characteristics of the aforementioned spatial trends and their variation over time. The principal aim is to study the spatio-temporal evolution of this coastal wetland area, in order to indentify tipping points, namely thresholds, beyond which the system reaches critical state and the main climatic, hydrodynamic and morphological variables that may influence and increase this behaviour. This research represents a new approach to study the geomorphological processes and to improve the management and conservation planning for coastal areas. Reference: Gitay H., Finlayson C.M. and Davidson N.(2011) - A Framework for assessing the vulnerability of wetlands to climate change, Ramsar Technical Report No. 5, 1-18.

Evaluation of LANDSAT-D Thematic Mapper performance as applied to hydrocarbon exploration

NASA Technical Reports Server (NTRS)

Dykstra, J. D.; Everett, J. R.; Livaccarri, R.; Michael, R.; Richardson, G.; Prucha, S.; Russell, O.; Ruth, M.; Sheffield, C. A.; Staskowski, R.

1984-01-01

Work with digital data of Oklahoma, Colorado, Wyoming, Utah and California demonstrate that the increased spectral refinement and spatial resolution of TM over MSS data greatly increase the value of the data to petroleum exploration in roles ranging from logistic planning to direct detection of phenomena related to microseepage of hydrocarbons. The value of the spatial content versus the spectral content of the data increases as soil and vegetation cover increase. The structural detail visible in the imagery can contribute to exploration at the prospect level. Examination of the variance/covariance matrix suggests that a combination of bands 1, 4, and 5 displays the most information for most areas.

Diverse Responses of Global Vegetation to Climate Changes: Spatial Patterns and Time-lag Effects

NASA Astrophysics Data System (ADS)

Wu, D.; Zhao, X.; Zhou, T.; Huang, K.; Xu, W.

2014-12-01

Global climate changes have enormous influences on vegetation growth, meanwhile, response of vegetation to climate express space diversity and time-lag effects, which account for spatial-temporal disparities of climate change and spatial heterogeneity of ecosystem. Revelation of this phenomenon will help us further understanding the impact of climate change on vegetation. Assessment and forecast of global environmental change can be also improved under further climate change. Here we present space diversity and time-lag effects patterns of global vegetation respond to three climate factors (temperature, precipitation and solar radiation) based on quantitative analysis of satellite data (NDVI) and Climate data (Climate Research Unit). We assessed the time-lag effects of global vegetation to main climate factors based on the great correlation fitness between NDVI and the three climate factors respectively among 0-12 months' temporal lags. On this basis, integrated response model of NDVI and the three climate factors was built to analyze contribution of different climate factors to vegetation growth with multiple regression model and partial correlation model. In the result, different vegetation types have distinct temporal lags to the three climate factors. For the precipitation, temporal lags of grasslands are the shortest while the evergreen broad-leaf forests are the longest, which means that grasslands are more sensitive to precipitation than evergreen broad-leaf forests. Analysis of different climate factors' contribution to vegetation reveal that vegetation are dominated by temperature in the high northern latitudes; they are mainly restricted by precipitation in arid and semi-arid areas (Australia, Western America); in humid areas of low and intermediate latitudes (Amazon, Eastern America), vegetation are mainly influenced by solar radiation. Our results reveal the time-lag effects and major driving factors of global vegetation growth and explain the spatiotemporal variations of global vegetation in last 30 years. Significantly, it is as well as in forecasting and assessing the influences of future climate change on the vegetation dynamics. This work was supported by the High Technology Research and Development Program of China (Grant NO.2013AA122801).

[Estimation of desert vegetation coverage based on multi-source remote sensing data].

PubMed

Wan, Hong-Mei; Li, Xia; Dong, Dao-Rui

2012-12-01

Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study areaAbstract: Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study area and based on the ground investigation and the multi-source remote sensing data of different resolutions, the estimation models for desert vegetation coverage were built, with the precisions of different estimation methods and models compared. The results showed that with the increasing spatial resolution of remote sensing data, the precisions of the estimation models increased. The estimation precision of the models based on the high, middle-high, and middle-low resolution remote sensing data was 89.5%, 87.0%, and 84.56%, respectively, and the precisions of the remote sensing models were higher than that of vegetation index method. This study revealed the change patterns of the estimation precision of desert vegetation coverage based on different spatial resolution remote sensing data, and realized the quantitative conversion of the parameters and scales among the high, middle, and low spatial resolution remote sensing data of desert vegetation coverage, which would provide direct evidence for establishing and implementing comprehensive remote sensing monitoring scheme for the ecological restoration in the study area.

Modeling Above-Ground Biomass Across Multiple Circum-Arctic Tundra Sites Using High Spatial Resolution Remote Sensing

NASA Astrophysics Data System (ADS)

Räsänen, Aleksi; Juutinen, Sari; Aurela, Mika; Virtanen, Tarmo

2017-04-01

Biomass is one of the central bio-geophysical variables in Earth observation for tracking plant productivity, and flow of carbon, nutrients, and water. Most of the satellite based biomass mapping exercises in Arctic environments have been performed by using rather coarse spatial resolution data, e.g. Landsat and AVHRR which have spatial resolutions of 30 m and >1 km, respectively. While the coarse resolution images have high temporal resolution, they are incapable of capturing the fragmented nature of tundra environment and fine-scale changes in vegetation and carbon exchange patterns. Very high spatial resolution (VHSR, spatial resolution 0.5-2 m) satellite images have the potential to detect environmental variables with an ecologically sound spatial resolution. The usage of VHSR images has, nevertheless, been modest so far in biomass modeling in the Arctic. Our objectives were to use VHSR for predicting above ground biomass in tundra landscapes, evaluate whether a common predictive model can be applied across circum-Arctic tundra and peatland sites having different types of vegetation, and produce knowledge on distribution of plant functional types (PFT) in these sites. Such model development is dependent on ground-based surveys of vegetation with the same spatial resolution and extent with the VHSR images. In this study, we conducted ground-based surveys of vegetation composition and biomass in four different arctic tundra or peatland areas located in Russia, Canada, and Finland. First, we sorted species into PFTs and developed PFT-specific models to predict biomass on the basis of non-destructive measurements (cover, height). Second, we predicted overall biomass on landscape scale by combinations of single bands and vegetation indices of very high resolution satellite images (QuickBird or WorldView-2 images of the eight sites). We compared area-specific empirical regression models and common models that were applied across all sites. We found that NDVI was usually the highest scoring spectral indices in explaining biomass distribution with good explanatory power. Furthermore, models which had more than one explanatory variable had higher explanatory power than models with a single index. The dissimilarity between common and site-specific model estimates was, however, high and data indicates that variation in vegetation properties and its impact on spectral reflectance needs to be acknowledged. Our work produced knowledge on above-ground biomass distribution and contribution of PFTs across circum-Arctic low-growth landscapes and will contribute to developing space-borne vegetation monitoring schemes utilizing VHSR satellite images.

Ecosystem services and urban heat riskscape moderation: water, green spaces, and social inequality in Phoenix, USA.

PubMed

Jenerette, G Darrel; Harlan, Sharon L; Stefanov, William L; Martin, Chris A

2011-10-01

Urban ecosystems are subjected to high temperatures--extreme heat events, chronically hot weather, or both-through interactions between local and global climate processes. Urban vegetation may provide a cooling ecosystem service, although many knowledge gaps exist in the biophysical and social dynamics of using this service to reduce climate extremes. To better understand patterns of urban vegetated cooling, the potential water requirements to supply these services, and differential access to these services between residential neighborhoods, we evaluated three decades (1970-2000) of land surface characteristics and residential segregation by income in the Phoenix, Arizona, USA metropolitan region. We developed an ecosystem service trade-offs approach to assess the urban heat riskscape, defined as the spatial variation in risk exposure and potential human vulnerability to extreme heat. In this region, vegetation provided nearly a 25 degrees C surface cooling compared to bare soil on low-humidity summer days; the magnitude of this service was strongly coupled to air temperature and vapor pressure deficits. To estimate the water loss associated with land-surface cooling, we applied a surface energy balance model. Our initial estimates suggest 2.7 mm/d of water may be used in supplying cooling ecosystem services in the Phoenix region on a summer day. The availability and corresponding resource use requirements of these ecosystem services had a strongly positive relationship with neighborhood income in the year 2000. However, economic stratification in access to services is a recent development: no vegetation-income relationship was observed in 1970, and a clear trend of increasing correlation was evident through 2000. To alleviate neighborhood inequality in risks from extreme heat through increased vegetation and evaporative cooling, large increases in regional water use would be required. Together, these results suggest the need for a systems evaluation of the benefits, costs, spatial structure, and temporal trajectory for the use of ecosystem services to moderate climate extremes. Increasing vegetation is one strategy for moderating regional climate changes in urban areas and simultaneously providing multiple ecosystem services. However, vegetation has economic, water, and social equity implications that vary dramatically across neighborhoods and need to be managed through informed environmental policies.

Seasonal Changes in Connectivity and Nitrate Processing in Deltaic Floodplains

NASA Astrophysics Data System (ADS)

Christensen, A.; Twilley, R.; Castaneda, E.

2017-12-01

Hydrological connectivity (HC) describes the exchange between distributary channels and floodplains in river-dominated systems, and ultimately controls delivery of nitrate-enriched water to floodplain wetlands. Within a river delta, HC is controlled by several biophysical processes including tides, wind events, river discharge, vegetation, and geomorphology that operate at different temporal and spatial scales. We quantified seasonal changes in vegetation density and river flooding, to better understand HC in Wax Lake Delta (WLD), a prograding delta in southeastern Louisiana. Previous results from our hydrodynamic model indicate longer residences times in intertidal zones (1-3 days) than in subtidal zones (<1.5 days) of WLD islands. This model also showed increases in HC during the flood season, despite vegetation growth. Residence time plays a large role in nitrate removal as it allows for biogeochemical processes such as denitrification and biological uptake to occur. Thus, our model results led us to investigate seasonal variations in nitrate removal rates through WLD. First, to improve model simulations of water flow through the deltaic floodplain, we conducted a vegetation survey to measure stem density and diameter. We found a relationship between floodplain geomorphology (bed elevation relative to the tidal datum and distance from island apex) and vegetation structure. These findings are incorporated into the model by representing vegetation as rigid rods and new results are directly coupled with a Delft3d Water Quality model to simulate changes in nitrate concentrations. Moreover, results from nitrogen tracer field experiments are used to parameterize reaction rates. These field experiments highlight the importance of spatially explicit data as nitrate concentrations varied from 6 umol/L to 88 umol/L at two sites with distinct environmental conditions. The model is calibrated using field data from six stations recording continuous hourly water quality data within a deltaic island since March 2014 and several field campaigns focused on sampling distributary channels. These initial attempts to understand the fate of nitrate in this system highlight the nitrate removal capacity of deltaic floodplains and the control of HC by river pulsing events, vegetation dynamics, and local hydrology.

Cytoarchitecture of Caudiverbera caudiverbera stage VI oocytes: a light and electron microscope study.

PubMed

Dabiké, M; Preller, A

1999-06-01

The general characteristics and salient features of the full-grown stage VI Caudiverbera caudiverbera oocyte at the light and electron microscopy level are described. The oocyte is a huge cell with radial symmetry and distinct polarity. A black animal hemisphere, rich in pigment granules and containing the nucleus, is clearly distinguished from the unpigmented white-yellowish vegetal hemisphere. The cell is surrounded by a highly invaginated plasma membrane, with numerous microvilli. The cortex underlying the plasma membrane contains cortical and pigment granules, mitochondria, rough endoplasmic reticulum and coated vesicles. Cytoskeletal components, such as actin filaments and microtubules, are also found in this region. The predominant structures, distributed throughout the cell, are the yolk platelets, which show a gradient in size with small platelets in the animal half and very large ones in the vegetal zone. Mitochondria are also very abundant in both hemispheres and clouds of these organelles are found in the perinuclear region, frequently associated with microtubules. Developed Golgi complexes are present in the cytoplasm and occasionally, annulate lamellae appear towards the inner zones. The nucleus is a large structure containing numerous nucleoli. The nuclear envelope is highly invaginated, especially at the side facing the vegetal pole. It is regularly perforated by large nuclear pores. Our results show that the structural organization of Caudiverbera oocytes, although similar to that of other amphibian oocytes, differs from them especially concerning the spatial distribution of several structural components.

The impact of persistent volcanic degassing on vegetation: A case study at Turrialba volcano, Costa Rica

NASA Astrophysics Data System (ADS)

Tortini, R.; van Manen, S. M.; Parkes, B. R. B.; Carn, S. A.

2017-07-01

Although the impacts of large volcanic eruptions on the global environment have been frequently studied, the impacts of lower tropospheric emissions from persistently degassing volcanoes remain poorly understood. Gas emissions from persistent degassing exceed those from sporadic eruptive activity, and can have significant long-term (years to decades) effects on local and regional scales, both on humans and the environment. Here, we exploit a variety of high temporal and high spatial resolution satellite-based time series and complementary ground-based measurements of element deposition and surveys of species richness, to enable a comprehensive spatio-temporal assessment of sulfur dioxide (SO2) emissions and their associated impacts on vegetation at Turrialba volcano (Costa Rica) from 2000 to 2013. We observe increased emissions of SO2 coincident with a decline in vegetation health downwind of the vents, in accordance with the prevalent wind direction at Turrialba. We also find that satellite-derived vegetation indices at various spatial resolutions are able to accurately define the vegetation kill zone, the extent of which is independently confirmed by ground-based sampling, and monitor its expansion over time. In addition, ecological impacts in terms of vegetation composition and diversity and physiological damage to vegetation, all spatially correspond to fumigation by Turrialba's plume. This study shows that analyzing and relating satellite observations to conditions and impacts on the ground can provide an increased understanding of volcanic degassing, its impacts in terms of the long-term vegetation response and the potential of satellite-based monitoring to inform hazard management strategies related to land use.

Development of population structure and spatial distribution patterns of a restored forest during 17-year succession (1993-2010) in Pingshuo opencast mine spoil, China.

PubMed

Zhao, Zhongqiu; Wang, Lianhua; Bai, Zhongke; Pan, Ziguan; Wang, Yun

2015-07-01

Afforestation of native tree species is often recommended for ecological restoration in mining areas, but the understanding of the ecological processes of restored vegetation is quite limited. In order to provide insight of the ecological processes of restored vegetation, in this study, we investigate the development of the population structure and spatial distribution patterns of restored Robinia pseudoacacia (ROPS) and Pinus tabuliformis (PITA) mixed forests during the 17 years of the mine spoil period of the Pingshuo opencast mine, Shanxi Province, China. After a 17-year succession, apart from the two planted species, Ulmus pumila (ULPU), as an invasive species, settled in the plot along with a large number of small diameter at breast height (DBH) size. In total, there are 10,062 living individual plants, much more than that at the plantation (5105), and ROPS had become the dominant species with a section area with a breast height of 9.40 m(2) hm(-2) and a mean DBH of 6.72 cm, much higher than both PITA and ULPU. The DBH size classes of all the total species showed inverted J-shaped distributions, which may have been a result of the large number of small regenerated ULPU trees. The DBH size classes of both ROPS and PITA showed peak-type structures with individuals mainly gathering in the moderate DBH size class, indicating a relatively healthy DBH size class structure. Meanwhile, invasive ULPU were distributed in a clear L shape, concentrating on the small DBH size class, indicating a relatively low survival rate for adult trees. Both ROPS and PITA species survival in the plantation showed uniform and aggregated distribution at small scales and random with scales increasing. ULPU showed a strong aggregation at small scales as well as random with scales increasing. Both the population structure and spatial distribution indicated that ROPS dominates and will continue to dominate the community in the future succession, which should be continuously monitored.

Using estimates of natural variation to detect ecologically important change in forest spatial patterns: a case study, Cascade Range, eastern Washington.

Treesearch

Paul F. Hessburg; Bradley G. Smith; R. Brion Salter

1999-01-01

Using hierarchical clustering techniques, we grouped subwatersheds on the eastern slope of the Cascade Range in Washington State into ecological subregions by similarity of area in potential vegetation and climate attributes. We then built spatially continuous historical and current vegetation maps for 48 randomly selected subwatersheds from interpretations of 1938-49...

This is like that, only bigger and messier

USDA-ARS?s Scientific Manuscript database

Cluster analysis is a core tool of vegetation science; we have always wanted to divide a complex world into manageable chunks. In vegetation science, we classify both vegetation and sites. Both have clear management applications. Various types of spatial classifications are used to delineate agroec...

Evaluating nitrogen removal by vegetation uptake using satellite image time series in riparian catchments.

PubMed

Wang, Xuelei; Wang, Qiao; Yang, Shengtian; Zheng, Donghai; Wu, Chuanqing; Mannaerts, C M

2011-06-01

Nitrogen (N) removal by vegetation uptake is one of the most important functions of riparian buffer zones in preventing non-point source pollution (NSP), and many studies about N uptake at the river reach scale have proven the effectiveness of plants in controlling nutrient pollution. However, at the watershed level, the riparian zones form dendritic networks and, as such, may be the predominant spatially structured feature in catchments and landscapes. Thus, assessing the functions of riparian system at the basin scale is important. In this study, a new method coupling remote sensing and ecological models was used to assess the N removal by riparian vegetation on a large spatial scale. The study site is located around the Guanting reservoir in Beijing, China, which was abandoned as the source water system for Beijing due to serious NSP in 1997. SPOT 5 data was used to map the land cover, and Landsat-5 TM time series images were used to retrieve land surface parameters. A modified forest nutrient cycling and biomass model (ForNBM) was used to simulate N removal, and the modified net primary productivity (NPP) module was driven by remote sensing image time series. Besides the remote sensing data, the necessary database included meteorological data, soil chemical and physical data and plant nutrient data. Pot and plot experiments were used to calibrate and validate the simulations. Our study has proven that, by coupling remote sensing data and parameters retrieval techniques to plant growth process models, catchment scale estimations of nitrogen uptake rates can be improved by spatial pixel-based modelling. Copyright © 2011 Elsevier B.V. All rights reserved.

A forestry GIS-based study on evaluating the potential of imaging spectroscopy in mapping forest land fertility

NASA Astrophysics Data System (ADS)

Mõttus, Matti; Takala, Tuure

2014-12-01

Fertility, or the availability of nutrients and water, controls forest productivity. It affects its carbon sequestration, and thus the forest's effect on climate, as well as its commercial value. Although the availability of nutrients cannot be measured directly using remote sensing methods, fertility alters several vegetation traits detectable from the reflectance spectra of the forest stand, including its pigment content and water stress. However, forest reflectance is also influenced by other factors, such as species composition and stand age. Here, we present a case study demonstrating how data obtained using imaging spectroscopy is correlated with site fertility. The study was carried out in Hyytiälä, Finland, in the southern boreal forest zone. We used a database of state-owned forest stands including basic forestry variables and a site fertility index. To test the suitability of imaging spectroscopy with different spatial and spectral resolutions for site fertility mapping, we performed two airborne acquisitions using different sensor configurations. First, the sensor was flown at a high altitude with high spectral resolution resulting in a pixel size in the order of a tree crown. Next, the same area was flown to provide reflectance data with sub-meter spatial resolution. However, to maintain usable signal-to-noise ratios, several spectral channels inside the sensor were combined, thus reducing spectral resolution. We correlated a number of narrowband vegetation indices (describing canopy biochemical composition, structure, and photosynthetic activity) on site fertility. Overall, site fertility had a significant influence on the vegetation indices but the strength of the correlation depended on dominant species. We found that high spatial resolution data calculated from the spectra of sunlit parts of tree crowns had the strongest correlation with site fertility.

Restoration of the fire-grazing interaction in Artemisia filifolia shrubland

USGS Publications Warehouse

Winter, S.L.; Fuhlendorf, S.D.; Goad, C.L.; Davis, C.A.; Hickman, K.R.; Leslie, David M.

2012-01-01

Patterns of landscape heterogeneity are crucial to the maintenance of biodiversity in shrublands and grasslands, yet management practices in these ecosystems typically seek to homogenize landscapes. Furthermore, there is limited understanding of how the interaction of ecological processes, such as fire and grazing, affects patterns of heterogeneity at different spatial scales. We conducted research in Artemisia filifolia (Asteraceae) shrublands located in the southern Great Plains of North America to determine the effect of restoring the fire-grazing interaction on vegetation structure. Data were collected for 3years in replicated pastures grazed by cattle Bos taurus where the fire-grazing interaction had been restored (fire and grazing=treatment pastures) and in pastures that were grazed but remained unburned (grazing only, no fire=control pastures). The effect of the fire-grazing interaction on heterogeneity (variance) of vegetation structure was assessed at scales from 12??5m 2 to 609ha. Most measurements of vegetation structure within treatment pastures differed from control pastures for 1-3years after being burned but were thereafter similar to the values found in unburned control pastures. Treatment pastures were characterized by a lower amount of total heterogeneity and a lower amount of heterogeneity through time. Heterogeneity of vegetation structure tended to decrease as the scale of measurement increased in both treatment and control pastures. There was deviation from this trend, however, in the treatment pastures that exhibited much higher heterogeneity at the patch scale (mean patch size=202ha) of measurement, the scale at which patch fires were conducted. Synthesis and applications.Vegetation structure in A. filifolia shrublands of our study was readily altered by the fire-grazing interaction but also demonstrated substantial resilience to these effects. The fire-grazing interaction also changed the total amount of heterogeneity characterizing this system, the scale at which heterogeneity in this system was expressed and the amount of heterogeneity expressed through time. Land managers seeking to impose a shifting mosaic of heterogeneity on this vegetation type can do so by restoring the fire-grazing interaction with potential conservation benefits similar to what has been achieved in other ecosystems where historic cycles of disturbance and rest have been restored. ?? 2011 The Authors. Journal of Applied Ecology ?? 2011 British Ecological Society.

Terrestrial vegetation redistribution and carbon balance under climate change

PubMed Central

Lucht, Wolfgang; Schaphoff, Sibyll; Erbrecht, Tim; Heyder, Ursula; Cramer, Wolfgang

2006-01-01

Background Dynamic Global Vegetation Models (DGVMs) compute the terrestrial carbon balance as well as the transient spatial distribution of vegetation. We study two scenarios of moderate and strong climate change (2.9 K and 5.3 K temperature increase over present) to investigate the spatial redistribution of major vegetation types and their carbon balance in the year 2100. Results The world's land vegetation will be more deciduous than at present, and contain about 125 billion tons of additional carbon. While a recession of the boreal forest is simulated in some areas, along with a general expansion to the north, we do not observe a reported collapse of the central Amazonian rain forest. Rather, a decrease of biomass and a change of vegetation type occurs in its northeastern part. The ability of the terrestrial biosphere to sequester carbon from the atmosphere declines strongly in the second half of the 21st century. Conclusion Climate change will cause widespread shifts in the distribution of major vegetation functional types on all continents by the year 2100. PMID:16930462

Processing of airborne laser scanning data to generate accurate DTM for floodplain wetland

NASA Astrophysics Data System (ADS)

Szporak-Wasilewska, Sylwia; Mirosław-Świątek, Dorota; Grygoruk, Mateusz; Michałowski, Robert; Kardel, Ignacy

2015-10-01

Structure of the floodplain, especially its topography and vegetation, influences the overland flow and dynamics of floods which are key factors shaping ecosystems in surface water-fed wetlands. Therefore elaboration of the digital terrain model (DTM) of a high spatial accuracy is crucial in hydrodynamic flow modelling in river valleys. In this study the research was conducted in the unique Central European complex of fens and marshes - the Lower Biebrza river valley. The area is represented mainly by peat ecosystems which according to EU Water Framework Directive (WFD) are called "water-dependent ecosystems". Development of accurate DTM in these areas which are overgrown by dense wetland vegetation consisting of alder forest, willow shrubs, reed, sedges and grass is very difficult, therefore to represent terrain in high accuracy the airborne laser scanning data (ALS) with scanning density of 4 points/m2 was used and the correction of the "vegetation effect" on DTM was executed. This correction was performed utilizing remotely sensed images, topographical survey using the Real Time Kinematic positioning and vegetation height measurements. In order to classify different types of vegetation within research area the object based image analysis (OBIA) was used. OBIA allowed partitioning remotely sensed imagery into meaningful image-objects, and assessing their characteristics through spatial and spectral scale. The final maps of vegetation patches that include attributes of vegetation height and vegetation spectral properties, utilized both the laser scanning data and the vegetation indices developed on the basis of airborne and satellite imagery. This data was used in process of segmentation, attribution and classification. Several different vegetation indices were tested to distinguish different types of vegetation in wetland area. The OBIA classification allowed correction of the "vegetation effect" on DTM. The final digital terrain model was compared and examined within distinguished land cover classes (formed mainly by natural vegetation of the river valley) with archival height models developed through interpolation of ground points measured with GPS RTK and also with elevation models from the ASTER-GDEM and SRTM programs. The research presented in this paper allowed improving quality of hydrodynamic modelling in the surface water-fed wetlands protected within Biebrza National Park. Additionally, the comparison with other digital terrain models allowed to demonstrate the importance of accurate topography products in such modelling. The ALS data also significantly improved the accuracy and actuality of the river Biebrza course, its tributaries and location of numerous oxbows typical in this part of the river valley in comparison to previously available data. This type of data also helped to refine the river valley cross-sections, designate river banks and to develop the slope map of the research area.

Spectral modelling of multicomponent landscapes in the Sahel

NASA Technical Reports Server (NTRS)

Hanan, N. P.; Prince, S. D.; Hiernaux, P. H. Y.

1991-01-01

Simple additive models are used to examine the infuence of differing soil types on the spatial average spectral reflectance and normalized difference vegetation index (NDVI). The spatial average NDVI is shown to be a function of the brightness (red plus near-infrared reflectances), the NDVI, and the fractional cover of the components. In landscapes where soil and vegetation can be considered the only components, the NDVI-brightness model can be inverted to obtain the NDVI of vegetation. The red and near-infrared component reflectances of soil and vegetation are determined on the basis of aerial photoradiometer data from Mali. The relationship between the vegetation component NDVI and plant cover is found to be better than between the NDVI of the entire landscape and plant cover. It is concluded that the usefulness of this modeling approach depends on the existence of clearly distinguishable landscape components.

Spatially dependent biotic and abiotic factors drive survivorship and physical structure of green roof vegetation.

PubMed

Aloisio, Jason M; Palmer, Matthew I; Giampieri, Mario A; Tuininga, Amy R; Lewis, James D

2017-01-01

Plant survivorship depends on biotic and abiotic factors that vary at local and regional scales. This survivorship, in turn, has cascading effects on community composition and the physical structure of vegetation. Survivorship of native plant species is variable among populations planted in environmentally stressful habitats like urban roofs, but the degree to which factors at different spatial scales affect survivorship in urban systems is not well understood. We evaluated the effects of biotic and abiotic factors on survivorship, composition, and physical structure of two native perennial species assemblages, one characterized by a mixture of C 4 grasses and forbs (Hempstead Plains, HP) and one characterized by a mixture of C 3 grasses and forbs (Rocky Summit, RS), that were initially sown at equal ratios of growth forms (5:1:4; grass, N-fixing forb and non-N-fixing forb) in replicate 2-m 2 plots planted on 10 roofs in New York City (New York, USA). Of 24 000 installed plants, 40% survived 23 months after planting. Within-roof factors explained 71% of variation in survivorship, with biotic (species identity and assemblage) factors accounting for 54% of the overall variation, and abiotic (growing medium depth and plot location) factors explaining 17% of the variation. Among-roof factors explained 29% of variation in survivorship and increased solar radiation correlated with decreased survivorship. While growing medium properties (pH, nutrients, metals) differed among roofs there was no correlation with survivorship. Percent cover and sward height increased with increasing survivorship. At low survivorship, cover of the HP assemblage was greater compared to the RS assemblage. Sward height of the HP assemblage was about two times greater compared to the RS assemblage. These results highlight the effects of local biotic and regional abiotic drivers on community composition and physical structure of green roof vegetation. As a result, initial green roof plant composition and roof microclimate may have long-term effects on community dynamics, ecosystem function, and urban biodiversity. © 2016 by the Ecological Society of America.

Factors affecting the remotely sensed response of coniferous forest plantations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Danson, F.M.; Curran, P.J.

1993-01-01

Remote sensing of forest biophysical properties has concentrated upon forest sites with a wide range of green vegetation amount and thereby leaf area index and canopy cover. However, coniferous forest plantations, an important forest type in Europe, are managed to maintain a large amount of green vegetation with little spatial variation. Therefore, the strength of the remotely sensed signal will, it is hypothesized, be determined more by the structure of this forest than by its cover. Airborne Thematic Mapper (ATM) and SPOT-1 HRV data were used to determine the effects of this structural variation on the remotely sensed response ofmore » a coniferous forest plantation in the United Kingdom. Red and near infrared radiance were strongly and negatively correlated with a range of structural properties and with the age of the stands but weakly correlated with canopy cover. A composite variable, related to the volume of the canopy, accounted for over 75% of the variation in near infrared radiance. A simple model that related forest structural variables to the remotely sensed response was used to understand and explain this response from a coniferous forest plantation.« less

Quantifying forest vertical structure to determine bird habitat quality in the Greenbelt Corridor, Denton, TX

NASA Astrophysics Data System (ADS)

Matsubayashi, Shiho

This study presents the integration of light detection and range (LiDAR) and hyperspectral remote sensing to create a three-dimensional bird habitat map in the Greenbelt Corridor of the Elm Fork of the Trinity River. This map permits to examine the relationship between forest stand structure, landscape heterogeneity, and bird community composition. A biannual bird census was conducted at this site during the breeding seasons of 2009 and 2010. Census data combined with the three-dimensional map suggest that local breeding bird abundance, community structure, and spatial distribution patterns are highly influenced by vertical heterogeneity of vegetation surface. For local breeding birds, vertical heterogeneity of canopy surface within stands, connectivity to adjacent forest patches, largest forest patch index, and habitat (vegetation) types proved to be the most influential factors to determine bird community assemblages. Results also highlight the critical role of secondary forests to increase functional connectivity of forest patches. Overall, three-dimensional habitat descriptions derived from integrated LiDAR and hyperspectral data serve as a powerful bird conservation tool that shows how the distribution of bird species relates to forest composition and structure at various scales.

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Brien, Sarah L.; Gibbons, Sean M.; Owens, Sarah M.

Soil microbial communities are essential for ecosystem function, but linking community composition to biogeochemical processes is challenging because of high microbial diversity and large spatial variability of most soil characteristics. We investigated soil bacterial community structure in a switchgrass stand planted on soil with a history of grassland vegetation at high spatial resolution to determine whether biogeographic trends occurred at the centimeter scale. Moreover, we tested whether such heterogeneity, if present, influenced community structure within or among ecosystems. Pronounced heterogeneity was observed at centimeter scales, with abrupt changes in relative abundance of phyla from sample to sample. At the ecosystemmore » scale (> 10 m), however, bacterial community composition and structure were subtly, but significantly, altered by fertilization, with higher alpha diversity in fertilized plots. Moreover, by comparing these data with data from 1772 soils from the Earth Microbiome Project, it was found that 20% diverse globally sourced soil samples, while grassland soils shared approximately 40% of their operational taxonomic units with the current study. By spanning several orders of magnitude, the analysis suggested that extreme patchiness characterized community structure at smaller scales but that coherent patterns emerged at larger length scales.« less

Spatial-temporal consistency between gross primary productivity and solar-induced chlorophyll fluorescence of vegetation in China during 2007-2014

NASA Astrophysics Data System (ADS)

Ma, J.; Xiao, X.; Zhang, Y.; Chen, B.; Zhao, B.

2017-12-01

Great significance exists in accurately estimating spatial-temporal patterns of gross primary production (GPP) because of its important role in global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatially time-sires GPP. However, the estimation of the accuracy of GPP simulations from LUE at both spatial and temporal scales is still a challenging work. In this study, we simulated GPP of vegetation in China during 2007-2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images of 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPPVPM) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPPVPM and SIF data over both single year (2010) and multiple years (2007-2014) in China. Annual GPPVPM is significantly positive correlated with SIF (R2>0.43) spatially for all years during 2007-2014 and all seasons in 2010 (R2>0.37). GPP dynamic trends is high spatial-temporal heterogeneous in China during 2007-2014. The results of this study indicate that GPPVPM is temporally and spatially in line with SIF data, and space-borne SIF data have great potential in validating and parameterizing GPP estimation of LUE-based models.

New forest vegetation maps facilitate assessment of biodiversity indicators over large, multi-ownership regions.

Treesearch

Janet L. Ohmann

2003-01-01

Natural resource policy analysis and conservation planning are best served by broad-scale information about vegetation that is detailed, spatially complete, and consistent across land ownerships and allocations. In this paper I describe how a new generation of forest vegetation maps can be used to assess the distribution of vegetation biodiversity among land ownerships...

Spatial distribution of lacunarity of voxelized airborne LiDAR point clouds in various forest assemblages

NASA Astrophysics Data System (ADS)

Székely, Balázs; Kania, Adam; Standovár, Tibor; Heilmeier, Hermann

2015-04-01

Forest ecosystems have characteristic structure of features defined by various structural elements of different scales and vertical positions: shrub layers, understory vegetation, tree trunks, and branches. Furthermore in most of the cases there are superimposed structures in distributions (mosaic or island patterns) due to topography, soil variability, or even anthropogenic factors like past/present forest management activity. This multifaceted spatial context of the forests is relevant for many ecological issues, especially for maintaining forest biodiversity. Our aim in this study is twofold: (1) to quantify this structural variability laterally and vertically using lacunarity, and (2) to relate these results to relevant ecological features, i.e quantitatively described forest properties. Airborne LiDAR data of various quality and point density have been used for our study including a number of forested sites in Central and East Europe (partly Natura 2000 sites). The point clouds have been converted to voxel format and then converted to horizontal layers as images. These images were processed further for the lacunarity calculation. Areas of interest (AOIs) have been selected based on evaluation of the forested areas and auxiliary field information. The calculation has been performed for the AOIs for all available vertical data slices. The lacunarity function referring to a certain point and given vicinity varies horizontally and vertically, depending on the vegetation structure. Furthermore, the topography may also influence this property as the growth of plants, especially spacing and size of trees are influenced by the local topography and relief (e.g., slope, aspect). The comparisons of the flatland and hilly settings show interesting differences and the spatial patterns also vary differently. Because of the large amount of data resulting from these calculations, sophisticated methods are required to analyse the results. The large data amount then has been structured according to AOIs and relevant AOI pairs or small groups have been formed for comparative purposes. Change detection techniques have been applied to reveal fine differences. The spatial variation can be related to ecologically relevant forest characteristics. Data used in this study have been acquired in the framework of ChangeHabitat2 project (an IAPP Marie Curie Actions project of the European Union), in Hungarian-Slovakian Transnational Cooperation Programme 2007-2013, "Management of World Heritage Aggtelek Karst/Slovakian Karst Caves" (HUSK/1101/221/0180, Aggtelek NP). These studies were partly carried out in the project 'Multipurpose assessment serving forest biodiversity conservation in the Carpathian region of Hungary', Swiss-Hungarian Cooperation Programme (SH/4/13 Project). BS contributed as an Alexander von Humboldt Research Fellow.

Identifying residential neighbourhood types from settlement points in a machine learning approach.

PubMed

Jochem, Warren C; Bird, Tomas J; Tatem, Andrew J

2018-05-01

Remote sensing techniques are now commonly applied to map and monitor urban land uses to measure growth and to assist with development and planning. Recent work in this area has highlighted the use of textures and other spatial features that can be measured in very high spatial resolution imagery. Far less attention has been given to using geospatial vector data (i.e. points, lines, polygons) to map land uses. This paper presents an approach to distinguish residential settlement types (regular vs. irregular) using an existing database of settlement points locating structures. Nine data features describing the density, distance, angles, and spacing of the settlement points are calculated at multiple spatial scales. These data are analysed alone and with five common remote sensing measures on elevation, slope, vegetation, and nighttime lights in a supervised machine learning approach to classify land use areas. The method was tested in seven provinces of Afghanistan (Balkh, Helmand, Herat, Kabul, Kandahar, Kunduz, Nangarhar). Overall accuracy ranged from 78% in Kandahar to 90% in Nangarhar. This research demonstrates the potential to accurately map land uses from even the simplest representation of structures.

the Role of Species, Structure, and Biochemical Traits in the Spatial Distribution of a Woodland Community

NASA Astrophysics Data System (ADS)

Adeline, K.; Ustin, S.; Roth, K. L.; Huesca Martinez, M.; Schaaf, C.; Baldocchi, D. D.; Gastellu-Etchegorry, J. P.

2015-12-01

The assessment of canopy biochemical diversity is critical for monitoring ecological and physiological functioning and for mapping vegetation change dynamics in relation to environmental resources. For example in oak woodland savannas, these dynamics are mainly driven by water constraints. Inversion using radiative transfer theory is one method for estimating canopy biochemistry. However, this approach generally only considers relatively simple scenarios to model the canopy due to the difficulty in encompassing stand heterogeneity with spatial and temporal consistency. In this research, we compared 3 modeling strategies for estimating canopy biochemistry variables (i.e. chlorophyll, carotenoids, water, dry matter) by coupling of the PROSPECT (leaf level) and DART (canopy level) models : i) a simple forest representation made of ellipsoid trees, and two representations taking into account the tree species and structural composition, and the landscape spatial pattern, using (ii) geometric tree crown shapes and iii) detailed tree crown and wood structure retrieved from terrestrial lidar acquisitions. AVIRIS 18m remote sensing data are up-scaled to simulate HyspIRI 30m images. Both spatial resolutions are validated by measurements acquired during 2013-2014 field campaigns (cover/tree inventory, LAI, leaf sampling, optical measures). The results outline the trade-off between accurate and abstract canopy modeling for inversion purposes and may provide perspectives to assess the impact of the California drought with multi-temporal monitoring of canopy biochemistry traits.

MODIS Vegetative Cover Conversion and Vegetation Continuous Fields

NASA Astrophysics Data System (ADS)

Carroll, Mark; Townshend, John; Hansen, Matthew; DiMiceli, Charlene; Sohlberg, Robert; Wurster, Karl

Land cover change occurs at various spatial and temporal scales. For example, large-scale mechanical removal of forests for agro-industrial activities contrasts with the small-scale clearing of subsistence farmers. Such dynamics vary in spatial extent and rate of land conversion. Such changes are attributable to both natural and anthropogenic factors. For example, lightning- or human-ignited fires burn millions of acres of land surface each year. Further, land cover conversion requires ­contrasting with the land cover modification. In the first instance, the dynamic represents extensive categorical change between two land cover types. Land cover modification mechanisms such as selective logging and woody encroachment depict changes within a given land cover type rather than a conversion from one land cover type to another. This chapter describes the production of two standard MODIS land products used to document changes in global land cover. The Vegetative Cover Conversion (VCC) product is designed primarily to serve as a global alarm for areas where land cover change occurs rapidly (Zhan et al. 2000). The Vegetation Continuous Fields (VCF) product is designed to continuously ­represent ground cover as a proportion of basic vegetation traits. Terra's launch in December 1999 afforded a new opportunity to observe the entire Earth every 1.2 days at 250-m spatial resolution. The MODIS instrument's appropriate spatial and ­temporal resolutions provide the opportunity to substantially improve the characterization of the land surface and changes occurring thereupon (Townshend et al. 1991).

Water availability as a driver of spatial and temporal variability in vegetation in the La Mancha plain (Spain): Implications for the land-surface energy, water and carbon budget

NASA Astrophysics Data System (ADS)

Los, Sietse

2017-04-01

Vegetation is water limited in large areas of Spain and therefore a close link exists between vegetation greenness observed from satellite and moisture availability. Here we exploit this link to infer spatial and temporal variability in moisture from MODIS NDVI data and thermal data. Discrepancies in the precipitation - vegetation relationship indicate areas with an alternative supply of water (i.e. not rainfall), this can be natural where moisture is supplied by upwelling groundwater, or can be artificial where crops are irrigated. As a result spatial and temporal variability in vegetation in the La Mancha Plain appears closely linked to topography, geology, rainfall and land use. Crop land shows large variability in year-to-year vegetation greenness; for some areas this variability is linked to variability in rainfall but in other cases this variability is linked to irrigation. The differences in irrigation treatment within one plant functional type, in this case crops, will lead to errors in land surface models when ignored. The magnitude of these effects on the energy, carbon and water balance are assessed at the scale of 250 m to 200 km. Estimating the water balance correctly is of particular important since in some areas in Spain more water is used for irrigation than is supplemented by rainfall.

[Temporal and spatial heterogeneity analysis of optimal value of sensitive parameters in ecological process model: The BIOME-BGC model as an example.

PubMed

Li, Yi Zhe; Zhang, Ting Long; Liu, Qiu Yu; Li, Ying

2018-01-01

The ecological process models are powerful tools for studying terrestrial ecosystem water and carbon cycle at present. However, there are many parameters for these models, and weather the reasonable values of these parameters were taken, have important impact on the models simulation results. In the past, the sensitivity and the optimization of model parameters were analyzed and discussed in many researches. But the temporal and spatial heterogeneity of the optimal parameters is less concerned. In this paper, the BIOME-BGC model was used as an example. In the evergreen broad-leaved forest, deciduous broad-leaved forest and C3 grassland, the sensitive parameters of the model were selected by constructing the sensitivity judgment index with two experimental sites selected under each vegetation type. The objective function was constructed by using the simulated annealing algorithm combined with the flux data to obtain the monthly optimal values of the sensitive parameters at each site. Then we constructed the temporal heterogeneity judgment index, the spatial heterogeneity judgment index and the temporal and spatial heterogeneity judgment index to quantitatively analyze the temporal and spatial heterogeneity of the optimal values of the model sensitive parameters. The results showed that the sensitivity of BIOME-BGC model parameters was different under different vegetation types, but the selected sensitive parameters were mostly consistent. The optimal values of the sensitive parameters of BIOME-BGC model mostly presented time-space heterogeneity to different degrees which varied with vegetation types. The sensitive parameters related to vegetation physiology and ecology had relatively little temporal and spatial heterogeneity while those related to environment and phenology had generally larger temporal and spatial heterogeneity. In addition, the temporal heterogeneity of the optimal values of the model sensitive parameters showed a significant linear correlation with the spatial heterogeneity under the three vegetation types. According to the temporal and spatial heterogeneity of the optimal values, the parameters of the BIOME-BGC model could be classified in order to adopt different parameter strategies in practical application. The conclusion could help to deeply understand the parameters and the optimal values of the ecological process models, and provide a way or reference for obtaining the reasonable values of parameters in models application.

Predicting intensity of white-tailed deer herbivory in the Central Appalachian Mountains

USGS Publications Warehouse

Kniowski, Andrew B.; Ford, W. Mark

2018-01-01

In eastern North America, white-tailed deer (Odocoileus virginianus) can have profound influences on forest biodiversity and forest successional processes. Moderate to high deer populations in the central Appalachians have resulted in lower forest biodiversity. Legacy effects in some areas persist even following deer population reductions or declines. This has prompted managers to consider deer population management goals in light of policies designed to support conservation of biodiversity and forest regeneration while continuing to support ample recreational hunting opportunities. However, despite known relationships between herbivory intensity and biodiversity impact, little information exists on the predictability of herbivory intensity across the varied and spatially diverse habitat conditions of the central Appalachians. We examined the predictability of browsing rates across central Appalachian landscapes at four environmental scales: vegetative community characteristics, physical environment, habitat configuration, and local human and deer population demographics. In an information-theoretic approach, we found that a model fitting the number of stems browsed relative to local vegetation characteristics received most (62%) of the overall support of all tested models assessing herbivory impact. Our data suggest that deer herbivory responded most predictably to differences in vegetation quantity and type. No other spatial factors or demographic factors consistently affected browsing intensity. Because herbivory, vegetation communities, and productivity vary spatially, we suggest that effective broad-scale herbivory impact assessment should include spatially-balanced vegetation monitoring that accounts for regional differences in deer forage preference. Effective monitoring is necessary to avoid biodiversity impacts and deleterious changes in vegetation community composition that are difficult to reverse and/or may not be detected using traditional deer-density based management goals.

Change of spatial information under rescaling: A case study using multi-resolution image series

NASA Astrophysics Data System (ADS)

Chen, Weirong; Henebry, Geoffrey M.

Spatial structure in imagery depends on a complicated interaction between the observational regime and the types and arrangements of entities within the scene that the image portrays. Although block averaging of pixels has commonly been used to simulate coarser resolution imagery, relatively little attention has been focused on the effects of simple rescaling on spatial structure and the explanation and a possible solution to the problem. Yet, if there are significant differences in spatial variance between rescaled and observed images, it may affect the reliability of retrieved biogeophysical quantities. To investigate these issues, a nested series of high spatial resolution digital imagery was collected at a research site in eastern Nebraska in 2001. An airborne Kodak DCS420IR camera acquired imagery at three altitudes, yielding nominal spatial resolutions ranging from 0.187 m to 1 m. The red and near infrared (NIR) bands of the co-registered image series were normalized using pseudo-invariant features, and the normalized difference vegetation index (NDVI) was calculated. Plots of grain sorghum planted in orthogonal crop row orientations were extracted from the image series. The finest spatial resolution data were then rescaled by averaging blocks of pixels to produce a rescaled image series that closely matched the spatial resolution of the observed image series. Spatial structures of the observed and rescaled image series were characterized using semivariogram analysis. Results for NDVI and its component bands show, as expected, that decreasing spatial resolution leads to decreasing spatial variability and increasing spatial dependence. However, compared to the observed data, the rescaled images contain more persistent spatial structure that exhibits limited variation in both spatial dependence and spatial heterogeneity. Rescaling via simple block averaging fails to consider the effect of scene object shape and extent on spatial information. As the features portrayed by pixels are equally weighted regardless of the shape and extent of the underlying scene objects, the rescaled image retains more of the original spatial information than would occur through direct observation at a coarser sensor spatial resolution. In contrast, for the observed images, due to the effect of the modulation transfer function (MTF) of the imaging system, high frequency features like edges are blurred or lost as the pixel size increases, resulting in greater variation in spatial structure. Successive applications of a low-pass spatial convolution filter are shown to mimic a MTF. Accordingly, it is recommended that such a procedure be applied prior to rescaling by simple block averaging, if insufficient image metadata exist to replicate the net MTF of the imaging system, as might be expected in land cover change analysis studies using historical imagery.

Vegetation-induced spatial variability of soil redox properties in wetlands

NASA Astrophysics Data System (ADS)

Szalai, Zoltán; Jakab, Gergely; Kiss, Klaudia; Ringer, Marianna; Balázs, Réka; Zacháry, Dóra; Horváth Szabó, Kata; Perényi, Katalin

2016-04-01

Vegetation induced land patches may result spatial pattern of on soil Eh and pH. These spatial pattern are mainly emerged by differences of aeration and exudation of assimilates. Present paper focuses on vertical extent and temporal dynamics of these patterns in wetlands. Two study sites were selected: 1. a plain wetland on calcareous sandy parent material (Ceglédbercel, Danube-Tisza Interfluve, Hungary); 2. headwater wetland with calcareous loamy parent material (Bátaapáti, Hungary). Two vegetation patches were studied in site 1: sedgy (dominated by Carex riparia) and reedy (dominated by Phragmites australis). Three patches were studied in site2: sedgy1 (dominated by C vulpina), sedgy 2 (C. riparia); nettle-horsetail (Urtica dioica and Equisetum arvense). Boundaries between patches were studied separately. Soil redox, pH and temperature studied by automated remote controlled instruments. Three digital sensors (Ponsell) were installed in each locations: 20cm and 40cm sensors represent the solum and 100 cm sensor monitors the subsoil). Groundwater wells were installed near to triplets for soil water sampling. Soil Eh, pH and temperature values were recorded in each 10 minutes. Soil water sampling for iron and DOC were carried out during saturated periods. Spatial pattern of soil Eh is clearly caused by vegetation. We measured significant differences between Eh values of the studied patches in the solum. We did not find this kinds horizontal differences in the subsoil. Boundaries of the patches usually had more reductive soil environment than the core areas. We have found temporal dynamics of the spatial redox pattern. Differences were not so well expressed during wintertime. These spatial patterns had influence on the DOC and iron content of porewater, as well. Highest temporal dynamics of soil redox properties and porewater iron could be found in the boundaries. These observations refer to importance patchiness of vegetation on soil chemical properties in wetlands. Authors are grateful to Hungarian Scientific research Fund (K100180)

Monitoring ecosystem reclamation recovery using optical remote sensing: Comparison with field measurements and eddy covariance.

PubMed

Chasmer, L; Baker, T; Carey, S K; Straker, J; Strilesky, S; Petrone, R

2018-06-12

Time series remote sensing vegetation indices derived from SPOT 5 data are compared with vegetation structure and eddy covariance flux data at 15 dry to wet reclamation and reference sites within the Oil Sands region of Alberta, Canada. This comprehensive analysis examines the linkages between indicators of ecosystem function and change trajectories observed both at the plot level and within pixels. Using SPOT imagery, we find that higher spatial resolution datasets (e.g. 10 m) improves the relationship between vegetation indices and structural measurements compared with interpolated (lower resolution) pixels. The simple ratio (SR) vegetation index performs best when compared with stem density-based indicators (R 2  = 0.65; p < 0.00), while the normalised difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI) are most comparable to foliage indicators (leaf area index (LAI) and canopy cover (R 2  = 0.52-0.78; p > 0.02). Fluxes (net ecosystem production (NEP) and gross ecosystem production (GEP)) are most related to NDVI and SAVI when these are interpolated to larger 20 m × 20 m pixels (R 2  = 0.44-0.50; p < 0.00). As expected, decreased sensitivity of NDVI is problematic for sites with LAI > 3 m 2  m -2 , making this index more appropriate for newly regenerating reclamation areas. For sites with LAI < 3 m 2  m -2 , trajectories of vegetation change can be mapped over time and are within 2.7% and 3.3% of annual measured LAI changes observed at most sites. This study demonstrates the utility of remote sensing in combination with field and eddy covariance data for monitoring and scaling of reclaimed and reference site productivity within and beyond the Oil Sands Region of western Canada. Copyright © 2018 Elsevier B.V. All rights reserved.

Vegetation Disturbance and Recovery Following a Rare Windthrow Event in the Great Smoky Mountains National Park

NASA Astrophysics Data System (ADS)

Bernardes, S.; Madden, M.

2016-06-01

The tornado outbreak of April 2011 in the Southeastern United States caused major damage to property and natural ecosystems. During the outbreak, the Great Smoky Mountains National Park (GRSM) was hit by an EF4 tornado, resulting in a long strip of broken branches and toppled old-growth forest trees. Little is known of the consequences of extreme windthrow events, partly due to limitations in characterizing and monitoring wind-driven vegetation disturbance and recovery over large areas and over time. This work analyzed vegetation damage in the GRSM resulting from the 2011 tornado outbreak and monitored vegetation recovery in the region over a four-year period. Anomalies of the Enhanced Vegetation Index (EVI) calculated using Landsat scenes showed that the 2011 tornado affected 21.38 km2 of forest, including submesic to mesic oak/hardwoods, Southern Appalachian cove hardwood forests and montane alluvial forests. Tornado damage severity was mapped and investigated by using anomalies of EVI over space and time and showed track discontinuity and significant variation in damage intensity along the tornado track, suggesting vortex-topography interactions. Temporal profiles and spatial representations of EVI anomalies for the period 2011-2015 indicated that EVI in 2015 was above pre-event values, indicating homogeneous canopy and lack of vertical structure during regrowth.

Disentangling vegetation diversity from climate–energy and habitat heterogeneity for explaining animal geographic patterns

USGS Publications Warehouse

Jimenez-Alfaro, Borja; Chytry, Milan; Mucina, Ladislav; Grace, James B.; Rejmanek, Marcel

2016-01-01

Broad-scale animal diversity patterns have been traditionally explained by hypotheses focused on climate–energy and habitat heterogeneity, without considering the direct influence of vegetation structure and composition. However, integrating these factors when considering plant–animal correlates still poses a major challenge because plant communities are controlled by abiotic factors that may, at the same time, influence animal distributions. By testing whether the number and variation of plant community types in Europe explain country-level diversity in six animal groups, we propose a conceptual framework in which vegetation diversity represents a bridge between abiotic factors and animal diversity. We show that vegetation diversity explains variation in animal richness not accounted for by altitudinal range or potential evapotranspiration, being the best predictor for butterflies, beetles, and amphibians. Moreover, the dissimilarity of plant community types explains the highest proportion of variation in animal assemblages across the studied regions, an effect that outperforms the effect of climate and their shared contribution with pure spatial variation. Our results at the country level suggest that vegetation diversity, as estimated from broad-scale classifications of plant communities, may contribute to our understanding of animal richness and may be disentangled, at least to a degree, from climate–energy and abiotic habitat heterogeneity.

The landscape of fear as an emergent property of heterogeneity: Contrasting patterns of predation risk in grassland ecosystems.

PubMed

Atuo, Fidelis Akunke; O'Connell, Timothy John

2017-07-01

The likelihood of encountering a predator influences prey behavior and spatial distribution such that non-consumptive effects can outweigh the influence of direct predation. Prey species are thought to filter information on perceived predator encounter rates in physical landscapes into a landscape of fear defined by spatially explicit heterogeneity in predation risk. The presence of multiple predators using different hunting strategies further complicates navigation through a landscape of fear and potentially exposes prey to greater risk of predation. The juxtaposition of land cover types likely influences overlap in occurrence of different predators, suggesting that attributes of a landscape of fear result from complexity in the physical landscape. Woody encroachment in grasslands furnishes an example of increasing complexity with the potential to influence predator distributions. We examined the role of vegetation structure on the distribution of two avian predators, Red-tailed Hawk ( Buteo jamaicensis ) and Northern Harrier ( Circus cyaneus ), and the vulnerability of a frequent prey species of those predators, Northern Bobwhite ( Colinus virginianus ). We mapped occurrences of the raptors and kill locations of Northern Bobwhite to examine spatial vulnerability patterns in relation to landscape complexity. We use an offset model to examine spatially explicit habitat use patterns of these predators in the Southern Great Plains of the United States, and monitored vulnerability patterns of their prey species based on kill locations collected during radio telemetry monitoring. Both predator density and predation-specific mortality of Northern Bobwhite increased with vegetation complexity generated by fine-scale interspersion of grassland and woodland. Predation pressure was lower in more homogeneous landscapes where overlap of the two predators was less frequent. Predator overlap created areas of high risk for Northern Bobwhite amounting to 32% of the land area where landscape complexity was high and 7% where complexity was lower. Our study emphasizes the need to evaluate the role of landscape structure on predation dynamics and reveals another threat from woody encroachment in grasslands.

Mapping vegetation and fuels for fire management on the Gila National Forest Complex, New Mexico

Treesearch

Robert E. Keane; Scott A. Mincemoyer; Kirsten M. Schmidt; Donald G. Long; Janice L. Garner

2000-01-01

(Please note: This PDF is part of a CD-ROM package only and was not printed on paper.) Fuels and vegetation spatial data layers required by the spatially explicit fire growth model FARSITE were developed for all lands in and around the Gila National Forest in New Mexico. Satellite imagery, terrain modeling, and biophysical simulation were used to create the three...

Seasonal albedo of an urban/rural landscape from satellite observations

NASA Technical Reports Server (NTRS)

Brest, Christopher L.

1987-01-01

Using data from 27 calibrated Landsat observations of the Hartford, Connecticut area, the spatial distribution and seasonal variation of surface reflectance and albedo were examined. Mean values of visible reflectance, near-IR reflectance, and albedo are presented (for both snow-free and snow-cover observations) according to 14 land use/land cover categories. A diversity of albedo values was found to exist in this type of environment, associated with land cover. Many land-cover categories display a seasonal dependence, with intracategory seasonal differences being of comparable magnitude to intercategory differences. Key factors in determining albedo (and its seasonal dynamics) are the presence or absence of vegetation and the canopy structure. Snow-cover/snow-free differences range from a few percent (for urban land covers) to over 40 percent (for low-canopy vegetation).

Habitat suitability of patch types: a case study of the Yosemite toad

USGS Publications Warehouse

Liang, Christina T.; Stohlgren, Thomas J.

2011-01-01

Understanding patch variability is crucial in understanding the spatial population structure of wildlife species, especially for rare or threatened species. We used a well-tested maximum entropy species distribution model (Maxent) to map the Yosemite toad (Anaxyrus (= Bufo) canorus) in the Sierra Nevada mountains of California. Twenty-six environmental variables were included in the model representing climate, topography, land cover type, and disturbance factors (e.g., distances to agricultural lands, fire perimeters, and timber harvest areas) throughout the historic range of the toad. We then took a novel approach to the study of spatially structured populations by applying the species-environmental matching model separately for 49 consistently occupied sites of the Yosemite toad compared to 27 intermittently occupied sites. We found that the distribution of the entire population was highly predictable (AUC = 0.95±0.03 SD), and associated with low slopes, specific vegetation types (wet meadow, alpine-dwarf shrub, montane chaparral, red fir, and subalpine conifer), and warm temperatures. The consistently occupied sites were also associated with these same factors, and they were also highly predictable (AUC = 0.95±0.05 SD). However, the intermittently occupied sites were associated with distance to fire perimeter, a slightly different response to vegetation types, distance to timber harvests, and a much broader set of aspect classes (AUC = 0.90±0.11 SD). We conclude that many studies of species distributions may benefit by modeling spatially structured populations separately. Modeling and monitoring consistently-occupied sites may provide a realistic snapshot of current species-environment relationships, important climatic and topographic patterns associated with species persistence patterns, and an understanding of the plasticity of the species to respond to varying climate regimes across its range. Meanwhile, modeling and monitoring of widely dispersing individuals and intermittently occupied sites may uncover environmental thresholds and human-related threats to population persistence.

LEAF AREA INDEX CHANGE DETECTION OF UNDERSTORY VEGETATION IN THE ALBEMARLE-PAMLICO BASIN USING IKOMOS AND LANDSAT ETM+ SATELLITE DATA

EPA Science Inventory

The advent of remotely sensed data from satellite platforms has enabled the research community to examine vegetative spatial distributions over regional and global scales. This assessment of ecosystem condition through the synoptic monitoring of terrestrial vegetation extent, bio...

LEAF AREA INDEX (LAI) CHANGES DETECTION OF UNDERSTORY VEGETATION IN THE ALBEMARLE-PAMLICO BASIN IKONOS AND LANDSAT ETM+ SATELLITE DATA

EPA Science Inventory

The advent of remotely sensed data from satellite platforms has enabled the research community to examine vegetative spatial distributions over regional and global scales. This assessment of ecosystem condition through the synoptic monitoring of terrestrial vegetation extent, bio...

Development of a Multi-experience Approach in Introductory Soil and Vegetation Geography Courses.

ERIC Educational Resources Information Center

Limbird, Arthur

1982-01-01

Describes an introductory college level course in soil and vegetation which uses lecture, audiovisual tutorial, individualized instruction, field trips, films, and games. The course consists of three segments: basic concepts of soils, basic concepts of plants, and soil and vegetation concepts in a spatial context. (KC)

Temporal and spatial analysis of vegetation coverage changes in Ordos area based on time series GIMMS-NDVI data

NASA Astrophysics Data System (ADS)

Han, Ruimei; Zou, Youfeng; Ma, Chao; Liu, Pei

2014-11-01

Ordos area is the desert-wind erosion desertification steppe transition zone and the complex ecological zone. As the research area, Ordos City has the similar natural geographic environment to ShenDong coalfield. To research its ecological patterns and natural evolution law, it has instructive to reveal temporal and spatial changes of ecological environment with artificial disturbance in western mining. In this paper, a time series of AVHRR-NDVI(Normalized Difference Vegetation Index) data was used to monitor the change of vegetation temporal and spatial dynamics from 1981 to 2006 in Ordos City and ShenDong coalfield, where were as the research area. The MVC (Maximum Value Composites) method, average operation, linear regression, and gradation for NDVI change trend were used to obtained some results, as follows: ¬vegetation coverage had obvious characteristics with periodic change in research area for 26 years, and vegetation growth peak appeared on August, while the lowest appeared on January. The extreme values in Ordos City were 0.2351 and 0.1176, while they were 0.2657 and 0.1272 in ShenDong coalfield. The NDVI value fluctuation was a modest rise trend overall in research area. The extreme values were 0.3071 and 0.1861 in Ordos City, while they were 0.3454 and 0.1904 in ShenDong coalfield. In spatial distribution, slight improvement area and slight degradation area were accounting for 42.49% and 8.37% in Ordos City, while slight improvement area moderate improvement area were accounting for 70.59% and 29.41% in ShenDong coalfield. Above of results indicated there was less vegetation coverage in research area, which reflected the characteristics of fragile natural geographical environment. In addition, vegetation coverage was with a modest rise on the whole, which reflected the natural environment change.

Understory vegetation mediates permafrost active layer dynamics and carbon dioxide fluxes in open-canopy larch forests of northeastern Siberia.

PubMed

Loranty, Michael M; Berner, Logan T; Taber, Eric D; Kropp, Heather; Natali, Susan M; Alexander, Heather D; Davydov, Sergey P; Zimov, Nikita S

2018-01-01

Arctic ecosystems are characterized by a broad range of plant functional types that are highly heterogeneous at small (~1-2 m) spatial scales. Climatic changes can impact vegetation distribution directly, and also indirectly via impacts on disturbance regimes. Consequent changes in vegetation structure and function have implications for surface energy dynamics that may alter permafrost thermal dynamics, and are therefore of interest in the context of permafrost related climate feedbacks. In this study we examine small-scale heterogeneity in soil thermal properties and ecosystem carbon and water fluxes associated with varying understory vegetation in open-canopy larch forests in northeastern Siberia. We found that lichen mats comprise 16% of understory vegetation cover on average in open canopy larch forests, and lichen abundance was inversely related to canopy cover. Relative to adjacent areas dominated by shrubs and moss, lichen mats had 2-3 times deeper permafrost thaw depths and surface soils warmer by 1-2°C in summer and less than 1°C in autumn. Despite deeper thaw depths, ecosystem respiration did not differ across vegetation types, indicating that autotrophic respiration likely dominates areas with shrubs and moss. Summertime net ecosystem exchange of CO2 was negative (i.e. net uptake) in areas with high shrub cover, while positive (i.e. net loss) in lichen mats and areas with less shrub cover. Our results highlight relationships between vegetation and soil thermal dynamics in permafrost ecosystems, and underscore the necessity of considering both vegetation and permafrost dynamics in shaping carbon cycling in permafrost ecosystems.

Deforestation and benthic indicators: how much vegetation cover is needed to sustain healthy Andean streams?

PubMed

Iñiguez-Armijos, Carlos; Leiva, Adrián; Frede, Hans-Georg; Hampel, Henrietta; Breuer, Lutz

2014-01-01

Deforestation in the tropical Andes is affecting ecological conditions of streams, and determination of how much forest should be retained is a pressing task for conservation, restoration and management strategies. We calculated and analyzed eight benthic metrics (structural, compositional and water quality indices) and a physical-chemical composite index with gradients of vegetation cover to assess the effects of deforestation on macroinvertebrate communities and water quality of 23 streams in southern Ecuadorian Andes. Using a geographical information system (GIS), we quantified vegetation cover at three spatial scales: the entire catchment, the riparian buffer of 30 m width extending the entire stream length, and the local scale defined for a stream reach of 100 m in length and similar buffer width. Macroinvertebrate and water quality metrics had the strongest relationships with vegetation cover at catchment and riparian scales, while vegetation cover did not show any association with the macroinvertebrate metrics at local scale. At catchment scale, the water quality metrics indicate that ecological condition of Andean streams is good when vegetation cover is over 70%. Further, macroinvertebrate community assemblages were more diverse and related in catchments largely covered by native vegetation (>70%). Our results suggest that retaining an important quantity of native vegetation cover within the catchments and a linkage between headwater and riparian forests help to maintain and improve stream biodiversity and water quality in Andean streams affected by deforestation. This research proposes that a strong regulation focused to the management of riparian buffers can be successful when decision making is addressed to conservation/restoration of Andean catchments.

Deforestation and Benthic Indicators: How Much Vegetation Cover Is Needed to Sustain Healthy Andean Streams?

PubMed Central

Iñiguez–Armijos, Carlos; Leiva, Adrián; Frede, Hans–Georg; Hampel, Henrietta; Breuer, Lutz

2014-01-01

Deforestation in the tropical Andes is affecting ecological conditions of streams, and determination of how much forest should be retained is a pressing task for conservation, restoration and management strategies. We calculated and analyzed eight benthic metrics (structural, compositional and water quality indices) and a physical-chemical composite index with gradients of vegetation cover to assess the effects of deforestation on macroinvertebrate communities and water quality of 23 streams in southern Ecuadorian Andes. Using a geographical information system (GIS), we quantified vegetation cover at three spatial scales: the entire catchment, the riparian buffer of 30 m width extending the entire stream length, and the local scale defined for a stream reach of 100 m in length and similar buffer width. Macroinvertebrate and water quality metrics had the strongest relationships with vegetation cover at catchment and riparian scales, while vegetation cover did not show any association with the macroinvertebrate metrics at local scale. At catchment scale, the water quality metrics indicate that ecological condition of Andean streams is good when vegetation cover is over 70%. Further, macroinvertebrate community assemblages were more diverse and related in catchments largely covered by native vegetation (>70%). Our results suggest that retaining an important quantity of native vegetation cover within the catchments and a linkage between headwater and riparian forests help to maintain and improve stream biodiversity and water quality in Andean streams affected by deforestation. This research proposes that a strong regulation focused to the management of riparian buffers can be successful when decision making is addressed to conservation/restoration of Andean catchments. PMID:25147941

Understanding interaction effects of climate change and fire management on bird distributions through combined process and habitat models

USGS Publications Warehouse

White, Joseph D.; Gutzwiller, Kevin J.; Barrow, Wylie C.; Johnson-Randall, Lori; Zygo, Lisa; Swint, Pamela

2011-01-01

Avian conservation efforts must account for changes in vegetation composition and structure associated with climate change. We modeled vegetation change and the probability of occurrence of birds to project changes in winter bird distributions associated with climate change and fire management in the northern Chihuahuan Desert (southwestern U.S.A.). We simulated vegetation change in a process-based model (Landscape and Fire Simulator) in which anticipated climate change was associated with doubling of current atmospheric carbon dioxide over the next 50 years. We estimated the relative probability of bird occurrence on the basis of statistical models derived from field observations of birds and data on vegetation type, topography, and roads. We selected 3 focal species, Scaled Quail (Callipepla squamata), Loggerhead Shrike (Lanius ludovicianus), and Rock Wren (Salpinctes obsoletus), that had a range of probabilities of occurrence for our study area. Our simulations projected increases in relative probability of bird occurrence in shrubland and decreases in grassland and Yucca spp. and ocotillo (Fouquieria splendens) vegetation. Generally, the relative probability of occurrence of all 3 species was highest in shrubland because leaf-area index values were lower in shrubland. This high probability of occurrence likely is related to the species' use of open vegetation for foraging. Fire suppression had little effect on projected vegetation composition because as climate changed there was less fuel and burned area. Our results show that if future water limits on plant type are considered, models that incorporate spatial data may suggest how and where different species of birds may respond to vegetation changes.

Understanding interaction effects of climate change and fire management on bird distributions through combined process and habitat models

USGS Publications Warehouse

White, Joseph D.; Gutzwiller, Kevin J.; Barrow, Wylie C.; Johnson-Randall, Lori; Zygo, Lisa; Swint, Pamela

2011-01-01

Avian conservation efforts must account for changes in vegetation composition and structure associated with climate change. We modeled vegetation change and the probability of occurrence of birds to project changes in winter bird distributions associated with climate change and fire management in the northern Chihuahuan Desert (southwestern U.S.A.). We simulated vegetation change in a process-based model (Landscape and Fire Simulator) in which anticipated climate change was associated with doubling of current atmospheric carbon dioxide over the next 50 years. We estimated the relative probability of bird occurrence on the basis of statistical models derived from field observations of birds and data on vegetation type, topography, and roads. We selected 3 focal species, Scaled Quail (Callipepla squamata), Loggerhead Shrike (Lanius ludovicianus), and Rock Wren (Salpinctes obsoletus), that had a range of probabilities of occurrence for our study area. Our simulations projected increases in relative probability of bird occurrence in shrubland and decreases in grassland and Yucca spp. and ocotillo (Fouquieria splendens) vegetation. Generally, the relative probability of occurrence of all 3 species was highest in shrubland because leaf-area index values were lower in shrubland. This high probability of occurrence likely is related to the species' use of open vegetation for foraging. Fire suppression had little effect on projected vegetation composition because as climate changed there was less fuel and burned area. Our results show that if future water limits on plant type are considered, models that incorporate spatial data may suggest how and where different species of birds may respond to vegetation changes. ??2011 Society for Conservation Biology.

Mapping and exploring variation in post-fire vegetation recovery following mixed severity wildfire using airborne LiDAR.

PubMed

Gordon, Christopher E; Price, Owen F; Tasker, Elizabeth M

2017-07-01

There is a public perception that large high-severity wildfires decrease biodiversity and increase fire hazard by homogenizing vegetation composition and increasing the cover of mid-story vegetation. But a growing literature suggests that vegetation responses are nuanced. LiDAR technology provides a promising remote sensing tool to test hypotheses about post-fire vegetation regrowth because vegetation cover can be quantified within different height strata at fine scales over large areas. We assess the usefulness of airborne LiDAR data for measuring post-fire mid-story vegetation regrowth over a range of spatial resolutions (10 × 10 m, 30 × 30 m, 50 × 50 m, 100 × 100 m cell size) and investigate the effect of fire severity on regrowth amount and spatial pattern following a mixed severity wildfire in Warrumbungle National Park, Australia. We predicted that recovery would be more vigorous in areas of high fire severity, because park managers observed dense post-fire regrowth in these areas. Moderate to strong positive associations were observed between LiDAR and field surveys of mid-story vegetation cover between 0.5-3.0 m. Thus our LiDAR survey was an apt representation of on-ground vegetation cover. LiDAR-derived mid-story vegetation cover was 22-40% lower in areas of low and moderate than high fire severity. Linear mixed-effects models showed that fire severity was among the strongest biophysical predictors of mid-story vegetation cover irrespective of spatial resolution. However much of the variance associated with these models was unexplained, presumably because soil seed banks varied at finer scales than our LiDAR maps. Dense patches of mid-story vegetation regrowth were small (median size 0.01 ha) and evenly distributed between areas of low, moderate and high fire severity, demonstrating that high-severity fires do not homogenize vegetation cover. Our results are relevant for ecosystem conservation and fire management because they: indicate that native vegetation are responsive and resilient to high-severity fire, and show the usefulness of remote sensing tools such as LiDAR to monitor post-fire vegetation recovery over large areas in situ. © 2017 by the Ecological Society of America.

Small-scale spatial heterogeneity of ecosystem properties, microbial community composition and microbial activities in a temperate mountain forest soil.

PubMed

Štursová, Martina; Bárta, Jiří; Šantrůčková, Hana; Baldrian, Petr

2016-12-01

Forests are recognised as spatially heterogeneous ecosystems. However, knowledge of the small-scale spatial variation in microbial abundance, community composition and activity is limited. Here, we aimed to describe the heterogeneity of environmental properties, namely vegetation, soil chemical composition, fungal and bacterial abundance and community composition, and enzymatic activity, in the topsoil in a small area (36 m 2 ) of a highly heterogeneous regenerating temperate natural forest, and to explore the relationships among these variables. The results demonstrated a high level of spatial heterogeneity in all properties and revealed differences between litter and soil. Fungal communities had substantially higher beta-diversity than bacterial communities, which were more uniform and less spatially autocorrelated. In litter, fungal communities were affected by vegetation and appeared to be more involved in decomposition. In the soil, chemical composition affected both microbial abundance and the rates of decomposition, whereas the effect of vegetation was small. Importantly, decomposition appeared to be concentrated in hotspots with increased activity of multiple enzymes. Overall, forest topsoil should be considered a spatially heterogeneous environment in which the mean estimates of ecosystem-level processes and microbial community composition may confound the existence of highly specific microenvironments. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Mapping Vegetation Community Types in a Highly-Disturbed Landscape: Integrating Hiearchical Object-Based Image Analysis with Digital Surface Models

NASA Astrophysics Data System (ADS)

Snavely, Rachel A.

Focusing on the semi-arid and highly disturbed landscape of San Clemente Island, California, this research tests the effectiveness of incorporating a hierarchal object-based image analysis (OBIA) approach with high-spatial resolution imagery and light detection and range (LiDAR) derived canopy height surfaces for mapping vegetation communities. The study is part of a large-scale research effort conducted by researchers at San Diego State University's (SDSU) Center for Earth Systems Analysis Research (CESAR) and Soil Ecology and Restoration Group (SERG), to develop an updated vegetation community map which will support both conservation and management decisions on Naval Auxiliary Landing Field (NALF) San Clemente Island. Trimble's eCognition Developer software was used to develop and generate vegetation community maps for two study sites, with and without vegetation height data as input. Overall and class-specific accuracies were calculated and compared across the two classifications. The highest overall accuracy (approximately 80%) was observed with the classification integrating airborne visible and near infrared imagery having very high spatial resolution with a LiDAR derived canopy height model. Accuracies for individual vegetation classes differed between both classification methods, but were highest when incorporating the LiDAR digital surface data. The addition of a canopy height model, however, yielded little difference in classification accuracies for areas of very dense shrub cover. Overall, the results show the utility of the OBIA approach for mapping vegetation with high spatial resolution imagery, and emphasizes the advantage of both multi-scale analysis and digital surface data for accuracy characterizing highly disturbed landscapes. The integrated imagery and digital canopy height model approach presented both advantages and limitations, which have to be considered prior to its operational use in mapping vegetation communities.

Spatial and Temporal Variation in Primary Productivity (NDVI) of Coastal Alaskan Tundra: Decreased Vegetation Growth Following Earlier Snowmelt

NASA Technical Reports Server (NTRS)

Gamon, John A.; Huemmrich, K. Fred; Stone, Robert S.; Tweedie, Craig E.

2015-01-01

In the Arctic, earlier snowmelt and longer growing seasons due to warming have been hypothesized to increase vegetation productivity. Using the Normalized Difference Vegetation Index (NDVI) from both field and satellite measurements as an indicator of vegetation phenology and productivity, we monitored spatial and temporal patterns of vegetation growth for a coastal wet sedge tundra site near Barrow, Alaska over three growing seasons (2000-2002). Contrary to expectation, earlier snowmelt did not lead to increased productivity. Instead, productivity was associated primarily with precipitation and soil moisture, and secondarily with growing degree days, which, during this period, led to reduced growth in years with earlier snowmelt. Additional moisture effects on productivity and species distribution, operating over a longer time scale, were evident in spatial NDVI patterns associated with microtopography. Lower, wetter regions dominated by graminoids were more productive than higher, drier locations having a higher percentage of lichens and mosses, despite the earlier snowmelt at the more elevated sites. These results call into question the oft-stated hypothesis that earlier arctic growing seasons will lead to greater vegetation productivity. Rather, they agree with an emerging body of evidence from recent field studies indicating that early-season, local environmental conditions, notably moisture and temperature, are primary factors determining arctic vegetation productivity. For this coastal arctic site, early growing season conditions are strongly influenced by microtopography, hydrology, and regional sea ice dynamics, and may not be easily predicted from snowmelt date or seasonal average air temperatures alone. Our comparison of field to satellite NDVI also highlights the value of in-situ monitoring of actual vegetation responses using field optical sampling to obtain detailed information on surface conditions not possible from satellite observations alone.

Monitoring Spatial Patterns of Vegetation Phenology in AN Australian Tropical Transect Using Modis Evi

NASA Astrophysics Data System (ADS)

Ma, X.; Huete, A.; Yu, Q.; Davies, K.; Coupe, N. R.

2012-07-01

Phenology is receiving increasing interest in the area of climate change and vegetation adaptation to climate. The phenology of a landscape can be used as a key parameter in land surface models and dynamic global vegetation models to more accurately simulate carbon, water and energy exchanges between land cover and atmosphere. However, the characterisation of phenology is lacking in tropical savannas which cover more than 30% of global land area, and are highly vulnerable to climate change. The objective of this study is to investigate the spatial pattern of vegetation phenology along the Northern Australia Tropical Transect (NATT) where the major biomes are wet and dry tropical savannas. For this analysis we used more than 11 years Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) product from 2000 to 2011. Eight phenological metrics were derived: Start of Season (SOS), End of Season (EOS), Length of Season (LOS), Maximum EVI (MaxG), Minimum EVI (MinG), annual amplitude (AMP), large integral (LIG), and small integral (SIG) were generated for each year and each pixel. Our results showed there are significant spatial patterns and considerable interannual variations of vegetation phenology along the NATT study area. Generally speaking, vegetation growing season started and ended earlier in the north, and started and ended later in the south, resulting in a southward decrease of growing season length (LOS). Vegetation productivity, which was represented by annual integral EVI (LIG), showed a significant descending trend from the northern part of NATT to the southern part. Segmented regression analysis showed that there exists a distinguishable breakpoint along the latitudinal gradient, at least in terms of annual minimum EVI (EVI), which is located between 18.84°S to 20.04°S.

Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using Satellite Soil Moisture Data, GRACE Water Storage and Precipitation Observations

NASA Astrophysics Data System (ADS)

A, G.; Velicogna, I.; Kimball, J. S.; Du, J.; Kim, Y.; Njoku, E. G.; Colliander, A.

2016-12-01

We combine soil moisture (SM) data from AMSR-E, AMSR-2 and SMAP, terrestrial water storage (TWS) changes from GRACE and precipitation measurements from GPCP to delineate and characterize drought and water supply pattern and its impact on vegetation growth. GRACE TWS provides spatially continuous observations of total terrestrial water storage changes and regional drought extent, persistence and severity, while satellite derived soil moisture estimates provide enhanced delineation of plant-available soil moisture. Together these data provide complementary metrics quantifying available plant water supply and have important implications for water resource management. We use these data to investigate the supply changes from different water components in relation to satellite based vegetation productivity metrics from MODIS, before, during and following the major drought events observed in the continental US during the past 13 years. We observe consistent trends and significant correlations between monthly time series of TWS, SM, and vegetation productivity. In Texas and surrounding semi-arid areas, we find that the spatial pattern of the vegetation-moisture relation follows the gradient in mean annual precipitation. In Texas, GRACE TWS and surface SM show strong coupling and similar characteristic time scale in relatively normal years, while during the 2011 onward hydrological drought, GRACE TWS manifests a longer time scale than that of surface SM, implying stronger drought persistence in deeper water storage. In the Missouri watershed, we find a spatially varying vegetation-moisture relationship where in the drier northwestern portion of the basin, the inter-annual variability in summer vegetation productivity is closely associated with changes in carry-on GRACE TWS from spring, whereas in the moist southeastern portion of the basin, summer precipitation is the dominant controlling factor on vegetation growth.

On the creation of high spatial resolution imaging spectroscopy data from multi-temporal low spatial resolution imagery

NASA Astrophysics Data System (ADS)

Yao, Wei; van Aardt, Jan; Messinger, David

2017-05-01

The Hyperspectral Infrared Imager (HyspIRI) mission aims to provide global imaging spectroscopy data to the benefit of especially ecosystem studies. The onboard spectrometer will collect radiance spectra from the visible to short wave infrared (VSWIR) regions (400-2500 nm). The mission calls for fine spectral resolution (10 nm band width) and as such will enable scientists to perform material characterization, species classification, and even sub-pixel mapping. However, the global coverage requirement results in a relatively low spatial resolution (GSD 30m), which restricts applications to objects of similar scales. We therefore have focused on the assessment of sub-pixel vegetation structure from spectroscopy data in past studies. In this study, we investigate the development or reconstruction of higher spatial resolution imaging spectroscopy data via fusion of multi-temporal data sets to address the drawbacks implicit in low spatial resolution imagery. The projected temporal resolution of the HyspIRI VSWIR instrument is 15 days, which implies that we have access to as many as six data sets for an area over the course of a growth season. Previous studies have shown that select vegetation structural parameters, e.g., leaf area index (LAI) and gross ecosystem production (GEP), are relatively constant in summer and winter for temperate forests; we therefore consider the data sets collected in summer to be from a similar, stable forest structure. The first step, prior to fusion, involves registration of the multi-temporal data. A data fusion algorithm then can be applied to the pre-processed data sets. The approach hinges on an algorithm that has been widely applied to fuse RGB images. Ideally, if we have four images of a scene which all meet the following requirements - i) they are captured with the same camera configurations; ii) the pixel size of each image is x; and iii) at least r2 images are aligned on a grid of x/r - then a high-resolution image, with a pixel size of x/r, can be reconstructed from the multi-temporal set. The algorithm was applied to data from NASA's classic Airborne Visible and Infrared Imaging Spectrometer (AVIRIS-C; GSD 18m), collected between 2013-2015 (summer and fall) over our study area (NEON's Southwest Pacific Domain; Fresno, CA) to generate higher spatial resolution imagery (GSD 9m). The reconstructed data set was validated via comparison to NEON's imaging spectrometer (NIS) data (GSD 1m). The results showed that algorithm worked well with the AVIRIS-C data and could be applied to the HyspIRI data.

Neighborhood deprivation, vehicle ownership, and potential spatial access to a variety of fruits and vegetables in a large rural area in Texas.

PubMed

Sharkey, Joseph R; Horel, Scott; Dean, Wesley R

2010-05-25

There has been limited study of all types of food stores, such as traditional (supercenters, supermarkets, and grocery stores), convenience stores, and non-traditional (dollar stores, mass merchandisers, and pharmacies) as potential opportunities for purchase of fresh and processed (canned and frozen) fruits and vegetables, especially in small-town or rural areas. Data from the Brazos Valley Food Environment Project (BVFEP) are combined with 2000 U.S. Census data for 101 Census block groups (CBG) to examine neighborhood access to fruits and vegetables. BVFEP data included identification and geocoding of all food stores (n = 185) in six rural counties in Texas, using ground-truthed methods and on-site assessment of the availability and variety of fresh and processed fruits and vegetables in all food stores. Access from the population-weighted centroid of each CBG was measured using proximity (minimum network distance) and coverage (number of shopping opportunities) for a good selection of fresh and processed fruits and vegetables. Neighborhood inequalities (deprivation and vehicle ownership) and spatial access for fruits and vegetables were examined using Wilcoxon matched-pairs signed-rank test and multivariate regression models. The variety of fruits or vegetables was greater at supermarkets compared with grocery stores. Among non-traditional and convenience food stores, the largest variety was found at dollar stores. On average, rural neighborhoods were 9.9 miles to the nearest supermarket, 6.7 miles and 7.4 miles to the nearest food store with a good variety of fresh fruits and vegetables, respectively, and 4.7 miles and 4.5 miles to a good variety of fresh and processed fruits or vegetables. High deprivation or low vehicle ownership neighborhoods had better spatial access to a good variety of fruits and vegetables, both in the distance to the nearest source and in the number of shopping opportunities. Supermarkets and grocery stores are no longer the only shopping opportunities for fruits or vegetables. The inclusion of data on availability of fresh or processed fruits or vegetables in the measurements provides robust meaning to the concept of potential access in this large rural area.

Neighborhood deprivation, vehicle ownership, and potential spatial access to a variety of fruits and vegetables in a large rural area in Texas

PubMed Central

2010-01-01

Objective There has been limited study of all types of food stores, such as traditional (supercenters, supermarkets, and grocery stores), convenience stores, and non-traditional (dollar stores, mass merchandisers, and pharmacies) as potential opportunities for purchase of fresh and processed (canned and frozen) fruits and vegetables, especially in small-town or rural areas. Methods Data from the Brazos Valley Food Environment Project (BVFEP) are combined with 2000 U.S. Census data for 101 Census block groups (CBG) to examine neighborhood access to fruits and vegetables. BVFEP data included identification and geocoding of all food stores (n = 185) in six rural counties in Texas, using ground-truthed methods and on-site assessment of the availability and variety of fresh and processed fruits and vegetables in all food stores. Access from the population-weighted centroid of each CBG was measured using proximity (minimum network distance) and coverage (number of shopping opportunities) for a good selection of fresh and processed fruits and vegetables. Neighborhood inequalities (deprivation and vehicle ownership) and spatial access for fruits and vegetables were examined using Wilcoxon matched-pairs signed-rank test and multivariate regression models. Results The variety of fruits or vegetables was greater at supermarkets compared with grocery stores. Among non-traditional and convenience food stores, the largest variety was found at dollar stores. On average, rural neighborhoods were 9.9 miles to the nearest supermarket, 6.7 miles and 7.4 miles to the nearest food store with a good variety of fresh fruits and vegetables, respectively, and 4.7 miles and 4.5 miles to a good variety of fresh and processed fruits or vegetables. High deprivation or low vehicle ownership neighborhoods had better spatial access to a good variety of fruits and vegetables, both in the distance to the nearest source and in the number of shopping opportunities. Conclusion Supermarkets and grocery stores are no longer the only shopping opportunities for fruits or vegetables. The inclusion of data on availability of fresh or processed fruits or vegetables in the measurements provides robust meaning to the concept of potential access in this large rural area. PMID:20500853

An approach for detecting five typical vegetation types on the Chinese Loess Plateau using Landsat TM data.

PubMed

Wang, Zhi-Jie; Jiao, Ju-Ying; Lei, Bo; Su, Yuan

2015-09-01

Remote sensing can provide large-scale spatial data for the detection of vegetation types. In this study, two shortwave infrared spectral bands (TM5 and TM7) and one visible spectral band (TM3) of Landsat 5 TM data were used to detect five typical vegetation types (communities dominated by Bothriochloa ischaemum, Artemisia gmelinii, Hippophae rhamnoides, Robinia pseudoacacia, and Quercus liaotungensis) using 270 field survey data in the Yanhe watershed on the Loess Plateau. The relationships between 200 field data points and their corresponding radiance reflectance were analyzed, and the equation termed the vegetation type index (VTI) was generated. The VTI values of five vegetation types were calculated, and the accuracy was tested using the remaining 70 field data points. The applicability of VTI was also tested by the distribution of vegetation type of two small watersheds in the Yanhe watershed and field sample data collected from other regions (Ziwuling Region, Huangling County, and Luochuan County) on the Loess Plateau. The results showed that the VTI can effectively detect the five vegetation types with an average accuracy exceeding 80 % and a representativeness above 85 %. As a new approach for monitoring vegetation types using remote sensing at a larger regional scale, VTI can play an important role in the assessment of vegetation restoration and in the investigation of the spatial distribution and community diversity of vegetation on the Loess Plateau.

Analysis on Temporal-Spatial Changes of Vegetation Cverrge in Farming-Pastoral Ecotone of Inner Mongolia

NASA Astrophysics Data System (ADS)

Yan, X.; Li, J.; Yang, Z.

2018-04-01

Chen Barag Banner is located in the typical farming-pastoral ecotone of Inner Mongolia, and it is also the core area of Hulunbuir steppe. Typical agricultural and pastoral staggered production mode so that the vegetation growth of the region not only determines the local ecological environment, and animal husbandry production, but also have a significant impact on the whole Hulunbuir ecological security and economic development. Therefore, it is necessary to monitor the change of vegetation in this area. Based on 17 MODIS Normalized Difference Vegetation Index (NDVI) images, the authors reconstructed the dynamic change characteristics of Fraction vegetation coverage (FVC) in Chen Barag Banner from 2000 to 2016. In this paper, first at all, Pixel Decomposition Models was introduced to inversion FVC, and the time series of vegetation coverage was reconstructed. Then we analyzed the temporal-spatial changes of FVC by employing transition matrix. Finally, through image analyzing and processing, the results showed that the vegetation coverage in the study area was influenced by effectors including climate, topography and human actives. In the past 17 years, the overall effect of vegetation coverage showed a downward trend of fluctuation. The average vegetation coverage decreased from 58.81 % in 2000 to 48.14 % in 2016, and the area of vegetation cover degradation accounts for 40.09 % of the total change area. Therefore, the overall degradation trend was obvious.

Riparian vegetation controls on braided stream dynamics

NASA Astrophysics Data System (ADS)

Gran, Karen; Paola, Chris

2001-12-01

Riparian vegetation can significantly influence the morphology of a river, affecting channel geometry and flow dynamics. To examine the effects of riparian vegetation on gravel bed braided streams, we conducted a series of physical experiments at the St. Anthony Falls Laboratory with varying densities of bar and bank vegetation. Water discharge, sediment discharge, and grain size were held constant between runs. For each run, we allowed a braided system to develop, then seeded the flume with alfalfa (Medicago sativa), allowed the seeds to grow, and then continued the run. We collected data on water depth, surface velocity, and bed elevation throughout each run using image-based techniques designed to collect data over a large spatial area with minimal disturbance to the flow. Our results show that the influence of vegetation on overall river patterns varied systematically with the spatial density of plant stems. Vegetation reduced the number of active channels and increased bank stability, leading to lower lateral migration rates, narrower and deeper channels, and increased channel relief. These effects increased with vegetation density. Vegetation influenced flow dynamics, increasing the variance of flow direction in vegetated runs and increasing scour depths through strong downwelling where the flow collided with relatively resistant banks. This oblique bank collision also provides a new mechanism for producing secondary flows. We found it to be more important than the classical curvature-driven mechanism in vegetated runs.

Microspatial ecotone dynamics at a shifting range limit: plant–soil variation across salt marsh–mangrove interfaces

USGS Publications Warehouse

Yando, Erik S.; Osland, Michael J.; Hester, Mark H.

2018-01-01

Ecotone dynamics and shifting range limits can be used to advance our understanding of the ecological implications of future range expansions in response to climate change. In the northern Gulf of Mexico, the salt marsh–mangrove ecotone is an area where range limits and ecotone dynamics can be studied in tandem as recent decreases in winter temperature extremes have allowed for mangrove expansion at the expense of salt marsh. In this study, we assessed aboveground and belowground plant–soil dynamics across the salt marsh–mangrove ecotone quantifying micro-spatial patterns in horizontal extent. Specifically, we studied vegetation and rooting dynamics of large and small trees, the impact of salt marshes (e.g. species and structure) on mangroves, and the influence of vegetation on soil properties along transects from underneath the mangrove canopy into the surrounding salt marsh. Vegetation and rooting dynamics differed in horizontal reach, and there was a positive relationship between mangrove tree height and rooting extent. We found that the horizontal expansion of mangrove roots into salt marsh extended up to eight meters beyond the aboveground boundary. Variation in vegetation structure and local hydrology appear to control mangrove seedling dynamics. Finally, soil carbon density and organic matter did not differ within locations across the salt marsh-mangrove interface. By studying aboveground and belowground variation across the ecotone, we can better predict the ecological effects of continued range expansion in response to climate change.

Microspatial ecotone dynamics at a shifting range limit: plant-soil variation across salt marsh-mangrove interfaces.

PubMed

Yando, E S; Osland, M J; Hester, M W

2018-05-01

Ecotone dynamics and shifting range limits can be used to advance our understanding of the ecological implications of future range expansions in response to climate change. In the northern Gulf of Mexico, the salt marsh-mangrove ecotone is an area where range limits and ecotone dynamics can be studied in tandem as recent decreases in winter temperature extremes have allowed for mangrove expansion at the expense of salt marsh. In this study, we assessed aboveground and belowground plant-soil dynamics across the salt marsh-mangrove ecotone quantifying micro-spatial patterns in horizontal extent. Specifically, we studied vegetation and rooting dynamics of large and small trees, the impact of salt marshes (e.g. species and structure) on mangroves, and the influence of vegetation on soil properties along transects from underneath the mangrove canopy into the surrounding salt marsh. Vegetation and rooting dynamics differed in horizontal reach, and there was a positive relationship between mangrove tree height and rooting extent. We found that the horizontal expansion of mangrove roots into salt marsh extended up to eight meters beyond the aboveground boundary. Variation in vegetation structure and local hydrology appear to control mangrove seedling dynamics. Finally, soil carbon density and organic matter did not differ within locations across the salt marsh-mangrove interface. By studying aboveground and belowground variation across the ecotone, we can better predict the ecological effects of continued range expansion in response to climate change.

Remote Sensing of Atlanta's Urban Sprawl and the Distribution of Land Cover and Surface Temperatures

NASA Technical Reports Server (NTRS)

Laymon, Charles A.; Estes, Maurice G., Jr.; Quattrochi, Dale A.; Arnold, James E. (Technical Monitor)

2001-01-01

Between 1973 and 1992, an average of 20 ha of forest was lost each day to urban expansion of Atlanta, Georgia. Urban surfaces have very different thermal properties than natural surfaces-storing solar energy throughout the day and continuing to release it as sensible heat well after sunset. The resulting heat island effect serves as catalysts for chemical reactions from vehicular exhaust and industrialization leading to a deterioration in air quality. In this study, high spatial resolution multispectral remote sensing data has been used to characterize the type, thermal properties, and distribution of land surface materials throughout the Atlanta metropolitan area. Ten-meter data were acquired with the Advanced Thermal and Land Applications Sensor (ATLAS) on May 11 and 12, 1997. ATLAS is a 15-channel multispectral scanner that incorporates the Landsat TM bands with additional bands in the middle reflective infrared and thermal infrared range. The high spatial resolution permitted discrimination of discrete surface types (e.g., concrete, asphalt), individual structures (e.g., buildings, houses) and their associated thermal characteristics. There is a strong temperature contrast between vegetation and anthropomorphic features. Vegetation has a modal temperature at about 20 C, whereas asphalt shingles, pavement, and buildings have a modal temperature of about 39 C. Broad-leaf vegetation classes are indistinguishable on a thermal basis alone. There is slightly more variability (plus or minus 5 C) among the urban surfaces. Grasses, mixed vegetation and mixed urban surfaces are intermediate in temperature and are characterized by broader temperature distributions with modes of about 29 C. Thermal maps serve as a basis for understanding the distribution of "hotspots", i.e., how landscape features and urban fabric contribute the most heat to the lower atmosphere.

Remote Sensing of Atlanta's Urban Sprawl and the Distribution of Land Cover and Surface Temperature

NASA Technical Reports Server (NTRS)

Laymon, Charles A.; Estes, Maurice G., Jr.; Quattrochi, Dale A.; Goodman, H. Michael (Technical Monitor)

2001-01-01

Between 1973 and 1992, an average of 20 ha of forest was lost each day to urban expansion of Atlanta, Georgia. Urban surfaces have very different thermal properties than natural surfaces-storing solar energy throughout the day and continuing to release it as sensible heat well after sunset. The resulting heat island effect serves as catalysts for chemical reactions from vehicular exhaust and industrialization leading to a deterioration in air quality. In this study, high spatial resolution multispectral remote sensing data has been used to characterize the type, thermal properties, and distribution of land surface materials throughout the Atlanta metropolitan area. Ten-meter data were acquired with the Advanced Thermal and Land Applications Sensor (ATLAS) on May 11 and 12, 1997. ATLAS is a 15-channel multispectral scanner that incorporates the Landsat TM bands with additional bands in the middle reflective infrared and thermal infrared range. The high spatial resolution permitted discrimination of discrete surface types (e.g., concrete, asphalt), individual structures (e.g., buildings, houses) and their associated thermal characteristics. There is a strong temperature contrast between vegetation and anthropomorphic features. Vegetation has a modal temperature at about 20 C, whereas asphalt shingles, pavement, and buildings have a modal temperature of about 39 C. Broad-leaf vegetation classes are indistinguishable on a thermal basis alone. There is slightly more variability (+/-5 C) among the urban surfaces. Grasses, mixed vegetation and mixed urban surfaces are intermediate in temperature and are characterized by broader temperature distributions with modes of about 29 C. Thermal maps serve as a basis for understanding the distribution of "hotspots", i.e., how landscape features and urban fabric contribute the most heat to the lower atmosphere.

A new multi-angle remote sensing framework for scaling vegetation properties from tower-based spectro-radiometers to next generation "CubeSat"-satellites.

NASA Astrophysics Data System (ADS)

Hilker, T.; Hall, F. G.; Dyrud, L. P.; Slagowski, S.

2014-12-01

Frequent earth observations are essential for assessing the risks involved with global climate change, its feedbacks on carbon, energy and water cycling and consequences for live on earth. Often, satellite-remote sensing is the only practical way to provide such observations at comprehensive spatial scales, but relationships between land surface parameters and remotely sensed observations are mostly empirical and cannot easily be scaled across larger areas or over longer time intervals. For instance, optically based methods frequently depend on extraneous effects that are unrelated to the surface property of interest, including the sun-server geometry or background reflectance. As an alternative to traditional, mono-angle techniques, multi-angle remote sensing can help overcome some of these limitations by allowing vegetation properties to be derived from comprehensive reflectance models that describe changes in surface parameters based on physical principles and radiative transfer theory. Recent results have shown in theoretical and experimental research that multi-angle techniques can be used to infer and scale the photosynthetic rate of vegetation, its biochemical and structural composition robustly from remote sensing. Multi-angle remote sensing could therefore revolutionize estimates of the terrestrial carbon uptake as scaling of primary productivity may provide a quantum leap in understanding the spatial and temporal complexity of terrestrial earth science. Here, we introduce a framework of next generation tower-based instruments to a novel and unique constellation of nano-satellites (Figure 1) that will allow us to systematically scale vegetation parameters from stand to global levels. We provide technical insights, scientific rationale and present results. We conclude that future earth observation from multi-angle satellite constellations, supported by tower based remote sensing will open new opportunities for earth system science and earth system modeling.

Effect of vegetation on cutaneous leishmaniasis in Paraná, Brazil

PubMed Central

Melo, Helen Aline; Rossoni, Diogo Francisco; Teodoro, Ueslei

2018-01-01

BACKGROUND Cutaneous leishmaniasis (CL) is endemic in the state of Paraná, Brazil. OBJECTIVE This study aimed at analysing the influence of the remaining native vegetation on the prevalence of CL in Paraná. METHODS Global testing was used for spatial autocorrelation along with simultaneous autoregressive model (SAR). The regression was based on the CL coefficient (cases/100,000 inhabitants) as a function of the percentage of natural vegetation cover, altitude, total number of cases, and spatial density (SD) per km2; the location data of the Paraná state municipalities and the detection coefficient (DC) (cases/100,000 inhabitants) of autochthonous cases of CL were obtained from the SINAN in 2012 and 2016. Data on the remaining forests were collected from the Fundação SOS Mata Atlântica and Instituto Nacional de Pesquisas Espaciais. FINDINGS The spatial regression of DC revealed statistical significance for SD (Z = 24.1359, p < 0.05, 2012-2013; Z = 24.0817, p < 0.05, 2013-2014; Z = 33.4824, p < 0.05, 2014-2015; and Z = 27.1515, p < 0.05, 2015-2016. CONCLUSIONS CL cases are reported in areas with native vegetation, such as in riparian forests. However, vegetation is not the only variable that influences the incidence of CL. PMID:29768531

Plant diversity and structure describe the presence of a new, threatened Australian marsupial within its highly restricted, post-fire habitat.

PubMed

Mason, Eugene D; Firn, Jennifer; Hines, Harry B; Baker, Andrew M

2017-01-01

Management of critical habitat for threatened species with small ranges requires location-specific, fine-scale survey data. The silver-headed antechinus (Antechinus argentus) is known from only two isolated, fire-prone locations. At least one of these populations, at Kroombit Tops National Park in central-eastern Queensland, Australia, possesses a very small range. Here, we present detailed vegetation species diversity and structure data from three sites comprising the known habitat of A. argentus at Kroombit Tops and relate it to capture data obtained over two years. We found differences in both vegetation and capture data between burnt and unburnt habitat. Leaf litter and grasstrees (Xanthorrhoea johnsonii) were the strongest vegetative predictors for A. argentus capture. The species declined considerably over the two years of the trapping study, and we raise concern for its survival at Kroombit Tops. We suggest that future work should focus on structural vegetative variables (specifically, the diameter and leaf density of grasstree crowns) and relate them to A. argentus occurrence. We also recommend a survey of invertebrate diversity in grasstrees and leaf litter with a comparison to A. argentus prey. The data presented here illustrates how critical detailed monitoring is for planning habitat management and fire regimes, and highlights the utility of a high-resolution approach to habitat mapping. While a traditional approach to fire management contends that pyrodiversity encourages biodiversity, the present study demonstrates that some species prefer long-unburnt habitat. Additionally, in predicting the distribution of rare species like A. argentus, data quality (i.e., spatial resolution) may prevail over data quantity (i.e., number of data).

Effects of Emergent Vegetation on Sediment Dynamics within a Retreating Coastal Marshland

NASA Astrophysics Data System (ADS)

Stellern, C.; Grossman, E.; Fuller, R.; Wallin, D.; Linneman, S. R.

2015-12-01

Coastal emergent vegetation in estuaries physically interrupts flow within the water column, reduces wave energy and increases sediment deposition. Previous workers conclude that wave attenuation rates decrease exponentially with distance from the marsh edge and are dependent on site and species-specific plant characteristics (Yang et al., 2011). Sediment deposition may exhibit similar patterns; however, sediment, geomorphic and habitat models seldom integrate site-specific biophysical plant parameters into change analyses. We paired vegetation and sediment dynamic studies to: (1) characterize vegetation structure, (2) estimate sediment available for deposition, (3) estimate rate, distribution and composition of sediment deposits, (4) determine sediment accumulation on vegetation, (5) compare sediment deposition within dense tidal wetland relative to non-vegetated tidal flat. These studies integrate a variety of monitoring methods, including the use of sediment traps, turbidity sensors, side-on photographs of vegetation and remote sensing image analysis. We compared sedimentation data with vegetation characteristics and spatial distribution data to examine the relative role of vegetation morphologic traits (species, stem density, biomass, distribution, tidal channels, etc.) on sediment dynamics. Our study is focused on Port Susan Bay of Washington State; a protected delta that has experienced up to 1 kilometer of marsh retreat (loss) over the past fifty years. Preliminary results show that the highest winter deposition occurred in the high marsh/mid-marsh boundary, up to 300m inland of the marsh edge, where bulrush species are most dense. These results will inform restoration efforts aimed at reestablishing sediment supply to the retreating marshland. This research is necessary to understand the vulnerability and adaptability of coastal marshlands to climate change related stressors such as, increased water levels (sea-level rise) and wave energy.

Ecohydrological implications of aeolian sediment trapping by sparse vegetation in drylands

USGS Publications Warehouse

Gonzales, Howell B.; Ravi, Sujith; Li, Junran; Sankey, Joel B.

2018-01-01

Aeolian processes are important drivers of ecosystem dynamics in drylands, and important feedbacks exist among aeolian – hydrological processes and vegetation. The trapping of wind-borne sediments by vegetation may result in changes in soil properties beneath the vegetation, which, in turn, can alter hydrological and biogeochemical processes. Despite the relevance of aeolian transport to ecosystem dynamics, the interactions between aeolian transport and vegetation in shaping dryland landscapes where sediment distribution is altered by relatively rapid changes in vegetation composition such as shrub encroachment, is not well understood. Here, we used a computational fluid dynamics (CFD) modeling framework to investigate the sediment trapping efficiencies of vegetation canopies commonly found in a shrub-grass ecotone in the Chihuahuan Desert (New Mexico, USA) and related the results to spatial heterogeneity in soil texture and infiltration measured in the field. A CFD open-source software package was used to simulate aeolian sediment movement through three-dimensional architectural depictions of Creosote shrub (Larrea tridentata) and Black Grama grass (Bouteloua eriopoda) vegetation types. The vegetation structures were created using a computer-aided design software (Blender), with inherent canopy porosities, which were derived using LIDAR (Light Detection and Ranging) measurements of plant canopies. Results show that considerable heterogeneity in infiltration and soil grain size distribution exist between the microsites, with higher infiltration and coarser soil texture under shrubs. Numerical simulations also indicate that the differential trapping of canopies might contribute to the observed heterogeneity in soil texture. In the early stages of encroachment, the shrub canopies, by trapping coarser particles more efficiently, might maintain higher infiltration rates leading to faster development of the microsites (among other factors) with enhanced ecological productivity, which might provide positive feedbacks to shrub encroachment.

The combined effects of topography and vegetation on catchment connectivity

NASA Astrophysics Data System (ADS)

Nippgen, F.; McGlynn, B. L.; Emanuel, R. E.

2012-12-01

The deconvolution of whole catchment runoff response into its temporally dynamic source areas is a grand challenge in hydrology. The extent to which the intersection of static and dynamic catchment characteristics (e.g. topography and vegetation) influences water redistribution within a catchment and the hydrologic connectivity of hillslopes to the riparian and stream system is largely unknown. Over time, patterns of catchment storage shift and, because of threshold connectivity behavior, catchment areas become disconnected from the stream network. We developed a simple but spatially distributed modeling framework that explicitly incorporates static (topography) and dynamic (vegetation) catchment structure to document the evolution of catchment connectivity over the course of a water year. We employed directly measured eddy-covariance evapotranspiration data co-located within a highly instrumented (>150 recording groundwater wells) and gauged catchment to parse the effect of current and zero vegetation scenarios on the temporal evolution of hydrologic connectivity. In the absence of vegetation, and thus in the absence of evapotranspiration, modeled absolute connectivity was 4.5% greater during peak flow and 3.9% greater during late summer baseflow when compared to the actual vegetation scenario. The most significant differences in connected catchment area between current and zero vegetation (14.9%) occurred during the recession period in early July, when water and energy availability were at an optimum. However, the greatest relative difference in connected area occurs during the late summer baseflow period when the absence of evapotranspiration results in a connected area approximately 500% greater than when vegetation is present, while the relative increase during peak flow is just 6%. Changes in connected areas ultimately lead to propose a biologically modified geomorphic width function. This biogeomorphic width function is the result of lateral water redistribution driven by topography and water uptake by vegetation.

Relationships of Biomass with Environmental Factors in the Grassland Area of Hulunbuir, China

PubMed Central

Liu, Miao; Liu, Guohua; Gong, Li; Wang, Dongbo; Sun, Jian

2014-01-01

Many studies have focused on the relationship between vegetation biomass and environmental factors in grassland. However, several questions remain to be answered, especially with regards to the spatial pattern of vegetation biomass. Thus, the distributed mechanism will be explored in the present study. Here, plant biomass was measured at 23 sites along a transect survey during the peak growing season in 2006. The data were analyzed with a classification and regression tree (CART) model. The structural equation modeling (SEM) was conducted to explicitly evaluate the both direct and indirect effects of these critical environmental elements on vegetation biomass. The results demonstrated that mean annual temperature (MAT) affected aboveground biomass (AGB) scored at −0.811 (P<0.05). The direct effect of MAT on belowground biomass (BGB) was −0.490 (P<0.05). The results were determined by SEM. Our results indicate that AGB and BGB in semi-arid ecosystems is strongly affected by precipitation and temperature. Future work shall attempt to take into account the integrated effects of precipitation and temperature. Meanwhile, partitioning the influences of environmental variations and vegetation types are helpful in illuminating the internal mechanism of biomass distribution. PMID:25032808

Relationships of biomass with environmental factors in the grassland area of Hulunbuir, China.

PubMed

Liu, Miao; Liu, Guohua; Gong, Li; Wang, Dongbo; Sun, Jian

2014-01-01

Many studies have focused on the relationship between vegetation biomass and environmental factors in grassland. However, several questions remain to be answered, especially with regards to the spatial pattern of vegetation biomass. Thus, the distributed mechanism will be explored in the present study. Here, plant biomass was measured at 23 sites along a transect survey during the peak growing season in 2006. The data were analyzed with a classification and regression tree (CART) model. The structural equation modeling (SEM) was conducted to explicitly evaluate the both direct and indirect effects of these critical environmental elements on vegetation biomass. The results demonstrated that mean annual temperature (MAT) affected aboveground biomass (AGB) scored at -0.811 (P<0.05). The direct effect of MAT on belowground biomass (BGB) was -0.490 (P<0.05). The results were determined by SEM. Our results indicate that AGB and BGB in semi-arid ecosystems is strongly affected by precipitation and temperature. Future work shall attempt to take into account the integrated effects of precipitation and temperature. Meanwhile, partitioning the influences of environmental variations and vegetation types are helpful in illuminating the internal mechanism of biomass distribution.

Airborne Instrument Simulator for the Lidar Surface Topography (LIST) Mission

NASA Technical Reports Server (NTRS)

Yu, Anthony W.; Krainak, Michael A.; Harding, David J.; Abshire, James B.; Sun, Xiaoli; Cavanaugh, John; Valett, Susan; Ramos-Izquierdo, Luis

2010-01-01

In 2007, the National Research Council (NRC) completed its first decadal survey for Earth science at the request of NASA, NOAA, and USGS. The Lidar Surface Topography (LIST) mission is one of fifteen missions recommended by NRC, whose primary objectives are to map global topography and vegetation structure at 5 m spatial resolution, and to acquire global coverage with a few years. NASA Goddard conducted an initial mission concept study for the LIST mission 2007, and developed the initial measurement requirements for the mission.

Implications of scale-independent habitat specialization on persistence of a rare small mammal

USGS Publications Warehouse

Cleaver, Michael; Klinger, Robert C.; Anderson, Steven T.; Maier, Paul A.; Clark, Jonathan

2015-01-01

We assessed the habitat use patterns of the Amargosa vole Microtus californicus scirpensis , an endangered rodent endemic to wetland vegetation along a 3.5 km stretch of the Amargosa River in the Mojave Desert, USA. Our goals were to: (1) quantify the vole’s abundance, occupancy rates and habitat selection patterns along gradients of vegetation cover and spatial scale; (2) identify the processes that likely had the greatest influence on its habitat selection patterns. We trapped voles monthly in six 1 ha grids from January to May 2012 and measured habitat structure at subgrid (View the MathML source225m2) and trap (View the MathML source1m2) scales in winter and spring seasons. Regardless of scale, analyses of density, occupancy and vegetation structure consistently indicated that voles occurred in patches of bulrush (Schoenoplectus americanus ; Cyperaceae) where cover >50%. The majority of evidence indicates the vole's habitat selectivity is likely driven by bulrush providing protection from intense predation. However, a combination of selective habitat use and limited movement resulted in a high proportion of apparently suitable bulrush patches being unoccupied. This suggests the Amargosa vole's habitat selection behavior confers individual benefits but may not allow the overall population to persist in a changing environment.

Seasonal variations of leaf and canopy properties tracked by ground-based NDVI imagery in a temperate forest.

PubMed

Yang, Hualei; Yang, Xi; Heskel, Mary; Sun, Shucun; Tang, Jianwu

2017-04-28

Changes in plant phenology affect the carbon flux of terrestrial forest ecosystems due to the link between the growing season length and vegetation productivity. Digital camera imagery, which can be acquired frequently, has been used to monitor seasonal and annual changes in forest canopy phenology and track critical phenological events. However, quantitative assessment of the structural and biochemical controls of the phenological patterns in camera images has rarely been done. In this study, we used an NDVI (Normalized Difference Vegetation Index) camera to monitor daily variations of vegetation reflectance at visible and near-infrared (NIR) bands with high spatial and temporal resolutions, and found that the infrared camera based NDVI (camera-NDVI) agreed well with the leaf expansion process that was measured by independent manual observations at Harvard Forest, Massachusetts, USA. We also measured the seasonality of canopy structural (leaf area index, LAI) and biochemical properties (leaf chlorophyll and nitrogen content). We found significant linear relationships between camera-NDVI and leaf chlorophyll concentration, and between camera-NDVI and leaf nitrogen content, though weaker relationships between camera-NDVI and LAI. Therefore, we recommend ground-based camera-NDVI as a powerful tool for long-term, near surface observations to monitor canopy development and to estimate leaf chlorophyll, nitrogen status, and LAI.

Spatial forecast of landslides in three gorges based on spatial data mining.

PubMed

Wang, Xianmin; Niu, Ruiqing

2009-01-01

The Three Gorges is a region with a very high landslide distribution density and a concentrated population. In Three Gorges there are often landslide disasters, and the potential risk of landslides is tremendous. In this paper, focusing on Three Gorges, which has a complicated landform, spatial forecasting of landslides is studied by establishing 20 forecast factors (spectra, texture, vegetation coverage, water level of reservoir, slope structure, engineering rock group, elevation, slope, aspect, etc). China-Brazil Earth Resources Satellite (Cbers) images were adopted based on C4.5 decision tree to mine spatial forecast landslide criteria in Guojiaba Town (Zhigui County) in Three Gorges and based on this knowledge, perform intelligent spatial landslide forecasts for Guojiaba Town. All landslides lie in the dangerous and unstable regions, so the forecast result is good. The method proposed in the paper is compared with seven other methods: IsoData, K-Means, Mahalanobis Distance, Maximum Likelihood, Minimum Distance, Parallelepiped and Information Content Model. The experimental results show that the method proposed in this paper has a high forecast precision, noticeably higher than that of the other seven methods.

Spatial Forecast of Landslides in Three Gorges Based On Spatial Data Mining

PubMed Central

Wang, Xianmin; Niu, Ruiqing

2009-01-01

The Three Gorges is a region with a very high landslide distribution density and a concentrated population. In Three Gorges there are often landslide disasters, and the potential risk of landslides is tremendous. In this paper, focusing on Three Gorges, which has a complicated landform, spatial forecasting of landslides is studied by establishing 20 forecast factors (spectra, texture, vegetation coverage, water level of reservoir, slope structure, engineering rock group, elevation, slope, aspect, etc). China-Brazil Earth Resources Satellite (Cbers) images were adopted based on C4.5 decision tree to mine spatial forecast landslide criteria in Guojiaba Town (Zhigui County) in Three Gorges and based on this knowledge, perform intelligent spatial landslide forecasts for Guojiaba Town. All landslides lie in the dangerous and unstable regions, so the forecast result is good. The method proposed in the paper is compared with seven other methods: IsoData, K-Means, Mahalanobis Distance, Maximum Likelihood, Minimum Distance, Parallelepiped and Information Content Model. The experimental results show that the method proposed in this paper has a high forecast precision, noticeably higher than that of the other seven methods. PMID:22573999

On the spatial distribution of the transpiration and soil moisture of a Mediterranean heterogeneous ecosystem in water-limited conditions.

NASA Astrophysics Data System (ADS)

Curreli, Matteo; Corona, Roberto; Montaldo, Nicola; Albertson, John D.; Oren, Ram

2014-05-01

Mediterranean ecosystems are characterized by a strong heterogeneity, and often by water-limited conditions. In these conditions contrasting plant functional types (PFT, e.g. grass and woody vegetation) compete for the water use. Both the vegetation cover spatial distribution and the soil properties impact the soil moisture (SM) spatial distribution. Indeed, vegetation cover density and type affects evapotranspiration (ET), which is the main lack of the soil water balance in these ecosystems. With the objective to carefully estimate SM and ET spatial distribution in a Mediterranean water-limited ecosystem and understanding SM and ET relationships, an extended field campaign is carried out. The study was performed in a heterogeneous ecosystem in Orroli, Sardinia (Italy). The experimental site is a typical Mediterranean ecosystem where the vegetation is distributed in patches of woody vegetation (wild olives mainly) and grass. Soil depth is low and spatially varies between 10 cm and 40 cm, without any correlation with the vegetation spatial distribution. ET, land-surface fluxes and CO2 fluxes are estimated by an eddy covariance technique based micrometeorological tower. But in heterogeneous ecosystems a key assumption of the eddy covariance theory, the homogeneity of the surface, is not preserved and the ET estimate may be not correct. Hence, we estimate ET of the woody vegetation using the thermal dissipation method (i.e. sap flow technique) for comparing the two methodologies. Due the high heterogeneity of the vegetation and soil properties of the field a total of 54 sap flux sensors were installed. 14 clumps of wild olives within the eddy covariance footprint were identified as the most representative source of flux and they were instrumented with the thermal dissipation probes. Measurements of diameter at the height of sensor installation (height of 0.4 m above ground) were recorded in all the clumps. Bark thickness and sapwood depth were measured on several trees to obtain a generalized estimates of sapwood depth. The known of allometric relationships between sapwood area, diameter and canopy cover area within the eddy covariance footprint helped for the application of a reliable scaling procedure of the local sap flow estimates which are in a good agreement with the estimates of ET eddy covariance based. Soil moisture were also extensively monitored through 25 probes installed in the eddy covariance footprint. Results show that comparing eddy covariance and sap flow ET estimates eddy covariance technique is still accurate in this heterogeneous field, whereas the key assumption, surface homogeneity, is not preserved. Furthermore, interestingly wild olives still transpire at higher rates for the driest soil moisture conditions, confirming the hydraulic redistribution from soil below the roots, and from roots penetrating deep cracks in the underlying basalt parent rock.

Performance of vegetation indices from Landsat time series in deforestation monitoring

NASA Astrophysics Data System (ADS)

Schultz, Michael; Clevers, Jan G. P. W.; Carter, Sarah; Verbesselt, Jan; Avitabile, Valerio; Quang, Hien Vu; Herold, Martin

2016-10-01

The performance of Landsat time series (LTS) of eight vegetation indices (VIs) was assessed for monitoring deforestation across the tropics. Three sites were selected based on differing remote sensing observation frequencies, deforestation drivers and environmental factors. The LTS of each VI was analysed using the Breaks For Additive Season and Trend (BFAST) Monitor method to identify deforestation. A robust reference database was used to evaluate the performance regarding spatial accuracy, sensitivity to observation frequency and combined use of multiple VIs. The canopy cover sensitive Normalized Difference Fraction Index (NDFI) was the most accurate. Among those tested, wetness related VIs (Normalized Difference Moisture Index (NDMI) and the Tasselled Cap wetness (TCw)) were spatially more accurate than greenness related VIs (Normalized Difference Vegetation Index (NDVI) and Tasselled Cap greenness (TCg)). When VIs were fused on feature level, spatial accuracy was improved and overestimation of change reduced. NDVI and NDFI produced the most robust results when observation frequency varies.

Spatial analysis of agro-ecological data: Detection of spatial patterns combining three different methodical approaches

NASA Astrophysics Data System (ADS)

Heuer, A.; Casper, M. C.; Vohland, M.

2009-04-01

Processes in natural systems and the resulting patterns occur in ecological space and time. To study natural structures and to understand the functional processes it is necessary to identify the relevant spatial and temporal space at which these all occur; or with other words to isolate spatial and temporal patterns. In this contribution we will concentrate on the spatial aspects of agro-ecological data analysis. Data were derived from two agricultural plots, each of about 5 hectares, in the area of Newel, located in Western Palatinate, Germany. The plots had been conventionally cultivated with a crop rotation of winter rape, winter wheat and spring barley. Data about physical and chemical soil properties, vegetation and topography were i) collected by measurements in the field during three vegetation periods (2005-2008) and/or ii) derived from hyperspectral image data, acquired by a HyMap airborne imaging sensor (2005). To detect spatial variability within the plots, we applied three different approaches that examine and describe relationships among data. First, we used variography to get an overview of the data. A comparison of the experimental variograms facilitated to distinguish variables, which seemed to occur in related or dissimilar spatial space. Second, based on data available in raster-format basic cell statistics were conducted, using a geographic information system. Here we could make advantage of the powerful classification and visualization tool, which supported the spatial distribution of patterns. Third, we used an approach that is being used for visualization of complex highly dimensional environmental data, the Kohonen self-organizing map. The self-organizing map (SOM) uses multidimensional data that gets further reduced in dimensionality (2-D) to detect similarities in data sets and correlation between single variables. One of SOM's advantages is its powerful visualization capability. The combination of the three approaches leads to comprehensive and reasonable results, which will be presented in detail. It can be concluded, that the chosen strategy made it possible to complement preliminary findings, to validate the results of a single approach and to clearly delineate spatial patterns.

Predicting spatial patterns of plant recruitment using animal-displacement kernels.

PubMed

Santamaría, Luis; Rodríguez-Pérez, Javier; Larrinaga, Asier R; Pias, Beatriz

2007-10-10

For plants dispersed by frugivores, spatial patterns of recruitment are primarily influenced by the spatial arrangement and characteristics of parent plants, the digestive characteristics, feeding behaviour and movement patterns of animal dispersers, and the structure of the habitat matrix. We used an individual-based, spatially-explicit framework to characterize seed dispersal and seedling fate in an endangered, insular plant-disperser system: the endemic shrub Daphne rodriguezii and its exclusive disperser, the endemic lizard Podarcis lilfordi. Plant recruitment kernels were chiefly determined by the disperser's patterns of space utilization (i.e. the lizard's displacement kernels), the position of the various plant individuals in relation to them, and habitat structure (vegetation cover vs. bare soil). In contrast to our expectations, seed gut-passage rate and its effects on germination, and lizard speed-of-movement, habitat choice and activity rhythm were of minor importance. Predicted plant recruitment kernels were strongly anisotropic and fine-grained, preventing their description using one-dimensional, frequency-distance curves. We found a general trade-off between recruitment probability and dispersal distance; however, optimal recruitment sites were not necessarily associated to sites of maximal adult-plant density. Conservation efforts aimed at enhancing the regeneration of endangered plant-disperser systems may gain in efficacy by manipulating the spatial distribution of dispersers (e.g. through the creation of refuges and feeding sites) to create areas favourable to plant recruitment.

Climate and anthropogenic impacts on forest vegetation derived from satellite data

NASA Astrophysics Data System (ADS)

Zoran, M.; Savastru, R.; Savastru, D.; Tautan, M.; Miclos, S.; Baschir, L.

2010-09-01

Vegetation and climate interact through a series of complex feedbacks, which are not very well understood. The patterns of forest vegetation are largely determined by temperature, precipitation, solar irradiance, soil conditions and CO2 concentration. Vegetation impacts climate directly through moisture, energy, and momentum exchanges with the atmosphere and indirectly through biogeochemical processes that alter atmospheric CO2 concentration. Changes in forest vegetation land cover/use alter the surface albedo and radiation fluxes, leading to a local temperature change and eventually a vegetation response. This albedo (energy) feedback is particularly important when forests mask snow cover. Forest vegetation-climate feedback regimes are designated based on the temporal correlations between the vegetation and the surface temperature and precipitation. The different feedback regimes are linked to the relative importance of vegetation and soil moisture in determining land-atmosphere interactions. Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modeling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal forest vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images over 1989 - 2009 period for a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, from IKONOS and LANDSAT TM and ETM satellite images and meteorological data. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. For investigated test area, considerable NDVI decline was observed for drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation .

Demonstrating vegetation dynamics using SIMPPLLE

Treesearch

Glenda Scott; Jimmie D. Chew

1997-01-01

Understanding vegetation dynamics, both spatially and temporally, is essential to the management of natural resources. SIMPPLLE has been designed to help us quantify and communicate these concepts: What levels of process, i.e., fire or insect and disease, to expect; how they spread; what the vegetative distribution and composition is over time; and how silvicultural...

Cyberpark 2000: Protected Areas Management Pilot Project. Satellite time series vegetation monitoring

NASA Astrophysics Data System (ADS)

Monteleone, M.; Lanorte, A.; Lasaponara, R.

2009-04-01

Cyberpark 2000 is a project funded by the UE Regional Operating Program of the Apulia Region (2000-2006). The main objective of the Cyberpark 2000 project is to develop a new assessment model for the management and monitoring of protected areas in Foggia Province (Apulia Region) based on Information and Communication Technologies. The results herein described are placed inside the research activities finalized to develop an environmental monitoring system knowledge based on the use of satellite time series. This study include: - A- satellite time series of high spatial resolution data for supporting the analysis of fire static risk factors through land use mapping and spectral/quantitative characterization of vegetation fuels; - B- satellite time series of MODIS for supporting fire dynamic risk evaluation of study area - Integrated fire detection by using thermal imaging cameras placed on panoramic view-points; - C - integrated high spatial and high temporal satellite time series for supporting studies in change detection factors or anomalies in vegetation covers; - D - satellite time-series for monitoring: (i) post fire vegetation recovery and (ii) spatio/temporal vegetation dynamics in unburned and burned vegetation covers.

Landscapes of facilitation: how self-organized patchiness of aquatic macrophytes promotes diversity in streams.

PubMed

Cornacchia, Loreta; van de Koppel, Johan; van der Wal, Daphne; Wharton, Geraldene; Puijalon, Sara; Bouma, Tjeerd J

2018-04-01

Spatial heterogeneity plays a crucial role in the coexistence of species. Despite recognition of the importance of self-organization in creating environmental heterogeneity in otherwise uniform landscapes, the effects of such self-organized pattern formation in promoting coexistence through facilitation are still unknown. In this study, we investigated the effects of pattern formation on species interactions and community spatial structure in ecosystems with limited underlying environmental heterogeneity, using self-organized patchiness of the aquatic macrophyte Callitriche platycarpa in streams as a model system. Our theoretical model predicted that pattern formation in aquatic vegetation - due to feedback interactions between plant growth, water flow and sedimentation processes - could promote species coexistence, by creating heterogeneous flow conditions inside and around the plant patches. The spatial plant patterns predicted by our model agreed with field observations at the reach scale in naturally vegetated rivers, where we found a significant spatial aggregation of two macrophyte species around C. platycarpa. Field transplantation experiments showed that C. platycarpa had a positive effect on the growth of both beneficiary species, and the intensity of this facilitative effect was correlated with the heterogeneous hydrodynamic conditions created within and around C. platycarpa patches. Our results emphasize the importance of self-organized patchiness in promoting species coexistence by creating a landscape of facilitation, where new niches and facilitative effects arise in different locations. Understanding the interplay between competition and facilitation is therefore essential for successful management of biodiversity in many ecosystems. © 2018 The Authors Ecology published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.

An Ecology of Prestige in New York City: Examining the Relationships Among Population Density, Socio-economic Status, Group Identity, and Residential Canopy Cover

NASA Astrophysics Data System (ADS)

Grove, J. Morgan; Locke, Dexter H.; O'Neil-Dunne, Jarlath P. M.

2014-09-01

Several social theories have been proposed to explain the uneven distribution of vegetation in urban residential areas: population density, social stratification, luxury effect, and ecology of prestige. We evaluate these theories using a combination of demographic and socio-economic predictors of vegetative cover on all residential lands in New York City. We use diverse data sources including the City's property database, time-series demographic and socio-economic data from the US Census, and land cover data from the University of Vermont's Spatial Analysis Lab (SAL). These data are analyzed using a multi-model inferential, spatial econometrics approach. We also examine the distribution of vegetation within distinct market categories using Claritas' Potential Rating Index for Zipcode Markets (PRIZM™) database. These categories can be disaggregated, corresponding to the four social theories. We compare the econometric and categorical results for validation. Models associated with ecology of prestige theory are more effective for predicting the distribution of vegetation. This suggests that private, residential patterns of vegetation, reflecting the consumption of environmentally relevant goods and services, are associated with different lifestyles and lifestages. Further, our spatial and temporal analyses suggest that there are significant spatial and temporal dependencies that have theoretical and methodological implications for understanding urban ecological systems. These findings may have policy implications. Decision makers may need to consider how to most effectively reach different social groups in terms of messages and messengers in order to advance land management practices and achieve urban sustainability.