Characterizing Woody Vegetation Spectral and Structural Parameters with a 3-D Scene Model
NASA Astrophysics Data System (ADS)
Qin, W.; Yang, L.
2004-05-01
Quantification of structural and biophysical parameters of woody vegetation is of great significance in understanding vegetation condition, dynamics and functionality. Such information over a landscape scale is crucial for global and regional land cover characterization, global carbon-cycle research, forest resource inventories, and fire fuel estimation. While great efforts and progress have been made in mapping general land cover types over large area, at present, the ability to quantify regional woody vegetation structural and biophysical parameters is limited. One approach to address this research issue is through an integration of physically based 3-D scene model with multiangle and multispectral remote sensing data and in-situ measurements. The first step of this work is to model woody vegetation structure and its radiation regime using a physically based 3-D scene model and field data, before a robust operational algorithm can be developed for retrieval of important woody vegetation structural/biophysical parameters. In this study, we use an advanced 3-D scene model recently developed by Qin and Gerstl (2000), based on L-systems and radiosity theories. This 3-D scene model has been successfully applied to semi-arid shrubland to study structure and radiation regime at a regional scale. We apply this 3-D scene model to a more complicated and heterogeneous forest environment dominated by deciduous and coniferous trees. The data used in this study are from a field campaign conducted by NASA in a portion of the Superior National Forest (SNF) near Ely, Minnesota during the summers of 1983 and 1984, and supplement data collected during our revisit to the same area of SNF in summer of 2003. The model is first validated with reflectance measurements at different scales (ground observations, helicopter, aircraft, and satellite). Then its ability to characterize the structural and spectral parameters of the forest scene is evaluated. Based on the results from this study and the current multi-spectral and multi-angular satellite data (MODIS, MISR), a robust retrieval system to estimate woody vegetation structural/biophysical parameters is proposed.
Impact of small-scale vegetation structure on tephra layer preservation
Cutler, Nick A.; Shears, Olivia M.; Streeter, Richard T.; Dugmore, Andrew J.
2016-01-01
The factors that influence tephra layer taphonomy are poorly understood, but vegetation cover is likely to play a role in the preservation of terrestrial tephra deposits. The impact of vegetation on tephra layer preservation is important because: 1) the morphology of tephra layers could record key characteristics of past land surfaces and 2) vegetation-driven variability in tephra thickness could affect attempts to infer eruption and dispersion parameters. We investigated small- (metre-) scale interactions between vegetation and a thin (<10 cm), recent tephra layer. We conducted surveys of vegetation structure and tephra thickness at two locations which received a similar tephra deposit, but had contrasting vegetation cover (moss vs shrub). The tephra layer was thicker and less variable under shrub cover. Vegetation structure and layer thickness were correlated on the moss site but not under shrub cover, where the canopy reduced the influence of understory vegetation on layer morphology. Our results show that vegetation structure can influence tephra layer thickness on both small and medium (site) scales. These findings suggest that some tephra layers may carry a signal of past vegetation cover. They also have implications for the sampling effort required to reliably estimate the parameters of initial deposits. PMID:27845415
NASA Astrophysics Data System (ADS)
Karyati, K.; Ipor, I. B.; Jusoh, I.; Wasli, M. E.
2018-04-01
The tree growth is influenced by soil morphological and physicochemical properties in the site. The purpose of this study was to describe correlation between soil properties under various stage secondary forests and vegetation parameters, such as floristic structure parameters and floristic diversity indices. The vegetation surveys were conducted in 5, 10, and 20 years old at secondary tropical forests in Sarawak, Malaysia. Nine sub plots sized 20 m × 20 m were established within each study site. The Pearson analysis showed that soil physicochemical properties were significantly correlated to floristic structure parameters and floristic diversity indices. The result of PCA clarified the correlation among most important soil properties, floristic structure parameters, and floristic diversity indices. The PC1 represented cation retention capacity and soil texture which were little affected by the fallow age and its also were correlated by floristic structure and diversity. The PC2 was linked to the levels of soil acidity. This property reflected the remnant effects of ash addition and fallow duration, and the significant correlation were showed among pH (H2O), floristic structure and diversity. The PC3 represented the soil compactness. The soil hardness could be influenced by fallow period and it was also correlated by floristic structure.
Spatial-structural analysis of leafless woody riparian vegetation for hydraulic considerations
NASA Astrophysics Data System (ADS)
Weissteiner, Clemens; Jalonen, Johanna; Järvelä, Juha; Rauch, Hans Peter
2013-04-01
Woody riparian vegetation is a vital element of riverine environments. On one hand woody riparian vegetation has to be taken into account from a civil engineering point of view due to boundary shear stress and vegetation drag. On the other hand it has to be considered from a river ecological point of view due to shadowing effects and as a source of organic material for aquatic habitats. In hydrodynamic and hydro-ecological studies the effects of woody riparian vegetation on flow patterns are usually investigated on a very detailed level. On the contrary vegetation elements and their spatial patterns are generally analysed and discussed on the basis of an integral approach measuring for example basal diameters, heights and projected plant areas. For a better understanding of the influence of woody riparian vegetation on turbulent flow and on river ecology, it is essential to record and analyse plant data sets on the same level of quality as for hydrodynamic or hydro-ecologic purposes. As a result of the same scale of the analysis it is possible to incorporate riparian vegetation as a sub-model in the hydraulic analysis. For plant structural components, such as branches on different topological levels it is crucial to record plant geometrical parameters describing the habitus of the plant on branch level. An exact 3D geometrical model of real plants allows for an extraction of various spatial-structural plant parameters. In addition, allometric relationships help to summarize and describe plant traits of riparian vegetation. This paper focuses on the spatial-structural composition of leafless riparia woddy vegetation. Structural and spatial analyses determine detailed geometric properties of the structural components of the plants. Geometrical and topological parameters were recorded with an electro-magnetic scanning device. In total, 23 plants (willows, alders and birches) were analysed in the study. Data were recorded on branch level, which allowed for the development of a 3D geometric plant model. The results are expected to improve knowledge on how the architectural system and allometric relationships of the plants relate to ecological and hydrodynamic properties.
Lidar and Hyperspectral Remote Sensing for the Analysis of Coniferous Biomass Stocks and Fluxes
NASA Astrophysics Data System (ADS)
Halligan, K. Q.; Roberts, D. A.
2006-12-01
Airborne lidar and hyperspectral data can improve estimates of aboveground carbon stocks and fluxes through their complimentary responses to vegetation structure and biochemistry. While strong relationships have been demonstrated between lidar-estimated vegetation structural parameters and field data, research is needed to explore the portability of these methods across a range of topographic conditions, disturbance histories, vegetation type and climate. Additionally, research is needed to evaluate contributions of hyperspectral data in refining biomass estimates and determination of fluxes. To address these questions we are a conducting study of lidar and hyperspectral remote sensing data across sites including coniferous forests, broadleaf deciduous forests and a tropical rainforest. Here we focus on a single study site, Yellowstone National Park, where tree heights, stem locations, above ground biomass and basal area were mapped using first-return small-footprint lidar data. A new method using lidar intensity data was developed for separating the terrain and vegetation components in lidar data using a two-scale iterative local minima filter. Resulting Digital Terrain Models (DTM) and Digital Canopy Models (DCM) were then processed to retrieve a diversity of vertical and horizontal structure metrics. Univariate linear models were used to estimate individual tree heights while stepwise linear regression was used to estimate aboveground biomass and basal area. Three small-area field datasets were compared for their utility in model building and validation of vegetation structure parameters. All structural parameters were linearly correlated with lidar-derived metrics, with higher accuracies obtained where field and imagery data were precisely collocated . Initial analysis of hyperspectral data suggests that vegetation health metrics including measures of live and dead vegetation and stress indices may provide good indicators of carbon flux by mapping vegetation vigor or senescence. Additionally, the strength of hyperspectral data for vegetation classification suggests these data have additional utility for modeling carbon flux dynamics by allowing more accurate plant functional type mapping.
NASA Technical Reports Server (NTRS)
Musick, H. Brad
1993-01-01
The objectives of this research are: to develop and test predictive relations for the quantitative influence of vegetation canopy structure on wind erosion of semiarid rangeland soils, and to develop remote sensing methods for measuring the canopy structural parameters that determine sheltering against wind erosion. The influence of canopy structure on wind erosion will be investigated by means of wind-tunnel and field experiments using structural variables identified by the wind-tunnel and field experiments using model roughness elements to simulate plant canopies. The canopy structural variables identified by the wind-tunnel and field experiments as important in determining vegetative sheltering against wind erosion will then be measured at a number of naturally vegetated field sites and compared with estimates of these variables derived from analysis of remotely sensed data.
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
A remote sensing based vegetation classification logic for global land cover analysis
Running, Steven W.; Loveland, Thomas R.; Pierce, Lars L.; Nemani, R.R.; Hunt, E. Raymond
1995-01-01
This article proposes a simple new logic for classifying global vegetation. The critical features of this classification are that 1) it is based on simple, observable, unambiguous characteristics of vegetation structure that are important to ecosystem biogeochemistry and can be measured in the field for validation, 2) the structural characteristics are remotely sensible so that repeatable and efficient global reclassifications of existing vegetation will be possible, and 3) the defined vegetation classes directly translate into the biophysical parameters of interest by global climate and biogeochemical models. A first test of this logic for the continental United States is presented based on an existing 1 km AVHRR normalized difference vegetation index database. Procedures for solving critical remote sensing problems needed to implement the classification are discussed. Also, some inferences from this classification to advanced vegetation biophysical variables such as specific leaf area and photosynthetic capacity useful to global biogeochemical modeling are suggested.
NASA Astrophysics Data System (ADS)
Entekhabi, D.; Jagdhuber, T.; Das, N. N.; Baur, M.; Link, M.; Piles, M.; Akbar, R.; Konings, A. G.; Mccoll, K. A.; Alemohammad, S. H.; Montzka, C.; Kunstmann, H.
2016-12-01
The active-passive soil moisture retrieval algorithm of NASA's SMAP mission depends on robust statistical estimation of active-passive covariation (β) and vegetation structure (Γ) parameters in order to provide reliable global measurements of soil moisture on an intermediate level (9km) compared to the native resolution of the radiometer (36km) and radar (3km) instruments. These parameters apply to the SMAP radiometer-radar combination over the period of record that was cut short with the end of the SMAP radar transmission. They also apply to the current SMAP radiometer and Sentinel 1A/B radar combination for high-resolution surface soil moisture mapping. However, the performance of the statistically-based approach is directly dependent on the selection of a representative time frame in which these parameters can be estimated assuming dynamic soil moisture and stationary soil roughness and vegetation cover. Here, we propose a novel, data-driven and physics-based single-pass retrieval of active-passive microwave covariation and vegetation parameters for the SMAP mission. The algorithm does not depend on time series analyses and can be applied using minimum one pair of an active-passive acquisition. The algorithm stems from the physical link between microwave emission and scattering via conservation of energy. The formulation of the emission radiative transfer is combined with the Distorted Born Approximation of radar scattering for vegetated land surfaces. The two formulations are simultaneously solved for the covariation and vegetation structure parameters. Preliminary results from SMAP active-passive observations (April 13th to July 7th 2015) compare well with the time-series statistical approach and confirms the capability of this method to estimate these parameters. Moreover, the method is not restricted to a given frequency (applies to both L-band and C-band combinations for the radar) or incidence angle (all angles and not just the fixed 40° incidence). Therefore, the approach is applicable to the combination of SMAP and Sentinel-1A/B data for active-passive and high-resolution soil moisture estimation.
Exploring tropical forest vegetation dynamics using the FATES model
NASA Astrophysics Data System (ADS)
Koven, C. D.; Fisher, R.; Knox, R. G.; Chambers, J.; Kueppers, L. M.; Christoffersen, B. O.; Davies, S. J.; Dietze, M.; Holm, J.; Massoud, E. C.; Muller-Landau, H. C.; Powell, T.; Serbin, S.; Shuman, J. K.; Walker, A. P.; Wright, S. J.; Xu, C.
2017-12-01
Tropical forest vegetation dynamics represent a critical climate feedback in the Earth system, which is poorly represented in current global modeling approaches. We discuss recent progress on exploring these dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a demographic vegetation model for the CESM and ACME ESMs. We will discuss benchmarks of FATES predictions for forest structure against inventory sites, sensitivity of FATES predictions of size and age structure to model parameter uncertainty, and experiments using the FATES model to explore PFT competitive dynamics and the dynamics of size and age distributions in responses to changing climate and CO2.
Ecological optimality in water-limited natural soil-vegetation systems. I - Theory and hypothesis
NASA Technical Reports Server (NTRS)
Eagleson, P. S.
1982-01-01
The solution space of an approximate statistical-dynamic model of the average annual water balance is explored with respect to the hydrologic parameters of both soil and vegetation. Within the accuracy of this model it is shown that water-limited natural vegetation systems are in stable equilibrium with their climatic and pedologic environments when the canopy density and species act to minimize average water demand stress. Theory shows a climatic limit to this equilibrium above which it is hypothesized that ecological pressure is toward maximization of biomass productivity. It is further hypothesized that natural soil-vegetation systems will develop gradually and synergistically, through vegetation-induced changes in soil structure, toward a set of hydraulic soil properties for which the minimum stress canopy density of a given species is maximum in a given climate. Using these hypotheses, only the soil effective porosity need be known to determine the optimum soil and vegetation parameters in a given climate.
Approximating Reflectance and Transmittance of Vegetation Using Multiple Spectral Invariants
NASA Astrophysics Data System (ADS)
Mottus, M.
2011-12-01
Canopy spectral invariants, eigenvalues of the radiative transfer equation and photon recollision probability are some of the new theoretical tools that have been applied in remote sensing of vegetation and atmosphere. The theoretical approach based on spectral invariants, informally also referred to as the p-theory, owns its attractivity to several factors. Firstly, it provides a rapid and physically-based way of describing canopy scattering. Secondly, the p-theory aims at parameterizing canopy structure in reflectance models using a simple and intuitive concept which can be applied at various structural levels, from shoot to tree crown. The theory has already been applied at scales from the molecular level to forest stands. The most important shortcoming of the p-theory lies in its inability to predict the directionality of scattering. The theory is currently based on only one physical parameter, the photon recollision probability p. It is evident that one parameter cannot contain enough information to reasonably predict the observed complex reflectance patterns produced by natural vegetation canopies. Without estimating scattering directionality, however, the theory cannot be compared with even the most simple (and well-tested) two-stream vegetation reflectance models. In this study, we evaluate the possibility to use additional parameters to fit the measured reflectance and transmittance of a vegetation stand. As a first step, the parameters are applied to separate canopy scattering into reflectance and transmittance. New parameters are introduced following the general approach of eigenvector expansion. Thus, the new parameters are coined higher-order spectral invariants. Calculation of higher-order invariants is based on separating first-order scattering from total scattering. Thus, the method explicitly accounts for different view geometries with different fractions of visible sunlit canopy (e.g., hot-spot). It additionally allows to produce different irradiation levels on leaf surfaces for direct and diffuse incidence, thus (in theory) allowing more accurate calculation of potential photosynthesis rates. Similarly to the p-theory, the use of multiple spectral invariants facilitates easy parametrization of canopy structure and scaling between different structural levels (leaf-shoot-stand). Spectral invariant-based remote sensing approaches are well suited for relatively large pixels even when no detailed ground truth information is available. In a case study, the theory of multiple spectral invariants was applied to measured canopy scattering. Spectral reflectance and transmittance measurements were carried out in gray alder (Alnus incana) plantation at Tartu Observatory, Estonia, in August 2006. The equations produced by the theory of spectral invariants were fitted to measured radiation fluxes. Preliminary results indicate that quantities with invariant-like behavior may indeed be used to approximate canopy scattering directionality.
NASA Technical Reports Server (NTRS)
Oneill, P.; Jackson, T.; Blanchard, B. J.; Vandenhoek, R.; Gould, W.; Wang, J.; Glazar, W.; Mcmurtrey, J., III
1983-01-01
Field experiments to (1) study the biomass and geometrical structure properties of vegetation canopies to determine their impact on microwave emission data, and (2) to verify whether time series microwave data can be related to soil hydrologic properties for use in soil type classification. Truck mounted radiometers at 1.4 GHz and 5 GHz were used to obtain microwave brightness temperatures of bare vegetated test plots under different conditions of soil wetness, plant water content and canopy structure. Observations of soil moisture, soil temperature, vegetation biomass and other soil and canopy parameters were made concurrently with the microwave measurements. The experimental design and data collection procedures for both experiments are documented and the reduced data are presented in tabular form.
NASA Astrophysics Data System (ADS)
Ma, B.; Li, J.; Fan, W.; Ren, H.; Xu, X.
2017-12-01
Leaf area index (LAI) is one of the important parameters of vegetation canopy structure, which can represent the growth condition of vegetation effectively. The accuracy, availability and timeliness of LAI data can be improved greatly, which is of great importance to vegetation-related research, such as the study of atmospheric, land surface and hydrological processes to obtain LAI by remote sensing method. Heihe River Basin is the inland river basin in northwest China. There are various types of vegetation and all kinds of terrain conditions in the basin, so it is helpful for testing the accuracy of the model under the complex surface and evaluating the correctness of the model to study LAI in this area. On the other hand, located in west arid area of China, the ecological environment of Heihe Basin is fragile, LAI is an important parameter to represent the vegetation growth condition, and can help us understand the status of vegetation in the Heihe River Basin. Different from the previous LAI inversion models, the BRDF (bidirectional reflectance distribution function) unified model can be applied for both continuous vegetation and discrete vegetation, it is appropriate to the complex vegetation distribution. LAI is the key input parameter of the model. We establish the inversion algorithm that can exactly retrieve LAI using remote sensing image based on the unified model. First, we determine the vegetation type through the vegetation classification map to obtain the corresponding G function, leaf and surface reflectivity. Then, we need to determine the leaf area index (LAI), the aggregation index (ζ) and the sky scattered light ratio (β) range and the value of the interval, entering all the parameters into the model to calculate the corresponding reflectivity ρ and establish the lookup table of different vegetation. Finally, we can invert LAI on the basis of the established lookup table. The principle of inversion is least squares method. We have produced 1 km LAI products from 2000 to 2014, once every 8 days. The results show that the algorithm owns good stability and can effectively invert LAI in areas with very complex vegetation and terrain conditions.
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.
NASA Technical Reports Server (NTRS)
Musick, H. Brad; Truman, C. Randall; Trujillo, Steven M.
1992-01-01
Wind erosion in semi-arid regions is a significant problem for which the sheltering effect of rangeland vegetation is poorly understood. Individual plants may be considered as porous roughness elements which absorb or redistribute the wind's momentum. The saltation threshold is the minimum wind velocity at which soil movement begins. The dependence of the saltation threshold on geometrical parameters of a uniform roughness array was studied in a wind tunnel. Both solid and porous elements were used to determine relationships between canopy structure and the threshold velocity for soil transport. The development of a predictive relation for the influence of vegetation canopy structure on wind erosion of soil is discussed.
NASA Astrophysics Data System (ADS)
Vasilopoulos, G.; Leyland, J.; Nield, J. M.
2016-12-01
Plants function as large-scale, flexible obstacles that exert additional drag on water flows, affecting local scale turbulence and the structure of the boundary layer. Hence, vegetation plays a significant role controlling surface water flows and modulating geomorphic change. This makes it an important, but often under considered, component when undertaking flood or erosion control actions, or designing river restoration strategies. Vegetative drag varies depending on flow conditions and the associated vegetation structure and temporary reconfiguration of the plant. Whilst several approaches have been developed to describe this relationship, they have been limited due to the difficulty of accurately and precisely characterising the vegetation itself, especially when it is submerged in flow. In practice, vegetative drag is commonly expressed through bulk parameters that are typically derived from lookup tables. Terrestrial Laser Scanning (TLS) has the ability to capture the surface of in situ objects as 3D point clouds, at high resolution (mm), precision and accuracy, even when submerged in water. This allows for the development of workflows capable of quantifying vegetation structure in 3D from dense TLS point cloud data. A physical modelling experiment investigated the impact of a series of structurally variable plants on flow at three different velocities. Acoustic Doppler Velocimetry (ADV) was employed to measure the velocity field and the corresponding fluvial drag of the vegetation was estimated using a bulk roughness function calculated from precise measurements of the water surface slope. Simultaneously, through-water TLS was employed to capture snapshots of plant deformation and distinguish plant structure during flow, using a porosity approach. Although plant type is important, we find a good relationship between plant structure, drag and adjustments of the velocity field.
NASA Astrophysics Data System (ADS)
Bochet, E.; García-Fayos, P.; Molina, M. J.; Moreno de las Heras, M.; Espigares, T.; Nicolau, J. M.; Monleon, V. J.
2017-12-01
Theoretical models predict that drylands are particularly prone to suffer critical transitions with abrupt non-linear changes in their structure and functions as a result of the existing complex interactions between climatic fluctuations and human disturbances. How drylands undergo functional change has become an important issue in ecology which needs empirical data to validate theoretical models. We aim at determining the response of Mediterranean holm oak woodlands to human disturbance in three different climatic areas from Eastern Spain, under the hypothesis that semiarid and dry-transition landscapes are more prone to suffer abrupt functional changes than sub-humid ones. We used (a) remote-sensing estimations of precipitation-use-efficiency (PUE) from enhanced vegetation index (EVI) observations performed in 231 x 231 m plots of the Moderate Resolution Imaging Spectroradiometer (MODIS); (b) soil parameter (enzyme activity, organic matter) and (c) vegetation parameter (functional groups) determinations from soil sampling and vegetation surveys, respectively, performed in the same plots. We analyzed and compared the shape of the functional change (in terms of PUE, soil and vegetation parameters) in response to human disturbance intensity for our holm oak sites in the three climatic areas. Although no threshold of abrupt change is observed, important differences in the functional response of holm oak woodlands to disturbance exist between climatic conditions. Overall, semiarid and dry-transition woodlands suffer a non-linear functional decrease in terms of PUE, soil organic matter and enzyme activity with disturbance intensity. Differently, sub-humid woodlands experience a linear decrease of PUE with disturbance intensity and an increase of both soil parameters at high disturbance intensities after an important decrease at low disturbance intensities. The structural change from woody- to herbaceous-dominated landscapes in sub-humid areas explains the recovery of the functional state of the system at high disturbance intensities. This structural change in the vegetation provides resilience to sub-humid woodlands at high intensity levels where semiarid and dry-transition woodlands suffer a pronounced degradation.
Wallace, C.S.A.; Marsh, S.E.
2005-01-01
Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts. ?? 2005 Taylor & Francis Group Ltd.
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.
Modeling the bidirectional reflectance distribution function of mixed finite plant canopies and soil
NASA Technical Reports Server (NTRS)
Schluessel, G.; Dickinson, R. E.; Privette, J. L.; Emery, W. J.; Kokaly, R.
1994-01-01
An analytical model of the bidirectional reflectance for optically semi-infinite plant canopies has been extended to describe the reflectance of finite depth canopies contributions from the underlying soil. The model depends on 10 independent parameters describing vegetation and soil optical and structural properties. The model is inverted with a nonlinear minimization routine using directional reflectance data for lawn (leaf area index (LAI) is equal to 9.9), soybeans (LAI, 2.9) and simulated reflectance data (LAI, 1.0) from a numerical bidirectional reflectance distribution function (BRDF) model (Myneni et al., 1988). While the ten-parameter model results in relatively low rms differences for the BRDF, most of the retrieved parameters exhibit poor stability. The most stable parameter was the single-scattering albedo of the vegetation. Canopy albedo could be derived with an accuracy of less than 5% relative error in the visible and less than 1% in the near-infrared. Sensitivity were performed to determine which of the 10 parameters were most important and to assess the effects of Gaussian noise on the parameter retrievals. Out of the 10 parameters, three were identified which described most of the BRDF variability. At low LAI values the most influential parameters were the single-scattering albedos (both soil and vegetation) and LAI, while at higher LAI values (greater than 2.5) these shifted to the two scattering phase function parameters for vegetation and the single-scattering albedo of the vegetation. The three-parameter model, formed by fixing the seven least significant parameters, gave higher rms values but was less sensitive to noise in the BRDF than the full ten-parameter model. A full hemispherical reflectance data set for lawn was then interpolated to yield BRDF values corresponding to advanced very high resolution radiometer (AVHRR) scan geometries collected over a period of nine days. The resulting parameters and BRDFs are similar to those for the full sampling geometry, suggesting that the limited geometry of AVHRR measurements might be used to reliably retrieve BRDF and canopy albedo with this model.
NASA Astrophysics Data System (ADS)
Gao, Tian; Qiu, Ling; Hammer, Mårten; Gunnarsson, Allan
2012-02-01
Temporal and spatial vegetation structure has impact on biodiversity qualities. Yet, current schemes of biotope mapping do only to a limited extend incorporate these factors in the mapping. The purpose of this study is to evaluate the application of a modified biotope mapping scheme that includes temporal and spatial vegetation structure. A refined scheme was developed based on a biotope classification, and applied to a green structure system in Helsingborg city in southern Sweden. It includes four parameters of vegetation structure: continuity of forest cover, age of dominant trees, horizontal structure, and vertical structure. The major green structure sites were determined by interpretation of panchromatic aerial photographs assisted with a field survey. A set of biotope maps was constructed on the basis of each level of modified classification. An evaluation of the scheme included two aspects in particular: comparison of species richness between long-continuity and short-continuity forests based on identification of woodland continuity using ancient woodland indicators (AWI) species and related historical documents, and spatial distribution of animals in the green space in relation to vegetation structure. The results indicate that (1) the relationship between forest continuity: according to verification of historical documents, the richness of AWI species was higher in long-continuity forests; Simpson's diversity was significantly different between long- and short-continuity forests; the total species richness and Shannon's diversity were much higher in long-continuity forests shown a very significant difference. (2) The spatial vegetation structure and age of stands influence the richness and abundance of the avian fauna and rabbits, and distance to the nearest tree and shrub was a strong determinant of presence for these animal groups. It is concluded that continuity of forest cover, age of dominant trees, horizontal and vertical structures of vegetation should now be included in urban biotope classifications.
NASA Astrophysics Data System (ADS)
Perdana, B. P.; Setiawan, Y.; Prasetyo, L. B.
2018-02-01
Recently, a highway development is required as a liaison between regions to support the economic development of the regions. Even the availability of highways give positive impacts, it also has negative impacts, especially related to the changes of vegetated lands. This study aims to determine the change of vegetation coverage in Jagorawi corridor Jakarta-Bogor during 37 years, and to analyze landscape patterns in the corridor based on distance factor from Jakarta to Bogor. In this study, we used a long-series of Landsat images taken by Landsat 2 MSS (1978), Landsat 5 TM (1988, 1995, and 2005) and Landsat 8 OLI/TIRS (2015). Analysis of landscape metrics was conducted through patch analysis approach to determine the change of landscape patterns in the Jagorawi corridor Jakarta-Bogor. Several parameters of landscape metrics used are Number of Patches (NumP), Mean Patch Size (MPS), Mean Shape Index (MSI), and Edge Density (ED). These parameters can be used to provide information of structural elements of landscape, composition and spatial distribution in the corridor. The results indicated that vegetation coverage in the Jagorawi corridor Jakarta-Bogor decreased about 48% for 35 years. Moreover, NumP value increased and decreasing of MPS value as a means of higher fragmentation level occurs with patch size become smaller. Meanwhile, The increase in ED parameters indicates that vegetated land is damaged annually. MSI parameter shows a decrease in every year which means land degradation on vegetated land. This indicates that the declining value of MSI will have an impact on land degradation.
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.
NASA Astrophysics Data System (ADS)
Scholl, V.; Hulslander, D.; Goulden, T.; Wasser, L. A.
2015-12-01
Spatial and temporal monitoring of vegetation structure is important to the ecological community. Airborne Light Detection and Ranging (LiDAR) systems are used to efficiently survey large forested areas. From LiDAR data, three-dimensional models of forests called canopy height models (CHMs) are generated and used to estimate tree height. A common problem associated with CHMs is data pits, where LiDAR pulses penetrate the top of the canopy, leading to an underestimation of vegetation height. The National Ecological Observatory Network (NEON) currently implements an algorithm to reduce data pit frequency, which requires two height threshold parameters, increment size and range ceiling. CHMs are produced at a series of height increments up to a height range ceiling and combined to produce a CHM with reduced pits (referred to as a "pit-free" CHM). The current implementation uses static values for the height increment and ceiling (5 and 15 meters, respectively). To facilitate the generation of accurate pit-free CHMs across diverse NEON sites with varying vegetation structure, the impacts of adjusting the height threshold parameters were investigated through development of an algorithm which dynamically selects the height increment and ceiling. A series of pit-free CHMs were generated using three height range ceilings and four height increment values for three ecologically different sites. Height threshold parameters were found to change CHM-derived tree heights up to 36% compared to original CHMs. The extent of the parameters' influence on modelled tree heights was greater than expected, which will be considered during future CHM data product development at NEON. (A) Aerial image of Harvard National Forest, (B) standard CHM containing pits, appearing as black speckles, (C) a pit-free CHM created with the static algorithm implementation, and (D) a pit-free CHM created through varying the height threshold ceiling up to 82 m and the increment to 1 m.
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.
Estimating Vegetation Structure in African Savannas using High Spatial Resolution Imagery
NASA Astrophysics Data System (ADS)
Axelsson, C.; Hanan, N. P.
2016-12-01
High spatial resolution satellite imagery allows for detailed mapping of trees in savanna landscapes, including estimates of woody cover, tree densities, crown sizes, and the spatial pattern of trees. By linking these vegetation parameters to rainfall and soil properties we gain knowledge of how the local environment influences vegetation. A thorough understanding of the underlying ecosystem processes is key to assessing the future productivity and stability of these ecosystems. In this study, we have processed and analyzed hundreds of sites sampled from African savannas across a wide range of rainfall and soil conditions. The vegetation at each site is classified using unsupervised classification with manual assignment into woody, herbaceous and bare cover classes. A crown delineation method further divides the woody areas into individual tree crowns. The results show that rainfall, soil, and topography interactively influence vegetation structure. We see that both total rainfall and rainfall seasonality play important roles and that soil type influences woody cover and the sizes of tree crowns.
Effects of corn stalk orientation and water content on passive microwave sensing of soil moisture
NASA Technical Reports Server (NTRS)
Oneill, P. E.; Blanchard, B. J.; Wang, J. R.; Gould, W. I.; Jackson, T. J.
1984-01-01
A field experiment was conducted utilizing artificial arrangements of plant components during the summer of 1982 to examine the effects of corn canopy structure and plant water content on microwave emission. Truck-mounted microwave radiometers at C (5 GHz) and L (1.4 GHz) band sensed vertically and horizontally polarized radiation concurrent with ground observations of soil moisture and vegetation parameters. Results indicate that the orientation of cut stalks and the distribution of their dielectric properties through the canopy layer can influence the microwave emission measured from a vegetation/soil scene. The magnitude of this effect varies with polarization and frequency and with the amount of water in the plant, disappearing at low levels of vegetation water content. Although many of the canopy structures and orientations studied in this experiment are somewhat artificial, they serve to improve understanding of microwave energy interactions within a vegetation canopy and to aid in the development of appropriate physically based vegetation models.
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.
Barton Clinton; James Vose; Jennifer Knoepp; Katherine Elliott; Barbara Reynolds; Stanley Zarnock
2010-01-01
We characterized structural and functional attributes along hillslope gradients in headwater catchments. We endeavored to identify parameters that described significant transitions along the hillslope. On each of four catchments, we installed eight 50 m transects perpendicular to the stream. Structural attributes included woody and herbaceous vegetation; woody debris...
MODELING PHYSICAL HABITAT PARAMETERS
Salmonid populations can be affected by alterations in stream physical habitat. Fish productivity is determined by the stream's physical habitat structure ( channel form, substrate distribution, riparian vegetation), water quality, flow regime and inputs from the watershed (sedim...
Mapping Vegetation Structure in Kakadu National Park: An AIRSAR and GIS Application in Conservation
NASA Technical Reports Server (NTRS)
Imhoff, Marc L.; Sisk, Thomas D.; Hampton, Haydee; Milne, Anthony K.
1999-01-01
Airborne Synthetic Aperture Radar (AIRSAR) data were used to map vegetation structure in Kakadu National Park Australia as part of the PACRIM project. SAR data were co-registered with Landsat TM, aerial photos, and map data in a geographic information system for a small test area consisting of mangrove, floodplain grasslands, lowland tropical evergreen forest and upland mixed deciduous and evergreen tropical forest near the South Alligator River. Landsat (Thematic Mapper) TM very clearly showed the floristic composition and burn scars from the previous years fires and the AIRSAR data provided a profile of vegetation structure. Extensive field data on vegetation species composition and structure were collected across a series of transects in cooperation with a survey of avifauna in an effort to link the habitat edge structure with bird species responses. A test site was found that contained two types of habitat edges: 1) A structure specific edge - characterized by the appearance of a very strong structural change in the forest canopy occurring in the absence of a substantial turnover in floristics. 2) Floristic edge - a sharp transition in vegetation genetic composition with a mixed set of structural changes. Specific polarization combinations were selected that were highly correlated to a set of desired structural parameters found in the field data. Classification routines were employed to group radar pixels into 3 structural classes based on: the Surface Area to Volume ratio (SA/V) of the stems, the SA/V of the branches, and the leaf area index of the canopy. Separate canopy structure maps were then entered into the GIS and bird responses were observed relative to the classes and their boundaries. Follow-on work will consist of extending this approach to neighboring areas, generating structure maps, predicting bird responses across the edges, and make accuracy assessments.
Derivation of global vegetation biophysical parameters from EUMETSAT Polar System
NASA Astrophysics Data System (ADS)
García-Haro, Francisco Javier; Campos-Taberner, Manuel; Muñoz-Marí, Jordi; Laparra, Valero; Camacho, Fernando; Sánchez-Zapero, Jorge; Camps-Valls, Gustau
2018-05-01
This paper presents the algorithm developed in LSA-SAF (Satellite Application Facility for Land Surface Analysis) for the derivation of global vegetation parameters from the AVHRR (Advanced Very High Resolution Radiometer) sensor on board MetOp (Meteorological-Operational) satellites forming the EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Polar System (EPS). The suite of LSA-SAF EPS vegetation products includes the leaf area index (LAI), the fractional vegetation cover (FVC), and the fraction of absorbed photosynthetically active radiation (FAPAR). LAI, FAPAR, and FVC characterize the structure and the functioning of vegetation and are key parameters for a wide range of land-biosphere applications. The algorithm is based on a hybrid approach that blends the generalization capabilities offered by physical radiative transfer models with the accuracy and computational efficiency of machine learning methods. One major feature is the implementation of multi-output retrieval methods able to jointly and more consistently estimate all the biophysical parameters at the same time. We propose a multi-output Gaussian process regression (GPRmulti), which outperforms other considered methods over PROSAIL (coupling of PROSPECT and SAIL (Scattering by Arbitrary Inclined Leaves) radiative transfer models) EPS simulations. The global EPS products include uncertainty estimates taking into account the uncertainty captured by the retrieval method and input errors propagation. A sensitivity analysis is performed to assess several sources of uncertainties in retrievals and maximize the positive impact of modeling the noise in training simulations. The paper discusses initial validation studies and provides details about the characteristics and overall quality of the products, which can be of interest to assist the successful use of the data by a broad user's community. The consistent generation and distribution of the EPS vegetation products will constitute a valuable tool for monitoring of earth surface dynamic processes.
Algorithm for retrieving vegetative canopy and leaf parameters from multi- and hyperspectral imagery
NASA Astrophysics Data System (ADS)
Borel, Christoph
2009-05-01
In recent years hyper-spectral data has been used to retrieve information about vegetative canopies such as leaf area index and canopy water content. For the environmental scientist these two parameters are valuable, but there is potentially more information to be gained as high spatial resolution data becomes available. We developed an Amoeba (Nelder-Mead or Simplex) based program to invert a vegetative canopy radiosity model coupled with a leaf (PROSPECT5) reflectance model and modeled for the background reflectance (e.g. soil, water, leaf litter) to a measured reflectance spectrum. The PROSPECT5 leaf model has five parameters: leaf structure parameter Nstru, chlorophyll a+b concentration Cab, carotenoids content Car, equivalent water thickness Cw and dry matter content Cm. The canopy model has two parameters: total leaf area index (LAI) and number of layers. The background reflectance model is either a single reflectance spectrum from a spectral library() derived from a bare area pixel on an image or a linear mixture of soil spectra. We summarize the radiosity model of a layered canopy and give references to the leaf/needle models. The method is then tested on simulated and measured data. We investigate the uniqueness, limitations and accuracy of the retrieved parameters on canopy parameters (low, medium and high leaf area index) spectral resolution (32 to 211 band hyperspectral), sensor noise and initial conditions.
Effective Tree Scattering at L-Band
NASA Technical Reports Server (NTRS)
Kurum, Mehmet; ONeill, Peggy E.; Lang, Roger H.; Joseph, Alicia T.; Cosh, Michael H.; Jackson, Thomas J.
2011-01-01
For routine microwave Soil Moisture (SM) retrieval through vegetation, the tau-omega [1] model [zero-order Radiative Transfer (RT) solution] is attractive due to its simplicity and eases of inversion and implementation. It is the model used in baseline retrieval algorithms for several planned microwave space missions, such as ESA's Soil Moisture Ocean Salinity (SMOS) mission (launched November 2009) and NASA's Soil Moisture Active Passive (SMAP) mission (to be launched 2014/2015) [2 and 3]. These approaches are adapted for vegetated landscapes with effective vegetation parameters tau and omega by fitting experimental data or simulation outputs of a multiple scattering model [4-7]. The model has been validated over grasslands, agricultural crops, and generally light to moderate vegetation. As the density of vegetation increases, sensitivity to the underlying SM begins to degrade significantly and errors in the retrieved SM increase accordingly. The zero-order model also loses its validity when dense vegetation (i.e. forest, mature corn, etc.) includes scatterers, such as branches and trunks (or stalks in the case of corn), which are large with respect to the wavelength. The tau-omega model (when applied over moderately to densely vegetated landscapes) will need modification (in terms of form or effective parameterization) to enable accurate characterization of vegetation parameters with respect to specific tree types, anisotropic canopy structure, presence of leaves and/or understory. More scattering terms (at least up to first-order at L-band) should be included in the RT solutions for forest canopies [8]. Although not really suitable to forests, a zero-order tau-omega model might be applied to such vegetation canopies with large scatterers, but that equivalent or effective parameters would have to be used [4]. This requires that the effective values (vegetation opacity and single scattering albedo) need to be evaluated (compared) with theoretical definitions of these parameters. In a recent study [9], effective vegetation opacity of coniferous trees was compared with two independent estimates of the same parameter. First, a zero-order RT model was fitted to multiangular microwave emissivity data in a least-square sense to provide effective vegetation optical depth as done in spaceborne retrieval algorithms. Second, a ratio between radar backscatter measurements with a corner reflector under trees and in an open area was calculated to obtain measured tree propagation characteristics. Finally, the theoretical propagation constant was determined by forward scattering theorem using detailed measurements of size/angle distributions and dielectric constants of the tree constituents (trunk, branches, and needles). Results indicated that the effective attenuation values are smaller than but of similar magnitude to both the theoretical and measured values. This study will complement the previous work [9] and will focus on characterization of effective scattering albedo by assuming that effective vegetation opacity is same as theoretical opacity. The resultant effective albedo will not be the albedo of single forest canopy element anymore, but it becomes a global parameter, which depends on all the processes taking place within the canopy including multiple scattering as described.
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.
NASA Astrophysics Data System (ADS)
Song, Jinling; Qu, Yonghua; Wang, Jindi; Wan, Huawei; Liu, Xiaoqing
2007-06-01
Radiosity method is based on the computer simulation of 3D real structures of vegetations, such as leaves, branches and stems, which are composed by many facets. Using this method we can simulate the canopy reflectance and its bidirectional distribution of the vegetation canopy in visible and NIR regions. But with vegetations are more complex, more facets to compose them, so large memory and lots of time to calculate view factors are required, which are the choke points of using Radiosity method to calculate canopy BRF of lager scale vegetation scenes. We derived a new method to solve the problem, and the main idea is to abstract vegetation crown shapes and to simplify their structures, which can lessen the number of facets. The facets are given optical properties according to the reflectance, transmission and absorption of the real structure canopy. Based on the above work, we can simulate the canopy BRF of the mix scenes with different species vegetation in the large scale. In this study, taking broadleaf trees as an example, based on their structure characteristics, we abstracted their crowns as ellipsoid shells, and simulated the canopy BRF in visible and NIR regions of the large scale scene with different crown shape and different height ellipsoids. Form this study, we can conclude: LAI, LAD the probability gap, the sunlit and shaded surfaces are more important parameter to simulate the simplified vegetation canopy BRF. And the Radiosity method can apply us canopy BRF data in any conditions for our research.
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.
On the use of tower-flux measurements to assess the performance of global ecosystem models
NASA Astrophysics Data System (ADS)
El Maayar, M.; Kucharik, C.
2003-04-01
Global ecosystem models are important tools for the study of biospheric processes and their responses to environmental changes. Such models typically translate knowledge, gained from local observations, into estimates of regional or even global outcomes of ecosystem processes. A typical test of ecosystem models consists of comparing their output against tower-flux measurements of land surface-atmosphere exchange of heat and mass. To perform such tests, models are typically run using detailed information on soil properties (texture, carbon content,...) and vegetation structure observed at the experimental site (e.g., vegetation height, vegetation phenology, leaf photosynthetic characteristics,...). In global simulations, however, earth's vegetation is typically represented by a limited number of plant functional types (PFT; group of plant species that have similar physiological and ecological characteristics). For each PFT (e.g., temperate broadleaf trees, boreal conifer evergreen trees,...), which can cover a very large area, a set of typical physiological and physical parameters are assigned. Thus, a legitimate question arises: How does the performance of a global ecosystem model run using detailed site-specific parameters compare with the performance of a less detailed global version where generic parameters are attributed to a group of vegetation species forming a PFT? To answer this question, we used a multiyear dataset, measured at two forest sites with contrasting environments, to compare seasonal and interannual variability of surface-atmosphere exchange of water and carbon predicted by the Integrated BIosphere Simulator-Dynamic Global Vegetation Model. Two types of simulations were, thus, performed: a) Detailed runs: observed vegetation characteristics (leaf area index, vegetation height,...) and soil carbon content, in addition to climate and soil type, are specified for model run; and b) Generic runs: when only observed climates and soil types at the measurement sites are used to run the model. The generic runs were performed for the number of years equal to the current age of the forests, initialized with no vegetation and a soil carbon density equal to zero.
Yang, Yanzheng; Zhu, Qiuan; Peng, Changhui; Wang, Han; Xue, Wei; Lin, Guanghui; Wen, Zhongming; Chang, Jie; Wang, Meng; Liu, Guobin; Li, Shiqing
2016-01-01
Increasing evidence indicates that current dynamic global vegetation models (DGVMs) have suffered from insufficient realism and are difficult to improve, particularly because they are built on plant functional type (PFT) schemes. Therefore, new approaches, such as plant trait-based methods, are urgently needed to replace PFT schemes when predicting the distribution of vegetation and investigating vegetation sensitivity. As an important direction towards constructing next-generation DGVMs based on plant functional traits, we propose a novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China. The results demonstrated that a Gaussian mixture model (GMM) trained with a LMA-Nmass-LAI data combination yielded an accuracy of 72.82% in simulating vegetation distribution, providing more detailed parameter information regarding community structures and ecosystem functions. The new approach also performed well in analyses of vegetation sensitivity to different climatic scenarios. Although the trait-climate relationship is not the only candidate useful for predicting vegetation distributions and analysing climatic sensitivity, it sheds new light on the development of next-generation trait-based DGVMs. PMID:27052108
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.
Najgebauer-Lejko, Dorota; Tabaszewska, Małgorzata; Grega, Tadeusz
2015-01-01
Vegetables, apart from having high nutritional value, also contain considerable amounts of dietary fibre and other components, which may affect physico-chemical properties of fermented milks, e.g. viscosity, texture, susceptibility to syneresis, flavour profile etc. The present work was established to study the effect of selected vegetables addition on the rheological, textural, microbiological and flavour profile parameters of yoghurts. The vegetable preparations (carrot, pumpkin, broccoli and red sweet pepper) were added (10% w/w) to the processed cow's milk fermented with DVS yoghurt culture. Texture profile analysis, determination of viscosity, susceptibility to syneresis and descriptive flavour evaluation were conducted at the 1st, 7th and 14th day after production. Additionally, microbiological studies were performed for 28 days, at 7-day intervals. The highest apparent viscosity and adhesiveness were obtained for the carrot yoghurt, whereas yoghurt with pumpkin was the least susceptible to syneresis. The other texture parameters were not affected by the addition of vegetables. Broccoli and red sweet pepper flavours were dominating in the fermented milks fortified with these vegetables, whereas carrot and pumpkin flavours were less distinctive. Yoghurt supplemented with red sweet pepper got the highest sensoric acceptability. The number of starter bacteria was not influenced by the vegetable additives, except for pumpkin yoghurt, which contained lower population of lactobacilli. Among all tested vegetables, carrot additive had the greatest potential to improve yoghurt structure, whereas red sweet pepper imparted the most acceptable flavour.
Rentería, Jorge Luis; Gardener, Mark R.; Panetta, F. Dane; Atkinson, Rachel; Crawley, Mick J.
2012-01-01
Originally from Asia, Rubus niveus has become one of the most widespread invasive plant species in the Galapagos Islands. It has invaded open vegetation, shrubland and forest alike. It forms dense thickets up to 4 m high, appearing to displace native vegetation, and threaten the integrity of several native communities. This study used correlation analysis between a R. niveus cover gradient and a number of biotic (vascular plant species richness, cover and vegetation structure) and abiotic (light and soil properties) parameters to help understand possible impacts in one of the last remaining fragments of the Scalesia forest in Santa Cruz Island, Galapagos. Higher cover of R. niveus was associated with significantly lower native species richness and cover, and a different forest structure. Results illustrated that 60% R. niveus cover could be considered a threshold for these impacts. We suggest that a maximum of 40% R. niveus cover could be a suitable management target. PMID:23118934
Nikolic, Nina; Böcker, Reinhard; Nikolic, Miroslav
2016-07-01
Despite the growing popularity of ecological restoration approach, data on primary succession on toxic post-mining substrates, under site environmental conditions which considerably differ from the surrounding environment, are still scarce. Here, we studied the spontaneous vegetation development on an unusual locality created by long-term and large-scale fluvial deposition of sulphidic tailings from a copper mine in a pronouncedly xerothermic, calcareous surrounding. We performed multivariate analyses of soil samples (20 physical and chemical parameters) and vegetation samples (floristic and structural parameters in three types of occurring forests), collected along the pollution gradients throughout the affected floodplain. The nature can cope with two types of imposed constraints: (a) excessive Cu concentrations and (b) very low pH, combined with nutrient deficiency. The former will still allow convergence to the original vegetation, while the latter will result in novel, depauperate assemblages of species typical for cooler and moister climate. Our results for the first time demonstrate that with the increasing severity of environmental filtering, the relative importance of the surrounding vegetation for primary succession strongly decreases.
Building a global hotspot ecology with Triana data
NASA Astrophysics Data System (ADS)
Gerstl, Siegfried A. W.
1999-12-01
Triana is an Earth remote sensing satellite to be located at the distant Langrange Point L-1, the gravity-neutral point between the Earth and the Sun. It will provide continuous fill disk images of the entire sunlit side of the Earth with 8 km pixel resolution. The primary remote sensing instrument on Triana is a calibrated multispectral imager with 10 spectral channels in the UV, VIS, and NIR between 317 and 870 nm (reflected solar radiation). Due to its unique location at the Lagrange L-1 point, in the direct line-of-sight between Earth and Sun, Triana will view the Earth always in and near the solar retro-reflection direction which is also known as the hotspot direction. The canopy hotspot effect has rich information content for vegetation characterization, especially indications of canopy structure and vegetation health and stress situations. Primary vegetation-related data are the hotspot angular width W, and a hotspot factor C that quantifies the magnitude of the hotspot effect. Both quantities are related to the structural parameters of canopy height, foliage size, shape, and leaf area index (LAI). The continuous observations by Triana will allow us to establish time-series of these ecological parameters for all land biomes by longitude, latitude, and wavelength, that form the basis data set for a new global hotspot land vegetation ecology. The hotspot factor C will allow the determination of the enhanced radiant flux reflected from the Earth into space due to the hotspot effect. The hotspot flux enhancement due to the vegetation hotspot effect is estimated to account for about 1% of the entire Earth radiative energy balance.
Burgio, Giovanni; Sommaggio, Daniele; Marini, Mario; Puppi, Giovanna; Chiarucci, Alessandro; Landi, Sara; Fabbri, Roberto; Pesarini, Fausto; Genghini, Marco; Ferrari, Roberto; Muzzi, Enrico; van Lenteren, Joop C; Masetti, Antonio
2015-10-01
Landscape structure as well as local vegetation influence biodiversity in agroecosystems. A study was performed to evaluate the effect of floristic diversity, vegetation patterns, and landscape structural connectivity on butterflies (Lepidoptera: Papilionoidea and Hesperiidae), carabids (Coleoptera: Carabidae), syrphids (Diptera: Syrphidae), and sawflies (Hymenoptera: Symphyta). Vegetation analysis and insect samplings were carried out in nine sites within an intensively farmed landscape in northern Italy. Plant species richness and the percentage of tree, shrub, and herb cover were determined by means of the phytosociological method of Braun-Blanquet. Landscape structural connectivity was measured as the total length of hedgerow network (LHN) in a radius of 500 m around the center of each sampling transect. Butterflies species richness and abundance were positively associated both to herb cover and to plant species richness, but responded negatively to tree and shrub cover. Shrub cover was strictly correlated to both species richness and activity density of carabids. The species richness of syrphids was positively influenced by herb cover and plant richness, whereas their abundance was dependent on ligneous vegetation and LHN. Rarefaction analysis revealed that sawfly sampling was not robust and no relationship could be drawn with either vegetation parameters or structural connectivity. The specific responses of each insect group to the environmental factors should be considered in order to refine and optimize landscape management interventions targeting specific conservation endpoints. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Estimating riparian understory vegetation cover with beta regression and copula models
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.
NASA Astrophysics Data System (ADS)
A, Y.; Wang, G.
2017-12-01
Water shortage is the main limiting factor for semi-arid grassland development. However, the grassland are gradually degraded represented by species conversion, biomass decrease and ecosystem structure simplification under the influence of human activity. Soil water characteristics such as moisture, infiltration and conductivity are critical variables affecting the interactions between soil parameters and vegetation. In this study, Cover, Height, Shannon-Wiener diversity index, Pielou evenness index and Richness index are served as indexes of vegetation productivity and community structure. And saturated hydraulic conductivity (Ks) and soil moisture content are served as indexes of soil water characters. The interaction between vegetation and soil water is investigated through other soil parameters, such as soil organic matter content at different vertical depths and in different degradation area (e.g., initial, transition and degraded plots). The results show that Ks significantly controlled by soil texture other than soil organic matter content. So the influence of vegetation on Ks through increasing soil organic content (SOM) might be slight. However, soil moisture content (SMC) appeared significantly positive relationship with SOM and silt content and negative relationship with sand content at all depth, significantly. This indicated that capacity of soil water storage was influenced both by soil texture and organic matter. In addition, the highest correlation coefficient of SMC was with SOM at the sub-surficial soil layer (20 40 cm). At the depth of 20 40 cm, the soil water content was relatively steady which slightly influenced by precipitation and evaporation. But it significantly influenced by soil organic matter content which related to vegetation. The correlation coefficient between SOM and SMC at topsoil layer (0 20 cm) was lowest (R2=0.36, p<0.01), which indicated the influence of vegetation on soil water content not only by soil organic matter content but also the other influential factors, such as the root water uptake, precipitation and evaporation.
Ji, Cuicui; Jia, Yonghong; Gao, Zhihai; Wei, Huaidong; Li, Xiaosong
2017-01-01
Desert vegetation plays significant roles in securing the ecological integrity of oasis ecosystems in western China. Timely monitoring of photosynthetic/non-photosynthetic desert vegetation cover is necessary to guide management practices on land desertification and research into the mechanisms driving vegetation recession. In this study, nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates are investigated through comparing the performance of linear and nonlinear spectral mixture models with different endmembers applied to field spectral measurements of two types of typical desert vegetation, namely, Nitraria shrubs and Haloxylon. The main results were as follows. (1) The correct selection of endmembers is important for improving the accuracy of vegetation cover estimates, and in particular, shadow endmembers cannot be neglected. (2) For both the Nitraria shrubs and Haloxylon, the Kernel-based Nonlinear Spectral Mixture Model (KNSMM) with nonlinear parameters was the best unmixing model. In consideration of the computational complexity and accuracy requirements, the Linear Spectral Mixture Model (LSMM) could be adopted for Nitraria shrubs plots, but this will result in significant errors for the Haloxylon plots since the nonlinear spectral mixture effects were more obvious for this vegetation type. (3) The vegetation canopy structure (planophile or erectophile) determines the strength of the nonlinear spectral mixture effects. Therefore, no matter for Nitraria shrubs or Haloxylon, the non-linear spectral mixing effects between the photosynthetic / non-photosynthetic vegetation and the bare soil do exist, and its strength is dependent on the three-dimensional structure of the vegetation canopy. The choice of linear or nonlinear spectral mixture models is up to the consideration of computational complexity and the accuracy requirement.
Jia, Yonghong; Gao, Zhihai; Wei, Huaidong
2017-01-01
Desert vegetation plays significant roles in securing the ecological integrity of oasis ecosystems in western China. Timely monitoring of photosynthetic/non-photosynthetic desert vegetation cover is necessary to guide management practices on land desertification and research into the mechanisms driving vegetation recession. In this study, nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates are investigated through comparing the performance of linear and nonlinear spectral mixture models with different endmembers applied to field spectral measurements of two types of typical desert vegetation, namely, Nitraria shrubs and Haloxylon. The main results were as follows. (1) The correct selection of endmembers is important for improving the accuracy of vegetation cover estimates, and in particular, shadow endmembers cannot be neglected. (2) For both the Nitraria shrubs and Haloxylon, the Kernel-based Nonlinear Spectral Mixture Model (KNSMM) with nonlinear parameters was the best unmixing model. In consideration of the computational complexity and accuracy requirements, the Linear Spectral Mixture Model (LSMM) could be adopted for Nitraria shrubs plots, but this will result in significant errors for the Haloxylon plots since the nonlinear spectral mixture effects were more obvious for this vegetation type. (3) The vegetation canopy structure (planophile or erectophile) determines the strength of the nonlinear spectral mixture effects. Therefore, no matter for Nitraria shrubs or Haloxylon, the non-linear spectral mixing effects between the photosynthetic / non-photosynthetic vegetation and the bare soil do exist, and its strength is dependent on the three-dimensional structure of the vegetation canopy. The choice of linear or nonlinear spectral mixture models is up to the consideration of computational complexity and the accuracy requirement. PMID:29240777
Review on urban vegetation and particle air pollution - Deposition and dispersion
NASA Astrophysics Data System (ADS)
Janhäll, Sara
2015-03-01
Urban vegetation affects air quality through influencing pollutant deposition and dispersion. Both processes are described by many existing models and experiments, on-site and in wind tunnels, focussing e.g. on urban street canyons and crossings or vegetation barriers adjacent to traffic sources. There is an urgent need for well-structured experimental data, including detailed empirical descriptions of parameters that are not the explicit focus of the study. This review revealed that design and choice of urban vegetation is crucial when using vegetation as an ecosystem service for air quality improvements. The reduced mixing in trafficked street canyons on adding large trees increases local air pollution levels, while low vegetation close to sources can improve air quality by increasing deposition. Filtration vegetation barriers have to be dense enough to offer large deposition surface area and porous enough to allow penetration, instead of deflection of the air stream above the barrier. The choice between tall or short and dense or sparse vegetation determines the effect on air pollution from different sources and different particle sizes.
Rocha-Pessôa, T C; Nunes-Freitas, A F; Cogliatti-Carvalho, L; Rocha, C F D
2008-05-01
We studied some ecological parameters such as richness, abundance, density, biomass and variation in species composition in four vegetation zones and in a zone with anthropic disturbance in the Massambaba Restinga in Arraial do Cabo, Rio de Janeiro State. We sampled 100 plots of 100 m(2) (10 x 10 m) recording the bromeliad species and their abundance. We found a total of seven bromeliad species, with Vriesea neoglutinosa (5647 ramets) and Tillandsia stricta (1277 ramets) being the most abundant. The vegetation zone called Clusia shrubs had the highest richness (S = 5) and density (6360 ramets.ha(-1)) of bromeliads. The differences found in abundance and variation in species composition among vegetation zones seems to be related to the vegetation structure of each zone.
Using a LIDAR Vegetation Model to Predict UHF SAR Attenuation in Coniferous Forests
Swanson, Alan; Huang, Shengli; Crabtree, Robert
2009-01-01
Attenuation of radar signals by vegetation can be a problem for target detection and GPS reception, and is an important parameter in models describing vegetation backscatter. Here we first present a model describing the 3D distribution of stem and foliage structure based on small footprint scanning LIDAR data. Secondly we present a model that uses ray-tracing methodology to record detailed interactions between simulated radar beams and vegetation components. These interactions are combined over the SAR aperture and used to predict two-way attenuation of the SAR signal. Accuracy of the model is demonstrated using UHF SAR observations of large trihedral corner reflectors in coniferous forest stands. Our study showed that the model explains between 66% and 81% of the variability in observed attenuation. PMID:22573972
NASA Astrophysics Data System (ADS)
Callegaro, Chiara; Ursino, Nadia
2016-04-01
Self-organizing vegetation patterns are natural water harvesting systems in arid and semi-arid regions of the world and should be imitated when designing man-managed water-harvesting systems for rain-fed crop. Disconnected vegetated and bare zones, functioning as a source-sink system of resources, sustain vegetation growth and reduce water and soil losses. Mechanisms such as soil crusting over bare areas and soil loosening in vegetated areas feed back to the local net facilitation effect and contribute to maintain the patterned landscape structure. Dis-connectivity of run-off production and run-on infiltration sites reduces runoff production at the landscape scale, and increases water retention in the vegetated patches. What is the effect of species adaptation to different resource niches on the landscape structure? A minimal model for two coexisting species and soil moisture balance was formulated, to improve our understanding of the effects of species differentiation on the dynamics of plants and water at single-pattern and landscape scale within a tiger bush type ecosystem. A basic assumption of our model was that soil moisture availability is a proxy for the environmental niche of plant species. Connectivity and dis-connectivity of specific niches of adaptation of two differing plant species was an input parameter of our model, in order to test the effect of coexistence on the ecosystem structure. The ecosystem structure is the model outcome, including: patterns persistence of coexisting species; patterns persistence of one species with exclusion of the other; patterns decline with just one species surviving in a non organized structure; bare landscape with loss of both species. Results suggest that pattern-forming-species communities arise as a result of complementary niche adaptation (niche dis-connecivity), whereas niche superposition (niche connectivity) may lead to impoverishment of environmental resources and loss of vegetation cover and diversity.
Measuring grassland structure for recovery of grassland species at risk
NASA Astrophysics Data System (ADS)
Guo, Xulin; Gao, Wei; Wilmshurst, John
2005-09-01
An action plan for recovering species at risk (SAR) depends on an understanding of the plant community distribution, vegetation structure, quality of the food source and the impact of environmental factors such as climate change at large scale and disturbance at small scale, as these are fundamental factors for SAR habitat. Therefore, it is essential to advance our knowledge of understanding the SAR habitat distribution, habitat quality and dynamics, as well as developing an effective tool for measuring and monitoring SAR habitat changes. Using the advantages of non-destructive, low cost, and high efficient land surface vegetation biophysical parameter characterization, remote sensing is a potential tool for helping SAR recovery action. The main objective of this paper is to assess the most suitable techniques for using hyperspectral remote sensing to quantify grassland biophysical characteristics. The challenge of applying remote sensing in semi-arid and arid regions exists simply due to the lower biomass vegetation and high soil exposure. In conservation grasslands, this problem is enhanced because of the presence of senescent vegetation. Results from this study demonstrated that hyperspectral remote sensing could be the solution for semi-arid grassland remote sensing applications. Narrow band raw data and derived spectral vegetation indices showed stronger relationships with biophysical variables compared to the simulated broad band vegetation indices.
Mapping Alpine Vegetation Location Properties by Dense Matching
NASA Astrophysics Data System (ADS)
Niederheiser, Robert; Rutzinger, Martin; Lamprecht, Andrea; Steinbauer, Klaus; Winkler, Manuela; Pauli, Harald
2016-06-01
Highly accurate 3D micro topographic mapping in mountain research demands for light equipment and low cost solutions. Recent developments in structure from motion and dense matching techniques provide promising tools for such applications. In the following, the feasibility of terrestrial photogrammetry for mapping topographic location properties of sparsely vegetated areas in selected European mountain regions is investigated. Changes in species composition at alpine vegetation locations are indicators of climate change consequences, such as the pronounced rise of average temperatures in mountains compared to the global average. Better understanding of climate change effects on plants demand for investigations on a micro-topographic scale. We use professional and consumer grade digital single-lens reflex cameras mapping 288 plots each 3 x 3 m on 18 summits in the Alps and Mediterranean Mountains within the GLORIA (GLobal Observation Research Initiative in Alpine environments) network. Image matching tests result in accuracies that are in the order of millimetres in the XY-plane and below 0.5 mm in Z-direction at the second image pyramid level. Reconstructing vegetation proves to be a challenge due to its fine and small structured architecture and its permanent movement by wind during image acquisition, which is omnipresent on mountain summits. The produced 3D point clouds are gridded to 6 mm resolution from which topographic parameters such as slope, aspect and roughness are derived. At a later project stage these parameters will be statistically linked to botanical reference data in order to conclude on relations between specific location properties and species compositions.
Divergent Impacts of Two Cattle Types on Vegetation in Coastal Meadows: Implications for Management
NASA Astrophysics Data System (ADS)
Laurila, Marika; Huuskonen, Arto; Pesonen, Maiju; Kaseva, Janne; Joki-Tokola, Erkki; Hyvärinen, Marko
2015-11-01
The proportion of beef cattle in relation to the total number of cattle has increased in Europe, which has led to a higher contribution of beef cattle in the management of semi-natural grasslands. Changes in vegetation caused by this change in grazers are virtually unexplored so far. In the present study, the impacts of beef and dairy cattle on vegetation structure and composition were compared on Bothnian Bay coastal meadows. Vegetation parameters were measured in seven beef cattle, six dairy heifer pastures, and in six unmanaged meadows. Compared to unmanaged meadows, vegetation in grazed meadows was significantly lower in height and more frequently colonized by low-growth species. As expected, vegetation grazed by beef cattle was more open than that on dairy heifer pastures where litter cover and proportion of bare ground were in the same level as in the unmanaged meadows. However, the observed differences may have in part arisen from the higher cattle densities in coastal meadows grazed by beef cattle than by dairy heifers. The frequencies of different species groups and the species richness values of vegetation did not differ between the coastal meadows grazed by the two cattle types. One reason for this may be the relatively short management history of the studied pastures. The potential differences in grazing impacts of the two cattle types on vegetation structure can be utilized in the management of coastal meadows for species with divergent habitat requirements.
Critical thickness ratio for buckled and wrinkled fruits and vegetables
NASA Astrophysics Data System (ADS)
Dai, Hui-Hui; Liu, Yang
2014-11-01
This work aims at establishing the geometrical constraint for buckled and wrinkled shapes by modeling a fruit/vegetable with exocarp and sarcocarp as a hyperelastic layer-substrate structure subjected to uniaxial compression. A careful analysis on the derived bifurcation condition leads to the finding of a critical thickness ratio which separates the buckling and wrinkling modes, and remarkably, which is independent of the material stiffnesses. More specifically, it is found that if the thickness ratio is smaller than this critical value a fruit/vegetable should be in a buckled shape (under a sufficient stress); if a fruit/vegetable is in a wrinkled shape the thickness ratio is always larger than this critical value. To verify the theoretical prediction, we consider four types of buckled fruits/vegetables and four types of wrinkled fruits/vegetables with three samples in each type. The geometrical parameters for the 24 samples are measured and it is found that indeed all the data fall into the theoretically predicted buckling or wrinkling domains.
Wheat growth monitoring with radar vegetation indices
USDA-ARS?s Scientific Manuscript database
Microwave remote sensing can help in the monitoring of crop growth. Many experiments have been carried out to investigate the sensitivity of microwave sensors to crop growth parameters. These have clearly shown that canopy structure and water content can greatly affect the measurements. For agricult...
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.
NASA Astrophysics Data System (ADS)
Tinoco, R. O.; Goldstein, E. B.; Coco, G.
2016-12-01
We use a machine learning approach to seek accurate, physically sound predictors, to estimate two relevant flow parameters for open-channel vegetated flows: mean velocities and drag coefficients. A genetic programming algorithm is used to find a robust relationship between properties of the vegetation and flow parameters. We use data published from several laboratory experiments covering a broad range of conditions to obtain: a) in the case of mean flow, an equation that matches the accuracy of other predictors from recent literature while showing a less complex structure, and b) for drag coefficients, a predictor that relies on both single element and array parameters. We investigate different criteria for dataset size and data selection to evaluate their impact on the resulting predictor, as well as simple strategies to obtain only dimensionally consistent equations, and avoid the need for dimensional coefficients. The results show that a proper methodology can deliver physically sound models representative of the processes involved, such that genetic programming and machine learning techniques can be used as powerful tools to study complicated phenomena and develop not only purely empirical, but "hybrid" models, coupling results from machine learning methodologies into physics-based models.
NASA Astrophysics Data System (ADS)
Braghiere, Renato; Quaife, Tristan; Black, Emily
2016-04-01
Incoming shortwave radiation is the primary source of energy driving the majority of the Earth's climate system. The partitioning of shortwave radiation by vegetation into absorbed, reflected, and transmitted terms is important for most of biogeophysical processes, including leaf temperature changes and photosynthesis, and it is currently calculated by most of land surface schemes (LSS) of climate and/or numerical weather prediction models. The most commonly used radiative transfer scheme in LSS is the two-stream approximation, however it does not explicitly account for vegetation architectural effects on shortwave radiation partitioning. Detailed three-dimensional (3D) canopy radiative transfer schemes have been developed, but they are too computationally expensive to address large-scale related studies over long time periods. Using a straightforward one-dimensional (1D) parameterisation proposed by Pinty et al. (2006), we modified a two-stream radiative transfer scheme by including a simple function of Sun zenith angle, so-called "structure factor", which does not require an explicit description and understanding of the complex phenomena arising from the presence of vegetation heterogeneous architecture, and it guarantees accurate simulations of the radiative balance consistently with 3D representations. In order to evaluate the ability of the proposed parameterisation in accurately represent the radiative balance of more complex 3D schemes, a comparison between the modified two-stream approximation with the "structure factor" parameterisation and state-of-art 3D radiative transfer schemes was conducted, following a set of virtual scenarios described in the RAMI4PILPS experiment. These experiments have been evaluating the radiative balance of several models under perfectly controlled conditions in order to eliminate uncertainties arising from an incomplete or erroneous knowledge of the structural, spectral and illumination related canopy characteristics typical of model comparisons with in-situ observations. The structure factor parameters were obtained for each canopy structure through the inversion against direct and diffuse fraction of absorbed photosynthetically active radiation (fAPAR), and albedo PAR. Overall, the modified two-stream approximation consistently showed a good agreement with the RAMI4PILPS reference values under direct and diffuse illumination conditions. It is an efficient and accurate tool to derive PAR absorptance and reflectance for scenarios with different canopy densities, leaf densities and soil background albedos, with especial attention to brighter backgrounds, i.e., snowy. The major difficulty of its applicability in the real world is to acquire the parameterisation parameters from in-situ observations. The derivation of parameters from Digital Hemispherical Photographs (DHP) is highly promising at forest stands scales. DHP provide a permanent record and are a valuable information source for position, size, density, and distribution of canopy gaps. The modified two-stream approximation parameters were derived from gap probability data extracted from DHP obtained in a woody savannah in California, USA. Values of fAPAR and albedo PAR were evaluated against a tree-based vegetation canopy model, MAESPA, which used airborne LiDAR data to define the individual-tree locations, and extract structural information such as tree height and crown diameter. The parameterisation improved the performance of a two-stream approximation by making it achieves comparable results to complex 3D model calculations under observed conditions.
NASA Astrophysics Data System (ADS)
Moorthy, Inian
Spectroscopic observational data for vegetated environments, have been coupled with 3D physically-based radiative transfer models for retrievals of biochemical and biophysical indicators of vegetation health and condition. With the recent introduction of Terrestrial Laser Scanning (TLS) units, there now exists a means of rapidly measuring intricate structural details of vegetation canopies, which can also serve as input into 3D radiative transfer models. In this investigation, Intelligent Laser Ranging and Imaging System (ILRIS-3D) data was acquired of individual tree crowns in laboratory, and field-based experiments. The ILRIS-3D uses the Time-Of-Flight (TOF) principle to measure the distances of objects based on the time interval between laser pulse exitance and return, upon reflection from an object. At the laboratory-level, this exploratory study demonstrated and validated innovative approaches for retrieving crown-level estimates of Leaf Area Index (LAI) (r2 = 0.98, rmse = 0.26m2/m2), a critical biophysical parameter for vegetation monitoring and modeling. These methods were implemented and expanded in field experiments conducted in olive (Olea europaea L.) orchards in Cordoba, Spain, where ILRIS-3D observations for 24 structurally-variable trees were made. Robust methodologies were developed to characterize diagnostic architectural parameters, such as tree height (r2 = 0.97, rmse = 0.21m), crown width (r 2 = 0.98, rmse = 0.12m), crown height (r2 = 0.81, rmse = 0.11m), crown volume (r2 = 0.99, rmse = 2.6m3), and LAI (r2 = 0.76, rmse = 0.27m2/ m2). These parameters were subsequently used as direct inputs into the Forest LIGHT (FLIGHT) 3D ray tracing model for characterization of the spectral behavior of the olive crowns. Comparisons between FLIGHT-simulated spectra and measured data showed small differences in the visible (< 3%) and near infrared (< 10%) spectral ranges. These differences between model simulations and measurements were significantly correlated to TLS-derived tree crown complexity metrics. The specific implications of internal crown complexity on estimating leaf chlorophyll concentration, a pertinent physiological health indicator, is highlighted. This research demonstrates that TLS systems can potentially be the new observational tool and benchmark for precise characterization of vegetation architecture for synergy with 3D radiative transfer models for improved operational management of agricultural crops.
Simulation of Soil Quality with Riparian Forests and Cultivated with Sugarcane
NASA Astrophysics Data System (ADS)
da Silva, Luiz Gabriel; Colato, Alexandre; Casagrande, José Carlos; Soares, Marcio Roberto; Perissatto Meneghin, Silvana
2013-04-01
Riparian forests are entrusted with important hydrological functions, such as riparian zone protection, filtering sediments and nutrients and mitigation of the amount of nutrients and xenobiotic molecules from the surrounding agro ecosystems. The soil was sampled in the depths of 0-0,2 and 0.2-0.4 m and its chemical (nutrient content and organic matter, cationic exchange capacity - CEC, sum of bases-SB, bases saturation, V%, and aluminum saturation, m%); physical (particle size distribution, density and porosity) and microbiological attributes (basal respiration and microbial biomass) were determined. This work aimed to study the liner method of combining data, figures of merit (FoM), weighing process and the scoring functions developed by Wymore and asses the quality of the soil (SQI) by means of chemical, physical and microbiological soil attributes, employing the additive pondered model for two areas of riparian forest at different stages of ecological succession and an adjacent area cultivated with sugar cane, located on the dam shores of Sugar Mill Saint Lucia-Araras/SP. Some hierarchical functions containing FoMs and their parameters were constructed, and from them weights were assigned to each FoM and parameter, in a way that cluster of structures with the same FoMs and parameters with different weights were formed. These clusters were used to calculate the SQI for all vegetal formations considering two types of soil (Oxisol and Podzol), in that way, the SQI was calculated for each combination of vegetation and soil. The SQIs values were usually higher in the oldest riparian forest, while the recent riparian forest showed the smallest SQI values, for both types of soil. The variation of values within a combination vegetation/soil was also different between all combinations, being that the set of values from the oldest riparian forest presented the lowest amplitude. It was also observed that the Oxisols, regardless of the vegetation, presented higher SQIs values and smaller amplitude than the Podzols. It can be noted that this occurs mainly due to the amount of organic matter (OM) in the soil, that besides differ between all the vegetations and types of soil, influences many parameters used in the model. Thus, in the structures where was assigned higher weighs to OM, the SQIs values tended to present higher differences between the combinations with great amount of OM and these with small amount of OM, which can be noted clearly comparing the SQIs values from the oldest riparian forest with the other vegetations.
NASA Technical Reports Server (NTRS)
Treuhaft, Robert N.; Law, Beverly E.; Siqueira, Paul R.
2000-01-01
Parameters describing the vertical structure of forests, for example tree height, height-to-base-of-live-crown, underlying topography, and leaf area density, bear on land-surface, biogeochemical, and climate modeling efforts. Single, fixed-baseline interferometric synthetic aperture radar (INSAR) normalized cross-correlations constitute two observations from which to estimate forest vertical structure parameters: Cross-correlation amplitude and phase. Multialtitude INSAR observations increase the effective number of baselines potentially enabling the estimation of a larger set of vertical-structure parameters. Polarimetry and polarimetric interferometry can further extend the observation set. This paper describes the first acquisition of multialtitude INSAR for the purpose of estimating the parameters describing a vegetated land surface. These data were collected over ponderosa pine in central Oregon near longitude and latitude -121 37 25 and 44 29 56. The JPL interferometric TOPSAR system was flown at the standard 8-km altitude, and also at 4-km and 2-km altitudes, in a race track. A reference line including the above coordinates was maintained at 35 deg for both the north-east heading and the return southwest heading, at all altitudes. In addition to the three altitudes for interferometry, one line was flown with full zero-baseline polarimetry at the 8-km altitude. A preliminary analysis of part of the data collected suggests that they are consistent with one of two physical models describing the vegetation: 1) a single-layer, randomly oriented forest volume with a very strong ground return or 2) a multilayered randomly oriented volume; a homogeneous, single-layer model with no ground return cannot account for the multialtitude correlation amplitudes. Below the inconsistency of the data with a single-layer model is followed by analysis scenarios which include either the ground or a layered structure. The ground returns suggested by this preliminary analysis seem too strong to be plausible, but parameters describing a two-layer compare reasonably well to a field-measured probability distribution of tree heights in the area.
NASA Astrophysics Data System (ADS)
Borg, Å.; Pihl, L.; Wennhage, H.
1997-08-01
Habitat choice by juvenile cod ( Gadus morhua L.) on sandy bottoms with different vegetation types was studied in laboratory. The experiment was conducted day and night in flow-through tanks on two different size-classes of cod (7-13 and 17-28 cm TL). Four habitats, typical of shallow soft bottoms on the Swedish west coast: Fucus vesiculosus, Zostera marina, Cladophora sp. and bare sand, were set up pair-wise in six combinations. The main difference between habitats in this study was vegetation structure, since all parameters except vegetation type was considered equal for both sides of the experimental tanks and natural prey was eliminated. The results showed a difference in habitat utilization by juvenile cod between day (light) and night (dark). During day time the fishes showed a significant preference for vegetation, while nocturnally no significant choice of habitat was made. Both size-classes preferred Fucus, considered the most complex habitat in this study, when this was available. The smaller size-class seemed to be able to utilize the other vegetation types as well, always preferring vegetation over sand. Larger juvenile cod, on the other hand, appeared to be restricted to Fucus. This difference in habitat choice by the two size-classes might be due to a greater dependence on shelter from predation by the smaller juveniles, causing them to associate more strongly with vegetation. The larger juveniles avoided Cladophora, since they might have difficulties in entering the compact structure of this filamentous algae. Availability of vegetation at day time, as a predation refuge, as well as of open sandy areas for feeding during night, thus seems to be important for juvenile cod. It is concluded that eutrophication-induced changes in habitat structure, such as increased dominance by filamentous algae, could alter the availability of predation refuges and foraging habitats for juvenile cod.
Modelisation de l'architecture des forets pour ameliorer la teledetection des attributs forestiers
NASA Astrophysics Data System (ADS)
Cote, Jean-Francois
The quality of indirect measurements of canopy structure, from in situ and satellite remote sensing, is based on knowledge of vegetation canopy architecture. Technological advances in ground-based, airborne or satellite remote sensing can now significantly improve the effectiveness of measurement programs on forest resources. The structure of vegetation canopy describes the position, orientation, size and shape of elements of the canopy. The complexity of the canopy in forest environments greatly limits our ability to characterize forest structural attributes. Architectural models have been developed to help the interpretation of canopy structural measurements by remote sensing. Recently, the terrestrial LiDAR systems, or TLiDAR (Terrestrial Light Detection and Ranging), are used to gather information on the structure of individual trees or forest stands. The TLiDAR allows the extraction of 3D structural information under the canopy at the centimetre scale. The methodology proposed in my Ph.D. thesis is a strategy to overcome the weakness in the structural sampling of vegetation cover. The main objective of the Ph.D. is to develop an architectural model of vegetation canopy, called L-Architect (LiDAR data to vegetation Architecture), and to focus on the ability to document forest sites and to get information on canopy structure from remote sensing tools. Specifically, L-Architect reconstructs the architecture of individual conifer trees from TLiDAR data. Quantitative evaluation of L-Architect consisted to investigate (i) the structural consistency of the reconstructed trees and (ii) the radiative coherence by the inclusion of reconstructed trees in a 3D radiative transfer model. Then, a methodology was developed to quasi-automatically reconstruct the structure of individual trees from an optimization algorithm using TLiDAR data and allometric relationships. L-Architect thus provides an explicit link between the range measurements of TLiDAR and structural attributes of individual trees. L-Architect has finally been applied to model the architecture of forest canopy for better characterization of vertical and horizontal structure with airborne LiDAR data. This project provides a mean to answer requests of detailed canopy architectural data, difficult to obtain, to reproduce a variety of forest covers. Because of the importance of architectural models, L-Architect provides a significant contribution for improving the capacity of parameters' inversion in vegetation cover for optical and lidar remote sensing. Mots-cles: modelisation architecturale, lidar terrestre, couvert forestier, parametres structuraux, teledetection.
Radar polarimetry - Analysis tools and applications
NASA Technical Reports Server (NTRS)
Evans, Diane L.; Farr, Tom G.; Van Zyl, Jakob J.; Zebker, Howard A.
1988-01-01
The authors have developed several techniques to analyze polarimetric radar data from the NASA/JPL airborne SAR for earth science applications. The techniques determine the heterogeneity of scatterers with subregions, optimize the return power from these areas, and identify probable scattering mechanisms for each pixel in a radar image. These techniques are applied to the discrimination and characterization of geologic surfaces and vegetation cover, and it is found that their utility varies depending on the terrain type. It is concluded that there are several classes of problems amenable to single-frequency polarimetric data analysis, including characterization of surface roughness and vegetation structure, and estimation of vegetation density. Polarimetric radar remote sensing can thus be a useful tool for monitoring a set of earth science parameters.
NASA Technical Reports Server (NTRS)
Blair, J. Bryan; Nelson, B.; dosSantos, J.; Valeriano, D.; Houghton, R.; Hofton, M.; Lutchke, S.; Sun, Q.
2002-01-01
A flight mission of NASA GSFC's Laser Vegetation Imaging Sensor (LVIS) is planned for June-August 2003 in the Amazon region of Brazil. The goal of this flight mission is to map the vegetation height and structure and ground topography of a large area of the Amazon. This data will be used to produce maps of true ground topography, vegetation height, and estimated above-ground biomass and for comparison with and potential calibration of Synthetic Aperture Radar (SAR) data. Approximately 15,000 sq. km covering various regions of the Amazon will be mapped. The LVIS sensor has the unique ability to accurately sense the ground topography beneath even the densest of forest canopies. This is achieved by using a high signal-to-noise laser altimeter to detect the very weak reflection from the ground that is available only through small gaps in between leaves and between tree canopies. Often the amount of ground signal is 1% or less of the total returned echo. Once the ground elevation is identified, that is used as the reference surface from which we measure the vertical height and structure of the vegetation. Test data over tropical forests have shown excellent correlation between LVIS measurements and biomass, basal area, stem density, ground topography, and canopy height. Examples of laser altimetry data over forests and the relationships to biophysical parameters will be shown. Also, recent advances in the LVIS instrument will be discussed.
Drag coefficients for modeling flow through emergent vegetation in the Florida Everglades
Lee, J.K.; Roig, L.C.; Jenter, H.L.; Visser, H.M.
2004-01-01
Hydraulic data collected in a flume fitted with pans of sawgrass were analyzed to determine the vertically averaged drag coefficient as a function of vegetation characteristics. The drag coefficient is required for modeling flow through emergent vegetation at low Reynolds numbers in the Florida Everglades. Parameters of the vegetation, such as the stem population per unit bed area and the average stem/leaf width, were measured for five fixed vegetation layers. The vertically averaged vegetation parameters for each experiment were then computed by weighted average over the submerged portion of the vegetation. Only laminar flow through emergent vegetation was considered, because this is the dominant flow regime of the inland Everglades. A functional form for the vegetation drag coefficient was determined by linear regression of the logarithmic transforms of measured resistance force and Reynolds number. The coefficients of the drag coefficient function were then determined for the Everglades, using extensive flow and vegetation measurements taken in the field. The Everglades data show that the stem spacing and the Reynolds number are important parameters for the determination of vegetation drag coefficient. ?? 2004 Elsevier B.V. All rights reserved.
Roberts, Susan L.; Van Wagtendonk, Jan W.; Miles, A. Keith; Kelt, Douglas A.; Lutz, James A.
2008-01-01
We evaluated the impact of fire severity and related spatial and vegetative parameters on small mammal populations in 2 yr- to 15 yr-old burns in Yosemite National Park, California, USA. We also developed habitat models that would predict small mammal responses to fires of differing severity. We hypothesized that fire severity would influence the abundances of small mammals through changes in vegetation composition, structure, and spatial habitat complexity. Deer mouse (Peromyscus maniculatus) abundance responded negatively to fire severity, and brush mouse (P. boylii) abundance increased with increasing oak tree (Quercus spp.) cover. Chipmunk (Neotamias spp.) abundance was best predicted through a combination of a negative response to oak tree cover and a positive response to spatial habitat complexity. California ground squirrel (Spermophilus beecheyi) abundance increased with increasing spatial habitat complexity. Our results suggest that fire severity, with subsequent changes in vegetation structure and habitat spatial complexity, can influence small mammal abundance patterns.
Stress-driven buckling patterns in spheroidal core/shell structures.
Yin, Jie; Cao, Zexian; Li, Chaorong; Sheinman, Izhak; Chen, Xi
2008-12-09
Many natural fruits and vegetables adopt an approximately spheroidal shape and are characterized by their distinct undulating topologies. We demonstrate that various global pattern features can be reproduced by anisotropic stress-driven buckles on spheroidal core/shell systems, which implies that the relevant mechanical forces might provide a template underpinning the topological conformation in some fruits and plants. Three dimensionless parameters, the ratio of effective size/thickness, the ratio of equatorial/polar radii, and the ratio of core/shell moduli, primarily govern the initiation and formation of the patterns. A distinct morphological feature occurs only when these parameters fall within certain ranges: In a prolate spheroid, reticular buckles take over longitudinal ridged patterns when one or more parameters become large. Our results demonstrate that some universal features of fruit/vegetable patterns (e.g., those observed in Korean melons, silk gourds, ribbed pumpkins, striped cavern tomatoes, and cantaloupes, etc.) may be related to the spontaneous buckling from mechanical perspectives, although the more complex biological or biochemical processes are involved at deep levels.
Geological and vegetational applications of Shuttle Imaging Radar-B, Mineral County, Nevada
NASA Technical Reports Server (NTRS)
Borengasser, M. X.; Kleiner, E. F.; Peterson, F. F.; Klieforth, H.; Vreeland, P.
1988-01-01
Multiple-incidence angle and multi-azimuth radar data were acquired from a Shuttle platform over test sites in Nevada in October 1984. An attempt was made to correlate these data with ground features for the purpose of evaluating the use of such data for geological and vegetational assessment. Standard ecological parameters with respect to the flora (community composition, dominance, and relative cover) were recorded in the field at the time of overflight. Although a total of 33 species representing 11 plant families were recognized, and plant cover ranged from 13 to 26 percent, radar data could not be used to separate plant communities. The signal return is more a function of abiotic conditions than vegetative characteristics. Illumination geometry plays an important role in the ability to detect strike-slip and dip-slip faults. Local incidence angle is the most important parameter, and SIR-B data takes with small incidence angles are superior for identifying certain styles of faulting. Look direction is critical for detecting faults with a dip-slip component. New structural features were not observed. Problems with radar antenna power and recording significantly affected data quality.
Large-eddy simulation of slope flow over and within a vegetation canopy
NASA Astrophysics Data System (ADS)
Li, W.; Katul, G. G.; Parlange, M. B.; Giometto, M. G.
2017-12-01
Large-eddy simulation is used to characterize the turbulent structure of katabatic flows interacting with vegetation canopies in the absence of rotation. Numerical experiments are conducted first considering homogeneous surface forcing over an infinite planar slope, resembling the settings of the classic Prandtl one-dimensional slope flow model. A series of homogeneous plant canopies are accounted for using a spatially-distributed drag and buoyancy-induced forces, both function of the canopy leaf-area density parameter. The current study provides a new perspective on the problem of canopy flows, whose numerical studies have to-date mostly focused on pressure-driven atmospheric boundary-layer flow settings or on complex topography but without buoyancy. The dependence of the solution to the grid stencil, subgrid-scale model, and domain size will be analyzed, to assess the quality and reliability of the proposed results. A sensitivity analysis will then be conducted to test the dependence of mean flow and turbulence to the model parameters. Results will be contrasted with those from corresponding runs with no vegetation canopy.
Resistance to uprooting of Alfalfa and Avena Sativa and related importance for flume experiments
NASA Astrophysics Data System (ADS)
Edmaier, K.; Crouzy, B.; Burlando, P.; Perona, P.
2012-04-01
Vegetation influences sediment dynamics by stabilizing the alluvial sediment with its root system. Thus, vegetation engineers the riparian ecosystem by contributing to the formation and stabilization of river bars and islands. The resistance to uprooting of young plants in non-cohesive sediment depends on the competition between flow induced drag and root growth timescales. The investigation of flow-sediment-plant interactions in situ is difficult since variables cannot be controlled and material hardly be collected. In order to investigate ecomorphological processes, laboratory experiments are essential and have gained importance in the last decade. To achieve a better understanding of the dependence of resistance to uprooting on the root system (length and structure) we conducted vertical uprooting experiments with Alfalfa and Avena Sativa which are both species that have been used in flume experiments on vegetation-flow interactions (e.g. Tal and Paola, 2010; Perona et al., in press). Seeds were seeded on quartz sand and vertically uprooted with constant velocity whereat the weight force required to uproot a seedling was measured. After uprooting, roots were scanned and analyzed and the correlation of root parameters with the uprooting work was studied. Total root length was found to be the best explanatory variable, in particular the uprooting work increases following a power law with increasing root length. The impact of other root parameters (main root length, root number, tortuosity) on the uprooting work was as well analyzed. Still, not all influencing root parameters could be captured, like the angle between roots or root hair distribution. Environmental conditions like grain size and saturation were also found to have an effect on the uprooting resistance of roots. So, lower saturated sediment results in a higher uprooting work. This work is a first step to better understand the energy regime for vegetation uprooting and its dependence on various biological and hydraulic variables. Future experiments using the same sediment and vegetation species will apply this knowledge to further investigate flow-vegetation-sediment interactions.
Shiklomanov, Alexey N.; Dietze, Michael C.; Viskari, Toni; ...
2016-06-09
The remote monitoring of plant canopies is critically needed for understanding of terrestrial ecosystem mechanics and biodiversity as well as capturing the short- to long-term responses of vegetation to disturbance and climate change. A variety of orbital, sub-orbital, and field instruments have been used to retrieve optical spectral signals and to study different vegetation properties such as plant biochemistry, nutrient cycling, physiology, water status, and stress. Radiative transfer models (RTMs) provide a mechanistic link between vegetation properties and observed spectral features, and RTM spectral inversion is a useful framework for estimating these properties from spectral data. However, existing approaches tomore » RTM spectral inversion are typically limited by the inability to characterize uncertainty in parameter estimates. Here, we introduce a Bayesian algorithm for the spectral inversion of the PROSPECT 5 leaf RTM that is distinct from past approaches in two important ways: First, the algorithm only uses reflectance and does not require transmittance observations, which have been plagued by a variety of measurement and equipment challenges. Second, the output is not a point estimate for each parameter but rather the joint probability distribution that includes estimates of parameter uncertainties and covariance structure. We validated our inversion approach using a database of leaf spectra together with measurements of equivalent water thickness (EWT) and leaf dry mass per unit area (LMA). The parameters estimated by our inversion were able to accurately reproduce the observed reflectance (RMSE VIS = 0.0063, RMSE NIR-SWIR = 0.0098) and transmittance (RMSE VIS = 0.0404, RMSE NIR-SWIR = 0.0551) for both broadleaved and conifer species. Inversion estimates of EWT and LMA for broadleaved species agreed well with direct measurements (CV EWT = 18.8%, CV LMA = 24.5%), while estimates for conifer species were less accurate (CV EWT = 53.2%, CV LMA = 63.3%). To examine the influence of spectral resolution on parameter uncertainty, we simulated leaf reflectance as observed by ten common remote sensing platforms with varying spectral configurations and performed a Bayesian inversion on the resulting spectra. We found that full-range hyperspectral platforms were able to retrieve all parameters accurately and precisely, while the parameter estimates of multispectral platforms were much less precise and prone to bias at high and low values. We also observed that variations in the width and location of spectral bands influenced the shape of the covariance structure of parameter estimates. Lastly, our Bayesian spectral inversion provides a powerful and versatile framework for future RTM development and single- and multi-instrumental remote sensing of vegetation.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shiklomanov, Alexey N.; Dietze, Michael C.; Viskari, Toni
The remote monitoring of plant canopies is critically needed for understanding of terrestrial ecosystem mechanics and biodiversity as well as capturing the short- to long-term responses of vegetation to disturbance and climate change. A variety of orbital, sub-orbital, and field instruments have been used to retrieve optical spectral signals and to study different vegetation properties such as plant biochemistry, nutrient cycling, physiology, water status, and stress. Radiative transfer models (RTMs) provide a mechanistic link between vegetation properties and observed spectral features, and RTM spectral inversion is a useful framework for estimating these properties from spectral data. However, existing approaches tomore » RTM spectral inversion are typically limited by the inability to characterize uncertainty in parameter estimates. Here, we introduce a Bayesian algorithm for the spectral inversion of the PROSPECT 5 leaf RTM that is distinct from past approaches in two important ways: First, the algorithm only uses reflectance and does not require transmittance observations, which have been plagued by a variety of measurement and equipment challenges. Second, the output is not a point estimate for each parameter but rather the joint probability distribution that includes estimates of parameter uncertainties and covariance structure. We validated our inversion approach using a database of leaf spectra together with measurements of equivalent water thickness (EWT) and leaf dry mass per unit area (LMA). The parameters estimated by our inversion were able to accurately reproduce the observed reflectance (RMSE VIS = 0.0063, RMSE NIR-SWIR = 0.0098) and transmittance (RMSE VIS = 0.0404, RMSE NIR-SWIR = 0.0551) for both broadleaved and conifer species. Inversion estimates of EWT and LMA for broadleaved species agreed well with direct measurements (CV EWT = 18.8%, CV LMA = 24.5%), while estimates for conifer species were less accurate (CV EWT = 53.2%, CV LMA = 63.3%). To examine the influence of spectral resolution on parameter uncertainty, we simulated leaf reflectance as observed by ten common remote sensing platforms with varying spectral configurations and performed a Bayesian inversion on the resulting spectra. We found that full-range hyperspectral platforms were able to retrieve all parameters accurately and precisely, while the parameter estimates of multispectral platforms were much less precise and prone to bias at high and low values. We also observed that variations in the width and location of spectral bands influenced the shape of the covariance structure of parameter estimates. Lastly, our Bayesian spectral inversion provides a powerful and versatile framework for future RTM development and single- and multi-instrumental remote sensing of vegetation.« less
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...
Development of the Smart Weapons Operability Enhancement Interim Thermal Model
1991-03-11
Absorptivity HFOL Vegetation Height (cm) (b.) hiveg.inp High Vegetation Parameters for VEGGIE 0.70 1.0 0.85 0.96 50.00 (c.) mnedveg.inp Medium Vegetation...Parameters for VEGGIE 0.40 1.0 0.85 0.96 100.00 (d.) grass.inp Grassland Parameters for VEGGIE 0.50 1.0 0.98 0.80 50.00 66 Table B-8. Input Records in
Probabilistic calibration of the SPITFIRE fire spread model using Earth observation data
NASA Astrophysics Data System (ADS)
Gomez-Dans, Jose; Wooster, Martin; Lewis, Philip; Spessa, Allan
2010-05-01
There is a great interest in understanding how fire affects vegetation distribution and dynamics in the context of global vegetation modelling. A way to include these effects is through the development of embedded fire spread models. However, fire is a complex phenomenon, thus difficult to model. Statistical models based on fire return intervals, or fire danger indices need large amounts of data for calibration, and are often prisoner to the epoch they were calibrated to. Mechanistic models, such as SPITFIRE, try to model the complete fire phenomenon based on simple physical rules, making these models mostly independent of calibration data. However, the processes expressed in models such as SPITFIRE require many parameters. These parametrisations are often reliant on site-specific experiments, or in some other cases, paremeters might not be measured directly. Additionally, in many cases, changes in temporal and/or spatial resolution result in parameters becoming effective. To address the difficulties with parametrisation and the often-used fitting methodologies, we propose using a probabilistic framework to calibrate some areas of the SPITFIRE fire spread model. We calibrate the model against Earth Observation (EO) data, a global and ever-expanding source of relevant data. We develop a methodology that tries to incorporate the limitations of the EO data, reasonable prior values for parameters and that results in distributions of parameters, which can be used to infer uncertainty due to parameter estimates. Additionally, the covariance structure of parameters and observations is also derived, whcih can help inform data gathering efforts and model development, respectively. For this work, we focus on Southern African savannas, an important ecosystem for fire studies, and one with a good amount of EO data relevnt to fire studies. As calibration datasets, we use burned area data, estimated number of fires and vegetation moisture dynamics.
de Moura, Yhasmin Mendes; Hilker, Thomas; Goncalves, Fabio Guimarães; Galvão, Lênio Soares; dos Santos, João Roberto; Lyapustin, Alexei; Maeda, Eduardo Eiji; de Jesus Silva, Camila Valéria
2018-01-01
Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r2= 0.54, RMSE=0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy (0.52≤ r2≤ 0.61; p<0.05), with similar slopes and offsets found throughout the season, and RMSE between 0.26 and 0.30 (units of entropy). The relationships between the MODIS-derived anisotropy and backscattering measurements (σ0) from SeaWinds/QuikSCAT presented an r2 of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon. PMID:29618964
NASA Technical Reports Server (NTRS)
Treuhaft, Robert N.
1996-01-01
This paper first gives a heuristic description of the sensitivity of Interferometric Synthetic Aperture Radar to vertical vegetation distributions and underlying surface topography. A parameter estimation scenario is then described in which the Interferometric Synthetic Aperture Radar cross-correlation amplitude and phase are the observations from which vegetation and surface topographic parameters are estimated. It is shown that, even in the homogeneous-layer model of the vegetation, the number of parameters needed to describe the vegetation and underlying topography exceeds the number of Interferometric Synthetic Aperture Radar observations for single-baseline, single-frequency, single-incidence-angle, single-polarization Interferometric Synthetic Aperture Radar. Using ancillary ground-truth data to compensate for the underdetermination of the parameters, forest depths are estimated from the INSAR data. A recently-analyzed multibaseline data set is also discussed and the potential for stand-alone Interferometric Synthetic Aperture Radar parameter estimation is assessed. The potential of combining the information content of Interferometric Synthetic Aperture Radar with that of infrared/optical remote sensing data is briefly discussed.
NASA Technical Reports Server (NTRS)
Treuhaft, Robert N.
1996-01-01
Drawing from recently submitted work, this paper first gives a heuristic description of the sensitivity of interferometric synthetic aperture radar (INSAR) to vertical vegetation distribution and under laying surface topography. A parameter estimation scenario is then described in which the INSAR cross correlation amplitude and phase are the observations from which vegetation and surface topographic parameters are estimated. It is shown that, even in the homogeneous layer model of the vegetation, the number of parameters needed to describe the vegetation and underlying topography exceeds the number of INSAR observations for single baseline, single frequency, single incidence-angle, single polarization INSAR. Using ancillary ground truth data to compensate for the under determination of the parameters, forest depths are estimated from the INSAR data. A recently analyzed multi-baseline data set is also discussed and the potential for stand alone INSAR parameter estimation is assessed. The potential of combining the information content of INSAR with that of infrared/optical remote sensing data is briefly discussed.
Modelling the impact of vegetation on marly catchments in the Southern Alps of France
NASA Astrophysics Data System (ADS)
Carriere, Alexandra; Le Bouteiller, Caroline; Tucker, Greg; Naaim, Mohamed
2017-04-01
The Southern Alps of France have been identified as a hot-spot in a global climate change context where the rainfall intensity increase may exacerbate the erosion of already badly erodible lands: Badlands. Vegetalization methods are a promising area of research for erosion control and slope and riverbed stabilization. Nevertheless the impact of vegetation on erosive dynamics is still poorly understood. We own data collected over the last thirty years on marly catchments in the Southern Alps of France from the Draix-Bléone Observatory, part of the Network of Drainage Basins RBV. These are temporal data of sedimentary flux at the scale of the precipitation event but also more recent topographic data on watersheds with areas ranging from 10-3 square kilometers to twenty square kilometers. Erosion rates in this landscape reach 1 cm per year. We simulate the topographic evolution of the catchments over a few decades to centuries with the landscape evolution model Landlab, using our data to calibrate and explicitly validate the model. This model, in comparison with other landscape evolution models, incorporates a more advanced vegetation module in terms of ecology. Nevertheless the erosion-vegetation coupling is not present in Landlab and we are working on its construction. To this end we use an erosion module and a vegetation module that we seek to couple. We want to see how the erosion laws parameters depend on the vegetation cover. We have implemented the calibration of parameters of a non-linear diffusion module coupled with a transport-limited law by comparing the simulated annual sediment flux with the one of the data of the observatory as a function of the percentage of vegetation cover of the ground. We obtained average values of parameters adjusted according to vegetation cover. We observe that the values of the erosion laws parameters are strongly affected by the percentage of vegetation cover. We will then spatialize these parameters on our vegetation maps in order to obtain different parameter values for different types of vegetation.
NASA Astrophysics Data System (ADS)
Arnold, Sven; Attinger, Sabine; Frank, Karin; Baxter, Peter; Hildebrandt, Anke
2010-05-01
Ephemeral rivers are located throughout the world's arid regions. They are characterised by temporary surface flow that strongly varies between seasons and years. Along the river course often a coupled eco-hydrological vegetation-groundwater system has established, which is referred to as linear oasis, reflecting the ecological and socio-economic importance of ephemeral rivers in otherwise dry areas. The Kuiseb River denotes such a linear oasis and is one of the most diversely used environments among the ephemeral rivers in Namibia. Along the entire river course surface runoff and ground water are exploited for drinking, farming, and mining. The middle section of the Kuiseb River is characterised by strong eco-hydrological feedbacks between the vegetation and the ground water resource. Temporary floods infiltrate into sediments, which are accumulated in geological pools of impermeable bedrocks. This enables the formation of shallow ground water. The low depth to ground water allows root water uptake by plants and the establishment of a thriving ecosystem. The sustainable use of ecological and hydrological resources along ephemeral rivers is crucial to preserve the natural ecosystem. However, the investigation of management strategies that consider both the regulation of water extraction and vegetation structure requires models that explicitly consider the feedbacks between the water resource and the ecosystem structure. Further, uncertainties arise from stochastic hydrologic drivers such as flash flood events. Particularly in the face of climate change, the management strategies have to be applicable to a wide range of possible flood regimes, i.e. they have to be robust to the uncertainty of future flood regimes. In this study we assess a variety of management strategies regarding their robustness under different theoretical ecosystems and under uncertainty in the future stochastic flood regimes along the Kuiseb River. We consider the trade-off between ecological and human requirements by investigating the management strategies in terms of their ability to sustainably exploit the ground water resource while preserving the natural vegetation structure (here: coexistence of three tree species). We apply a conceptual ecohydrological model and use the information gap decision theory to estimate the robustness of strategies to failure due to flood parameter uncertainty. The performance of every strategy decreased as flood parameter uncertainty increased. However, ecological performance was more vulnerable with increasing uncertainty than the water supply performance, suggesting that the vegetation structure can be used as sensitive indicator and pre-warning system for changing environmental conditions. With the integrated and adaptive strategy it was most likely to sustainably use the ground water while preserving the natural vegetation structure, however, with the effect of reducing the probability of a large total system biomass.
First and Higher Order Effects on Zero Order Radiative Transfer Model
NASA Astrophysics Data System (ADS)
Neelam, M.; Mohanty, B.
2014-12-01
Microwave radiative transfer model are valuable tool in understanding the complex land surface interactions. Past literature has largely focused on local sensitivity analysis for factor priotization and ignoring the interactions between the variables and uncertainties around them. Since land surface interactions are largely nonlinear, there always exist uncertainties, heterogeneities and interactions thus it is important to quantify them to draw accurate conclusions. In this effort, we used global sensitivity analysis to address the issues of variable uncertainty, higher order interactions, factor priotization and factor fixing for zero-order radiative transfer (ZRT) model. With the to-be-launched Soil Moisture Active Passive (SMAP) mission of NASA, it is very important to have a complete understanding of ZRT for soil moisture retrieval to direct future research and cal/val field campaigns. This is a first attempt to use GSA technique to quantify first order and higher order effects on brightness temperature from ZRT model. Our analyses reflect conditions observed during the growing agricultural season for corn and soybeans in two different regions in - Iowa, U.S.A and Winnipeg, Canada. We found that for corn fields in Iowa, there exist significant second order interactions between soil moisture, surface roughness parameters (RMS height and correlation length) and vegetation parameters (vegetation water content, structure and scattering albedo), whereas in Winnipeg, second order interactions are mainly due to soil moisture and vegetation parameters. But for soybean fields in both Iowa and Winnipeg, we found significant interactions only to exist between soil moisture and surface roughness parameters.
Incorporating Plant Phenology Dynamics in a Biophysical Canopy Model
NASA Technical Reports Server (NTRS)
Barata, Raquel A.; Drewry, Darren
2012-01-01
The Multi-Layer Canopy Model (MLCan) is a vegetation model created to capture plant responses to environmental change. Themodel vertically resolves carbon uptake, water vapor and energy exchange at each canopy level by coupling photosynthesis, stomatal conductance and leaf energy balance. The model is forced by incoming shortwave and longwave radiation, as well as near-surface meteorological conditions. The original formulation of MLCan utilized canopy structural traits derived from observations. This project aims to incorporate a plant phenology scheme within MLCan allowing these structural traits to vary dynamically. In the plant phenology scheme implemented here, plant growth is dependent on environmental conditions such as air temperature and soil moisture. The scheme includes functionality that models plant germination, growth, and senescence. These growth stages dictate the variation in six different vegetative carbon pools: storage, leaves, stem, coarse roots, fine roots, and reproductive. The magnitudes of these carbon pools determine land surface parameters such as leaf area index, canopy height, rooting depth and root water uptake capacity. Coupling this phenology scheme with MLCan allows for a more flexible representation of the structure and function of vegetation as it responds to changing environmental conditions.
NASA Technical Reports Server (NTRS)
Blair, B.; Hofton, M.; Rabine, D.; Padden, P.; Rhoads, J.
2004-01-01
Full-waveform, scanning laser altimeters (i.e. lidar) provide a unique and precise view of the vertical and horizontal structure of vegetation across wide swaths. These unique laser altimeters systems are able to simultaneously image sub-canopy topography and the vertical structure of any overlying vegetation. These data reveal the true 3-D distribution of vegetation in leaf-on conditions enabling important biophysical parameters such as canopy height and aboveground biomass to be estimated with unprecedented accuracy. An airborne lidar mission was conducted in the summer of 2003 in support of preliminary studies for the North America Carbon Program. NASA's Laser Vegetation Imaging Sensor (LVIS) was used to image approximately 2,000 sq km in Maine, New Hampshire, Massachusetts and Maryland. Areas with available ground and other data were included (e.g., experimental forests, FLUXNET sites) in order to facilitate numerous bio- and geophysical investigations. Data collected included ground elevation and canopy height measurements for each laser footprint, as well as the vertical distribution of intercepted surfaces (i.e. the return waveform). Data are currently available at the LVIS website (http://lvis.gsfc.nasa.gov/). Further details of the mission, including the lidar system technology, the locations of the mapped areas, and examples of the numerous data products that can be derived from the return waveform data products are available on the website and will be presented. Future applications including potential fusion with other remote sensing data sets and a spaceborne implementation of wide-swath, full-waveform imaging lidar will also be discussed.
NASA Astrophysics Data System (ADS)
Bochet, Esther; García-Fayos, Patricio; José Molina, Maria; Moreno de las Heras, Mariano; Espigares, Tíscar; Nicolau, Jose Manuel; Monleon, Vicente
2017-04-01
Theoretical models predict that drylands are particularly prone to suffer critical transitions with abrupt non-linear changes in their structure and functions as a result of the existing complex interactions between climatic fluctuations and human disturbances. However, so far, few studies provide empirical data to validate these models. We aim at determining how holm oak (Quercus ilex) woodlands undergo changes in their functions in response to human disturbance along an aridity gradient (from semi-arid to sub-humid conditions), in eastern Spain. For that purpose, we used (a) remote-sensing estimations of precipitation-use-efficiency (PUE) from enhanced vegetation index (EVI) observations performed in 231x231 m plots of the Moderate Resolution Imaging Spectroradiometer (MODIS); (b) biological and chemical soil parameter determinations (extracellular soil enzyme activity, soil respiration, nutrient cycling processes) from soil sampled in the same plots; (c) vegetation parameter determinations (ratio of functional groups) from vegetation surveys performed in the same plots. We analyzed and compared the shape of the functional change (in terms of PUE and soil and vegetation parameters) in response to human disturbance intensity for our holm oak sites along the aridity gradient. Overall, our results evidenced important differences in the shape of the functional change in response to human disturbance between climatic conditions. Semi-arid areas experienced a more accelerated non-linear decrease with an increasing disturbance intensity than sub-humid ones. The proportion of functional groups (herbaceous vs. woody cover) played a relevant role in the shape of the functional response of the holm oak sites to human disturbance.
Fire effects assessment using FIA data in the northern and central Rocky Mountains
Theresa B. Jain; Ralph Their; Wilson Michael
2003-01-01
Wildfires of 2000 and 2001 burned thousands of hectares in the Northern Rocky Mountains. Within the fire parameters, 162 Forest Inventory and Analysis (FIA) plots burned in Idaho and Montana where pre-wildfire information on forest structure, vegetation composition, soil productivity, and surface fuels was documented; thus providing a unique opportunity to assess...
A Passive Microwave L-Band Boreal Forest Freeze/Thaw and Vegetation Phenology Study
NASA Astrophysics Data System (ADS)
Roy, A.; Sonnentag, O.; Pappas, C.; Mavrovic, A.; Royer, A.; Berg, A. A.; Rowlandson, T. L.; Lemay, J.; Helgason, W.; Barr, A.; Black, T. A.; Derksen, C.; Toose, P.
2016-12-01
The boreal forest is the second largest land biome in the world and thus plays a major role in the global and regional climate systems. The extent, timing and duration of seasonal freeze/thaw (F/T) state influences vegetation developmental stages (phenology) and, consequently, constitute an important control on how boreal forest ecosystems exchange carbon, water and energy with the atmosphere. The effective retrieval of seasonal F/T state from L-Band radiometry was demonstrated using satellite mission. However, disentangling the seasonally differing contributions from forest overstory and understory vegetation, and the soil surface to the satellite signal remains challenging. Here we present initial results from a radiometer field campaign to improve our understanding of the L-Band derived boreal forest F/T signal and vegetation phenology. Two L-Band surface-based radiometers (SBR) are installed on a micrometeorological tower at the Southern Old Black Spruce site in central Saskatchewan over the 2016-2017 F/T season. One radiometer unit is installed on the flux tower so it views forest including all overstory and understory vegetation and the moss-covered ground surface. A second radiometer unit is installed within the boreal forest overstory, viewing the understory and the ground surface. The objectives of our study are (i) to disentangle the L-Band F/T signal contribution of boreal forest overstory from the understory and ground surface, (ii) to link the L-Band F/T signal to related boreal forest structural and functional characteristics, and (iii) to investigate the use of the L-Band signal to characterize boreal forest carbon, water and energy fluxes. The SBR observations above and within the forest canopy are used to retrieve the transmissivity (γ) and the scattering albedo (ω), two parameters that describe the emission of the forest canopy though the F/T season. These two forest parameters are compared with boreal forest structural and functional characteristics including eddy-covariance measurements of carbon dioxide, water and energy exchanges, sap flux density measurements of tree-level water dynamics, L-Band tree permittivity and temperature. The study will lead to improved monitoring of soil F/T and vegetation phenology at the boreal forest-scale from satellite L-Band observations.
Phenological Parameters Estimation Tool
NASA Technical Reports Server (NTRS)
McKellip, Rodney D.; Ross, Kenton W.; Spruce, Joseph P.; Smoot, James C.; Ryan, Robert E.; Gasser, Gerald E.; Prados, Donald L.; Vaughan, Ronald D.
2010-01-01
The Phenological Parameters Estimation Tool (PPET) is a set of algorithms implemented in MATLAB that estimates key vegetative phenological parameters. For a given year, the PPET software package takes in temporally processed vegetation index data (3D spatio-temporal arrays) generated by the time series product tool (TSPT) and outputs spatial grids (2D arrays) of vegetation phenological parameters. As a precursor to PPET, the TSPT uses quality information for each pixel of each date to remove bad or suspect data, and then interpolates and digitally fills data voids in the time series to produce a continuous, smoothed vegetation index product. During processing, the TSPT displays NDVI (Normalized Difference Vegetation Index) time series plots and images from the temporally processed pixels. Both the TSPT and PPET currently use moderate resolution imaging spectroradiometer (MODIS) satellite multispectral data as a default, but each software package is modifiable and could be used with any high-temporal-rate remote sensing data collection system that is capable of producing vegetation indices. Raw MODIS data from the Aqua and Terra satellites is processed using the TSPT to generate a filtered time series data product. The PPET then uses the TSPT output to generate phenological parameters for desired locations. PPET output data tiles are mosaicked into a Conterminous United States (CONUS) data layer using ERDAS IMAGINE, or equivalent software package. Mosaics of the vegetation phenology data products are then reprojected to the desired map projection using ERDAS IMAGINE
Potential of Sentinel-1 Radar Data for the Assessment of Soil and Cereal Cover Parameters.
Bousbih, Safa; Zribi, Mehrez; Lili-Chabaane, Zohra; Baghdadi, Nicolas; El Hajj, Mohammad; Gao, Qi; Mougenot, Bernard
2017-11-14
The main objective of this study is to analyze the potential use of Sentinel-1 (S1) radar data for the estimation of soil characteristics (roughness and water content) and cereal vegetation parameters (leaf area index (LAI), and vegetation height (H)) in agricultural areas. Simultaneously to several radar acquisitions made between 2015 and 2017, using S1 sensors over the Kairouan Plain (Tunisia, North Africa), ground measurements of soil roughness, soil water content, LAI and H were recorded. The NDVI (normalized difference vegetation index) index computed from Landsat optical images revealed a strong correlation with in situ measurements of LAI. The sensitivity of the S1 measurements to variations in soil moisture, which has been reported in several scientific publications, is confirmed in this study. This sensitivity decreases with increasing vegetation cover growth (NDVI), and is stronger in the VV (vertical) polarization than in the VH cross-polarization. The results also reveal a similar increase in the dynamic range of radar signals observed in the VV and VH polarizations as a function of soil roughness. The sensitivity of S1 measurements to vegetation parameters (LAI and H) in the VV polarization is also determined, showing that the radar signal strength decreases when the vegetation parameters increase. No vegetation parameter sensitivity is observed in the VH polarization, probably as a consequence of volume scattering effects.
Potential of Sentinel-1 Radar Data for the Assessment of Soil and Cereal Cover Parameters
Bousbih, Safa; Lili-Chabaane, Zohra; El Hajj, Mohammad; Gao, Qi
2017-01-01
The main objective of this study is to analyze the potential use of Sentinel-1 (S1) radar data for the estimation of soil characteristics (roughness and water content) and cereal vegetation parameters (leaf area index (LAI), and vegetation height (H)) in agricultural areas. Simultaneously to several radar acquisitions made between 2015 and 2017, using S1 sensors over the Kairouan Plain (Tunisia, North Africa), ground measurements of soil roughness, soil water content, LAI and H were recorded. The NDVI (normalized difference vegetation index) index computed from Landsat optical images revealed a strong correlation with in situ measurements of LAI. The sensitivity of the S1 measurements to variations in soil moisture, which has been reported in several scientific publications, is confirmed in this study. This sensitivity decreases with increasing vegetation cover growth (NDVI), and is stronger in the VV (vertical) polarization than in the VH cross-polarization. The results also reveal a similar increase in the dynamic range of radar signals observed in the VV and VH polarizations as a function of soil roughness. The sensitivity of S1 measurements to vegetation parameters (LAI and H) in the VV polarization is also determined, showing that the radar signal strength decreases when the vegetation parameters increase. No vegetation parameter sensitivity is observed in the VH polarization, probably as a consequence of volume scattering effects. PMID:29135929
NASA Astrophysics Data System (ADS)
Székely, Balázs; Telbisz, Tamás; Koma, Zsófia; Kelemen, Kristóf; Szmorad, Ferenc; Deák, Márton; Látos, Tamás; Standovár, Tibor
2015-04-01
Topography and lithology are two major factors influencing the vegetation cover, its mosaic pattern and lateral transitions. In karstic areas the topography has a high diversity, microtopographic landforms influence the local ecological setting, vegetation structure. Presence of sinkholes of various sizes and geometric arrangements causes rapid lateral variation of the slope, aspect patterns as well as highly modify the soil water balance in time and space. These diversity of factors defines a mosaicked habitat pattern for vegetation assemblages. The World Heritage Site Aggtelek Karst/Slovakian Karst Caves has characteristic natural and environmental properties concerning the geomorphological as well as the ecological values. In order to be able to study the topographic influence on the ecological setting, a high-resolution digital terrain model (DTM) and digital surface model (DSM) have been derived from airborne laser scanning data depicting the karstic micro- and macrotopographic Landscape elements and the envelope surface of the canopy. Additional vegetation parameters like closure and average height have been derived from a normalized digital surface model (nDSM). Extensive mapping of vegetation properties has been carried out: centered on points of a grid array several vegetation-specific data - including composition and structure of tree and shrub layers, herbacesous vegetation and tree regeneration - have been acquired. Various classification patterns - based on trees pecies composition, vertical vegetation structure - have been derived from this data set. The comparison of the vegetation classification data and the geomorphometric DTM derivatives yielded interesting results. Certain vegetation characteristics often correlate with the geomorphometric properties. We interpret this similarity as sensitivity of vegetion to fine-scale variations in geomorphic properties like aspect, illumination conditions and soil properties. However, in many cases the vegetation pattern shows no correlation with natural settings. It may be the result of human impact, which actively formed the local land use in these hilly-low mountain karst area since the Middle Ages. These studies have been financed partly by the following projects: data acquisition: "Hungarian-Slovakian Transnational Cooperation Programme 2007-2013", "Management of World Heritage Aggtelek Karst/Slovakian Karst Caves" (HUSK/1101/221/0180, Aggtelek NP), data evaluation: 'Multipurpose assessment serving forest biodiversity conservation in the Carpathian region of Hungary', Swiss-Hungarian Cooperation Programme (SH/4/13 Project), and Hungarian National Research Fund OTKA NK83400 and OTKA 104811. BS contributed as an Alexander von Humboldt Research Fellow, TT was supported by the János Bolyai Scolarship of the Hungarian Academy of Sciences.
Mendonça, Bruno A F DE; Fernandes, Elpídio I; Schaefer, Carlos E G R; Mendonça, Júlia G F DE; Vasconcelos, Bruno N F
2017-01-01
Viruá National Park encompasses a vast and complex system of hydromorphic sandy soils covered largely by the white sand vegetation ("Campinarana") ecosystem. The purpose of this study was to investigate a vegetation gradient of "terra-firme"-white sand vegetation at the Viruá National Park. Nine plots representing three physiognomic units were installed for floristic and phytosociological surveys as well as to collect composite soil samples. The data were subjected to assessments of floristic diversity and similarity, phytosociological parameters and to statistical analyses, focused on principal components (PC) and canonical correspondence analysis (CCA). The vegetation of the Campinaranas types and Forest differed in biomass and species density. Ten species, endemic to Brazil, were particularly well-represented. PC and CCA indicated a clear distinction between the studied plots, based on measured soil variables, especially base sum and clay, which were the most differentiating properties between Campinarana and Forest; For the separation of the Campinarana types, the main distinguishing variable was organic matter content and cation exchange capacity. Higher similarity of Campinaranas was associated to a monodominant species and the lower similarity of Forest was related to the high occurrence of locally rare species.
Canopy Modeling of Aquatic Vegetation: Construction of Submerged Vegetation Index
NASA Astrophysics Data System (ADS)
Ma, Z.; Zhou, G.
2018-04-01
The unique spectral characteristics of submerged vegetation in wetlands determine that the conventional terrestrial vegetation index cannot be directly employed to species identification and parameter inversion of submerged vegetation. Based on the Aquatic Vegetation Radiative Transfer model (AVRT), this paper attempts to construct an index suitable for submerged vegetation, the model simulated data and a scene of Sentinel-2A image in Taihu Lake, China are utilized for assessing the performance of the newly constructed indices and the existent vegetation indices. The results show that the angle index composed by 525 nm, 555 nm and 670 nm can resist the effects of water columns and is more sensitive to vegetation parameters such as LAI. Furthermore, it makes a well discrimination between submerged vegetation and water bodies in the satellite data. We hope that the new index will provide a theoretical basis for future research.
Research support of the WETNET Program
NASA Technical Reports Server (NTRS)
Estes, John E.; Mcgwire, Kenneth C.; Scepan, Joseph; Henderson, SY; Lawless, Michael
1995-01-01
This study examines various aspects of the Microwave Vegetation Index (MVI). MVI is a derived signal created by differencing the spectral response of the 37 GHz horizontally and vertically polarized passive microwave signals. The microwave signal employed to derive this index is thought to be primarily influenced by vegetation structure, vegetation growth, standing water, and precipitation. The state of California is the study site for this research. Imagery from the Special Sensor Microwave/Imager (SSM/I) is used for the creation of MVI datasets analyzed in this research. The object of this research is to determine whether MVI corresponds with some quantifiable vegetation parameter (such as vegetation density) or whether the index is more affected by known biogeophysical parameters such antecedent precipitation. A secondary question associated with the above is whether the vegetation attributes that MVI is employed to determine can be more easily and accurately evaluated by other remote sensing means. An important associated question to be addressed in the study is the effect of different multi-temporal composting techniques on the derived MVI dataset. This work advances our understanding of the fundamental nature of MVI by studying vegetation as a mixture of structural types, such as forest and grassland. The study further advances our understanding by creating multitemporal precipitation datasets to compare the affects of precipitation upon MVI. This work will help to lay the groundwork for the use of passive microwave spectral information either as an adjunct to visible and near infrared imagery in areas where that is feasible or for the use of passive microwave alone in areas of moderate cloud coverage. In this research, an MVI dataset, spanning the period February 15, 1989 through April 25, 1990, has been created using National Aeronautic and Space Administration (NASA) supplied brightness temperature data. Information from the DMSP satellite 37 GHz wavelength SSM/I sensor in both horizontal and vertical polarization has been processed using the MVI algorithm. In conjunction with the MVI algorithm a multitemporal compositing technique was used to create datasets that correspond to 14 day periods. In this technical report, Section Two contains background information on the State of California and the three MVI study sites. Section Three describes the methods used to create the MVI and independent variables datasets. Section Four presents the results of the experiment. Section Five summarizes and concludes the work.
Estimating tropical forest structure using LIDAR AND X-BAND INSAR
NASA Astrophysics Data System (ADS)
Palace, M. W.; Treuhaft, R. N.; Keller, M. M.; Sullivan, F.; Roberto dos Santos, J.; Goncalves, F. G.; Shimbo, J.; Neumann, M.; Madsen, S. N.; Hensley, S.
2013-12-01
Tropical forests are considered the most structurally complex of all forests and are experiencing rapid change due to anthropogenic and climatic factors. The high carbon stocks and fluxes make understanding tropical forests highly important to both regional and global studies involving ecosystems and climate. Large and remote areas in the tropics are prime targets for the use of remotely sensed data. Radar and lidar have previously been used to estimate forest structure, with an emphasis on biomass. These two remote sensing methods have the potential to yield much more information about forest structure, specifically through the use of X-band radar and waveform lidar data. We examined forest structure using both field-based and remotely sensed data in the Tapajos National Forest, Para, Brazil. We measured multiple structural parameters for about 70 plots in the field within a 25 x 15 km area that have TanDEM-X single-pass horizontally and vertically polarized radar interferometric data. High resolution airborne lidar were collected over a 22 sq km portion of the same area, within which 33 plots were co-located. Preliminary analyses suggest that X-band interferometric coherence decreases by about a factor of 2 (from 0.95 to 0.45) with increasing field-measured vertical extent (average heights of 7-25 m) and biomass (10-430 Mg/ha) for a vertical wavelength of 39 m, further suggesting, as has been observed at C-band, that interferometric synthetic aperture radar (InSAR) is substantially more sensitive to forest structure/biomass than SAR. Unlike InSAR coherence versus biomass, SAR power at X-band versus biomass shows no trend. Moreover, airborne lidar coherence at the same vertical wavenumbers as InSAR is also shown to decrease as a function of biomass, as well. Although the lidar coherence decrease is about 15% more than the InSAR, implying that lidar penetrates more than InSAR, these preliminary results suggest that X-band InSAR may be useful for structure and biomass estimation over large spatial scales not attainable with airborne lidar. In this study, we employed a set of less commonly used lidar metrics that we consider analogous to field-based measurements, such as the number of canopy maxima, measures of canopy vegetation distribution diversity and evenness (entropy), and estimates of gap fraction. We incorporated these metrics, as well as lidar coherence metrics pulled from discrete Fourier transforms of pseudowaveforms, and hypothetical stand characteristics of best-fit synthetic vegetation profiles into multiple regression analysis of forest biometric properties. Among simple and complex measures of forest structure, ranging from tree density, diameter at breast height, and various canopy geometry parameters, we found strong relationships with lidar canopy vegetation profile parameters. We suggest that the sole use of lidar height is limited in understanding biomass in a forest with little variation across the landscape and that there are many parameters that may be gleaned by lidar data that inform on forest biometric properties.
NASA Astrophysics Data System (ADS)
Bras, R. L.; Istanbulluoglu, E.
2004-12-01
Topography acts as a template for numerous landscape processes that includes hydrologic, ecologic and biologic phenomena. These processes not only interact with each other but also contribute to shaping the landscape as they influence geomorphic processes. We have investigated the effects of vegetation on known geomorphic relations, thresholds for channel initiation and landform evolution, using both analytical and numerical approaches. Vegetation is assumed to form a uniform ground cover. Runoff erosion is modeled based on power function of excess shear stress, in which shear stress efficiency is inversely proportional to vegetation cover. Plant effect on slope stability is represented by additional cohesion provided by plant roots. Vegetation cover is assumed to reduce sediment transport rates due to physical creep processes (rainsplash, dry ravel, and expansion and contraction of sediments) according to a negative exponential relationship. Vegetation grows as a function of both available cover and unoccupied space by plants, and is killed by geomorphic disturbances (runoff erosion and landsliding), and wildfires. Analytical results suggest that, in an equilibrium basin with a fixed vegetation cover, plants may cause a transition in the dominant erosion process at the channel head. A runoff erosion dominated landscape, under none or loose vegetation cover, may become landslide dominated under a denser vegetation cover. The sign of the predicted relationship between drainage density and vegetation cover depends on the relative influence of vegetation on different erosion phenomena. With model parameter values representative of the Oregon Coast Range (OCR), numerical experiments conducted using the CHILD model. Numerical experiments reveal the importance of vegetation disturbances on the landscape structure. Simulated landscapes resemble real-world catchments in the OCR when vegetation disturbances are considered.
NASA Astrophysics Data System (ADS)
Arévalo, José Ramón; Fernández-Lugo, Silvia; Reyes-Betancort, J. Alfredo; Tejedor, Marisa; Jiménez, Concepción; Díaz, Francisco J.
2017-11-01
Over 90% of terraced fields have been abandoned on the island of Lanzarote in the last 40 years. The present work analyses the effects of abandonment on the soil and vegetation recovery of terraced field agroecosystems by comparing them with adjacent non-terraced fields in Lanzarote, Canary Islands (Spain). This information is necessary to take the appropriate management actions to achieve goals such as soil protection and biodiversity conservation. Results indicate that terraced fields display better soil quality than non-terraced ones, as shown by the significant differences found in parameters such as SAR, exchangeable Na, CaCO3, B content, moisture content or soil depth. Moreover, the terraced fields' plant community has more species similarities with the native plant community when compared with non-terraced areas. Owing to characteristics such as deeper soils, more water capacity, lower salinity and less sodic soils, terraced soils provide better conditions for passive restoration of both soil and vegetation. Therefore, the recovery and maintenance of wall structures and revegetation with native/endemic species are proposed to promote the restoration of native systems and preserve a landscape with cultural and aesthetic value.
NASA Technical Reports Server (NTRS)
Mendes De Moura, Yhasmin; Hilker, Thomas; Goncalves, Fabio Guimaraes; Galvao, Lenio Soares; Roberto dos Santos, Joao; Lyapustin, Alexei; Maeda, Eduardo Eiji; de Jesus Silva, Camila Valeria
2016-01-01
Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r(exp 2)= 0.54, RMSE= 0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy(0.52 less than or equal to r(exp 2) less than or equal to 0.61; p less than 0.05), with similar slopes and offsets found throughout the season, and RMSE between 0.26 and 0.30 (units of entropy). The relationships between the MODIS-derived anisotropy and backscattering measurements (sigma(sup 0)) from SeaWinds/QuikSCAT presented an r(exp 2) of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon.
The Backscattering Enigma in Natural Waters
2006-09-30
down because the effects of changing particle composition are not adequately understood. Our long term goal is to better understand the source of...natural waters. APPROACH A key focus over the last year has been determining the scattering properties of phytoplankton populations and...spaces, etc.), and forms the basis of the terrestrial biomass parameter NDVI (normalized difference vegetation index). However, plant cell structures
Model-data integration to improve the LPJmL dynamic global vegetation model
NASA Astrophysics Data System (ADS)
Forkel, Matthias; Thonicke, Kirsten; Schaphoff, Sibyll; Thurner, Martin; von Bloh, Werner; Dorigo, Wouter; Carvalhais, Nuno
2017-04-01
Dynamic global vegetation models show large uncertainties regarding the development of the land carbon balance under future climate change conditions. This uncertainty is partly caused by differences in how vegetation carbon turnover is represented in global vegetation models. Model-data integration approaches might help to systematically assess and improve model performances and thus to potentially reduce the uncertainty in terrestrial vegetation responses under future climate change. Here we present several applications of model-data integration with the LPJmL (Lund-Potsdam-Jena managed Lands) dynamic global vegetation model to systematically improve the representation of processes or to estimate model parameters. In a first application, we used global satellite-derived datasets of FAPAR (fraction of absorbed photosynthetic activity), albedo and gross primary production to estimate phenology- and productivity-related model parameters using a genetic optimization algorithm. Thereby we identified major limitations of the phenology module and implemented an alternative empirical phenology model. The new phenology module and optimized model parameters resulted in a better performance of LPJmL in representing global spatial patterns of biomass, tree cover, and the temporal dynamic of atmospheric CO2. Therefore, we used in a second application additionally global datasets of biomass and land cover to estimate model parameters that control vegetation establishment and mortality. The results demonstrate the ability to improve simulations of vegetation dynamics but also highlight the need to improve the representation of mortality processes in dynamic global vegetation models. In a third application, we used multiple site-level observations of ecosystem carbon and water exchange, biomass and soil organic carbon to jointly estimate various model parameters that control ecosystem dynamics. This exercise demonstrates the strong role of individual data streams on the simulated ecosystem dynamics which consequently changed the development of ecosystem carbon stocks and fluxes under future climate and CO2 change. In summary, our results demonstrate challenges and the potential of using model-data integration approaches to improve a dynamic global vegetation model.
NASA Astrophysics Data System (ADS)
Blair, B.; Hofton, M.; Rabine, D.; Welch, W.; Ramos, L.; Padden, P.
2003-12-01
Full-Waveform lidar measurements provide unprecedented views of the vertical and horizontal structure of vegetation and the topography of the Earth's surface. Utilizing a high signal-to-noise ratio lidar system, larger than typical laser footprints (10-20 m), and the recorded time history of interaction between a short-duration (10 ns) pulse of laser light and the surface of the Earth, full-waveform lidar is able to simultaneously image sub-canopy topography as well as the vertical structure of any overlying vegetation. These data reveal the true 3-D vegetation structure in leaf-on conditions enabling important biophysical parameters such as above-ground biomass to be estimated with unprecedented accuracy. An airborne lidar mission was conducted July-August 2003 in support of the North America Carbon Program. NASA's Laser Vegetation Imaging Sensor (LVIS) was used to image approximately 2,000 sq. km in Maine, New Hampshire, Massachusetts and Maryland. Areas with available ground and other data were included (e.g., experimental forests, FLUXNET sites) in order to facilitate as many bio- and geophysical investigations as possible. Data collected included ground elevation and canopy height measurements for each laser footprint, as well as the vertical distribution of intercepted surfaces. Data will be publicly distributed within 6-12 months of collection. Further details of the mission, including the lidar system technology, the locations of the mapped areas, and examples of the numerous data products that can be derived from the return waveform data products will be presented. Future applications including detection of ground and vegetation canopy changes and a spaceborne implementation of wide-swath, full-waveform imaging lidar will also be discussed.
NASA Technical Reports Server (NTRS)
Blair, James B.; Hofton, M.; Rabine, David; Welch, Wayne; Ramos, Luis; Padden, Phillip
2003-01-01
Full-Waveform lidar measurements provide unprecedented views of the vertical and horizontal structure of vegetation and the topography of the Earth s surface. Utilizing a high signal-to-noise ratio lidar system, larger than typical laser footprints (10-20 m), and the recorded time history of interaction between a short-duration (approx. 10 ns) pulse of laser light and the surface of the Earth, full-waveform lidar is able to simultaneously image sub-canopy topography as well as the vertical structure of any overlying vegetation. These data reveal the true 3-D vegetation structure in leaf-on conditions enabling important biophysical parameters such as above-ground biomass to be estimated with unprecedented accuracy. An airborne lidar mission was conducted July-August 2003 in support of the North America Carbon Program. NASA s Laser Vegetation Imaging Sensor (LVIS) was used to image approximately 2,000 km$^2$ in Maine, New Hampshire, Massachusetts and Maryland. Areas with available ground and other data were included (e.g., experimental forests, FLUXNET sites) in order to facilitate as many bio- and geophysical investigations as possible. Data collected included ground elevation and canopy height measurements for each laser footprint, as well as the vertical distribution of intercepted surfaces. Data will be publicly distributed within 6- 12 months of collection. Further details of the mission, including the lidar system technology, the locations of the mapped areas, and examples of the numerous data products that can be derived from the return waveform data products will be presented. Future applications including detection of ground and vegetation canopy changes and a spaceborne implementation of wide-swath, full-waveform imaging lidar will also be discussed.
Bayesian calibration of the Community Land Model using surrogates
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi
2014-02-01
We present results from the Bayesian calibration of hydrological parameters of the Community Land Model (CLM), which is often used in climate simulations and Earth system models. A statistical inverse problem is formulated for three hydrological parameters, conditional on observations of latent heat surface fluxes over 48 months. Our calibration method uses polynomial and Gaussian process surrogates of the CLM, and solves the parameter estimation problem using a Markov chain Monte Carlo sampler. Posterior probability densities for the parameters are developed for two sites with different soil and vegetation covers. Our method also allows us to examine the structural errormore » in CLM under two error models. We find that surrogate models can be created for CLM in most cases. The posterior distributions are more predictive than the default parameter values in CLM. Climatologically averaging the observations does not modify the parameters' distributions significantly. The structural error model reveals a correlation time-scale which can be used to identify the physical process that could be contributing to it. While the calibrated CLM has a higher predictive skill, the calibration is under-dispersive.« less
NASA Astrophysics Data System (ADS)
Melillos, George; Themistocleous, Kyriacos; Prodromou, Maria; Hadjimitsis, Diofantos G.
2017-10-01
The purpose of this paper is to present the results obtained from unmanned aerial vehicle (UAV) and field spectroscopy campaigns for detecting underground structures. Underground structures can affect their surrounding landscapes in different ways, such as soil moisture content, soil composition and vegetation vigor. The last is often observed on the ground as a crop mark; a phenomenon which can be used as a proxy to denote the presence of underground non-visible structures. A number of vegetation indices such as the Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR), Difference Vegetation Index (DVI) and Soil Adjusted Vegetation Index (SAVI) were utilized for the development of a vegetation index-based procedure aiming at the detection of underground military structures by using existing vegetation indices or other in-band algorithms. The measurements were taken at the following test areas such as: (a) vegetation area covered with the vegetation (barley), in the presence of an underground military structure (b) vegetation area covered with the vegetation (barley), in the absence of an underground military structure.
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.
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.
Wu, Ling; Liu, Xiang-Nan; Zhou, Bo-Tian; Liu, Chuan-Hao; Li, Lu-Feng
2012-12-01
This study analyzed the sensitivities of three vegetation biochemical parameters [chlorophyll content (Cab), leaf water content (Cw), and leaf area index (LAI)] to the changes of canopy reflectance, with the effects of each parameter on the wavelength regions of canopy reflectance considered, and selected three vegetation indices as the optimization comparison targets of cost function. Then, the Cab, Cw, and LAI were estimated, based on the particle swarm optimization algorithm and PROSPECT + SAIL model. The results showed that retrieval efficiency with vegetation indices as the optimization comparison targets of cost function was better than that with all spectral reflectance. The correlation coefficients (R2) between the measured and estimated values of Cab, Cw, and LAI were 90.8%, 95.7%, and 99.7%, and the root mean square errors of Cab, Cw, and LAI were 4.73 microg x cm(-2), 0.001 g x cm(-2), and 0.08, respectively. It was suggested that to adopt vegetation indices as the optimization comparison targets of cost function could effectively improve the efficiency and precision of the retrieval of biochemical parameters based on PROSPECT + SAIL model.
Kalra, Tarandeep S.; Aretxabaleta, Alfredo; Seshadri, Pranay; Ganju, Neil K.; Beudin, Alexis
2017-01-01
Coastal hydrodynamics can be greatly affected by the presence of submerged aquatic vegetation. The effect of vegetation has been incorporated into the Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modeling System. The vegetation implementation includes the plant-induced three-dimensional drag, in-canopy wave-induced streaming, and the production of turbulent kinetic energy by the presence of vegetation. In this study, we evaluate the sensitivity of the flow and wave dynamics to vegetation parameters using Sobol' indices and a least squares polynomial approach referred to as Effective Quadratures method. This method reduces the number of simulations needed for evaluating Sobol' indices and provides a robust, practical, and efficient approach for the parameter sensitivity analysis. The evaluation of Sobol' indices shows that kinetic energy, turbulent kinetic energy, and water level changes are affected by plant density, height, and to a certain degree, diameter. Wave dissipation is mostly dependent on the variation in plant density. Performing sensitivity analyses for the vegetation module in COAWST provides guidance for future observational and modeling work to optimize efforts and reduce exploration of parameter space.
NASA Astrophysics Data System (ADS)
Phinn, S. R.; Scarth, P.; Armston, J.; Witte, C.; Danaher, T.; Flood, N.; Gill, T.; Lucas, R.
2011-12-01
Management of Australian ecosystems is carried out by state governments using information derived from satellite image data. The state of Queensland covers approximately 1.8 x 10^6 km^2 and uses satellite remote sensing and field survey programs to support legislated environmental monitoring, management and compliance activities.This poster outlines how the Joint Remote Sensing Research Program(JRSRP)delivered satellite image based data sets to address these activities by mapping foliage projective cover, vegetation height and biomass. Foliage projective cover (FPC), the vertically projected percentage cover of photosynthetic foliage of all strata, is produced from Landsat TM/ETM data using 88 scenes and over 1700 field sites. The JRSRP enabled government staff to be seconded to a university research group to work on the project, and the university provided postdoctoral and graduate student support. The JRSRP activities focussed on geometric and topographic corrections, BRDF corrections and time-series based approaches for correcting the archive of field survey and Landsat TM/ETM+ images. This has now progressed to a program using the entire Landsat TM/ETM+ archive on an annual basis and annual state-wide field survey data. The Landsat TM/ETM+ calibrations have been a critical input to the Landsat program's global vicarious calibration activities. Vegetation height is a critical parameter required for a range of state-wide activities and can be mapped accurately from field plots to regional areas using airborne Lidar. To develop statewide height estimates, an approach was developed using Icesat and existing vegetation community maps. By aggregating the spaceborne Icesat full waveform data within the mapped vegetation structure polygons it was possible to retrieve vegetation vertical structure information continuously across the landscape. This was used to derive mean canopy and understorey height, depth and density across Queensland, which was validated using airborne lidar data provided by the JRSRP. Biomass mapping is emerging as a critical environmental parameter for local, state and national agencies in Australia. Staff from JRSRP developed an approach with University of Aberystwyth in Wales, through JAXA's Kyoto and Carbon initiative, for acquiring ALOS PALSAR L-band image data, conducting geometric and radiometric corrections, and normalising for significant scene to scene differences in soil and vegetation moisture content. This pre-processing of 31 image strip time-series generated state-wide mosaics for Queensland that were then used with 1815 field survey sites collected across the state to produce a state-wide biomass estimation model for L-HV data, providing estimates for both remnant and non-remnant forests, with saturation at 263 Mg.Ha^-1 for 20% estimation error. The Joint Remote Sensing Research Program has enabled a sound approach to research and development for validated operational applications.
Rutten, Gemma; Ensslin, Andreas; Hemp, Andreas; Fischer, Markus
2015-01-01
In most habitats, vegetation provides the main structure of the environment. This complexity can facilitate biodiversity and ecosystem services. Therefore, measures of vegetation structure can serve as indicators in ecosystem management. However, many structural measures are laborious and require expert knowledge. Here, we used consistent and convenient measures to assess vegetation structure over an exceptionally broad elevation gradient of 866-4550 m above sea level at Mount Kilimanjaro, Tanzania. Additionally, we compared (human)-modified habitats, including maize fields, traditionally managed home gardens, grasslands, commercial coffee farms and logged and burned forests with natural habitats along this elevation gradient. We distinguished vertical and horizontal vegetation structure to account for habitat complexity and heterogeneity. Vertical vegetation structure (assessed as number, width and density of vegetation layers, maximum canopy height, leaf area index and vegetation cover) displayed a unimodal elevation pattern, peaking at intermediate elevations in montane forests, whereas horizontal structure (assessed as coefficient of variation of number, width and density of vegetation layers, maximum canopy height, leaf area index and vegetation cover) was lowest at intermediate altitudes. Overall, vertical structure was consistently lower in modified than in natural habitat types, whereas horizontal structure was inconsistently different in modified than in natural habitat types, depending on the specific structural measure and habitat type. Our study shows how vertical and horizontal vegetation structure can be assessed efficiently in various habitat types in tropical mountain regions, and we suggest to apply this as a tool for informing future biodiversity and ecosystem service studies.
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.
Directional radiance measurements: Challenges in the sampling of landscapes
NASA Technical Reports Server (NTRS)
Deering, D. W.
1994-01-01
Most earth surfaces, particularly those supporting natural vegetation ecosystems, constitute structurally and spectrally complex surfaces that are distinctly non-Lambertian reflectors. Obtaining meaningful measurements of the directional radiances of landscapes and obtaining estimates of the complete bidirectional reflectance distribution functions of ground targets with complex and variable landscape and radiometric features are challenging tasks. Reasons for the increased interest in directional radiance measurements are presented, and the issues that must be addressed when trying to acquire directional radiances for vegetated land surfaces from different types of remote sensing platforms are discussed. Priority research emphases are suggested, concerning field measurements of directional surface radiances and reflectances for future research. Primarily, emphasis must be given to the acquisition of more complete and directly associated radiometric and biometric parameter data sets that will empower the exploitation of the 'angular dimension' in remote sensing of vegetation through enabling the further development and rigorous validation of state of the art plant canopy models.
Modeling Vegetation Growth Impact on Groundwater Recharge
NASA Astrophysics Data System (ADS)
Anurag, H.; Ng, G. H. C.; Tipping, R.
2017-12-01
Vegetation growth is affected by variability in climate and land-cover / land-use over a range of temporal and spatial scales. Vegetation also modifies water budget through interception and evapotranspiration and thus has a significant impact on groundwater recharge. Most groundwater recharge assessments represent vegetation using specified, static parameter, such as for leaf-area-index, but this neglects the effect of vegetation dynamics on recharge estimates. Our study addresses this gap by including vegetation growth in model simulations of recharge. We use NCAR's Community Land Model v4.5 with its BGC module (BGC is the new CLM4.5 biogeochemistry). It integrates prognostic vegetation growth with land-surface and subsurface hydrological processes and can thus capture the effect of vegetation on groundwater. A challenge, however, is the need to resolve uncertainties in model inputs ranging from vegetation growth parameters all the way down to the water table. We have compiled diverse data spanning meteorological inputs to subsurface geology and use these to implement ensemble model simulations to evaluate the possible effects of dynamic vegetation growth (versus specified, static vegetation parameterizations) on estimating groundwater recharge. We present preliminary results for select data-intensive test locations throughout the state of Minnesota (USA), which has a sharp east-west precipitation gradient that makes it an apt testbed for examining ecohydrologic relationships across different temperate climatic settings and ecosystems. Using the ensemble simulations, we examine the effect of seasonal to interannual variability of vegetation growth on recharge and water table depths, which has implications for predicting the combined impact of climate, vegetation, and geology on groundwater resources. Future work will include distributed model simulations over the entire state, as well as conditioning uncertain vegetation and subsurface parameters on remote sensing data and statewide water table records using data assimilation.
Jiang, Yueyang; Zhuang, Qianlai; Schaphoff, Sibyll; Sitch, Stephen; Sokolov, Andrei; Kicklighter, David; Melillo, Jerry
2012-03-01
This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble Lund-Potsdam-Jena (LPJ) simulations for the northern high latitudes (45(o)N and polewards) for the period 1900-2100. The LPJ Dynamic Global Vegetation Model (LPJ-DGVM) was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT). In the current dynamic vegetation model, some parameters are more important than others in determining the vegetation distribution. Parameters that control plant carbon uptake and light-use efficiency have the predominant influence on the vegetation distribution of both woody and herbaceous plant functional types. The relative importance of different parameters varies temporally and spatially and is influenced by climate inputs. In addition to climate, these parameters play an important role in determining the vegetation distribution in the region. The parameter-based uncertainties contribute most to the total uncertainty. The current warming conditions lead to a complexity of vegetation responses in the region. Temperate trees will be more sensitive to climate variability, compared with boreal forest trees and C3 perennial grasses. This sensitivity would result in a unanimous northward greenness migration due to anomalous warming in the northern high latitudes. Temporally, boreal needleleaved evergreen plants are projected to decline considerably, and a large portion of C3 perennial grass is projected to disappear by the end of the 21st century. In contrast, the area of temperate trees would increase, especially under the most extreme A1FI scenario. As the warming continues, the northward greenness expansion in the Arctic region could continue.
Ecological optimality in water-limited natural soil-vegetation systems. II - Tests and applications
NASA Technical Reports Server (NTRS)
Eagleson, P. S.; Tellers, T. E.
1982-01-01
The long-term optimal climatic climax soil-vegetation system is defined for several climates according to previous hypotheses in terms of two free parameters, effective porosity and plant water use coefficient. The free parameters are chosen by matching the predicted and observed average annual water yield. The resulting climax soil and vegetation properties are tested by comparison with independent observations of canopy density and average annual surface runoff. The climax properties are shown also to satisfy a previous hypothesis for short-term optimization of canopy density and water use coefficient. Using these hypotheses, a relationship between average evapotranspiration and optimum vegetation canopy density is derived and is compared with additional field observations. An algorithm is suggested by which the climax soil and vegetation properties can be calculated given only the climate parameters and the soil effective porosity. Sensitivity of the climax properties to the effective porosity is explored.
Automatically Generated Vegetation Density Maps with LiDAR Survey for Orienteering Purpose
NASA Astrophysics Data System (ADS)
Petrovič, Dušan
2018-05-01
The focus of our research was to automatically generate the most adequate vegetation density maps for orienteering purpose. Application Karttapullatuin was used for automated generation of vegetation density maps, which requires LiDAR data to process an automatically generated map. A part of the orienteering map in the area of Kazlje-Tomaj was used to compare the graphical display of vegetation density. With different settings of parameters in the Karttapullautin application we changed the way how vegetation density of automatically generated map was presented, and tried to match it as much as possible with the orienteering map of Kazlje-Tomaj. Comparing more created maps of vegetation density the most suitable parameter settings to automatically generate maps on other areas were proposed, too.
Rutten, Gemma; Ensslin, Andreas; Hemp, Andreas; Fischer, Markus
2015-01-01
In most habitats, vegetation provides the main structure of the environment. This complexity can facilitate biodiversity and ecosystem services. Therefore, measures of vegetation structure can serve as indicators in ecosystem management. However, many structural measures are laborious and require expert knowledge. Here, we used consistent and convenient measures to assess vegetation structure over an exceptionally broad elevation gradient of 866–4550m above sea level at Mount Kilimanjaro, Tanzania. Additionally, we compared (human)-modified habitats, including maize fields, traditionally managed home gardens, grasslands, commercial coffee farms and logged and burned forests with natural habitats along this elevation gradient. We distinguished vertical and horizontal vegetation structure to account for habitat complexity and heterogeneity. Vertical vegetation structure (assessed as number, width and density of vegetation layers, maximum canopy height, leaf area index and vegetation cover) displayed a unimodal elevation pattern, peaking at intermediate elevations in montane forests, whereas horizontal structure (assessed as coefficient of variation of number, width and density of vegetation layers, maximum canopy height, leaf area index and vegetation cover) was lowest at intermediate altitudes. Overall, vertical structure was consistently lower in modified than in natural habitat types, whereas horizontal structure was inconsistently different in modified than in natural habitat types, depending on the specific structural measure and habitat type. Our study shows how vertical and horizontal vegetation structure can be assessed efficiently in various habitat types in tropical mountain regions, and we suggest to apply this as a tool for informing future biodiversity and ecosystem service studies. PMID:26406985
NASA Astrophysics Data System (ADS)
He, Yaqian; Bo, Yanchen; Chai, Leilei; Liu, Xiaolong; Li, Aihua
2016-08-01
Leaf Area Index (LAI) is an important parameter of vegetation structure. A number of moderate resolution LAI products have been produced in urgent need of large scale vegetation monitoring. High resolution LAI reference maps are necessary to validate these LAI products. This study used a geostatistical regression (GR) method to estimate LAI reference maps by linking in situ LAI and Landsat TM/ETM+ and SPOT-HRV data over two cropland and two grassland sites. To explore the discrepancies of employing different vegetation indices (VIs) on estimating LAI reference maps, this study established the GR models for different VIs, including difference vegetation index (DVI), normalized difference vegetation index (NDVI), and ratio vegetation index (RVI). To further assess the performance of the GR model, the results from the GR and Reduced Major Axis (RMA) models were compared. The results show that the performance of the GR model varies between the cropland and grassland sites. At the cropland sites, the GR model based on DVI provides the best estimation, while at the grassland sites, the GR model based on DVI performs poorly. Compared to the RMA model, the GR model improves the accuracy of reference LAI maps in terms of root mean square errors (RMSE) and bias.
The effect of row structure on soil moisture retrieval accuracy from passive microwave data.
Xingming, Zheng; Kai, Zhao; Yangyang, Li; Jianhua, Ren; Yanling, Ding
2014-01-01
Row structure causes the anisotropy of microwave brightness temperature (TB) of soil surface, and it also can affect soil moisture retrieval accuracy when its influence is ignored in the inversion model. To study the effect of typical row structure on the retrieved soil moisture and evaluate if there is a need to introduce this effect into the inversion model, two ground-based experiments were carried out in 2011. Based on the observed C-band TB, field soil and vegetation parameters, row structure rough surface assumption (Q p model and discrete model), including the effect of row structure, and flat rough surface assumption (Q p model), ignoring the effect of row structure, are used to model microwave TB of soil surface. Then, soil moisture can be retrieved, respectively, by minimizing the difference of the measured and modeled TB. The results show that soil moisture retrieval accuracy based on the row structure rough surface assumption is approximately 0.02 cm(3)/cm(3) better than the flat rough surface assumption for vegetated soil, as well as 0.015 cm(3)/cm(3) better for bare and wet soil. This result indicates that the effect of row structure cannot be ignored for accurately retrieving soil moisture of farmland surface when C-band is used.
Explaining fruit and vegetable intake using a consumer marketing tool.
Della, Lindsay J; Dejoy, David M; Lance, Charles E
2009-10-01
In response to calls to reinvent the 5 A Day fruit and vegetable campaign, this study assesses the utility of VALS, a consumer-based audience segmentation tool that divides the U.S. population into groups leading similar lifestyles. The study examines whether the impact of theory of planned behavior (TPB) constructs varies across VALS groups in a cross-sectional sample of 1,588 U.S. adults. In a multigroup structural equation model, the VALS audience group variable moderated latent TPB relationships. Attitudes, subjective norms, and perceived behavioral control explained 57% to 70% of the variation in intention to eat fruit and vegetables across 5 different VALS groups. Perceived behavioral control and intention also predicted self-reported consumption behavior (R2 = 20% to 71% across VALS groups). Bivariate z tests were calculated to determine statistical differences in parameter estimates across groups. Nine of the bivariate z tests were statistically significant (p < or = .04), with standardized coefficients ranging from .05 to .70. These findings confirm the efficacy of using the TPB to explain variation in fruit and vegetable consumption as well as the validity of using a consumer-based algorithm to segment audiences for fruit and vegetable consumption messaging.
USDA-ARS?s Scientific Manuscript database
Multi-angle remote sensing has been proved useful for mapping vegetation community types in desert regions. Based on Multi-angle Imaging Spectro-Radiometer (MISR) multi-angular images, this study compares roles played by Bidirectional Reflectance Distribution Function (BRDF) model parameters with th...
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.
NASA Astrophysics Data System (ADS)
Ceballos-Núñez, Verónika; Richardson, Andrew D.; Sierra, Carlos A.
2018-03-01
The global carbon cycle is strongly controlled by the source/sink strength of vegetation as well as the capacity of terrestrial ecosystems to retain this carbon. These dynamics, as well as processes such as the mixing of old and newly fixed carbon, have been studied using ecosystem models, but different assumptions regarding the carbon allocation strategies and other model structures may result in highly divergent model predictions. We assessed the influence of three different carbon allocation schemes on the C cycling in vegetation. First, we described each model with a set of ordinary differential equations. Second, we used published measurements of ecosystem C compartments from the Harvard Forest Environmental Measurement Site to find suitable parameters for the different model structures. And third, we calculated C stocks, release fluxes, radiocarbon values (based on the bomb spike), ages, and transit times. We obtained model simulations in accordance with the available data, but the time series of C in foliage and wood need to be complemented with other ecosystem compartments in order to reduce the high parameter collinearity that we observed, and reduce model equifinality. Although the simulated C stocks in ecosystem compartments were similar, the different model structures resulted in very different predictions of age and transit time distributions. In particular, the inclusion of two storage compartments resulted in the prediction of a system mean age that was 12-20 years older than in the models with one or no storage compartments. The age of carbon in the wood compartment of this model was also distributed towards older ages, whereas fast cycling compartments had an age distribution that did not exceed 5 years. As expected, models with C distributed towards older ages also had longer transit times. These results suggest that ages and transit times, which can be indirectly measured using isotope tracers, serve as important diagnostics of model structure and could largely help to reduce uncertainties in model predictions. Furthermore, by considering age and transit times of C in vegetation compartments as distributions, not only their mean values, we obtain additional insights into the temporal dynamics of carbon use, storage, and allocation to plant parts, which not only depends on the rate at which this C is transferred in and out of the compartments but also on the stochastic nature of the process itself.
NASA Astrophysics Data System (ADS)
de Souza Pereira, Francisca Rocha; Kampel, Milton; Cunha-Lignon, Marilia
2016-07-01
The potential use of phased array type L-band synthetic aperture radar (PALSAR) data for discriminating distinct physiographic mangrove types with different forest structure developments in a subtropical mangrove forest located in Cananéia on the Southern coast of São Paulo, Brazil, is investigated. The basin and fringe physiographic types and the structural development of mangrove vegetation were identified with the application of the Kruskal-Wallis statistical test to the SAR backscatter values of 10 incoherent attributes. The best results to separate basin to fringe types were obtained using copolarized HH, cross-polarized HV, and the biomass index (BMI). Mangrove structural parameters were also estimated using multiple linear regressions. BMI and canopy structure index were used as explanatory variables for canopy height, mean height, and mean diameter at breast height regression models, with significant R2=0.69, 0.73, and 0.67, respectively. The current study indicates that SAR L-band images can be used as a tool to discriminate physiographic types and to characterize mangrove forests. The results are relevant considering the crescent availability of freely distributed SAR images that can be more utilized for analysis, monitoring, and conservation of the mangrove ecosystem.
NASA Astrophysics Data System (ADS)
Bogner, Christina; Kühnel, Anna; Hepp, Johannes; Huwe, Bernd
2016-04-01
The Kilimanjaro region in Tanzania constitutes a particularity compared to other areas in the country. Because enough water is available the population grows rapidly and large areas are converted from natural ecosystems to agricultural areas. Therefore, the southern slopes of Mt. Kilimanjaro encompass a complex mosaic of different land uses like coffee plantations, maize, agroforestry or natural savannah. Coffee is an important cash crop in the region and is owned mostly by large companies. In contrast, the agroforestry is a traditional way of agriculture and has been sustained by the Chagga tribe for centuries. These so called homegardens are organised as multi-level systems and contain a mixture of different crops. Correlations in soil and vegetation data may serve as indicators for crop and management impacts associated to different types of land use. We hypothesize that Chagga homegardens, for example, show a more pronounced spatial autocorrelation compared to coffee plantations due to manifold above and belowground crop structures, whereas the degree of anisotropy is assumed to be higher in the coffee sites due to linear elements in management. Furthermore, we hypothesize that the overall diversity of soil parameters in homegardens on a larger scale is higher, as individual owners manage their field differently, whereas coffee plantation management often follows general rules. From these general hypotheses we derive two specific research questions: a) Are there characteristic differences in the spatial organisation of soil physical parameters of different land uses? b) Is there a recognizable relationship between vegetation structure and soil physical parameters of topsoils? We measured soil physical parameters in the topsoil (bulk density, stone content, texture, soil moisture and penetration resistance). Additionally, we took spectra of soil samples with a portable VIS-NIR spectrometer to determine C and N and measured leaf area index and troughfall as an indicator of vegetation patterns. First results support our general hypotheses. In the coffee plantation anisotropic variation of soil parameters clearly showed the anthropogenic influence like compaction due to agricultural machinery. However, soil bulk density and penetration resistance in the homegarden were also quite variable at the sites. The larger variability of throughfall in the homegarden is reflected in the patterns of soil moisture. Regarding the larger scale, where we compared different homegardens and coffee plantations along the southern slope of the mountain, soil parameters of the coffee plots were less diverse than those of the homegardens.
a R-Shiny Based Phenology Analysis System and Case Study Using Digital Camera Dataset
NASA Astrophysics Data System (ADS)
Zhou, Y. K.
2018-05-01
Accurate extracting of the vegetation phenology information play an important role in exploring the effects of climate changes on vegetation. Repeated photos from digital camera is a useful and huge data source in phonological analysis. Data processing and mining on phenological data is still a big challenge. There is no single tool or a universal solution for big data processing and visualization in the field of phenology extraction. In this paper, we proposed a R-shiny based web application for vegetation phenological parameters extraction and analysis. Its main functions include phenological site distribution visualization, ROI (Region of Interest) selection, vegetation index calculation and visualization, data filtering, growth trajectory fitting, phenology parameters extraction, etc. the long-term observation photography data from Freemanwood site in 2013 is processed by this system as an example. The results show that: (1) this system is capable of analyzing large data using a distributed framework; (2) The combination of multiple parameter extraction and growth curve fitting methods could effectively extract the key phenology parameters. Moreover, there are discrepancies between different combination methods in unique study areas. Vegetation with single-growth peak is suitable for using the double logistic module to fit the growth trajectory, while vegetation with multi-growth peaks should better use spline method.
NASA Astrophysics Data System (ADS)
Kalra, Tarandeep S.; Aretxabaleta, Alfredo; Seshadri, Pranay; Ganju, Neil K.; Beudin, Alexis
2017-12-01
Coastal hydrodynamics can be greatly affected by the presence of submerged aquatic vegetation. The effect of vegetation has been incorporated into the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system. The vegetation implementation includes the plant-induced three-dimensional drag, in-canopy wave-induced streaming, and the production of turbulent kinetic energy by the presence of vegetation. In this study, we evaluate the sensitivity of the flow and wave dynamics to vegetation parameters using Sobol' indices and a least squares polynomial approach referred to as the Effective Quadratures method. This method reduces the number of simulations needed for evaluating Sobol' indices and provides a robust, practical, and efficient approach for the parameter sensitivity analysis. The evaluation of Sobol' indices shows that kinetic energy, turbulent kinetic energy, and water level changes are affected by plant stem density, height, and, to a lesser degree, diameter. Wave dissipation is mostly dependent on the variation in plant stem density. Performing sensitivity analyses for the vegetation module in COAWST provides guidance to optimize efforts and reduce exploration of parameter space for future observational and modeling work.
A Forward GPS Multipath Simulator Based on the Vegetation Radiative Transfer Equation Model
Wu, Xuerui; Jin, Shuanggen; Xia, Junming
2017-01-01
Global Navigation Satellite Systems (GNSS) have been widely used in navigation, positioning and timing. Nowadays, the multipath errors may be re-utilized for the remote sensing of geophysical parameters (soil moisture, vegetation and snow depth), i.e., GPS-Multipath Reflectometry (GPS-MR). However, bistatic scattering properties and the relation between GPS observables and geophysical parameters are not clear, e.g., vegetation. In this paper, a new element on bistatic scattering properties of vegetation is incorporated into the traditional GPS-MR model. This new element is the first-order radiative transfer equation model. The new forward GPS multipath simulator is able to explicitly link the vegetation parameters with GPS multipath observables (signal-to-noise-ratio (SNR), code pseudorange and carrier phase observables). The trunk layer and its corresponding scattering mechanisms are ignored since GPS-MR is not suitable for high forest monitoring due to the coherence of direct and reflected signals. Based on this new model, the developed simulator can present how the GPS signals (L1 and L2 carrier frequencies, C/A, P(Y) and L2C modulations) are transmitted (scattered and absorbed) through vegetation medium and received by GPS receivers. Simulation results show that the wheat will decrease the amplitudes of GPS multipath observables (SNR, phase and code), if we increase the vegetation moisture contents or the scatters sizes (stem or leaf). Although the Specular-Ground component dominates the total specular scattering, vegetation covered ground soil moisture has almost no effects on the final multipath signatures. Our simulated results are consistent with previous results for environmental parameter detections by GPS-MR. PMID:28587255
Effects of topoclimatic complexity on the composition of woody plant communities.
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
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
A radiosity model for heterogeneous canopies in remote sensing
NASA Astrophysics Data System (ADS)
GarcíA-Haro, F. J.; Gilabert, M. A.; Meliá, J.
1999-05-01
A radiosity model has been developed to compute bidirectional reflectance from a heterogeneous canopy approximated by an arbitrary configuration of plants or clumps of vegetation, placed on the ground surface in a prescribed manner. Plants are treated as porous cylinders formed by aggregations of layers of leaves. This model explicitly computes solar radiation leaving each individual surface, taking into account multiple scattering processes between leaves and soil, and occlusion of neighboring plants. Canopy structural parameters adopted in this study have served to simplify the computation of the geometric factors of the radiosity equation, and thus this model has enabled us to simulate multispectral images of vegetation scenes. Simulated images have shown to be valuable approximations of satellite data, and then a sensitivity analysis to the dominant parameters of discontinuous canopies (plant density, leaf area index (LAI), leaf angle distribution (LAD), plant dimensions, soil optical properties, etc.) and scene (sun/ view angles and atmospheric conditions) has been undertaken. The radiosity model has let us gain a deep insight into the radiative regime inside the canopy, showing it to be governed by occlusion of incoming irradiance, multiple scattering of radiation between canopy elements and interception of upward radiance by leaves. Results have indicated that unlike leaf distribution, other structural parameters such as LAI, LAD, and plant dimensions have a strong influence on canopy reflectance. In addition, concepts have been developed that are useful to understand the reflectance behavior of the canopy, such as an effective LAI related to leaf inclination.
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.
Niu, Xiang; Gao, Peng; Wang, Bing; Liu, Yu
2015-12-03
Based on fractal theory, the fractal characteristics of soil particle size distribution (PSD) and soil water retention curve (WRC) under the five vegetation types were studied in the mountainous land of Northern China. Results showed that: (1) the fractal parameters of soil PSD and soil WRC varied greatly under each different vegetation type, with Quercus acutissima Carr. and Robina pseudoacacia Linn. mixed plantation (QRM) > Pinus thunbergii Parl. and Pistacia chinensis Bunge mixed plantation (PPM) > Pinus thunbergii Parl. (PTP) > Juglans rigia Linn. (JRL) > abandoned grassland (ABG); (2) the soil fractal dimensions of woodlands (QRM, PPM, PTP and JRL) were significantly higher than that in ABG, and mixed forests (QRM and PPM) were higher than that in pure forests (PTP and JRL); (3) the fractal dimension of soil was positively correlated with the silt and clay content but negatively correlated with the sand content; and (4) the fractal dimension of soil PSD was positively correlated with the soil WRC. These indicated that the fractal parameters of soil PSD and soil WRC could act as quantitative indices to reflect the physical properties of the soil, and could be used to describe the influences of the Return Farmland to Forests Projects on soil structure.
Niu, Xiang; Gao, Peng; Wang, Bing; Liu, Yu
2015-01-01
Based on fractal theory, the fractal characteristics of soil particle size distribution (PSD) and soil water retention curve (WRC) under the five vegetation types were studied in the mountainous land of Northern China. Results showed that: (1) the fractal parameters of soil PSD and soil WRC varied greatly under each different vegetation type, with Quercus acutissima Carr. and Robina pseudoacacia Linn. mixed plantation (QRM) > Pinus thunbergii Parl. and Pistacia chinensis Bunge mixed plantation (PPM) > Pinus thunbergii Parl. (PTP) > Juglans rigia Linn. (JRL) > abandoned grassland (ABG); (2) the soil fractal dimensions of woodlands (QRM, PPM, PTP and JRL) were significantly higher than that in ABG, and mixed forests (QRM and PPM) were higher than that in pure forests (PTP and JRL); (3) the fractal dimension of soil was positively correlated with the silt and clay content but negatively correlated with the sand content; and (4) the fractal dimension of soil PSD was positively correlated with the soil WRC. These indicated that the fractal parameters of soil PSD and soil WRC could act as quantitative indices to reflect the physical properties of the soil, and could be used to describe the influences of the Return Farmland to Forests Projects on soil structure. PMID:26633458
NASA Astrophysics Data System (ADS)
Istanbulluoglu, Erkan; Bras, Rafael L.
2005-06-01
Topography acts as a template for numerous landscape processes that include hydrologic, ecologic, and biologic phenomena. These processes not only interact with each other but also contribute to shaping the landscape as they influence geomorphic processes. We have investigated the effects of vegetation on thresholds for channel initiation and landform evolution using both analytical and numerical approaches. Vegetation is assumed to form a uniform ground cover. Runoff erosion is modeled based on a power function of excess shear stress, in which shear stress efficiency is inversely proportional to vegetation cover. This approach is validated using data. Plant effect on slope stability is represented by additional cohesion provided by plant roots. Vegetation cover is assumed to reduce sediment transport rates due to physical creep processes (rainsplash, dry ravel, and expansion and contraction of sediments) according to a negative exponential relationship. Vegetation grows as a function of both available cover and unoccupied space by plants and is killed by geomorphic disturbances (runoff erosion and landsliding) and wildfires. Analytical results suggest that in an equilibrium basin with a fixed vegetation cover, plants may cause a transition in the dominant erosion process at the channel head. A runoff erosion-dominated landscape, under none or poor vegetation cover, may become landslide dominated under a denser vegetation cover. The sign of the predicted relationship between drainage density and vegetation cover depends on the relative influence of vegetation on different erosion phenomena. With model parameter values representative of the Oregon Coast Range (OCR), numerical experiments conducted using the Channel Hillslope Integrated Landscape Development (CHILD) model confirm the findings based on the analytical theory. A highly dissected fluvial landscape emerges when surface is assumed bare. When vegetation cover is modeled, landscape relief increases, resulting in hollow erosion dominated by landsliding. Interestingly, our simulations underscore the importance of vegetation disturbances by geomorphic events and wildfires on the landscape structure. Simulated landscapes resemble real-world catchments in the OCR when such disturbances are considered.
NASA Astrophysics Data System (ADS)
Carothers, R. A.; Sangireddy, H.; Passalacqua, P.
2013-12-01
In his expansive 1957 study of over 80 basins in Arizona, Colorado, New Mexico, and Utah, Mark Melton measured key morphometric, soil, land cover, and climatic parameters [Melton, 1957]. He identified correlations between morphological parameters and climatic regimes in an attempt to characterize the geomorphology of the basin as a function of climate and vegetation. Using modern techniques such as high resolution digital terrain models in combination with high spatial resolution weather station records, vector soil maps, seamless raster geological data, and land cover vector maps, we revisit Melton's 1957 dataset with the following hypotheses: (1) Patterns of channelization carry strong, codependent signatures in the form of statistical correlations of rainfall variability, soil type, and vegetation patterns. (2) Channelization patterns reflect the erosion processes on sub-catchment scale and the subsequent processes of vegetation recovery and gullying. In order to characterize various topographic and climatic parameters, we obtain elevation and land cover data from the USGS National Elevation dataset, climate data from the Western Regional Climate Center and PRISM climate group database, and soil type from the USDA STATSGO soil database. We generate a correlative high resolution database on vegetation, soil cover, lithology, and climatology for the basins identified by Melton in his 1957 study. Using the GeoNet framework developed by Passalacqua et al. [2010], we extract various morphological parameters such as slope, drainage density, and stream frequency. We also calculate metrics for patterns of channelization such as number of channelized pixels in a basin and channel head density. In order to understand the correlation structure between climate and morphological variables, we compute the Pearson's correlation coefficient similar to Melton's analysis and also explore other statistical procedures to characterize the feedbacks between these variables. By identifying the differences in Melton's and our results, we address the influence of climate over the degree of channel dissection in the landscape. References: Melton, M. A. (1957). An analysis of the relations among elements of climate, surface properties, and geomorphology (No. CU-TR-11). COLUMBIA UNIV NEW YORK Passalacqua, P., Do Trung, T., Foufoula-Georgiou, E., Sapiro, G., & Dietrich, W. E. (2010). A geometric framework for channel network extraction from lidar: Nonlinear diffusion and geodesic paths. Journal of Geophysical Research: Earth Surface (2003-2012), 115(F1). PRISM Climate Group, Oregon State University, http://prism.oregonstate.edu, created 4 Feb 2004 Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture. U.S. General Soil Map (STATSGO2). Available online at http://soildatamart.nrcs.usda.gov USGS National Map Viewer, United States Geological Survey. Web. 10 June 2013. http://viewer.nationalmap.gov/viewer/ Western U.S. Historical Climate Summaries, Western Regional Climate Group, 2013. Web. 10 June 2013. http://www.wrcc.dri.edu/Climsum.html
Thompson, Robert S.; Anderson, Katherine H.; Pelltier, Richard T.; Strickland, Laura E.; Shafer, Sarah L.; Bartlein, Patrick J.
2012-01-01
Vegetation inventories (plant taxa present in a vegetation assemblage at a given site) can be used to estimate climatic parameters based on the identification of the range of a given parameter where all taxa in an assemblage overlap ("Mutual Climatic Range"). For the reconstruction of past climates from fossil or subfossil plant assemblages, we assembled the data necessary for such analyses for 530 woody plant taxa and eight climatic parameters in North America. Here we present examples of how these data can be used to obtain paleoclimatic estimates from botanical data in a straightforward, simple, and robust fashion. We also include matrices of climate parameter versus occurrence or nonoccurrence of the individual taxa. These relations are depicted graphically as histograms of the population distributions of the occurrences of a given taxon plotted against a given climatic parameter. This provides a new method for quantification of paleoclimatic parameters from fossil plant assemblages.
Jiang, Yueyang; Zhuang, Qianlai; Schaphoff, Sibyll; Sitch, Stephen; Sokolov, Andrei; Kicklighter, David; Melillo, Jerry
2012-01-01
This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble Lund-Potsdam-Jena (LPJ) simulations for the northern high latitudes (45oN and polewards) for the period 1900–2100. The LPJ Dynamic Global Vegetation Model (LPJ-DGVM) was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT). In the current dynamic vegetation model, some parameters are more important than others in determining the vegetation distribution. Parameters that control plant carbon uptake and light-use efficiency have the predominant influence on the vegetation distribution of both woody and herbaceous plant functional types. The relative importance of different parameters varies temporally and spatially and is influenced by climate inputs. In addition to climate, these parameters play an important role in determining the vegetation distribution in the region. The parameter-based uncertainties contribute most to the total uncertainty. The current warming conditions lead to a complexity of vegetation responses in the region. Temperate trees will be more sensitive to climate variability, compared with boreal forest trees and C3 perennial grasses. This sensitivity would result in a unanimous northward greenness migration due to anomalous warming in the northern high latitudes. Temporally, boreal needleleaved evergreen plants are projected to decline considerably, and a large portion of C3 perennial grass is projected to disappear by the end of the 21st century. In contrast, the area of temperate trees would increase, especially under the most extreme A1FI scenario. As the warming continues, the northward greenness expansion in the Arctic region could continue. PMID:22822437
NASA Technical Reports Server (NTRS)
Rincon, Rafael F.; Fatoyinbo, Temilola; Carter, Lynn; Ranson, K. Jon; Vega, Manuel; Osmanoglu, Batuhan; Lee, SeungKuk; Sun, Guoqing
2014-01-01
The Digital Beamforming Synthetic Aperture radar (DBSAR) is a state-of-the-art airborne radar developed at NASA/Goddard for the implementation, and testing of digital beamforming techniques applicable to Earth and planetary sciences. The DBSAR measurements have been employed to study: The estimation of vegetation biomass and structure - critical parameters in the study of the carbon cycle; The measurement of geological features - to explore its applicability to planetary science by measuring planetary analogue targets. The instrument flew two test campaigns over the East coast of the United States in 2011, and 2012. During the campaigns the instrument operated in full polarimetric mode collecting data from vegetation and topography features.
Plant basket hydraulic structures (PBHS) as a new river restoration measure.
Kałuża, Tomasz; Radecki-Pawlik, Artur; Szoszkiewicz, Krzysztof; Plesiński, Karol; Radecki-Pawlik, Bartosz; Laks, Ireneusz
2018-06-15
River restoration has become increasingly attractive worldwide as it provides considerable benefits to the environment as well as to the economy. This study focuses on changes of hydromorphological conditions in a small lowland river recorded during an experiment carried out in the Flinta River, central Poland. The proposed solution was a pilot project of the construction of vegetative sediment traps (plant basket hydraulic structures - PBHS). A set of three PBSH was installed in the riverbed in one row and a range of hydraulic parameters were recorded over a period of three years (six measurement sessions). Changes of sediment grain size were analysed, and the amount and size of plant debris in the plant barriers were recorded. Plant debris accumulation influencing flow hydrodynamics was detected as a result of the installation of vegetative sediment traps. Moreover, various hydromorphological processes in the river were initiated. Additional simulations based on the detected processes showed that the proposed plant basket hydraulic structures can improve the hydromorphological status of the river. Copyright © 2018 Elsevier B.V. All rights reserved.
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
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.
A Drone-based Tropical Forest Experiment to Estimate Vegetation Properties
NASA Astrophysics Data System (ADS)
Henke, D.
2017-12-01
In mid-latitudes, remote sensing technology is intensively used to monitor vegetation properties. However, in the tropics, high cloud-cover and saturation effects of vegetation indices (VI) hamper the reliability of vegetation parameters derived from satellite data. A drone experiment over the Barro Colorado Island (BCI), Panama, with high temporal repetition rates was conducted in spring 2017 to investigate the robustness and stability of remotely sensed vegetation parameters in tropical environments. For this purpose, three 10-day flight windows in February, March and April were selected and drone flights were repeated on daily intervals when weather conditions and equipment allowed it. In total, 18 days were recorded with two different optical cameras on sensefly's eBee drone: one red, green, blue (RGB) camera and one camera with near infra-red (NIR), green and blue channels. When possible, the data were acquired at the same time of day. Pix4D and Agisoft software were used to calculate the Normalized Difference VI (NDVI) and forest structure. In addition, leave samples were collected ones per month from 16 different plant species and the relative water content was measured as ground reference. Further data sources for the analysis are phenocam images (RGB & NIR) on BCI and satellite images of MODIS (NDVI; Enhanced VI EVI) and Sentinel-1 (radar backscatter). The attached figure illustrates the main data collected on BCI. Initial results suggest that the coefficient of determination (R2) is relatively high between ground samples and drone data, Sentinel-1 backscatter and MODIS EVI with R2 values ranging from 0.4 to 0.6; on the contrary, R2 values between ground measurements and MODIS NDVI or phenocam images are below 0.2. As the experiment took place mainly during dry season on BCI, cloud-cover rates are less dominate than during wet season. Under these conditions, MODIS EVI, which is less vulnerable to saturation effects, seems to be more reliable than MODIS NDVI. During wet season, Sentinel-1 backscatter might be the most reliable satellite option to derive vegetation parameters in the tropics. For a more robust conclusion, additional data takes over several years and during dry as well as wet season are needed to confirm initial findings presented here.
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.
Online vegetation parameter estimation using passive microwave remote sensing observations
USDA-ARS?s Scientific Manuscript database
In adaptive system identification the Kalman filter can be used to identify the coefficient of the observation operator of a linear system. Here the ensemble Kalman filter is tested for adaptive online estimation of the vegetation opacity parameter of a radiative transfer model. A state augmentatio...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Smith, J.R.
1986-01-01
Pre-law coal surface-mined lands in Pyramid State Park, Perry County, Illinois, were examined 1976-1980 to determine changes in fauna and flora from that on the area in 1954-1960. Vegetative development on naturally revegetated spoils reflected diverse habitat conditions with interspersion of cover types; some of oldest spoils displayed inhibited succession while others exhibited early flood plain forest development. Ground and overstory species richness and overstory density increased since mid 1950's and ground cover domination by therophytes in 1954-1956 shifted to phanerophytes and hemicryptophytes in 1976-1978. Thirty vegetative compositional and structural parameters indicated that ground cover was limited by subcanopy rathermore » than large scattered trees. Aquatic vegetation communities developed but hydrosphere was not well represented; emergent vegetation was limited by morphology of basins. Although isolated sites exhibited deleterious conditions, vegetation was not generally inhibited by physico-chemical factors. The 29 mammals reflected an increase in species richness. Abundance of early successional forms decreased while occupants of shrub/forest increased. Past habitat enhancement influenced wildlife distribution; and plantations attracted woodland fauna. Leveled spoil crests, valleys and clearings with fescue retarded succession and provided open areas and edges for others.« less
Do understorey or overstorey traits drive tree encroachment on a drained raised bog?
Jagodziński, A M; Horodecki, P; Rawlik, K; Dyderski, M K
2017-07-01
One of the most important threats to peatland ecosystems is drainage, resulting in encroachment of woody species. Our main aim was to check which features - overstorey or understorey vegetation - are more important for shaping the seedling bank of pioneer trees colonising peatlands (Pinus sylvestris and Betula pubescens). We hypothesised that tree stand parameters will be more important predictors of natural regeneration density than understorey vegetation parameters, and the former will be negatively correlated with species diversity and richness and also with functional richness and functional dispersion, which indicate a high level of habitat filtering. The study was conducted in the 'Zielone Bagna' nature reserve (NW Poland). We assessed the structure of tree stands and natural regeneration (of B. pubescens and P. sylvestris) and vegetation species composition. Random forest and DCA were applied to assess relationships between variables studied. Understorey vegetation traits affected tree seedling density (up to 0.5-m height) more than tree stand traits. Density of older seedlings depended more on tree stand traits. We did not find statistically significant relationships between natural regeneration densities and functional diversity components, except for functional richness, which was positively correlated with density of the youngest tree seedlings. Seedling densities were higher in plots with lower functional dispersion and functional divergence, which indicated that habitat filtering is more important than competition. Presence of an abundant seedling bank is crucial for the process of woody species encroachment on drained peatlands, thus its dynamics should be monitored in protected areas. © 2017 German Botanical Society and The Royal Botanical Society of the Netherlands.
NASA Astrophysics Data System (ADS)
Bertoldi, Giacomo; Cordano, Emanuele; Brenner, Johannes; Senoner, Samuel; Della Chiesa, Stefano; Niedrist, Georg
2017-04-01
In mountain regions, the plot- and catchment-scale water and energy budgets are controlled by a complex interplay of different abiotic (i.e. topography, geology, climate) and biotic (i.e. vegetation, land management) controlling factors. When integrated, physically-based eco-hydrological models are used in mountain areas, there are a large number of parameters, topographic and boundary conditions that need to be chosen. However, data on soil and land-cover properties are relatively scarce and do not reflect the strong variability at the local scale. For this reason, tools for uncertainty quantification and optimal parameters identification are essential not only to improve model performances, but also to identify most relevant parameters to be measured in the field and to evaluate the impact of different assumptions for topographic and boundary conditions (surface, lateral and subsurface water and energy fluxes), which are usually unknown. In this contribution, we present the results of a sensitivity analysis exercise for a set of 20 experimental stations located in the Italian Alps, representative of different conditions in terms of topography (elevation, slope, aspect), land use (pastures, meadows, and apple orchards), soil type and groundwater influence. Besides micrometeorological parameters, each station provides soil water content at different depths, and in three stations (one for each land cover) eddy covariance fluxes. The aims of this work are: (I) To present an approach for improving calibration of plot-scale soil moisture and evapotranspiration (ET). (II) To identify the most sensitive parameters and relevant factors controlling temporal and spatial differences among sites. (III) Identify possible model structural deficiencies or uncertainties in boundary conditions. Simulations have been performed with the GEOtop 2.0 model, which is a physically-based, fully distributed integrated eco-hydrological model that has been specifically designed for mountain regions, since it considers the effect of topography on radiation and water fluxes and integrates a snow module. A new automatic sensitivity and optimization tool based on the Particle Swarm Optimization theory has been developed, available as R package on https://github.com/EURAC-Ecohydro/geotopOptim2. The model, once calibrated for soil and vegetation parameters, predicts the plot-scale temporal SMC dynamics of SMC and ET with a RMSE of about 0.05 m3/m3 and 40 W/m2, respectively. However, the model tends to underestimate ET during summer months over apple orchards. Results show how most sensitive parameters are both soil and canopy structural properties. However, ranking is affected by the choice of the target function and local topographic conditions. In particular, local slope/aspect influences results in stations located over hillslopes, but with marked seasonal differences. Results for locations in the valley floor are strongly controlled by the choice of the bottom water flux boundary condition. The poorer model performances in simulating ET over apple orchards could be explained by a model structural deficiency in representing the stomatal control on vapor pressure deficit for this particular type of vegetation. The results of this sensitivity could be extended to other physically distributed models, and also provide valuable insights for optimizing new experimental designs.
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.
Effects of a large wildfire on vegetation structure in a variable fire mosaic.
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.
Performance evaluation of spectral vegetation indices using a statistical sensitivity function
Ji, Lei; Peters, Albert J.
2007-01-01
A great number of spectral vegetation indices (VIs) have been developed to estimate biophysical parameters of vegetation. Traditional techniques for evaluating the performance of VIs are regression-based statistics, such as the coefficient of determination and root mean square error. These statistics, however, are not capable of quantifying the detailed relationship between VIs and biophysical parameters because the sensitivity of a VI is usually a function of the biophysical parameter instead of a constant. To better quantify this relationship, we developed a “sensitivity function” for measuring the sensitivity of a VI to biophysical parameters. The sensitivity function is defined as the first derivative of the regression function, divided by the standard error of the dependent variable prediction. The function elucidates the change in sensitivity over the range of the biophysical parameter. The Student's t- or z-statistic can be used to test the significance of VI sensitivity. Additionally, we developed a “relative sensitivity function” that compares the sensitivities of two VIs when the biophysical parameters are unavailable.
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.
Remote sensing of crop parameters with a polarized, frequency-doubled Nd:YAG laser
NASA Astrophysics Data System (ADS)
Kalshoven, James E., Jr.; Tierney, Michael R., Jr.; Daughtry, Craig S. T.; McMurtrey, James E., III
1995-05-01
Polarized laser remote-sensing measurements that correlate the yield, the normalized difference vegetation index, and the leaf area index with the depolarized backscattered radiation from corn plots grown with eight different nitrogen fertilization dosages are presented. A polarized Nd:YAG laser emitting at 1064 and 532 nm is used. Depolarization increased significantly with increasing fertilization at the infrared wavelength, and there was a decrease in the depolarization at the green wavelength. The depolarization spectral difference index, defined as the absolute difference in the depolarization at the two wavelengths, is introduced as a parameter that is an indicator of the condition of the internal leaf structure.
Hydraulic resistance of submerged flexible vegetation
NASA Astrophysics Data System (ADS)
Stephan, Ursula; Gutknecht, Dieter
2002-12-01
The main research objective consisted in analysing the influence of roughness caused by aquatic vegetation (av), in particular submerged macrophytes, on the overall flow field. These plants are highly flexible and behave differently depending on the flow situation. They also react substantially to the flow field and thus, the roughness becomes variable and dynamic. Conventional flow formulas, such as the Manning or the Strickler formula, are one-dimensional and based on integral flow parameters. They are not suitable for quantifying the roughness of av, because the flow is complex and more dimensional due to the variable behaviour of the plants. Therefore, the present investigation concentrates on the definition of a characteristic hydraulic roughness parameter to quantify the resistance of av. Within this investigation laboratory experiments were carried out with three different types of av, chosen with respect to varying plant structures as well as stem lengths. Velocity measurements above these plants were conducted to determine the relationship between the hydraulic roughness and the deflected plant height. The deflected plant height is used as the geometric roughness parameter, whereas the equivalent sand roughness based on the universal logarithmic law modified by Nikuradse was used as hydraulic roughness parameter. The influence of relative submergence on the hydraulic roughness was also analysed. The analysis of the velocity measurements illustrates that equivalent sand roughness and zero plane displacement of the logarithmic law are correlated to the deflected plant height and are equally to this height.
Habitat and landscape effects on abundance of Missouri's grassland birds
Jacobs, R.B.; Thompson, F.R.; Koford, Rolf R.; La Sorte, F.A.; Woodward, H.D.; Fitzgerald, J.A.
2012-01-01
Of 6 million ha of prairie that once covered northern and western Missouri, <36,500 ha remain, with planted, managed, and restored grasslands comprising most contemporary grasslands. Most grasslands are used as pasture or hayfields. Native grasses largely have been replaced by fescue (Festuca spp.) on most private lands (almost 7 million ha). Previously cropped fields set aside under the Conservation Reserve Program (CRP) varied from a mix of cool-season grasses and forbs, or mix of native warm-season grasses and forbs, to simple tall-grass monocultures. We used generalized linear mixed models and distance sampling to assess abundance of 8 species of breeding grassland birds on 6 grassland types commonly associated with farm practices in Missouri and located in landscapes managed for grassland-bird conservation. We selected Bird Conservation Areas (BCAs) for their high percentage of grasslands and grassland-bird species, and for <5% forest cover. We used an information-theoretic approach to assess the relationship between bird abundance and 6 grassland types, 3 measures of vegetative structure, and 2 landscape variables (% grassland and edge density within a 1-km radius). We found support for all 3 levels of model parameters, although there was less support for landscape than vegetation structure effects likely because we studied high-percentage-grassland landscapes (BCAs). Henslow's sparrow (Ammodramus henslowii) counts increased with greater percentage of grassland, vegetation height-density, litter depth, and shrub cover and lower edge density. Henslow's sparrow counts were greatest in hayed native prairie. Dickcissel (Spiza americana) counts increased with greater vegetation height-density and were greatest in planted CRP grasslands. Grasshopper sparrow (A. savannarum) counts increased with lower vegetation height, litter depth, and shrub cover. Based on distance modeling, breeding densities of Henslow's sparrow, dickcissel, and grasshopper sparrow in the 6 grassland types ranged 0.9-2.6, 1.4-3.2, and 0.1-1.5 birds/ha, respectively. We suggest different grassland types and structures (vegetation height, litter depth, shrub cover) are needed to support priority grassland-bird species in Missouri. ?? 2011 The Wildlife Society.
Habitat and landscape effects on abundance of Missouri's grassland birds
Jacobson, Robert B.; Thompson, Frank R.; Koford, Rolf R.; La Sorte, Frank A.; Woodward, Hope D.; Fitzgerald, Jane A.
2012-01-01
Of 6 million ha of prairie that once covered northern and western Missouri, <36,500 ha remain, with planted, managed, and restored grasslands comprising most contemporary grasslands. Most grasslands are used as pasture or hayfields. Native grasses largely have been replaced by fescue (Festuca spp.) on most private lands (almost 7 million ha). Previously cropped fields set aside under the Conservation Reserve Program (CRP) varied from a mix of cool-season grasses and forbs, or mix of native warm-season grasses and forbs, to simple tall-grass monocultures. We used generalized linear mixed models and distance sampling to assess abundance of 8 species of breeding grassland birds on 6 grassland types commonly associated with farm practices in Missouri and located in landscapes managed for grassland-bird conservation. We selected Bird Conservation Areas (BCAs) for their high percentage of grasslands and grassland-bird species, and for <5% forest cover. We used an information-theoretic approach to assess the relationship between bird abundance and 6 grassland types, 3 measures of vegetative structure, and 2 landscape variables (% grassland and edge density within a 1-km radius). We found support for all 3 levels of model parameters, although there was less support for landscape than vegetation structure effects likely because we studied high-percentage-grassland landscapes (BCAs). Henslow's sparrow (Ammodramus henslowii) counts increased with greater percentage of grassland, vegetation height-density, litter depth, and shrub cover and lower edge density. Henslow's sparrow counts were greatest in hayed native prairie. Dickcissel (Spiza americana) counts increased with greater vegetation height-density and were greatest in planted CRP grasslands. Grasshopper sparrow (A. savannarum) counts increased with lower vegetation height, litter depth, and shrub cover. Based on distance modeling, breeding densities of Henslow's sparrow, dickcissel, and grasshopper sparrow in the 6 grassland types ranged 0.9–2.6, 1.4–3.2, and 0.1–1.5 birds/ha, respectively. We suggest different grassland types and structures (vegetation height, litter depth, shrub cover) are needed to support priority grassland-bird species in Missouri.
NASA Astrophysics Data System (ADS)
Assefa, Y.
The Bale mountain range is located between the wet east African mountains (proper) and the dry northeast African mountains, Southeast Ethiopia. This mountain range hosts some of endemic flora and fauna which are endangered of extinction. The most extensive Ericaceous vegetation in the continent is found in Bale Mountains. The southern slope of this mountain range is known for its distinct vegetation zonation of the Afromontane forests. The Ericaceous vegetation between the montane forest and the afroalpine of this slope is relatively little disturbed than other similar Ericaceous vegetation elsewhere in Africa. Study on the distribution and structure of this vegeta- tion was made from Nov. 1999- April 2000 on the southern slope, Harrena escarpment. The vegetation north of Rira village, between 3000m and 4200m was sampled after selecting continuous homogenous sites systematically along the altitudinal gradient. Cover abundance of the species for vascular plants, frequency, height and DBH for woody treeline species were taken in 110 quadrats. The environmental parameters along the altitudinal gradient including soil pH, texture, total nitrogen, and soil mois- ture were measured. Altitude, slope, and aspect were measured for all qudrats. All the environmental and vegetation data were analyzed with Syntax, Canoco, Minitab and Sigma plot. Anthropozogenic data was taken using questionnaire and analyzed. Thir- teen community types were described and their distribution showed a clear pattern at different parts of the Ericaceous vegetation. However some of the community types which were restricted to the Afroalpine belt were found in the Ericaceous vegetation. This might be a possible indication of the expansion of the afroalpine belt to lower altitude, even below 3400 m (Erica dominated Hagenia-Hypericum zone). The height of the tree and shrub species has shown a decreasing tendency with increase in al- titude. This trend was very gradual for E. trimera. The species occurs for about 1.2 km altitudinal range showing difference in height and habit along altitudinal gradi- ent. The regression analysis (r2=0.58) has shown a consistent decrease in height along altitude. No abrupt transition was documented in the systematically selected continu- ous Ericaceous vegetation. Among the environmental parameters taken, altitude was the strongest explanatory variable. While incidence of fire is correlated with socioeco- nomic parameters and relief Soil pH, and texture have shown stronger correlation with 1 altitude. While percent total nitrogen was showing more significant (p<0.01) correla- tion with microsite factors. Local people burn the Ericaceous vegetation mainly for grazing. Therefore, strategies that may reduce the rate of fire should take into account the pasture and the semi - pastoral local communities. Creat income-generating alter- natives for increasing population at Rira village. Barley used to be cultivated around Rira village in limited places. But now, indigenous settlers who were mainly depend- ing on animal rearing are shifting to mixed farming practices with increasing popu- lation. This could jeopardize the water shade of the area, in addition to the loss of biodiversity. Increasing awareness of the people on wise use of forest through school environmental clubs is also a possible option to approach the local people.
Effects of vegetation canopy on the radar backscattering coefficient
NASA Technical Reports Server (NTRS)
Mo, T.; Blanchard, B. J.; Schmugge, T. J.
1983-01-01
Airborne L- and C-band scatterometer data, taken over both vegetation-covered and bare fields, were systematically analyzed and theoretically reproduced, using a recently developed model for calculating radar backscattering coefficients of rough soil surfaces. The results show that the model can reproduce the observed angular variations of radar backscattering coefficient quite well via a least-squares fit method. Best fits to the data provide estimates of the statistical properties of the surface roughness, which is characterized by two parameters: the standard deviation of surface height, and the surface correlation length. In addition, the processes of vegetation attenuation and volume scattering require two canopy parameters, the canopy optical thickness and a volume scattering factor. Canopy parameter values for individual vegetation types, including alfalfa, milo and corn, were also determined from the best-fit results. The uncertainties in the scatterometer data were also explored.
Griotti, Mariana; Muñoz-Escobar, Christian; Ferretti, Nelson E
2017-08-01
The link between vegetation structure and spider diversity has been well explored in the literature. However, few studies have compared spider diversity and its response to vegetation at two conceptual levels: assemblage (species diversity) and ensemble (guild diversity). Because of this, we studied spider diversity in riparian and adjacent habitats of a river system from the Chacoan subregion in central Argentina and evaluated their linkage with vegetation structure at these two levels. To assess vegetation structure, we measured plant species richness and vegetation cover in the herb and shrub - tree layers. We collected spiders for over 6 months by using vacuum netting, sweep netting and pitfall traps. We collected 3,808 spiders belonging to 119 morphospecies, 24 families and 9 guilds. At spider assemblage level, SIMPROF analysis showed significant differences among studied habitats. At spider ensemble level, nevertheless, we found no significant differences among habitats. Concerning the linkage with vegetation structure, BIOENV test showed that spider diversity at either assemblage or ensemble level was not significantly correlated with the vegetation variables assessed. Our results indicated that spider diversity was not affected by vegetation structure. Hence, even though we found a pattern in spider assemblages among habitats, this could not be attributed to vegetation structure. In this study, we show that analyzing a community at two conceptual levels will be useful for recognizing different responses of spider communities to vegetation structure in diverse habitat types. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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.
Satellites observed widespread greening of Earth and increase of woody biomass
NASA Astrophysics Data System (ADS)
Chen, C.; Park, T.; Myneni, R.; Xu, L.; Saatchi, S. S.; Liu, Y.; Knyazikhin, Y.
2017-12-01
Global terrestrial vegetation is an important modulator of the planetary climate system that alters Earth's hydrology, atmosphere and energy circulations through biophysical and biochemical processes. Yet the internal structural change of the vegetation is not well understood. Leaf area index (LAI), unlike radiometric parameters (e.g. NDVI), is a well-defined and ground-measurable biophysical variable, which can better represent the greenness of vegetation. We evaluate 17-year (2000-2016) satellite-derived LAI from two MODIS sensors onboard Terra and Aqua. Results show that the global annual-averaged LAI has an increasing trend at 0.036 m2m-2 per decade (2.3% per decade). The widespread greening takes up 32.5% of the vegetated area, while only 5.2% of such exhibits browning. We further investigate the biome- and regional-specific patterns of the evolution of LAI: 1) Croplands (0.062 m2m-2 per decade) and forests (0.044 m2m-2 per decade) are the paramount contributors of the greening; 2) Temperate vegetation (0.052 m2m-2 per decade) greening outperform other regions, followed by high-latitude vegetation (0.031 m2m-2 per decade), and tropical vegetation (0.025 m2m-2 per decade) at the minimum. Two independent satellite-observed datasets from multiple bandwidths (optical, thermal and microwave) provide evidence that this large-scale LAI trend is mainly owing to the spatiotemporal transition of woody biomass and the change of canopy structure. The greening (browning) at the global scale is concordant with the increase (decrease) of tree cover and vegetation optical depth (VOD), while little correlation is found for herbaceous biomass (i.e. non-tree cover). The observed greening and expansion of woody biomass will lead to a smaller land surface diurnal temperature range (DTR) due to the increase of a) the evapotranspiration, b) the water storage (higher the specific heat capacity) and c) the aerodynamic resistance (vertical mixture) of the canopy. a) and c) can augment daytime cooling, while b) and c) can boost nighttime warming. We find, consistently, the MODIS observed land surface DTR decreases over greening regions, and increases over browning regions.
Ikin, Karen; Barton, Philip S.; Stirnemann, Ingrid A.; Stein, John R.; Michael, Damian; Crane, Mason; Okada, Sachiko; Lindenmayer, David B.
2014-01-01
Improving biodiversity conservation in fragmented agricultural landscapes has become an important global issue. Vegetation at the patch and landscape-scale is important for species occupancy and diversity, yet few previous studies have explored multi-scale associations between vegetation and community assemblages. Here, we investigated how patch and landscape-scale vegetation cover structure woodland bird communities. We asked: (1) How is the bird community associated with the vegetation structure of woodland patches and the amount of vegetation cover in the surrounding landscape? (2) Do species of conservation concern respond to woodland vegetation structure and surrounding vegetation cover differently to other species in the community? And (3) Can the relationships between the bird community and the woodland vegetation structure and surrounding vegetation cover be explained by the ecological traits of the species comprising the bird community? We studied 103 woodland patches (0.5 - 53.8 ha) over two time periods across a large (6,800 km2) agricultural region in southeastern Australia. We found that both patch vegetation and surrounding woody vegetation cover were important for structuring the bird community, and that these relationships were consistent over time. In particular, the occurrence of mistletoe within the patches and high values of woody vegetation cover within 1,000 ha and 10,000 ha were important, especially for bird species of conservation concern. We found that the majority of these species displayed similar, positive responses to patch and landscape vegetation attributes. We also found that these relationships were related to the foraging and nesting traits of the bird community. Our findings suggest that management strategies to increase both remnant vegetation quality and the cover of surrounding woody vegetation in fragmented agricultural landscapes may lead to improved conservation of bird communities. PMID:24830684
Ikin, Karen; Barton, Philip S; Stirnemann, Ingrid A; Stein, John R; Michael, Damian; Crane, Mason; Okada, Sachiko; Lindenmayer, David B
2014-01-01
Improving biodiversity conservation in fragmented agricultural landscapes has become an important global issue. Vegetation at the patch and landscape-scale is important for species occupancy and diversity, yet few previous studies have explored multi-scale associations between vegetation and community assemblages. Here, we investigated how patch and landscape-scale vegetation cover structure woodland bird communities. We asked: (1) How is the bird community associated with the vegetation structure of woodland patches and the amount of vegetation cover in the surrounding landscape? (2) Do species of conservation concern respond to woodland vegetation structure and surrounding vegetation cover differently to other species in the community? And (3) Can the relationships between the bird community and the woodland vegetation structure and surrounding vegetation cover be explained by the ecological traits of the species comprising the bird community? We studied 103 woodland patches (0.5 - 53.8 ha) over two time periods across a large (6,800 km(2)) agricultural region in southeastern Australia. We found that both patch vegetation and surrounding woody vegetation cover were important for structuring the bird community, and that these relationships were consistent over time. In particular, the occurrence of mistletoe within the patches and high values of woody vegetation cover within 1,000 ha and 10,000 ha were important, especially for bird species of conservation concern. We found that the majority of these species displayed similar, positive responses to patch and landscape vegetation attributes. We also found that these relationships were related to the foraging and nesting traits of the bird community. Our findings suggest that management strategies to increase both remnant vegetation quality and the cover of surrounding woody vegetation in fragmented agricultural landscapes may lead to improved conservation of bird communities.
NASA Astrophysics Data System (ADS)
Takemine, S.; Rikimaru, A.; Takahashi, K.
The rice is one of the staple foods in the world High quality rice production requires periodically collecting rice growth data to control the growth of rice The height of plant the number of stem the color of leaf is well known parameters to indicate rice growth Rice growth diagnosis method based on these parameters is used operationally in Japan although collecting these parameters by field survey needs a lot of labor and time Recently a laborsaving method for rice growth diagnosis is proposed which is based on vegetation cover rate of rice Vegetation cover rate of rice is calculated based on discriminating rice plant areas in a digital camera image which is photographed in nadir direction Discrimination of rice plant areas in the image was done by the automatic binarization processing However in the case of vegetation cover rate calculation method depending on the automatic binarization process there is a possibility to decrease vegetation cover rate against growth of rice In this paper a calculation method of vegetation cover rate was proposed which based on the automatic binarization process and referred to the growth hysteresis information For several images obtained by field survey during rice growing season vegetation cover rate was calculated by the conventional automatic binarization processing and the proposed method respectively And vegetation cover rate of both methods was compared with reference value obtained by visual interpretation As a result of comparison the accuracy of discriminating rice plant areas was increased by the proposed
MODELING DYNAMIC VEGETATION RESPONSE TO RAPID CLIMATE CHANGE USING BIOCLIMATIC CLASSIFICATION
Modeling potential global redistribution of terrestrial vegetation frequently is based on bioclimatic classifications which relate static regional vegetation zones (biomes) to a set of static climate parameters. The equilibrium character of the relationships limits our confidence...
NASA Astrophysics Data System (ADS)
Berrittella, C.; van Huissteden, J.
2011-10-01
Marine Isotope Stage 3 (MIS 3) interstadials are marked by a sharp increase in the atmospheric methane (CH4) concentration, as recorded in ice cores. Wetlands are assumed to be the major source of this CH4, although several other hypotheses have been advanced. Modelling of CH4 emissions is crucial to quantify CH4 sources for past climates. Vegetation effects are generally highly generalized in modelling past and present-day CH4 fluxes, but should not be neglected. Plants strongly affect the soil-atmosphere exchange of CH4 and the net primary production of the vegetation supplies organic matter as substrate for methanogens. For modelling past CH4 fluxes from northern wetlands, assumptions on vegetation are highly relevant since paleobotanical data indicate large differences in Last Glacial (LG) wetland vegetation composition as compared to modern wetland vegetation. Besides more cold-adapted vegetation, Sphagnum mosses appear to be much less dominant during large parts of the LG than at present, which particularly affects CH4 oxidation and transport. To evaluate the effect of vegetation parameters, we used the PEATLAND-VU wetland CO2/CH4 model to simulate emissions from wetlands in continental Europe during LG and modern climates. We tested the effect of parameters influencing oxidation during plant transport (fox), vegetation net primary production (NPP, parameter symbol Pmax), plant transport rate (Vtransp), maximum rooting depth (Zroot) and root exudation rate (fex). Our model results show that modelled CH4 fluxes are sensitive to fox and Zroot in particular. The effects of Pmax, Vtransp and fex are of lesser relevance. Interactions with water table modelling are significant for Vtransp. We conducted experiments with different wetland vegetation types for Marine Isotope Stage 3 (MIS 3) stadial and interstadial climates and the present-day climate, by coupling PEATLAND-VU to high resolution climate model simulations for Europe. Experiments assuming dominance of one vegetation type (Sphagnum vs. Carex vs. Shrubs) show that Carex-dominated vegetation can increase CH4 emissions by 50% to 78% over Sphagnum-dominated vegetation depending on the modelled climate, while for shrubs this increase ranges from 42% to 72%. Consequently, during the LG northern wetlands may have had CH4 emissions similar to their present-day counterparts, despite a colder climate. Changes in dominant wetland vegetation, therefore, may drive changes in wetland CH4 fluxes, in the past as well as in the future.
Plant characteristics and growth parameters of vegetable pigeon pea cultivars
USDA-ARS?s Scientific Manuscript database
Pigeon pea is an important crop in dry land and semi-arid regions and is a supplementary source of dietary protein for the resource-constrained farmers. The aim of this research was to evaluate growth parameters of twelve vegetable pigeon pea genotypes at two locations in Eastern Kenya. The number o...
Miglio, Cristiana; Chiavaro, Emma; Visconti, Attilio; Fogliano, Vincenzo; Pellegrini, Nicoletta
2008-01-09
The objective of the present study was to evaluate the effect of three common cooking practices (i.e., boiling, steaming, and frying) on phytochemical contents (i.e., polyphenols, carotenoids, glucosinolates, and ascorbic acid), total antioxidant capacities (TAC), as measured by three different analytical assays [Trolox equivalent antioxidant capacity (TEAC), total radical-trapping antioxidant parameter (TRAP), ferric reducing antioxidant power (FRAP)] and physicochemical parameters of three vegetables (carrots, courgettes, and broccoli). Water-cooking treatments better preserved the antioxidant compounds, particularly carotenoids, in all vegetables analyzed and ascorbic acid in carrots and courgettes. Steamed vegetables maintained a better texture quality than boiled ones, whereas boiled vegetables showed limited discoloration. Fried vegetables showed the lowest degree of softening, even though antioxidant compounds were less retained. An overall increase of TEAC, FRAP, and TRAP values was observed in all cooked vegetables, probably because of matrix softening and increased extractability of compounds, which could be partially converted into more antioxidant chemical species. Our findings defy the notion that processed vegetables offer lower nutritional quality and also suggest that for each vegetable a cooking method would be preferred to preserve the nutritional and physicochemical qualities.
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.
Charles E. Swift; Kerri T. Vierling; Andrew T. Hudak; Lee A. Vierling
2017-01-01
Ecologists have a long-term interest in understanding the relative influence of vegetation composition and vegetation structure on avian diversity. LiDAR remote sensing is useful in studying local patterns of avian diversity because it characterizes fine-scale vegetation structure across broad extents. We used LiDAR, aerial and satellite imagery, and avian field data...
NASA Astrophysics Data System (ADS)
Spengler, D.; Kuester, T.; Frick, A.; Scheffler, D.; Kaufmann, H.
2013-10-01
Surface soil moisture content is one of the key variables used for many applications especially in hydrology, meteorology and agriculture. Hyperspectral remote sensing provides effective methodologies for mapping soil moisture content over a broad area by different indices such as NSMI [1,2] and SMGM [3]. Both indices can achieve a high accuracy for non-vegetation influenced soil samples, but their accuracy is limited in case of the presence of vegetation. Since, the increase of the vegetation cover leads to non-linear variations of the indices. In this study a new methodology for moisture indices correcting the influence of vegetation is presented consisting of several processing steps. First, hyperspectral reflectance data are classified in terms of crop type and growth stage. Second, based on these parameters 3D plant models from a database used to simulate typical canopy reflectance considering variations in the canopy structure (e.g. plant density and distribution) and the soil moisture content for actual solar illumination and sensor viewing angles. Third, a vegetation correction function is developed, based on the calculated soil moisture indices and vegetation indices of the simulated canopy reflectance data. Finally this function is applied on hyperspectral image data. The method is tested on two hyperspectral image data sets of the AISA DUAL at the test site Fichtwald in Germany. The results show a significant improvements compared to solely use of NSMI index. Up to a vegetation cover of 75 % the correction function minimise the influences of vegetation cover significantly. If the vegetation is denser the method leads to inadequate quality to predict the soil moisture content. In summary it can be said that applying the method on weakly to moderately overgrown with vegetation locations enables a significant improvement in the quantification of soil moisture and thus greatly expands the scope of NSMI.
NASA Technical Reports Server (NTRS)
Lim, J. T.; Wilkerson, G. G.; Raper, C. D. Jr; Gold, H. J.
1990-01-01
A differential equation model of vegetative growth of the soya bean plant (Glycine max (L.) Merrill cv. Ransom') was developed to account for plant growth in a phytotron system under variation of root temperature and nitrogen concentration in nutrient solution. The model was tested by comparing model outputs with data from four different experiments. Model predictions agreed fairly well with measured plant performance over a wide range of root temperatures and over a range of nitrogen concentrations in nutrient solution between 0.5 and 10.0 mmol NO3- in the phytotron environment. Sensitivity analyses revealed that the model was most sensitive to changes in parameters relating to carbohydrate concentration in the plant and nitrogen uptake rate.
Luo, Shezhou; Chen, Jing M; Wang, Cheng; Xi, Xiaohuan; Zeng, Hongcheng; Peng, Dailiang; Li, Dong
2016-05-30
Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and ecosystem modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R2 = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m2), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data.
Do multiple fires interact to affect vegetation structure in temperate eucalypt forests?
Haslem, Angie; Leonard, Steve W J; Bruce, Matthew J; Christie, Fiona; Holland, Greg J; Kelly, Luke T; MacHunter, Josephine; Bennett, Andrew F; Clarke, Michael F; York, Alan
2016-12-01
Fire plays an important role in structuring vegetation in fire-prone regions worldwide. Progress has been made towards documenting the effects of individual fire events and fire regimes on vegetation structure; less is known of how different fire history attributes (e.g., time since fire, fire frequency) interact to affect vegetation. Using the temperate eucalypt foothill forests of southeastern Australia as a case study system, we examine two hypotheses about such interactions: (1) post-fire vegetation succession (e.g., time-since-fire effects) is influenced by other fire regime attributes and (2) the severity of the most recent fire overrides the effect of preceding fires on vegetation structure. Empirical data on vegetation structure were collected from 540 sites distributed across central and eastern Victoria, Australia. Linear mixed models were used to examine these hypotheses and determine the relative influence of fire and environmental attributes on vegetation structure. Fire history measures, particularly time since fire, affected several vegetation attributes including ground and canopy strata; others such as low and sub-canopy vegetation were more strongly influenced by environmental characteristics like rainfall. There was little support for the hypothesis that post-fire succession is influenced by fire history attributes other than time since fire; only canopy regeneration was influenced by another variable (fire type, representing severity). Our capacity to detect an overriding effect of the severity of the most recent fire was limited by a consistently weak effect of preceding fires on vegetation structure. Overall, results suggest the primary way that fire affects vegetation structure in foothill forests is via attributes of the most recent fire, both its severity and time since its occurrence; other attributes of fire regimes (e.g., fire interval, frequency) have less influence. The strong effect of environmental drivers, such as rainfall and topography, on many structural features show that foothill forest vegetation is also influenced by factors outside human control. While fire is amenable to human management, results suggest that at broad scales, structural attributes of these forests are relatively resilient to the effects of current fire regimes. Nonetheless, the potential for more frequent severe fires at short intervals, associated with a changing climate and/or fire management, warrant further consideration. © 2016 by the Ecological Society of America.
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.
NASA Astrophysics Data System (ADS)
Amatya, D. M.; Panda, S.; Chescheir, G. M.; Nettles, J. E.; Appelboom, T.; Skaggs, R. W.
2011-12-01
Vast areas of the land in the Southeastern United States are under pine forests managed primarily for timber and related byproducts. Evapotranspiration (ET) is the major loss in the water balance of this forest ecosystem. A long-term (1988-2008) study to evaluate hydrologic and nutrient balance during a life cycle of a pine stand was just completed. The study used both monitoring and modeling approaches to evaluate hydrologic and water quality effects of silvicultural and water management treatments on three 25 ha experimental watersheds in eastern North Carolina (NC). The research was extended in 2009 to include a dedicated energy crop, switchgrass (Panicum virgatum), by adding an adjacent 25 ha watershed. These multiple watersheds are being used to evaluate the hydrologic and water quality effects of switchgrass alone, young pine with natural understory, and young pine with switchgrass intercropping compared to the control (pine stand with a natural understory). The biofuels study has been further expanded to two other southern states, Alabama (AL) and Mississippi (MS). Each has five small watersheds (< 25 ha size) consisting of the above treatments and an additional woody biomass removal treatment. In this presentation we provide methods for estimating ET for these treatment watersheds in all three states (NC, AL, and MS) using remote sensing based spatial high resolution multispectral satellite imagery data with ground truthing, where possible, together with sensor technology. This technology is making ET parameter estimation a reality for various crops and vegetation surfaces. Slope-based vegetation indices like Normalized Difference Vegetation Index (NDVI) and Green Vegetation Index (GVI) and distance-based vegetation indices like Soil Adjusted Vegetation Index (SAVI) and Perpendicular Vegetation Index (PVI) will be developed using the R and NIR bands, vegetation density, and background soil reflectance as necessary. Landsat and high resolution aerial imageries of vegetation and soils will be used. IDRISI Taiga software will be used for the indices development. The forested vegetation health will be correlated to the leaf chlorophyll content for determining the vegetation health with a subsequent derivation of available plant water for radiation. Models will be developed to correlate the plant and soil available water to different vegetation indices. Correlation models will also be developed to obtain information on climatic parameters like surface air temperature, net radiation, albedo, soil moisture content, and stomatal water availability from Landsat imageries. On-site weather parameters used for the PET estimates will be combined with other vegetation parameters like leaf area index (LAI) obtained using LIDAR data and NAIP orthophotos of different seasons. That will also help detect the upper and understory vegetation. The LIDAR data will be processed to obtain the volume of vegetation to correctly estimate the total ET for each treatment.
Variability in vegetation effects on density and nesting success of grassland birds
Winter, Maiken; Johnson, Douglas H.; Shaffer, Jill A.
2005-01-01
The structure of vegetation in grassland systems, unlike that in forest systems, varies dramatically among years on the same sites, and among regions with similar vegetation. The role of this variation in vegetation structure on bird density and nesting success of grassland birds is poorly understood, primarily because few studies have included sufficiently large temporal and spatial scales to capture the variation in vegetation structure, bird density, or nesting success. To date, no large-scale study on grassland birds has been conducted to investigate whether grassland bird density and nesting success respond similarly to changes in vegetation structure. However, reliable management recommendations require investigations into the distribution and nesting success of grassland birds over larger temporal and spatial scales. In addition, studies need to examine whether bird density and nesting success respond similarly to changing environmental conditions. We investigated the effect of vegetation structure on the density and nesting success of 3 grassland-nesting birds: clay-colored sparrow (Spizella pallida), Savannah sparrow (Passerculus sandwichensis), and bobolink (Dolichonyx oryzivorus) in 3 regions of the northern tallgrass prairie in 1998-2001. Few vegetation features influenced the densities of our study species, and each species responded differently to those vegetation variables. We could identify only 1 variable that clearly influenced nesting success of 1 species: clay-colored sparrow nesting success increased with increasing percentage of nest cover from the surrounding vegetation. Because responses of avian density and nesting success to vegetation measures varied among regions, years, and species, land managers at all times need to provide grasslands with different types of vegetation structure. Management guidelines developed from small-scale, short-term studies may lead to misrepresentations of the needs of grassland-nesting birds.
Predicting Changes in Arctic Tundra Vegetation: Towards an Understanding of Plant Trait Uncertainty
NASA Astrophysics Data System (ADS)
Euskirchen, E. S.; Serbin, S.; Carman, T.; Iversen, C. M.; Salmon, V.; Helene, G.; McGuire, A. D.
2017-12-01
Arctic tundra plant communities are currently undergoing unprecedented changes in both composition and distribution under a warming climate. Predicting how these dynamics may play out in the future is important since these vegetation shifts impact both biogeochemical and biogeophysical processes. More precise estimates of these future vegetation shifts is a key challenge due to both a scarcity of data with which to parameterize vegetation models, particularly in the Arctic, as well as a limited understanding of the importance of each of the model parameters and how they may vary over space and time. Here, we incorporate newly available field data from arctic Alaska into a dynamic vegetation model specifically developed to take into account a particularly wide array of plant species as well as the permafrost soils of the arctic tundra (the Terrestrial Ecosystem Model with Dynamic Vegetation and Dynamic Organic Soil, Terrestrial Ecosystem Model; DVM-DOS-TEM). We integrate the model within the Predicative Ecosystem Analyzer (PEcAn), an open-source integrated ecological bioinformatics toolbox that facilitates the flows of information into and out of process models and model-data integration. We use PEcAn to evaluate the plant functional traits that contribute most to model variability based on a sensitivity analysis. We perform this analysis for the dominant types of tundra in arctic Alaska, including heath, shrub, tussock and wet sedge tundra. The results from this analysis will help inform future data collection in arctic tundra and reduce model uncertainty, thereby improving our ability to simulate Arctic vegetation structure and function in response to global change.
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.
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.
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.
A Model-Data Fusion Approach for Constraining Modeled GPP at Global Scales Using GOME2 SIF Data
NASA Astrophysics Data System (ADS)
MacBean, N.; Maignan, F.; Lewis, P.; Guanter, L.; Koehler, P.; Bacour, C.; Peylin, P.; Gomez-Dans, J.; Disney, M.; Chevallier, F.
2015-12-01
Predicting the fate of the ecosystem carbon, C, stocks and their sensitivity to climate change relies heavily on our ability to accurately model the gross carbon fluxes, i.e. photosynthesis and respiration. However, there are large differences in the Gross Primary Productivity (GPP) simulated by different land surface models (LSMs), not only in terms of mean value, but also in terms of phase and amplitude when compared to independent data-based estimates. This strongly limits our ability to provide accurate predictions of carbon-climate feedbacks. One possible source of this uncertainty is from inaccurate parameter values resulting from incomplete model calibration. Solar Induced Fluorescence (SIF) has been shown to have a linear relationship with GPP at the typical spatio-temporal scales used in LSMs (Guanter et al., 2011). New satellite-derived SIF datasets have the potential to constrain LSM parameters related to C uptake at global scales due to their coverage. Here we use SIF data derived from the GOME2 instrument (Köhler et al., 2014) to optimize parameters related to photosynthesis and leaf phenology of the ORCHIDEE LSM, as well as the linear relationship between SIF and GPP. We use a multi-site approach that combines many model grid cells covering a wide spatial distribution within the same optimization (e.g. Kuppel et al., 2014). The parameters are constrained per Plant Functional type as the linear relationship described above varies depending on vegetation structural properties. The relative skill of the optimization is compared to a case where only satellite-derived vegetation index data are used to constrain the model, and to a case where both data streams are used. We evaluate the results using an independent data-driven estimate derived from FLUXNET data (Jung et al., 2011) and with a new atmospheric tracer, Carbonyl sulphide (OCS) following the approach of Launois et al. (ACPD, in review). We show that the optimization reduces the strong positive bias of the ORCHIDEE model and increases the correlation compared to independent estimates. Differences in spatial patterns and gradients between simulated GPP and observed SIF remain largely unchanged however, suggesting that the underlying representation of vegetation type and/or structure and functioning in the model requires further investigation.
Estimation of Physical Parameters of a Multilayered Multi-Scale Vegetated Surface
NASA Astrophysics Data System (ADS)
Hosni, I.; Bennaceur Farah, L.; Naceur, M. S.; Farah, I. R.
2016-06-01
Soil moisture is important to enable the growth of vegetation in the way that it also conditions the development of plant population. Additionally, its assessment is important in hydrology and agronomy, and is a warning parameter for desertification. Furthermore, the soil moisture content affects exchanges with the atmosphere via the energy balance at the soil surface; it is significant due to its impact on soil evaporation and transpiration. Therefore, it conditions the energy transfer between Earth and atmosphere. Many remote sensing methods were tested. For the soil moisture; the first methods relied on the optical domain (short wavelengths). Obviously, due to atmospheric effects and the presence of clouds and vegetation cover, this approach is doomed to fail in most cases. Therefore, the presence of vegetation canopy complicates the retrieval of soil moisture because the canopy contains moisture of its own. This paper presents a synergistic methodology of SAR and optical remote sensing data, and it's for simulation of statistical parameters of soil from C-band radar measurements. Vegetation coverage, which can be easily estimated from optical data, was combined in the backscattering model. The total backscattering was divided into the amount attributed to areas covered with vegetation and that attributed to areas of bare soil. Backscattering coefficients were simulated using the established backscattering model. A two-dimensional multiscale SPM model has been employed to investigate the problem of electromagnetic scattering from an underlying soil. The water cloud model (WCM) is used to account for the effect of vegetation water content on radar backscatter data, whereof to eliminate the impact of vegetation layer and isolate the contributions of vegetation scattering and absorption from the total backscattering coefficient.
Spatial patterns in the effects of fire on savanna vegetation three-dimensional structure.
Levick, Shaun R; Asner, Gregory P; Smit, Izak P J
2012-12-01
Spatial variability in the effects of fire on savanna vegetation structure is seldom considered in ecology, despite the inherent heterogeneity of savanna landscapes. Much has been learned about the effects of fire on vegetation structure from long-term field experiments, but these are often of limited spatial extent and do not encompass different hillslope catena elements. We mapped vegetation three-dimensional (3-D) structure over 21 000 ha in nine savanna landscapes (six on granite, three on basalt), each with contrasting long-term fire histories (higher and lower fire frequency), as defined from a combination of satellite imagery and 67 years of management records. Higher fire frequency areas contained less woody canopy cover than their lower fire frequency counterparts in all landscapes, and woody cover reduction increased linearly with increasing difference in fire frequency (r2 = 0.58, P = 0.004). Vegetation height displayed a more heterogeneous response to difference in fire frequency, with taller canopies present in the higher fire frequency areas of the wetter sites. Vegetation 3-D structural differences between areas of higher and lower fire frequency differed between geological substrates and varied spatially across hillslopes. Fire had the greatest relative impact on vegetation structure on nutrient-rich basalt substrates, and it imparted different structural responses upon vegetation in upland, midslope, and lowland topographic positions. These results highlight the complexity of fire vegetation relationships in savanna systems, and they suggest that underlying landscape heterogeneity needs more explicit incorporation into fire management policies.
NASA Astrophysics Data System (ADS)
Owers, Christopher J.; Rogers, Kerrylee; Woodroffe, Colin D.
2018-05-01
Above-ground biomass represents a small yet significant contributor to carbon storage in coastal wetlands. Despite this, above-ground biomass is often poorly quantified, particularly in areas where vegetation structure is complex. Traditional methods for providing accurate estimates involve harvesting vegetation to develop mangrove allometric equations and quantify saltmarsh biomass in quadrats. However broad scale application of these methods may not capture structural variability in vegetation resulting in a loss of detail and estimates with considerable uncertainty. Terrestrial laser scanning (TLS) collects high resolution three-dimensional point clouds capable of providing detailed structural morphology of vegetation. This study demonstrates that TLS is a suitable non-destructive method for estimating biomass of structurally complex coastal wetland vegetation. We compare volumetric models, 3-D surface reconstruction and rasterised volume, and point cloud elevation histogram modelling techniques to estimate biomass. Our results show that current volumetric modelling approaches for estimating TLS-derived biomass are comparable to traditional mangrove allometrics and saltmarsh harvesting. However, volumetric modelling approaches oversimplify vegetation structure by under-utilising the large amount of structural information provided by the point cloud. The point cloud elevation histogram model presented in this study, as an alternative to volumetric modelling, utilises all of the information within the point cloud, as opposed to sub-sampling based on specific criteria. This method is simple but highly effective for both mangrove (r2 = 0.95) and saltmarsh (r2 > 0.92) vegetation. Our results provide evidence that application of TLS in coastal wetlands is an effective non-destructive method to accurately quantify biomass for structurally complex vegetation.
NASA Astrophysics Data System (ADS)
Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.
2017-12-01
Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land-atmosphere feedback strengths.
Climate is a key driver regulating vegetation structure across rural ecosystems. In urban ecosystems, multiple interactions between humans and the environment can have homogenizing influences, confounding the relationship between vegetation structure and climate. In fact, vegetat...
NASA Astrophysics Data System (ADS)
Gebrehiwot, Mesfin; Kifle, Demeke; Triest, Ludwig
2017-12-01
Understanding the biodiversity value of littoral zones of lakes is a priority for aquatic biodiversity conservation. However, less emphasis has been given to the littoral part of tropical African lakes, with many of the previous researches focusing only on the open water side. The aim of the present study was, therefore, to investigate the impact of the littoral zone of a shallow freshwater tropical lake (Ziway, Ethiopia), dominated by two emergent macrophytes, on zooplankton community structure. We hypothesized that the wetland vegetation serves as a preferred microhabitat for zooplankton communities. A lake with substantial coverage of emergent macrophytes was monitored monthly from January to August, 2016. The monitoring included the measurements of physical, chemical, and biological parameters. Sampling sites were selected to represent areas of the macrophyte vegetation ( Typha latifolia and Phragmites australis) and the open water part of the lake. Sites with macrophyte vegetation were found to be the home of more dense and diverse zooplankton community. However, during the period of high vegetation loss, the density of crustacean zooplankton showed significant reduction within the patches of macrophytes. From biodiversity conservation perspective, it was concluded that the preservation of such small areas of macrophytes covering the littoral zone of lakes could be as important as protecting the whole lake. However, the rapid degradation of wetland vegetation by human activities is a real threat to the lake ecosystem. In the not-too-far future, it could displace and evict riparian vegetation and the biota it supports.
NASA Technical Reports Server (NTRS)
Kimes, D. S.
1979-01-01
The effects of vegetation canopy structure on thermal infrared sensor response must be understood before vegetation surface temperatures of canopies with low percent ground cover can be accurately inferred. The response of a sensor is a function of vegetation geometric structure, the vertical surface temperature distribution of the canopy components, and sensor view angle. Large deviations between the nadir sensor effective radiant temperature (ERT) and vegetation ERT for a soybean canopy were observed throughout the growing season. The nadir sensor ERT of a soybean canopy with 35 percent ground cover deviated from the vegetation ERT by as much as 11 C during the mid-day. These deviations were quantitatively explained as a function of canopy structure and soil temperature. Remote sensing techniques which determine the vegetation canopy temperature(s) from the sensor response need to be studied.
NASA Astrophysics Data System (ADS)
Ceballos-Núñez, Verónika; Richardson, Andrew; Sierra, Carlos
2017-04-01
The global carbon cycle is strongly controlled by the source/sink strength of vegetation as well as the capacity of terrestrial ecosystems to retain this carbon. However, it is uncertain how some vegetation dynamics such as the allocation of carbon to different ecosystem compartments should be represented in models. The assumptions behind model structures may result in highly divergent model predictions. Here, we asses model performance by calculating the age of the carbon in the system and in each compartment, and the overall transit time of C in the system. We used these diagnostics to assess the influence of three different carbon allocation schemes on the rates of C cycling in vegetation. First, we used published measurements of ecosystem C compartments from the Harvard Forest Environmental Measurement Site to find the best set of parameters for the different model structures. Second, we calculated C stocks, respiration fluxes, radiocarbon values, ages, and transit times. We found a good fit of the three model structures to the available data, but the time series of C in foliage and wood need to be complemented with other ecosystem compartments in order to reduce the high parameter collinearity that we observed and reduce model equifinality. Differences in model structures had a small impact on predicting ecosystem C compartments, but overall they resulted in very different predictions of age and transit time distributions. In particular, the inclusion of a storage compartment had an important impact on predicting system ages and transit times. In the case of the models with 1 or 2 storage compartments, the age of carbon in the system and in each of the compartments was distributed more towards younger ages than in the model that had no storage; the mean system age of these two models with storage was 80 years younger than in the model without storage. As expected from these age distributions, the mean transit time for the two models with storage compartments was 50 years faster than for the model without storage. These results suggest that ages and transit times, which can be indirectly measured using isotope tracers, serve as important diagnostics of model structure and could largely help to reduce uncertainties in model predictions. Furthermore, by considering age and transit times of C in vegetation compartments as distributions, not only their mean values, we obtain additional insights on the temporal dynamics of carbon use, storage, and allocation to plant parts, which not only depends on the rate at which this C is transferred in and out of the compartments, but also on the stochastic nature of the process itself.
Automatic summary generating technology of vegetable traceability for information sharing
NASA Astrophysics Data System (ADS)
Zhenxuan, Zhang; Minjing, Peng
2017-06-01
In order to solve problems of excessive data entries and consequent high costs for data collection in vegetable traceablility for farmers in traceability applications, the automatic summary generating technology of vegetable traceability for information sharing was proposed. The proposed technology is an effective way for farmers to share real-time vegetable planting information in social networking platforms to enhance their brands and obtain more customers. In this research, the influencing factors in the vegetable traceablility for customers were analyzed to establish the sub-indicators and target indicators and propose a computing model based on the collected parameter values of the planted vegetables and standard legal systems on food safety. The proposed standard parameter model involves five steps: accessing database, establishing target indicators, establishing sub-indicators, establishing standard reference model and computing scores of indicators. On the basis of establishing and optimizing the standards of food safety and traceability system, this proposed technology could be accepted by more and more farmers and customers.
NASA Astrophysics Data System (ADS)
Mazur, Robert; Kałuża, Tomasz; Chmist, Joanna; Walczak, Natalia; Laks, Ireneusz; Strzeliński, Paweł
2016-08-01
This paper presents problems caused by organic material transported by flowing water. This material is usually referred to as plant debris or organic debris. Its composition depends on the characteristic of the watercourse. For lowland rivers, the share of the so-called small organic matter in plant debris is considerable. This includes both various parts of water plants and floodplain vegetation (leaves, stems, blades of grass, twigs, etc.). During floods, larger woody debris poses a significant risk to bridges or other water engineering structures. It may cause river jams and may lead to damming of the flowing water. This, in turn, affects flood safety and increases flood risk in river valleys, both directly and indirectly. The importance of fine plant debris for the phenomenon being studied comes down to the hydrodynamic aspect (plant elements carried by water end up on trees and shrubs, increase hydraulic flow resistance and contribute to the nature of flow through vegetated areas changed from micro-to macro-structural). The key part of the research problem under analysis was to determine qualitative and quantitative debris parameters and to establish the relationship between the type of debris and the type of land use of river valleys (crop fields, meadows and forested river sections). Another problem was to identify parameters of plant debris for various flow conditions (e.g. for low, medium and flood flows). The research also included an analysis of the materials deposited on the structure of shrubs under flood flow conditions during the 2010 flood on the Warta River.
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.
Determining the K coefficient to leaf area index estimations in a tropical dry forest
NASA Astrophysics Data System (ADS)
Magalhães, Sarah Freitas; Calvo-Rodriguez, Sofia; do Espírito Santo, Mário Marcos; Sánchez Azofeifa, Gerardo Arturo
2018-03-01
Vegetation indices are useful tools to remotely estimate several important parameters related to ecosystem functioning. However, improving and validating estimations for a wide range of vegetation types are necessary. In this study, we provide a methodology for the estimation of the leaf area index (LAI) in a tropical dry forest (TDF) using the light diffusion through the canopy as a function of the successional stage. For this purpose, we estimated the K coefficient, a parameter that relates the normalized difference vegetation index (NDVI) to LAI, based on photosynthetically active radiation (PAR) and solar radiation. The study was conducted in the Mata Seca State Park, in southeastern Brazil, from 2012 to 2013. We defined four successional stages (very early, early, intermediate, and late) and established one optical phenology tower at one plot of 20 × 20 m per stage. Towers measured the incoming and reflected solar radiation and PAR for NDVI calculation. For each plot, we established 24 points for LAI sampling through hemispherical photographs. Because leaf cover is highly seasonal in TDFs, we determined ΔK (leaf growth phase) and K max (leaf maturity phase). We detected a strong correlation between NDVI and LAI, which is necessary for a reliable determination of the K coefficient. Both NDVI and LAI varied significantly between successional stages, indicating sensitivity to structural changes in forest regeneration. Furthermore, the K values differed between successional stages and correlated significantly with other environmental variables such as air temperature and humidity, fraction of absorbed PAR, and soil moisture. Thus, we established a model based on spectral properties of the vegetation coupled with biophysical characteristics in a TDF that makes possible to estimate LAI from NDVI values. The application of the K coefficient can improve remote estimations of forest primary productivity and gases and energy exchanges between vegetation and atmosphere. This model can be applied to distinguish different successional stages of TDFs, supporting environmental monitoring and conservation policies towards this biome.
NASA Astrophysics Data System (ADS)
Ireland, Gareth; Petropoulos, George P.; Carlson, Toby N.; Purdy, Sarah
2015-04-01
Sensitivity analysis (SA) consists of an integral and important validatory check of a computer simulation model before it is used to perform any kind of analysis. In the present work, we present the results from a SA performed on the SimSphere Soil Vegetation Atmosphere Transfer (SVAT) model utilising a cutting edge and robust Global Sensitivity Analysis (GSA) approach, based on the use of the Gaussian Emulation Machine for Sensitivity Analysis (GEM-SA) tool. The sensitivity of the following model outputs was evaluated: the ambient CO2 concentration and the rate of CO2 uptake by the plant, the ambient O3 concentration, the flux of O3 from the air to the plant/soil boundary, and the flux of O3 taken up by the plant alone. The most sensitive model inputs for the majority of model outputs were related to the structural properties of vegetation, namely, the Leaf Area Index, Fractional Vegetation Cover, Cuticle Resistance and Vegetation Height. External CO2 in the leaf and the O3 concentration in the air input parameters also exhibited significant influence on model outputs. This work presents a very important step towards an all-inclusive evaluation of SimSphere. Indeed, results from this study contribute decisively towards establishing its capability as a useful teaching and research tool in modelling Earth's land surface interactions. This is of considerable importance in the light of the rapidly expanding use of this model worldwide, which also includes research conducted by various Space Agencies examining its synergistic use with Earth Observation data towards the development of operational products at a global scale. This research was supported by the European Commission Marie Curie Re-Integration Grant "TRANSFORM-EO". SimSphere is currently maintained and freely distributed by the Department of Geography and Earth Sciences at Aberystwyth University (http://www.aber.ac.uk/simsphere). Keywords: CO2 flux, ambient CO2, O3 flux, SimSphere, Gaussian process emulators, BACCO GEM-SA, TRANSFORM-EO.
[Crop geometry identification based on inversion of semiempirical BRDF models].
Huang, Wen-jiang; Wang, Jin-di; Mu, Xi-han; Wang, Ji-hua; Liu, Liang-yun; Liu, Qiang; Niu, Zheng
2007-10-01
Investigations have been made on identification of erective and horizontal varieties by bidirectional canopy reflected spectrum and semi-empirical bidirectional reflectance distribution function (BRDF) models. The qualitative effect of leaf area index (LAI) and average leaf angle (ALA) on crop canopy reflected spectrum was studied. The structure parameter sensitive index (SPEI) based on the weight for the volumetric kernel (fvol), the weight for the geometric kernel (fgeo), and the weight for constant corresponding to isotropic reflectance (fiso), was defined in the present study for crop geometry identification. However, the weights associated with the kernels of semi-empirical BRDF model do not have a direct relationship with measurable biophysical parameters. Therefore, efforts have focused on trying to find the relation between these semi-empirical BRDF kernel weights and various vegetation structures. SPEI was proved to be more sensitive to identify crop geometry structures than structural scattering index (SSI) and normalized difference f-index (NDFI), SPEI could be used to distinguish erective and horizontal geometry varieties. So, it is feasible to identify horizontal and erective varieties of wheat by bidirectional canopy reflected spectrum.
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.
Wang, Shu; Robertson, Megan L
2015-06-10
Vegetable oils and their fatty acids are promising sources for the derivation of polymers. Long-chain poly(n-alkyl acrylates) and poly(n-alkyl methacrylates) are readily derived from fatty acids through conversion of the carboxylic acid end-group to an acrylate or methacrylate group. The resulting polymers contain long alkyl side-chains with around 10-22 carbon atoms. Regardless of the monomer source, the presence of alkyl side-chains in poly(n-alkyl acrylates) and poly(n-alkyl methacrylates) provides a convenient mechanism for tuning their physical properties. The development of structured multicomponent materials, including block copolymers and blends, containing poly(n-alkyl acrylates) and poly(n-alkyl methacrylates) requires knowledge of the thermodynamic interactions governing their self-assembly, typically described by the Flory-Huggins interaction parameter χ. We have investigated the χ parameter between polystyrene and long-chain poly(n-alkyl acrylate) homopolymers and copolymers: specifically we have included poly(stearyl acrylate), poly(lauryl acrylate), and their random copolymers. Lauryl and stearyl acrylate were chosen as model alkyl acrylates derived from vegetable oils and have alkyl side-chain lengths of 12 and 18 carbon atoms, respectively. Polystyrene is included in this study as a model petroleum-sourced polymer, which has wide applicability in commercially relevant multicomponent polymeric materials. Two independent methods were employed to measure the χ parameter: cloud point measurements on binary blends and characterization of the order-disorder transition of triblock copolymers, which were in relatively good agreement with one another. The χ parameter was found to be independent of the alkyl side-chain length (n) for large values of n (i.e., n > 10). This behavior is in stark contrast to the n-dependence of the χ parameter predicted from solubility parameter theory. Our study complements prior work investigating the interactions between polystyrene and short-chain polyacrylates (n ≤ 10). To our knowledge, this is the first study to explore the thermodynamic interactions between polystyrene and long-chain poly(n-alkyl acrylates) with n > 10. This work lays the groundwork for the development of multicomponent structured systems (i.e., blends and copolymers) in this class of sustainable materials.
Forage quantity estimation from MERIS using band depth parameters
NASA Astrophysics Data System (ADS)
Ullah, Saleem; Yali, Si; Schlerf, Martin
Saleem Ullah1 , Si Yali1 , Martin Schlerf1 Forage quantity is an important factor influencing feeding pattern and distribution of wildlife. The main objective of this study was to evaluate the predictive performance of vegetation indices and band depth analysis parameters for estimation of green biomass using MERIS data. Green biomass was best predicted by NBDI (normalized band depth index) and yielded a calibration R2 of 0.73 and an accuracy (independent validation dataset, n=30) of 136.2 g/m2 (47 % of the measured mean) compared to a much lower accuracy obtained by soil adjusted vegetation index SAVI (444.6 g/m2, 154 % of the mean) and by other vegetation indices. This study will contribute to map and monitor foliar biomass over the year at regional scale which intern can aid the understanding of bird migration pattern. Keywords: Biomass, Nitrogen density, Nitrogen concentration, Vegetation indices, Band depth analysis parameters 1 Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands
A structural classification for inland northwest forest vegetation.
Kevin L. O' Hara; Penelope A. Latham; Paul Hessburg; Bradley G. Smith
1996-01-01
Existing approaches to vegetation classification range from those bassed on potential vegetation to others based on existing vegetation composition, or existing structural or physiognomic characteristics. Examples of these classifications are numerous, and in some cases, date back hundreds of years (Mueller-Dumbois and Ellenberg 1974). Small-scale or stand level...
NASA Astrophysics Data System (ADS)
Dupuy, Stéphane; Lainé, Gérard; Tassin, Jacques; Sarrailh, Jean-Michel
2013-12-01
This article's goal is to explore the benefits of using Digital Surface Model (DSM) and Digital Terrain Model (DTM) derived from LiDAR acquisitions for characterizing the horizontal structure of different facies in forested areas (primary forests vs. secondary forests) within the framework of an object-oriented classification. The area under study is the island of Mayotte in the western Indian Ocean. The LiDAR data were the data originally acquired by an airborne small-footprint discrete-return LiDAR for the "Litto3D" coastline mapping project. They were used to create a Digital Elevation Model (DEM) at a spatial resolution of 1 m and a Digital Canopy Model (DCM) using median filtering. The use of two successive segmentations at different scales allowed us to adjust the segmentation parameters to the local structure of the landscape and of the cover. Working in object-oriented mode with LiDAR allowed us to discriminate six vegetation classes based on canopy height and horizontal heterogeneity. This heterogeneity was assessed using a texture index calculated from the height-transition co-occurrence matrix. Overall accuracy exceeds 90%. The resulting product is the first vegetation map of Mayotte which emphasizes the structure over the composition.
NASA Astrophysics Data System (ADS)
Liu, W.; Ning, T.; Shen, H.; Li, Z.
2017-12-01
Vegetation, climate seasonality and topography are the main impact factors controlling the water and heat balance over a catchment, and they are usually empirically formulated into the controlling parameter in Budyko model. However, their interactions on different time scales have not been fully addressed. Taking 30 catchments in China's Loess Plateau as an example, on annual scale, vegetation coverage was found poorly correlated with climate seasonality index; therefore, they could be both parameterized into the Budyko model. On the long-term scale, vegetation coverage tended to have close relationships with topographic conditions and climate seasonality, which was confirmed by the multi-collinearity problems; in that sense, vegetation information could fit the controlling parameter exclusively. Identifying the dominant controlling factors over different time scales, this study simplified the empirical parameterization of the Budyko formula. Though the above relationships further investigation over the other regions/catchments.
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.
NASA Astrophysics Data System (ADS)
Tsalyuk, M.; Kelly, M.; Getz, W.
2012-12-01
Rangeland ecosystems cover more than fifty percent of earth's land surface, host considerable biodiversity and provide vital ecosystem services. However, rangelands around the world face degradation due to climate change, land use change and overgrazing. Human-driven changes to fire and grazing regimes enhance degradation processes. The purpose of this research is to develop a remote sensing methodology to characterize the structure and composition of savanna vegetation, in order to improve the ability of conservation managers to monitor and address such degradation processes. Our study site, Etosha National Park, is a 22,270 km^2 semi-arid savanna located in north-central Namibia. Fencing and provision of artificial water sources for wildlife have changed the natural grazing patterns, which has caused bush encroachment and vegetation degradation across the park. We used MODIS and Landsat ETM+ 7 satellite imagery to map the vegetation type, dominant species, density, cover and biomass of herbaceous and woody vegetation in Etosha. We used imagery for 2007-2012 together with extensive field sampling, both in the wet and the dry seasons. At each sampling point, we identified the dominant species and measured the density, canopy size, height and diameter of the trees and shrubs. At only 31% of the sampling points, the identified vegetation type matched the class assigned at the 1996 classification. This may indicate significant habitat modifications in Etosha. We used two parallel analytical approaches to correlate between radiometric and field data. First, we show that traditional supervised classification identifies well five classes: bare soil, grassland, steppe, shrub savanna and tree savanna. We then refined this classification to enable us to identify the species composition in an area utilizing the phenological differences in timing and duration of greenness of the dominant tree and shrub species in Etosha. Specifically, using multi-date images we were able to identify additional six sub-classes based on the dominant species in each class: Colophospermum mopane woodland, Colophospermum mopane shrubland, Cataphractes alexandri woodland, Acacia nebrownii shrubland, mixed Combretum species woodland and Terminalia prunioides woodland. Second, we used quantitative methods to relate satellite-based vegetation indices to the biometric properties measured on the ground. We found a correlation among measured height, diameter and canopy cover of woody vegetation and used this to improve the correlation between cover and Normalized Difference Vegetation Index (NDVI). We showed that the Soil Adjusted Total Vegetation Index (SATVI) and Normalized Difference Water Index (NDWI) were related to both greenness and density at a site. In order to measure grass biomass in the field, we calibrated Disc Pasture Mater by clipping, weighing and drying grass in 1m^2 plots, in the dry and wet seasons, with resulting R^2 of 0.87 and 0.83, respectively. MODIS-derived leaf area index (LAI) data was best correlated with dry grass biomass. We used these correlations to produce detailed maps of each vegetation parameter for the whole park. These maps will provide a baseline to employ historical imagery to better understand the effects of the park's management and changing grazing pressure on vegetation structure.
Retrieval of wheat growth parameters with radar vegetation indices
USDA-ARS?s Scientific Manuscript database
The Radar Vegetation Index (RVI) has a low sensitivity to changes in environmental conditions and has the potential as a tool to monitor the vegetation growth. In this study, we expand on previous research by investigating the radar response over a wheat canopy. RVI was computed using observations m...
Wagener, Thorsten; McGlynn, Brian
2015-01-01
Abstract Ungauged headwater basins are an abundant part of the river network, but dominant influences on headwater hydrologic response remain difficult to predict. To address this gap, we investigated the ability of a physically based watershed model (the Distributed Hydrology‐Soil‐Vegetation Model) to represent controls on metrics of hydrologic partitioning across five adjacent headwater subcatchments. The five study subcatchments, located in Tenderfoot Creek Experimental Forest in central Montana, have similar climate but variable topography and vegetation distribution. This facilitated a comparative hydrology approach to interpret how parameters that influence partitioning, detected via global sensitivity analysis, differ across catchments. Model parameters were constrained a priori using existing regional information and expert knowledge. Influential parameters were compared to perceptions of catchment functioning and its variability across subcatchments. Despite between‐catchment differences in topography and vegetation, hydrologic partitioning across all metrics and all subcatchments was sensitive to a similar subset of snow, vegetation, and soil parameters. Results also highlighted one subcatchment with low certainty in parameter sensitivity, indicating that the model poorly represented some complexities in this subcatchment likely because an important process is missing or poorly characterized in the mechanistic model. For use in other basins, this method can assess parameter sensitivities as a function of the specific ungauged system to which it is applied. Overall, this approach can be employed to identify dominant modeled controls on catchment response and their agreement with system understanding. PMID:27642197
Carter, Virginia; Ruhl, H.; Rybicki, N.B.; Reel, J.T.; Gammon, P.T.
1999-01-01
The U.S. Geological Survey is one of many agencies participating in the effort to restore the south Florida Everglades. We are sampling and characterizing the vegetation at selected sites in the Everglades as part of a study to quantify vegetative flow resistance. The objectives of the vegetative sampling are (1) to provide detailed information on species composition, vegetative characteristics, vegetative structure, and biomass for quantification of vegetative resistance to flow, and (2) to use this information to classify the vegetation and to improve existing vegetation maps for use with numerical models of surface-water flow. Vegetative sampling was conducted in the Shark River Slough in April, 1996. The data collected and presented here include live, dead, and periphyton biomass, vegetation characteristics and structure, and leaf area index.
NASA Astrophysics Data System (ADS)
Marselis, S.; Tang, H.; Blair, J. B.; Hofton, M. A.; Armston, J.; Dubayah, R.
2017-12-01
Terrestrial ecotones, transition zones between ecological systems, have been identified as important regions to monitor the effects of environmental and human pressures on ecosystems. To observe such changes, the variability in vegetation horizontal and vertical structure must be characterized. The objective of this study is to quantify changes in vegetation structure in a tropical forest-savanna mosaic using airborne waveform lidar data. The study area is located in the northern part of the Lopé National Park in Gabon and is comprised of the vegetation types: savanna, colonizing forest, monodominant Okoumé forest, young Marantaceae forest and mixed Marantaceae forest. The lidar data were collected by the Land Vegetation and Ice Sensor (LVIS) in early March 2016, during the AfriSAR campaign. Metrics derived from the LVIS waveforms were then used to classify the five main vegetation types and characterize observed structural variability within types and across ecotones. Several supervised and unsupervised classification alogrithms, in combination with statistical analysis, were applied. The investigated methods are promising in their use to directly describe the structural variability within and between different vegetation types, map these vegetation types and the extent and location of their transition zones, and to characterize, among other attributes, the sharpness and width of such ecotones. These results provide important information in ecosystem studies as these methods can be used to study changes in vegetation structure, species-specific habitat, or the effects of deforestation and other human and natural pressures on the exterior and interior forest structure. These methods thus provide ample opportunity to assess the vegetation structure in degraded and second growth tropical forests to explore effects of e.g. grazing, logging or fragmentation. From this study we can conclude that lidar waveform remote sensing is highly useful in distinguishing vegetation types and their transition zones which will be increasingly important when assessing the impact of natural and human pressures on the world's tropical forests.
NASA Astrophysics Data System (ADS)
Wells, J. R.; Kim, J. B.
2011-12-01
Parameters in dynamic global vegetation models (DGVMs) are thought to be weakly constrained and can be a significant source of errors and uncertainties. DGVMs use between 5 and 26 plant functional types (PFTs) to represent the average plant life form in each simulated plot, and each PFT typically has a dozen or more parameters that define the way it uses resource and responds to the simulated growing environment. Sensitivity analysis explores how varying parameters affects the output, but does not do a full exploration of the parameter solution space. The solution space for DGVM parameter values are thought to be complex and non-linear; and multiple sets of acceptable parameters may exist. In published studies, PFT parameters are estimated from published literature, and often a parameter value is estimated from a single published value. Further, the parameters are "tuned" using somewhat arbitrary, "trial-and-error" methods. BIOMAP is a new DGVM created by fusing MAPSS biogeography model with Biome-BGC. It represents the vegetation of North America using 26 PFTs. We are using simulated annealing, a global search method, to systematically and objectively explore the solution space for the BIOMAP PFTs and system parameters important for plant water use. We defined the boundaries of the solution space by obtaining maximum and minimum values from published literature, and where those were not available, using +/-20% of current values. We used stratified random sampling to select a set of grid cells representing the vegetation of the conterminous USA. Simulated annealing algorithm is applied to the parameters for spin-up and a transient run during the historical period 1961-1990. A set of parameter values is considered acceptable if the associated simulation run produces a modern potential vegetation distribution map that is as accurate as one produced by trial-and-error calibration. We expect to confirm that the solution space is non-linear and complex, and that multiple acceptable parameter sets exist. Further we expect to demonstrate that the multiple parameter sets produce significantly divergent future forecasts in NEP, C storage, and ET and runoff; and thereby identify a highly important source of DGVM uncertainty
Aboveground Biomass and Dynamics of Forest Attributes using LiDAR Data and Vegetation Model
NASA Astrophysics Data System (ADS)
V V L, P. A.
2015-12-01
In recent years, biomass estimation for tropical forests has received much attention because of the fact that regional biomass is considered to be a critical input to climate change. Biomass almost determines the potential carbon emission that could be released to the atmosphere due to deforestation or conservation to non-forest land use. Thus, accurate biomass estimation is necessary for better understating of deforestation impacts on global warming and environmental degradation. In this context, forest stand height inclusion in biomass estimation plays a major role in reducing the uncertainty in the estimation of biomass. The improvement in the accuracy in biomass shall also help in meeting the MRV objectives of REDD+. Along with the precise estimate of biomass, it is also important to emphasize the role of vegetation models that will most likely become an important tool for assessing the effects of climate change on potential vegetation dynamics and terrestrial carbon storage and for managing terrestrial ecosystem sustainability. Remote sensing is an efficient way to estimate forest parameters in large area, especially at regional scale where field data is limited. LIDAR (Light Detection And Ranging) provides accurate information on the vertical structure of forests. We estimated average tree canopy heights and AGB from GLAS waveform parameters by using a multi-regression linear model in forested area of Madhya Pradesh (area-3,08,245 km2), India. The derived heights from ICESat-GLAS were correlated with field measured tree canopy heights for 60 plots. Results have shown a significant correlation of R2= 74% for top canopy heights and R2= 57% for stand biomass. The total biomass estimation 320.17 Mt and canopy heights are generated by using random forest algorithm. These canopy heights and biomass maps were used in vegetation models to predict the changes biophysical/physiological characteristics of forest according to the changing climate. In our study we have used Dynamic Global Vegetation Model to understand the possible vegetation dynamics in the event of climate change. The vegetation represents a biogeographic regime. Simulations were carried out for 70 years time period. The model produced leaf area index and biomass for each plant functional type and biome for each grid in that region.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Martin, Mark A.
2002-04-16
Vegetation Management along the Rocky Reach – Maple Valley No. 1 Transmission Line ROW from structure 98/2 to structure 110/1. The transmission line is a 500 kV line. BPA proposes to clear targeted vegetation along access roads and around tower structures that may impede the operation and maintenance of the subject transmission line. BPA plans to conduct vegetation management along existing access road and around structure landings for the purpose of maintaining access to structures site. All work will be in accordance with the National Electrical Safety Code and BPA standards.
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.
NASA Astrophysics Data System (ADS)
Melillos, George; Themistocleous, Kyriacos; Hadjimitsis, Diofantos G.
2018-04-01
The purpose of this paper is to present the results obtained from unmanned aerial vehicle (UAV) using multispectral with thermal imaging sensors and field spectroscopy campaigns for detecting underground structures. Airborne thermal prospecting is based on the principle that there is a fundamental difference between the thermal characteristics of underground structures and the environment in which they are structure. This study aims to combine the flexibility and low cost of using an airborne drone with the accuracy of the registration of a thermal digital camera. This combination allows the use of thermal prospection for underground structures detection at low altitude with high-resolution information. In addition vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and Simple Ratio (SR), were utilized for the development of a vegetation index-based procedure aiming at the detection of underground military structures by using existing vegetation indices or other in-band algorithms. The measurements were taken at the following test areas such as: (a) vegetation area covered with the vegetation (barley), in the presence of an underground military structure (b) vegetation area covered with the vegetation (barley), in the absence of an underground military structure. It is important to highlight that this research is undertaken at the ERATOSTHENES Research Centre which received funding to be transformed to an EXcellence Research Centre for Earth SurveiLlance and Space-Based MonItoring Of the EnviRonment (Excelsior) from the HORIZON 2020 Widespread-04-2017: Teaming Phase 1(Grant agreement no: 763643).
Shenoy, Sonia F; Kazaks, Alexandra G; Holt, Roberta R; Chen, Hsin Ju; Winters, Barbara L; Khoo, Chor San; Poston, Walker S C; Haddock, C Keith; Reeves, Rebecca S; Foreyt, John P; Gershwin, M Eric; Keen, Carl L
2010-09-17
Recommendations for daily dietary vegetable intake were increased in the 2005 USDA Dietary Guidelines as consumption of a diet rich in vegetables has been associated with lower risk of certain chronic health disorders including cardiovascular disease. However, vegetable consumption in the United States has declined over the past decade; consequently, the gap between dietary recommendations and vegetable intake is widening. The primary aim of this study is to determine if drinking vegetable juice is a practical way to help meet daily dietary recommendations for vegetable intake consistent with the 2005 Dietary Guidelines and the Dietary Approaches to Stop Hypertension (DASH) diet. The secondary aim is to assess the effect of a vegetable juice on measures of cardiovascular health. We conducted a 12-week, randomized, controlled, parallel-arm study consisting of 3 groups of free-living, healthy volunteers who participated in study visits at the Ragle Human Nutrition Research Center at the University of California, Davis. All subjects received education on the DASH diet and 0, 8 or 16 fluid ounces of vegetable juice daily. Assessments were completed of daily vegetable servings before and after incorporation of vegetable juice and cardiovascular health parameters including blood pressure. Without the juice, vegetable intake in all groups was lower than the 2005 Dietary Guidelines and DASH diet recommendations. The consumption of the vegetable juice helped participants reach recommended intake. In general, parameters associated with cardiovascular health did not change over time. However, in the vegetable juice intervention groups, subjects who were pre-hypertensive at the start of the study showed a significant decrease in blood pressure during the 12-week intervention period. Including 1-2 cups of vegetable juice daily was an effective and acceptable way for healthy adults to close the dietary vegetable gap. Increase in daily vegetable intake was associated with a reduction in blood pressure in subjects who were pre-hypertensive at the start of the trial. Clinicaltrials.gov NCT01161706.
Ground-Vegetation Clutter Affects Phyllostomid Bat Assemblage Structure in Lowland Amazonian Forest.
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.
Definitions and codes for seral status and structure of vegetation.
Frederick C. Hall; Larry Bryant; Rod Clausnitzer; Kathy Geier-Hayes; Robert Keane; Jane Kertis; Ayn Shlisky; Robert Steel
1995-01-01
Definitions and codes for identifying vegetation seral status and structure are desired for land management planning, appraising wildlife habitat, and prescribing vegetation treatment. Codes are only presented; they are not a system for determining seral status or stand structure. Terms defined are climax, potential natural community (PNC), succession, seral status,...
Novel characterization of landscape-level variability in historical vegetation structure
Brandon M. Collins; Jamie M. Lydersen; Richard G. Everett; Danny L. Fry; Scott L. Stephens
2015-01-01
We analyzed historical timber inventory data collected systematically across a large mixed-conifer-dominated landscape to gain insight into the interaction between disturbances and vegetation structure and composition prior to 20th century land management practices. Using records from over 20 000 trees, we quantified historical vegetation structure and composition for...
Optimization test of the 2BSL-320 vegetable seeders with air-suction drum type
NASA Astrophysics Data System (ADS)
Tang, B.; Wang, Y. S.; Ji, S. Z.
2017-07-01
The seeding raising technology of the hole tray assembly line is an important part of modern agriculture. The 2BSL-320 vegetable seeders with air-suction drum type are implements that are used to fill nutritional soil and press a hole in a float tray to sow seeds precisely. It can complete the whole process of putting down the tray, bedding the soil, scraping the soil, pressing a hole, sowing the seeds, compacting the soil, watering and putting away the tray by one time. Based on the introduction of the structure and working principle of the implement’s critical components, in order to improve the seeding efficiency and the seeding accuracy of the seeders, the response surface tests and the group experiments were carried out in this paper. And the MATLAB tool box was used to conduct fitting and optimization analysis of the test results, also the rationality of the optimization results was validated by experiments, which had provided a theoretical basis for the design of operation parameters in the vegetable seeders and had improved the seeding efficiency and quality.
Ma, Y T; Wubs, A M; Mathieu, A; Heuvelink, E; Zhu, J Y; Hu, B G; Cournède, P H; de Reffye, P
2011-04-01
Many indeterminate plants can have wide fluctuations in the pattern of fruit-set and harvest. Fruit-set in these types of plants depends largely on the balance between source (assimilate supply) and sink strength (assimilate demand) within the plant. This study aims to evaluate the ability of functional-structural plant models to simulate different fruit-set patterns among Capsicum cultivars through source-sink relationships. A greenhouse experiment of six Capsicum cultivars characterized with different fruit weight and fruit-set was conducted. Fruit-set patterns and potential fruit sink strength were determined through measurement. Source and sink strength of other organs were determined via the GREENLAB model, with a description of plant organ weight and dimensions according to plant topological structure established from the measured data as inputs. Parameter optimization was determined using a generalized least squares method for the entire growth cycle. Fruit sink strength differed among cultivars. Vegetative sink strength was generally lower for large-fruited cultivars than for small-fruited ones. The larger the size of the fruit, the larger variation there was in fruit-set and fruit yield. Large-fruited cultivars need a higher source-sink ratio for fruit-set, which means higher demand for assimilates. Temporal heterogeneity of fruit-set affected both number and yield of fruit. The simulation study showed that reducing heterogeneity of fruit-set was obtained by different approaches: for example, increasing source strength; decreasing vegetative sink strength, source-sink ratio for fruit-set and flower appearance rate; and harvesting individual fruits earlier before full ripeness. Simulation results showed that, when we increased source strength or decreased vegetative sink strength, fruit-set and fruit weight increased. However, no significant differences were found between large-fruited and small-fruited groups of cultivars regarding the effects of source and vegetative sink strength on fruit-set and fruit weight. When the source-sink ratio at fruit-set decreased, the number of fruit retained on the plant increased competition for assimilates with vegetative organs. Therefore, total plant and vegetative dry weights decreased, especially for large-fruited cultivars. Optimization study showed that temporal heterogeneity of fruit-set and ripening was predicted to be reduced when fruits were harvested earlier. Furthermore, there was a 20 % increase in the number of extra fruit set.
NASA Astrophysics Data System (ADS)
Kumar, J.; Hargrove, W. W.; Norman, S. P.; Hoffman, F. M.
2017-12-01
Great Smoky Mountains National Park (GSMNP) in Tennessee is a biodiversity hotspot and home to a large number of plant, animal and bird species. Driven by gradients of climate (ex. temperature, precipitation regimes), topography (ex. elevation, slope, aspect), geology (ex. soil types, textures, depth), hydrology (ex. drainage, moisture availability) etc. GSMNP offers a diverse composition and distribution of vegetation which in turn supports an array of wildlife. Understanding the vegetation canopy structure is critical to understand, monitor and manage the complex forest ecosystems like the Great Smoky Mountain National Park (GSMNP). Vegetation canopies not only help understand the vegetation, but are also a critically important habitat characteristics of many threatened and endangered animal and bird species that GSMNP is home to. Using airborne Light Detection and Ranging (LiDAR) we characterize the three-dimensional structure of the vegetation. LiDAR based analysis gives detailed insight in the canopy structure (overstory and understory) and its spatial variability within and across forest types. Vegetation structure and spatial distribution show strong correlation with climate, topographic, and edaphic variables and our multivariate analysis not just mines rich and large LiDAR data but presents ecological insights and data for vegetation within the park that can be useful to forest managers in their management and conservation efforts.
Novel characterization of landscape-level variability in historical vegetation structure.
Collins, Brandon M; Lydersen, Jamie M; Everett, Richard G; Fry, Danny L; Stephens, Scott L
2015-07-01
We analyzed historical timber inventory data collected systematically across a large mixed-conifer-dominated landscape to gain insight into the interaction between disturbances and vegetation structure and composition prior to 20th century land management practices. Using records from over 20 000 trees, we quantified historical vegetation structure and composition for nine distinct vegetation groups. Our findings highlight some key aspects of forest structure under an intact disturbance regime: (1) forests were low density, with mean live basal area and tree density ranging from 8-30 m2 /ha and 25-79 trees/ha, respectively; (2) understory and overstory structure and composition varied considerably across the landscape; and (3) elevational gradients largely explained variability in forest structure over the landscape. Furthermore, the presence of large trees across most of the surveyed area suggests that extensive stand-replacing disturbances were rare in these forests. The vegetation structure and composition characteristics we quantified, along with evidence of largely elevational control on these characteristics, can provide guidance for restoration efforts in similar forests.
NASA Astrophysics Data System (ADS)
Rahman, Inayat Ur; Khan, Nasrullah; Ali, Kishwar
2017-04-01
An understory vegetation survey of the Pinus wallichiana-dominated temperate forests of Swat District was carried out to inspect the structure, composition and ecological associations of the forest vegetation. A quadrat method of sampling was used to record the floristic and phytosociological data necessary for the analysis using 300 quadrats of 10 × 10 m each. Some vegetation parameters viz. frequency and density for trees (overstory vegetation) as well as for the understory vegetation were recorded. The results revealed that in total, 92 species belonging to 77 different genera and 45 families existed in the area. The largest families were Asteraceae, Rosaceae and Lamiaceae with 12, ten and nine species, respectively. Ward's agglomerative cluster analysis for tree species resulted in three floristically and ecologically distinct community types along different topographic and soil variables. Importance value indices (IVI) were also calculated for understory vegetation and were subjected to ordination techniques, i.e. canonical correspondence analysis (CCA) and detrended correspondence analysis (DCA). DCA bi-plots for stands show that most of the stands were scattered around the centre of the DCA bi-plot, identified by two slightly scattered clusters. DCA for species bi-plot clearly identified three clusters of species revealing three types of understory communities in the study area. Results of the CCA were somewhat different from the DCA showing the impact of environmental variables on the understory species. CCA results reveal that three environmental variables, i.e. altitude, slope and P (mg/kg), have a strong influence on distribution of stands and species. Impact of tree species on the understory vegetation was also tested by CCA which showed that four tree species, i.e. P. wallichiana A.B. Jackson, Juglans regia Linn., Quercus dilatata Lindl. ex Royle and Cedrus deodara (Roxb. ex Lamb.) G. Don, have strong influences on associated understory vegetation. It is therefore concluded that Swat District has various microclimatic zones with suitable environmental variables to support distinct flora.
Chapter 8 - Mapping existing vegetation composition and structure for the LANDFIRE Prototype Project
Zhiliang Zhu; James Vogelmann; Donald Ohlen; Jay Kost; Xuexia Chen; Brian Tolk
2006-01-01
The Landscape Fire and Resource Management Planning Tools Prototype Project, or LANDFIRE Prototype Project, required the mapping of existing vegetation composition (cover type) and structural stages at a 30-m spatial resolution to provide baseline vegetation data for the development of wildland fuel maps and for comparison to simulated historical vegetation reference...
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.
Tundra fire alters stream water chemistry and benthic invertebrate communities, North Slope, Alaska
NASA Astrophysics Data System (ADS)
Allen, A. R.; Bowden, W. B.; Kling, G. W.; Schuett, E.; Kostrzewski, J. M.; Kolden Abatzoglou, C.; Findlay, R. H.
2010-12-01
Increased fire frequency and severity are potentially important consequences of climate change in high latitude ecosystems. The 2007 Anaktuvuk River fire, which burned from July until October, is the largest recorded tundra fire from Alaska's north slope (≈1,000 km2). The immediate effects of wildfire on water chemistry and biotic assemblages in tundra streams are heretofore unknown. We hypothesized that a tundra fire would increase inorganic nutrient inputs to P-limited tundra streams, increasing primary production and altering benthic macroinvertebrate community structure. We examined linkages among: 1) percentage of riparian zone and overall watershed vegetation burned, 2) physical, chemical and biological stream characteristics, and 3) macroinvertebrate communities in streams draining burned and unburned watersheds during the summers of 2008 and 2009. Streams in burned watersheds contained higher mean concentrations of soluble reactive phosphorus (SRP), ammonium (NH4+), and dissolved organic carbon (DOC). In contrast, stream nitrate (NO3-) concentrations were lower in burned watersheds. The net result was that the tundra fire did not affect concentrations of dissolved inorganic nitrogen (NH4+ + NO3-). In spite of increased SRP, benthic chlorophyll-a biomass was not elevated. Macroinvertebrate abundances were 1.5 times higher in streams draining burned watersheds; Chironomidae midges, Nematodes, and Nemoura stoneflies showed the greatest increases in abundance. Multivariate multiple regression identified environmental parameters associated with the observed changes in the macroinvertebrate communities. Since we identified stream latitude as a significant predictor variable, latitude was included in the model as a covariate. After removing the variation associated with latitude, 67.3 % of the variance in macroinvertebrate community structure was explained by a subset of 7 predictor variables; DOC, conductivity, mean temperature, NO3-, mean discharge, SRP and NH4+. The percentage of riparian vegetation burned, the percentage of watershed vegetation burned and total suspended solids were not included in the model as these parameters correlated with DOC concentration at r > 0.90. These results indicate that tundra fire not only alters stream water chemistry, it also affects benthic macroinvertebrate community structure.
NASA Technical Reports Server (NTRS)
Moghaddam, Mahta
2000-01-01
The addition of interferometric backscattering pairs to the conventional polarimetric SAR data over forests and other vegetated areas increases the dimensionality of the data space, in principle enabling the estimation of a larger number of vegetation parameters. Without regard to the sensitivity of these data to vegetation scattering parameters, this paper poses the question: Will increasing the data channels as such result in a one-to-one increase in the number of parameters that can be estimated, or do vegetation and data properties inherently limit that number otherwise? In this paper, the complete polarimetric interferometric covariance matrix is considered and various symmetry properties of the scattering medium are used to study whether any of the correlation pairs can be eliminated. The number of independent pairs has direct consequences in their utility in parameter estimation schemes, since the maximum number of parameters that can be estimated cannot exceed the number of unique measurements. The independent components of the polarimetric interferometric SAR (POL/INSAR) data are derived for media with reflection, rotation, and azimuth symmetries, which are often encountered in vegetated surfaces. Similar derivations have been carried out before for simple polarimetry, i.e., zero baseline. This paper extends those to the interferometric case of general nonzero baselines. It is shown that depending on the type of symmetries present, the number of independent available measurements that can be used to estimate medium parameters will vary. In particular, whereas in the general case there are 27 mathematically independent measurements possible from a polarimetric interferometer, this number can be reduced to 15, 9, and 6 if the medium has reflection, rotation, or azimuthal symmetries, respectively. The results can be used in several ways in the interpretation of SAR data and the development of parameter estimation schemes, which will be discussed at the presentation. Recent POL/INSAR data from the JPL AIRSAR over a forested area will be used to demonstrate the results of this derivation. This work was performed by the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, under contract from the National Aeronautics and Space Administration.
Choi, Jungyill; Harvey, Judson W.
2014-01-01
Surface water flow controls water velocities, water depths, and residence times, and influences sediment and nutrient transport and other ecological processes in shallow aquatic systems. Flow through wetlands is substantially influenced by drag on vegetation stems but is also affected by microtopography. Our goal was to use microtopography data directly in a widely used wetland model while retaining the advantages of the model’s one-dimensional structure. The base simulation with no explicit treatment of microtopography only performed well for a period of high water when vegetation dominated flow resistance. Extended simulations using microtopography can improve the fit to low-water conditions substantially. The best fit simulation had a flow conductance parameter that decreased in value by 70 % during dry season such that mcrotopographic features blocked 40 % of the cross sectional width for flow. Modeled surface water became ponded and flow ceased when 85 % of the cross sectional width became blocked by microtopographic features. We conclude that vegetation drag dominates wetland flow resistance at higher water levels and microtopography dominates at low water levels with the threshold delineated by the top of microtopographic features. Our results support the practicality of predicting flow on floodplains using relatively easily measured physical and biological variables.
Carter, Virginia; Reel, J.T.; Rybicki, N.B.; Ruhl, H.; Gammon, P.T.; Lee, J.K.
1999-01-01
The U.S. Geological Survey is one of many agencies participating in the effort to restore the South Florida Everglades. We are sampling and characterizing the vegetation at selected sites in the Everglades as part of a study to quantify vegetative flow resistance. The objectives of the vegetation sampling are (1) to provide detailed information on species composition, vegetation characteristics, vegetation structure, and biomass for quantification of vegetative resistance to flow, and (2) to use this information to classify the vegetation and to improve existing vegetation maps for use with numerical models of surface-water flow. Vegetation was sampled at two sites in the Shark River Slough in November, 1996. The data collected and presented here include those for live and dead standing sawgrass, other dead material, periphyton biomass, vegetation characteristics and structure, and leaf area index.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Peace, Gerald; Goering, Timothy James; Knight, Paul J.
A vegetation study was conducted in Technical Area 3 at Sandia National Laboratories, Albuquerque, New Mexico in 2003 to assist in the design and optimization of vegetative soil covers for hazardous, radioactive, and mixed waste landfills at Sandia National Laboratories/New Mexico and Kirtland Air Force Base. The objective of the study was to obtain site-specific, vegetative input parameters for the one-dimensional code UNSAT-H and to identify suitable, diverse native plant species for use on vegetative soil covers that will persist indefinitely as a climax ecological community with little or no maintenance. The identification and selection of appropriate native plant speciesmore » is critical to the proper design and long-term performance of vegetative soil covers. Major emphasis was placed on the acquisition of representative, site-specific vegetation data. Vegetative input parameters measured in the field during this study include root depth, root length density, and percent bare area. Site-specific leaf area index was not obtained in the area because there was no suitable platform to measure leaf area during the 2003 growing season due to severe drought that has persisted in New Mexico since 1999. Regional LAI data was obtained from two unique desert biomes in New Mexico, Sevilletta Wildlife Refuge and Jornada Research Station.« less
The stochastic Beer-Lambert-Bouguer law for discontinuous vegetation canopies
NASA Astrophysics Data System (ADS)
Shabanov, N.; Gastellu-Etchegorry, J.-P.
2018-07-01
The 3D distribution of canopy foliage affects the radiation regime and retrievals of canopy biophysical parameters. The gap fraction is one primary indicator of a canopy structure. Historically the Beer-Lambert-Bouguer law and the linear mixture model have served as a basis for multiple technologies for retrievals of the gap (or vegetation) fraction and Leaf Area Index (LAI). The Beer-Lambert-Bouguer law is a form of the Radiative Transfer (RT) equation for homogeneous canopies, which was later adjusted for a correlation between fitoelements using concept of the clumping index. The Stochastic Radiative Transfer (SRT) approach has been developed specifically for heterogeneous canopies, however the approach lacks a proper model of the vegetation fraction. This study is focused on the implementation of the stochastic version of the Beer-Lambert-Bouguer law for heterogeneous canopies, featuring the following principles: 1) two mechanisms perform photon transport- transmission through the turbid medium of foliage crowns and direct streaming through canopy gaps, 2) the radiation field is influenced by a canopy structure (quantified by the statistical moments of a canopy structure) and a foliage density (quantified by the gap fraction as a function of LAI), 3) the notions of canopy transmittance and gap fraction are distinct. The derived stochastic Beer-Lambert-Bouguer law is consistent with the Geometrical Optical and Radiative Transfer (GORT) derivations. Analytical and numerical analysis of the stochastic Beer-Lambert-Bouguer law presented in this study provides the basis to reformulate widely used technologies for retrievals of the gap fraction and LAI from ground and satellite radiation measurements.
[Research on identification of species of fruit trees by spectral analysis].
Xing, Dong-Xing; Chang, Qing-Rui
2009-07-01
Using the spectral reflectance data (R2) of canopies, the present paper identifies seven species of fruit trees bearing fruit in the fruit mature period. Firstly, it compares the fruit tree species identification capability of six kinds of satellite sensors and four kinds of vegetation index through re-sampling the spectral data with six kinds of pre-defined filter function and the related data processing of calculating vegetation indexes. Then, it structures a BP neural network model for identifying seven species of fruit trees on the basis of choosing the best transformation of R(lambda) and optimizing the model parameters. The main conclusions are: (1) the order of the identification capability of the six kinds of satellite sensors from strong to weak is: MODIS, ASTER, ETM+, HRG, QUICKBIRD and IKONOS; (2) among the four kinds of vegetation indexes, the identification capability of RVI is the most powerful, the next is NDVI, while the identification capability of SAVI or DVI is relatively weak; (3) The identification capability of RVI and NDVI calculated with the reflectance of near-infrared and red channels of ETM+ or MODIS sensor is relatively powerful; (4) Among R(lambda) and its 22 kinds of transformation data, d1 [log(1/R(lambda))](derivative gap is set 9 nm) is the best transformation for structuring BP neural network model; (5) The paper structures a 3-layer BP neural network model for identifying seven species of fruit trees using the best transformation of R(lambda) which is d1 [log(1/R(lambda))](derivative gap is set 9 nm).
2012-08-01
Difference Vegetation Index ( NDVI ) ..................................... 15 2.3 Methodology...Atmospheric Compensation ........................................................................ 31 3.2.3.1 Normalized Difference Vegetation Index ( NDVI ...anomaly detection algorithms are contrasted and implemented, and explains the use of the Normalized Difference Vegetation Index ( NDVI ) in post
Impacts of Seed Dispersal on Future Vegetation Structure under Changing Climates
NASA Astrophysics Data System (ADS)
Lee, E.; Schlosser, C. A.; Gao, X.; Prinn, R. G.
2011-12-01
As the impacts between land cover change, future climates and ecosystems are expected to be substantial, there are growing needs for improving the capability of simulating the global vegetation structure and landscape as realistically as possible. Current DGVMs assume ubiquitous availability of seeds and do not consider any seed dispersal mechanisms in plant migration process, which may influence the assessment of impacts to the ecosystem that rely on the vegetation structure changes (i.e., change in albedo, runoff, and terrestrial carbon sequestration capacity). This study incorporates time-varying wind-driven seed dispersal (i.e., the SEED configuration) as a dynamic constraint to the migration process of natural vegetation in the Community Land Model (CLM)-DGVM. The SEED configuration is validated using a satellite-derived tree cover dataset. Then the configuration is applied to project future vegetation structures and their implications for carbon fluxes, albedo, and hydrology under two climate mitigation scenarios (No-policy vs. 450ppm CO2 stabilization) for the 21st century. Our results show that regional changes of vegetation structure under changing climates are expected to be significant. For example, Alaska and Siberia are expected to experience substantial shifts of forestry structure, characterized by expansion of needle-leaf boreal forest and shrinkage of C3 grass Arctic. A suggested vulnerability assessment shows that vegetation structures in Alaska, Greenland, Central America, southern South America, East Africa and East Asia are susceptible to changing climates, regardless of the two climate mitigation scenarios. Regions such as Greenland, Tibet, South Asia and Northern Australia, however, may substantially alleviate their risks of rapid change in vegetation structure, given a robust greenhouse gas stabilization target. Proliferation of boreal forests in the high latitudes is expected to amplify the warming trend (i.e., a positive feedback to climate), if no mitigation policy is implemented. In contrast, under the 450ppm scenario, vegetation structure may buffer the warming trend, which is a negative feedback to climate. Moreover, runoff changes due to vegetation shifts may offset or complement runoff changes under anthropogenic climate warming.
Chapter 4. Monitoring vegetation composition and structure as habitat attributes
Thomas E. DeMeo; Mary M. Manning; Mary M. Rowland; Christina D. Vojta; Kevin S. McKelvey; C. Kenneth Brewer; Rebecca S.H. Kennedy; Paul A. Maus; Bethany Schulz; James A. Westfall; Timothy J. Mersmann
2013-01-01
Vegetation composition and structure are key components of wildlife habitat (Mc- Comb et al. 2010, Morrison et al. 2006) and are, therefore, essential components of all wildlife habitat monitoring. The objectives of this chapter are to describe common habitat attributes derived from vegetation composition and structure and to provide guidance for obtaining and using...
NASA Astrophysics Data System (ADS)
Morales, M. B.; Traba, J.; Carriles, E.; Delgado, M. P.; de la Morena, E. L. García
2008-11-01
We examined sexual differences in patterns of vegetation structure selection in the sexually dimorphic little bustard. Differences in vegetation structure between male, female and non-used locations during reproduction were examined and used to build a presence/absence model for each sex. Ten variables were measured in each location, extracting two PCA factors (PC1: a visibility-shelter gradient; PC2: a gradient in food availability) used as response variables in GLM explanatory models. Both factors significantly differed between female, male and control locations. Neither study site nor phenology was significant. Logistic regression was used to model male and female presence/absence. Female presence was positively associated to cover of ground by vegetation litter, as well as overall vegetation cover, and negatively to vegetation density over 30 cm above ground. Male presence was positively related to litter cover and short vegetation and negatively to vegetation density over 30 cm above ground. Models showed good global performance and robustness. Female microhabitat selection and distribution seems to be related to the balance between shelter and visibility for surveillance. Male microhabitat selection would be related mainly to the need of conspicuousness for courtship. Accessibility to food resources seems to be equally important for both sexes. Differences suggest ecological sexual segregation resulting from different ecological constraints. These are the first detailed results on vegetation structure selection in both male and female little bustards, and are useful in designing management measures addressing vegetation structure irrespective of landscape composition. Similar microhabitat approaches can be applied to manage the habitat of many declining farmland birds.
Kenison, Erin K; Litt, Andrea R.; Pilliod, David S.; McMahon, Tom E
2016-01-01
Predation by nonnative fishes has reduced abundance and increased extinction risk for amphibian populations worldwide. Although rare, fish and palatable amphibians have been observed to coexist where aquatic vegetation and structural complexity provide suitable refugia. We examined whether larval long-toed salamanders (Ambystoma macrodactylum Baird, 1849) increased use of vegetation cover in lakes with trout and whether adding vegetation structure could reduce predation risk and nonconsumptive effects (NCEs), such as reductions in body size and delayed metamorphosis. We compared use of vegetation cover by larval salamanders in lakes with and without trout and conducted a field experiment to investigate the influence of added vegetation structure on salamander body morphology and life history. The probability of catching salamanders in traps in lakes with trout was positively correlated with the proportion of submerged vegetation and surface cover. Growth rates of salamanders in enclosures with trout cues decreased as much as 85% and the probability of metamorphosis decreased by 56%. We did not find evidence that adding vegetation reduced NCEs in experimental enclosures, but salamanders in lakes with trout utilized more highly-vegetated areas which suggests that adding vegetation structure at the scale of the whole lake may facilitate coexistence between salamanders and introduced trout.
Takahashi, Keiko; Kamada, Chiemi; Yoshimura, Hidenori; Okumura, Ryota; Iimuro, Satoshi; Ohashi, Yasuo; Araki, Atsushi; Umegaki, Hiroyuki; Sakurai, Takashi; Yoshimura, Yukio; Ito, Hideki
2012-04-01
Many reports have shown that vegetable intake is effective in inhibiting the onset and progression of diabetes mellitus, although the amount of vegetable intake required to be effective remains as unclear. The present study therefore aimed to clarify the relationship between the amount of vegetable intake and glycated hemoglobin A1c (HbA1c) and other metabolic parameters using male Japanese type 2 diabetic patients aged 65 years or older as subjects. Participants were 417 male type 2 diabetic patients aged 65 years or older enrolled in the Japanese Elderly Diabetes Intervention Trial. Dietary intakes were measured by using the Food Frequency Questionnaires method. The patients were divided into five groups by their daily total vegetable intake (A1: ~100 g, A2: 100~150 g, A3: 150~200 g, A4: 200~300 g, A5: 300 g~), and compared HbA1c and other metabolic parameters. Furthermore, the relationship between daily green vegetable intake and HbA1c and other metabolic parameters were examined among five groups divided by quintile methods. There were significant decreases in HbA1c, triglycerides and waist circumference with an increase of total vegetable intake. A significant decrease of HbA1c levels was observed in patients with a daily total vegetable intake of 150 g or more. Furthermore, there was a significant decrease of serum triglyceride levels in patients with a total vegetable intake of 200 g or more. HbA1c levels showed a decreasing tendency with the increase of green vegetable intake, and HbA1c levels in the Q1 group (green vegetable intake: less than 40 g) was significantly higher than those in the other four groups (anovaP = 0.025). In addition, there were significant decreases of body mass index, triglyceride levels and waist circumference with the increase of green vegetable intake. Triglyceride levels decreased significantly from the Q3 group (green vegetable intake: 70 g or more) to the Q5 group (green vegetable intake: 130 g or more; anovaP = 0.016). In the group with a lower intake of total vegetables and green vegetables, the protein energy ratio decreased significantly. As a result, the fat energy ratio and energy intake tended to increase with the decrease of total and green vegetable intakes. Furthermore, intake of grains, sweets and alcoholic beverages increased with the decrease of total vegetable intake. In contrast, intake of nuts, potatoes, sugar, legumes, fruit, seaweed and fish increased with the increase of total vegetable intake Daily total vegetable intake of 200 g or more, and green vegetable intake of 70 g or more correlated with improved control of HbA1c and triglyceride levels in elderly type 2 diabetes patients through achieving a well-balanced diet. © 2012 Japan Geriatrics Society.
NASA Astrophysics Data System (ADS)
Morris, P. J.; Verhoef, A.; Van der Tol, C.; Macdonald, D.
2011-12-01
Rationale: Floodplain meadows are highly species-rich grassland ecosystems, unique in that their vegetation and soil structures have been shaped and maintained by ~1,000 yrs of traditional, low-intensity agricultural management. Widespread development on floodplains over the last two centuries has left few remaining examples of these once commonplace ecosystems and they are afforded high conservation value by British and European agencies. Increased incidences and severity of summer drought and winter flooding in Britain in recent years have placed floodplain plant communities under stress through altered soil moisture regimes. There is a clear need for improved management strategies if the last remaining British floodplain meadows are to be conserved under changing climates. Aim: As part of the Floodplain Underground Sensors Experiment (FUSE, a 3-year project funded by the Natural Environment Research Council) we aim to understand the environmental controls over soil-vegetation-atmosphere transfers (SVAT) of water, CO2 and energy at Yarnton Mead, a floodplain meadow in southern England. An existing model, SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes; van der Tol et al., 2009), uses remotely-sensed infrared radiance spectra to predict heat and water transfers between a vegetation canopy and the atmosphere. We intend to expand SCOPE by developing a more realistic, physically-based representation of water, gas and energy transfers between soil and vegetation. This improved understanding will eventually take the form of a new submodel within SCOPE, allowing more rigorous estimation of soil-canopy-atmosphere exchanges for the site using predominantly remotely-sensed data. In this context a number of existing SVAT models will be tested and compared to ensure that only reliable and robust underground model components will be coupled to SCOPE. Approach: For this study, we parameterised an existing and widely-used SVAT model (CoupModel; Jansson, 2011) for our study site and analysed the model's sensitivity to a comprehensive set of soil/plant biophysical processes and parameter values. Findings: The sensitivity analysis indicates those processes and parameters most important to soil-vegetation-atmosphere transfers at the site. We use the outcomes of the sensitivity analysis to indicate directly the desired structure of the new SCOPE submodel. In addition, existing soil-moisture, soil matric-potential and meteorological data for the site indicate that evapotranspiration is heavily water-limited during summer months, although soil moisture and soil matric-potential data alone provide very little explanation of the ratio of potential to actual evapotranspiration. A mechanistic representation of stomatal resistance and its response to short-term changes in meteorological conditions - independent of soil moisture status - will also likely improve SCOPE's predictions of heat and water transfers. Ultimately our work will contribute to improved understanding and management of floodplain meadows in Britain and elsewhere.
Bai, Gegenbaoleer; Bao, Yuying; Du, Guoxin; Qi, Yunlong
2013-05-01
The impact of rest grazing on arbuscular mycorrhizal fungi (AMF) and the interactions of AMF with vegetation and soil parameters under rest grazing condition were investigated between spring and late summer in a desert steppe ecosystem with different grazing managements (rest grazing with different lengths of resting period, banned or continuous grazing) in Inner Mongolia, China. AMF diversity and colonization, vegetation biomass, soil properties and soil phosphatase activity were examined. In rest grazing areas of 60 days, AMF spore number and diversity index at a 0-10 cm soil depth as well as vesicular and hyphal colonization rates were higher compared with other grazing treatments. In addition, soil organic matter and total N contents were highest and soil alkaline phosphatase was most active under 60-day rest grazing. In August and September, these areas also had the highest amount of aboveground vegetation. The results indicated that resting grazing for an appropriate period of time in spring has a positive effect on AMF sporulation, colonization and diversity, and that under rest grazing conditions, AMF parameters are positively correlated with some soil characteristics.
Ground-Vegetation Clutter Affects Phyllostomid Bat Assemblage Structure in Lowland Amazonian Forest
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
A 3D Joint Simulation Platform for Multiband_A Case Study in the Huailai Soybean and Maize Field
NASA Astrophysics Data System (ADS)
Zhang, Y.; Qinhuo, L.; Du, Y.; Huang, H.
2016-12-01
Canopy radiation and scattering signal contains abundant vegetation information. One can quantitatively retrieve the biophysical parameters by building canopy radiation and scattering models and inverting them. Joint simulation of the 3D models for different spectral (frequency) domains may produce complementary advantages and improves the precision. However, most of the currently models were based on one or two spectral bands (e.g. visible and thermal inferred bands, or visible and microwave bands). This manuscript established a 3D radiation and scattering simulation system which can simulate the BRDF, DBT, and backscattering coefficient based on the same structural description. The system coupled radiosity graphic model, Thermal RGM model and coherent microwave model by Yang Du for VIS/NIR, TIR, and MW, respectively. The models simulating the leaf spectral characteristics, component temperatures and dielectric properties were also coupled into the joint simulation system to convert the various parameters into fewer but more unified parameters. As a demonstration of our system, we applied the established system to simulate a mixed field with soybeans and maize based on the Huailai experiment data in August, 2014. With the help of Xfrog software, we remodeled soybean and maize in ".obj" and ".mtl" format. We extracted the structure information of the soybean and maize by statistics of the ".obj" files. We did simulations on red, NIR, TIR, C and L band. The simulation results were validated by the multi-angular observation data of Huailai experiment. Also, the spacial distribution (horizontal and vertical), leaf area index (LAI), leaf angle distribution (LAD), vegetation water content (VWC) and the incident observation geometry were analyzed in details. Validated by the experiment data, we indicate that the simulations of multiband were quite well. Because the crops were planted in regular rows and the maize and soybeans were with different height, different LAI, different LAD and different VWC, we did the sensitive analysis by changing on one of them and fixed the other parameters. The analysis showed that the parameters influenced the radiation and scattering signal of different spectral (frequency) with varying degrees.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Martin, Mark A.
2002-04-15
Vegetation Management along the Rocky Reach – Maple Valley No. 1 Transmission Line ROW from structure 110/1 to the Maple Valley Substation. The transmission line is a 500 kV line. BPA proposes to clear targeted vegetation along access roads and around tower structures that may impede the operation and maintenance of the subject transmission line. BPA plans to conduct vegetation management along existing access road and around structure landings for the purpose of maintaining access to structures site. All work will be in accordance with the National Electrical Safety Code and BPA standards.
NASA Technical Reports Server (NTRS)
Musick, H. Brad; Schaber, Gerald G.; Breed, Carol S.
1995-01-01
The replacement of semidesert grassland by woody shrubland is a widespread form of desertification. This change in physiognomy and species composition tends to sharply reduce the productivity of the land for grazing by domestic livestock, increase soil erosion and reduce soil fertility, and greatly alter many other aspects of ecosystem structure and functioning. Remote sensing methods are needed to assess and monitor shrubland encroachment. Detection of woody shrubs at low density would provide a particularly useful baseline on which to access changes, because an initially low shrub density often tends to increase even after cessation of the disturbance (e.g., overgrazing, drought, or fire suppression) responsible for triggering the initial stages of the invasion (Grover and Musick, 1990). Limited success has been achieved using optical remote sensing. In contrast to other forms of desertification, biomass does not consistently decrease with a shift from grassland to shrubland. Estimation of green vegetation amount (e.g., by NDVI) is thus of limited utility, unless the shrubs and herbaceous plants differ consistently in phenology and the area can be viewed during a season when only one of these is green. The objective of this study was to determine if the potential sensitivity of active microwave remote sensing to vegetation structure could be used to assess the degree of shrub invasion of grassland. Polarimetric Airborne Synthetic Aperture Radar (AIRSAR) data were acquired for a semiarid site containing varied mixtures of shrubs and herbaceous vegetation and compared with ground observations of vegetation type and other landsurface characteristics. In this preliminary report we examine the response of radar backscatter intensity to shrub density. The response of other multipolarization parameters will be examined in future work.
GIS-Based Noise Simulation Open Source Software: N-GNOIS
NASA Astrophysics Data System (ADS)
Vijay, Ritesh; Sharma, A.; Kumar, M.; Shende, V.; Chakrabarti, T.; Gupta, Rajesh
2015-12-01
Geographical information system (GIS)-based noise simulation software (N-GNOIS) has been developed to simulate the noise scenario due to point and mobile sources considering the impact of geographical features and meteorological parameters. These have been addressed in the software through attenuation modules of atmosphere, vegetation and barrier. N-GNOIS is a user friendly, platform-independent and open geospatial consortia (OGC) compliant software. It has been developed using open source technology (QGIS) and open source language (Python). N-GNOIS has unique features like cumulative impact of point and mobile sources, building structure and honking due to traffic. Honking is the most common phenomenon in developing countries and is frequently observed on any type of roads. N-GNOIS also helps in designing physical barrier and vegetation cover to check the propagation of noise and acts as a decision making tool for planning and management of noise component in environmental impact assessment (EIA) studies.
Diadema, Katia; Médail, Frédéric; Bretagnolle, François
2007-09-01
We examine the effects of fire and/or surrounding vegetation cover on demographic stage densities and plant performance for a rare endemic geophyte, Acis nicaeensis (Alliaceae), in Mediterranean xerophytic grasslands of the 'Alpes-Maritimes' French 'département', through sampling plots in unburned and burned treatments. Fire increases density of flowering individuals and seedling emergence, as well as clump densities and number of individuals per clump, per limiting vegetation height and cover, and increasing bare soil cover. In contrast, fire has no effect on reproductive success. Nevertheless, two growing seasons after fire, all parameters of demographic stages and plant performance do not significantly differ between the two treatments. Small-scale fire is beneficial for the regeneration of this threatened geophyte at a short-time scale. In this context, a conservation planning with small and controlled fires could maintain the regeneration window for populations of rare Mediterranean geophytes.
NASA Astrophysics Data System (ADS)
Krogh, Sebastian A.; Pomeroy, John W.; Marsh, Philip
2017-07-01
A better understanding of cold regions hydrological processes and regimes in transitional environments is critical for predicting future Arctic freshwater fluxes under climate and vegetation change. A physically based hydrological model using the Cold Regions Hydrological Model platform was created for a small Arctic basin in the tundra-taiga transition region. The model represents snow redistribution and sublimation by wind and vegetation, snowmelt energy budget, evapotranspiration, subsurface flow through organic terrain, infiltration to frozen soils, freezing and thawing of soils, permafrost and streamflow routing. The model was used to reconstruct the basin water cycle over 28 years to understand and quantify the mass fluxes controlling its hydrological regime. Model structure and parameters were set from the current understanding of Arctic hydrology, remote sensing, field research in the basin and region, and calibration against streamflow observations. Calibration was restricted to subsurface hydraulic and storage parameters. Multi-objective evaluation of the model using observed streamflow, snow accumulation and ground freeze/thaw state showed adequate simulation. Significant spatial variability in the winter mass fluxes was found between tundra, shrubs and forested sites, particularly due to the substantial blowing snow redistribution and sublimation from the wind-swept upper basin, as well as sublimation of canopy intercepted snow from the forest (about 17% of snowfall). At the basin scale, the model showed that evapotranspiration is the largest loss of water (47%), followed by streamflow (39%) and sublimation (14%). The models streamflow performance sensitivity to a set of parameter was analysed, as well as the mean annual mass balance uncertainty associated with these parameters.
NASA Astrophysics Data System (ADS)
Fan, Shuxin; Li, Xiaopeng; Han, Jing; Cao, Yu; Dong, Li
2017-10-01
In high-density metropolis, residential areas are important human living environments. Aimed at investigating the impacts of landscape structure on the levels of different-sized airborne particle in residential areas, we conducted field monitoring of the levels of TSP, PM10, PM2.5 and PM1 using mobile traverses in 18 residential areas during the daytime in winter (Dec. 2015-Feb. 2016) and summer (Jun.-Aug. 2016) in Beijing, China. The net concentration differences (d) of the four-sized particles (dTSP, dPM10, dPM2.5 and dPM1) between residential environments and nearby corresponding urban backgrounds, which can be regarded as the reduction of particle concentration in residential environments, were calculated. The effects and relative contributions of different landscape structure parameters on these net concentration differences were further investigated. Results showed that the distribution of particle concentrations has great spatial variation in urban environments. Within the residential environment, there were overall lower concentrations of the four-sized particles compared with the nearby urban background. The net concentration differences of the four-sized particles were all significantly different among the 18 studied residential areas. The average dTSP, dPM10, dPM2.5 and dPM1 reached 18.92, 12.28, 2.01 and 0.53 μg/m3 in summer, and 9.91, 7.81, 1.39 and 0.38 μg/m3 in winter, respectively. The impacts and relative contribution of different landscape structure parameters on the reductions of TSP, PM10, PM2.5 and PM1 in residential environments differed and showed seasonal variation. Percentage of vegetation cover (PerVC) and building cover (PerBC) had the greatest impact. A 10% increase in PerVC would increase about 5.03, 8.15, 2.16 and 0.20 μg/m3 of dTSP, dPM10, dPM2.5 and dPM1 in summer, and a 10% increase in PerBC would decreased about 41.37, 16.54, 2.47 and 0.95 μg/m3 of them in winter. Increased vegetation coverage and decreased building construction were found to be conducive to ameliorate airborne particle levels in residential environments. Moreover, landscape structure parameters can be served as indicators for predicting the potential particle reduction at local scale.
An empirical model for polarized and cross-polarized scattering from a vegetation layer
NASA Technical Reports Server (NTRS)
Liu, H. L.; Fung, A. K.
1988-01-01
An empirical model for scattering from a vegetation layer above an irregular ground surface is developed in terms of the first-order solution for like-polarized scattering and the second-order solution for cross-polarized scattering. The effects of multiple scattering within the layer and at the surface-volume boundary are compensated by using a correction factor based on the matrix doubling method. The major feature of this model is that all parameters in the model are physical parameters of the vegetation medium. There are no regression parameters. Comparisons of this empirical model with theoretical matrix-doubling method and radar measurements indicate good agreements in polarization, angular trends, and k sub a up to 4, where k is the wave number and a is the disk radius. The computational time is shortened by a factor of 8, relative to the theoretical model calculation.
NASA Astrophysics Data System (ADS)
Ma, Weiwei; Gong, Cailan; Hu, Yong; Li, Long; Meng, Peng
2015-10-01
Remote sensing technology has been broadly recognized for its convenience and efficiency in mapping vegetation, particularly in high-altitude and inaccessible areas where there are lack of in-situ observations. In this study, Landsat Thematic Mapper (TM) images and Chinese environmental mitigation satellite CCD sensor (HJ-1 CCD) images, both of which are at 30m spatial resolution were employed for identifying and monitoring of vegetation types in a area of Western China——Qinghai Lake Watershed(QHLW). A decision classification tree (DCT) algorithm using multi-characteristic including seasonal TM/HJ-1 CCD time series data combined with digital elevation models (DEMs) dataset, and a supervised maximum likelihood classification (MLC) algorithm with single-data TM image were applied vegetation classification. Accuracy of the two algorithms was assessed using field observation data. Based on produced vegetation classification maps, it was found that the DCT using multi-season data and geomorphologic parameters was superior to the MLC algorithm using single-data image, improving the overall accuracy by 11.86% at second class level and significantly reducing the "salt and pepper" noise. The DCT algorithm applied to TM /HJ-1 CCD time series data geomorphologic parameters appeared as a valuable and reliable tool for monitoring vegetation at first class level (5 vegetation classes) and second class level(8 vegetation subclasses). The DCT algorithm using multi-characteristic might provide a theoretical basis and general approach to automatic extraction of vegetation types from remote sensing imagery over plateau areas.
Relating Vegetation Aerodynamic Roughness Length to Interferometric SAR Measurements
NASA Technical Reports Server (NTRS)
Saatchi, Sassan; Rodriquez, Ernesto
1998-01-01
In this paper, we investigate the feasibility of estimating aerodynamic roughness parameter from interferometric SAR (INSAR) measurements. The relation between the interferometric correlation and the rms height of the surface is presented analytically. Model simulations performed over realistic canopy parameters obtained from field measurements in boreal forest environment demonstrate the capability of the INSAR measurements for estimating and mapping surface roughness lengths over forests and/or other vegetation types. The procedure for estimating this parameter over boreal forests using the INSAR data is discussed and the possibility of extending the methodology over tropical forests is examined.
NASA Technical Reports Server (NTRS)
Arain, Altaf M.; Shuttleworth, W. James; Yang, Z-Liang; Michaud, Jene; Dolman, Johannes
1997-01-01
A coupled model, which combines the Biosphere-Atmosphere Transfer Scheme (BATS) with an advanced atmospheric boundary-layer model, was used to validate hypothetical aggregation rules for BATS-specific surface cover parameters. The model was initialized and tested with observations from the Anglo-Brazilian Amazonian Climate Observational Study and used to simulate surface fluxes for rain forest and pasture mixes at a site near Manaus in Brazil. The aggregation rules are shown to estimate parameters which give area-average surface fluxes similar to those calculated with explicit representation of forest and pasture patches for a range of meteorological and surface conditions relevant to this site, but the agreement deteriorates somewhat when there are large patch-to-patch differences in soil moisture. The aggregation rules, validated as above, were then applied to remotely sensed 1 km land cover data set to obtain grid-average values of BATS vegetation parameters for 2.8 deg x 2.8 deg and 1 deg x 1 deg grids within the conterminous United States. There are significant differences in key vegetation parameters (aerodynamic roughness length, albedo, leaf area index, and stomatal resistance) when aggregate parameters are compared to parameters for the single, dominant cover within the grid. However, the surface energy fluxes calculated by stand-alone BATS with the 2-year forcing, data from the International Satellite Land Surface Climatology Project (ISLSCP) CDROM were reasonably similar using aggregate-vegetation parameters and dominant-cover parameters, but there were some significant differences, particularly in the western USA.
2010-01-01
Background Recommendations for daily dietary vegetable intake were increased in the 2005 USDA Dietary Guidelines as consumption of a diet rich in vegetables has been associated with lower risk of certain chronic health disorders including cardiovascular disease. However, vegetable consumption in the United States has declined over the past decade; consequently, the gap between dietary recommendations and vegetable intake is widening. The primary aim of this study is to determine if drinking vegetable juice is a practical way to help meet daily dietary recommendations for vegetable intake consistent with the 2005 Dietary Guidelines and the Dietary Approaches to Stop Hypertension (DASH) diet. The secondary aim is to assess the effect of a vegetable juice on measures of cardiovascular health. Methods We conducted a 12-week, randomized, controlled, parallel-arm study consisting of 3 groups of free-living, healthy volunteers who participated in study visits at the Ragle Human Nutrition Research Center at the University of California, Davis. All subjects received education on the DASH diet and 0, 8 or 16 fluid ounces of vegetable juice daily. Assessments were completed of daily vegetable servings before and after incorporation of vegetable juice and cardiovascular health parameters including blood pressure. Results Without the juice, vegetable intake in all groups was lower than the 2005 Dietary Guidelines and DASH diet recommendations. The consumption of the vegetable juice helped participants reach recommended intake. In general, parameters associated with cardiovascular health did not change over time. However, in the vegetable juice intervention groups, subjects who were pre-hypertensive at the start of the study showed a significant decrease in blood pressure during the 12-week intervention period. Conclusion Including 1-2 cups of vegetable juice daily was an effective and acceptable way for healthy adults to close the dietary vegetable gap. Increase in daily vegetable intake was associated with a reduction in blood pressure in subjects who were pre-hypertensive at the start of the trial. Trial Registration Clinicaltrials.gov NCT01161706 PMID:20849620
K.M. Bergen; S.J. Goetz; R.O. Dubayah; G.M. Henebry; C.T. Hunsaker; M.L. Imhoff; R.F. Nelson; G.G. Parker; V.C. Radeloff
2009-01-01
Biodiversity and habitat face increasing pressures due to human and natural influences that alter vegetation structure. Because of the inherent difficulty of measuring forested vegetation three-dimensional (3-D) structure on the ground, this important component of biodiversity and habitat has been, until recently, largely restricted to local measurements, or at larger...
Attempt at quantifying human-induced land-cover change during the Holocene in central eastern China
NASA Astrophysics Data System (ADS)
Li, Furong; Gaillard, Marie-José; Mazier, Florence; Sugita, Shinya; Xu, Qinghai; Li, Yuecong; Zhou, Zhongze
2016-04-01
China is one of the key regions of the world where agricultural civilizations already flourished several millennia ago. However, the role of human activity in vegetation change is not yet fully understood. As a contribution to the PAGES LandCover6k initiative, this study aims to achieve a first attempt at Holocene land-cover reconstructions in the temperate zone of China using the REVEALS model (Sugita, 2007). Pollen productivity estimates (PPEs) are key parameters required for the model and were lacking so far for major taxa characteristic of ancient cultural landscapes in that part of the world. Remains of traditional agricultural structures and practices are still found in the low mountain ranges of the Shandong province located in central-eastern China. The area was chosen for a study of pollen-vegetation relationships and calculation of pollen productivity estimates. Pollen counts and vegetation data from 37 random sites within an area of 200 x 100 km are used for calculation. The vegetation inventory within 100 meters from the pollen sampling site follows the standard methods of Bunting et al. (2013). Vegetation data beyond 100 meters up to 1.5 km from the pollen sampling site is extracted from satellite images. The PPEs are calculated using the three sub-models of the Extended R-value model and compared with existing PPEs from northern China's biomes and temperate Europe. The PPEs' relevance for reconstruction of past human-induced land-cover change in temperate China are evaluated. Key words China, traditional agricultural landscape, ERV model, pollen productivity estimates References Bunting, M. J., et al. (2013). "Palynological perspectives on vegetation survey: a critical step for model-based reconstruction of Quaternary land cover." Quaternary Science Reviews 82: 41-55. Sugita, S. (2007). "Theory of quantitative reconstruction of vegetation I: pollen from large sites REVEALS regional vegetation composition." The Holocene 17(2): 229-241.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sherer, Brett M.
2003-02-19
BPA proposes to remove unwanted vegetation along the right-of-way, access roads, and around tower structures of the subject transmission line corridor that may impede the operation and maintenance of the identified transmission lines. BPA plans to conduct vegetation control with the goal of removing tall growing vegetation that is currently or will soon be a hazard to the transmission line. BPA’s overall goal is to have low-growing plant communities along the rights-of-way to control the development of potentially threatening vegetation. Vegetation Management for the Eugene-Alvey 115 kV transmission line from structure 7/1 through structure 12/2m, and along portions of themore » following adjacent transmission lines: Hawkins-Alvey 115KV and Alvey-Lane 115KV.« less
Relationship of attenuation in a vegetation canopy to physical parameters of the canopy
NASA Technical Reports Server (NTRS)
Karam, M. A.; Levine, D. M.
1993-01-01
A discrete scatter model is employed to compute the radiometric response (i.e. emissivity) of a layer of vegetation over a homogeneous ground. This was done to gain insight into empirical formulas for the emissivity which have recently appeared in the literature and which indicate that the attenuation through the canopy is proportional to the water content of the vegetation and inversely proportional to wavelength raised to a power around unity. The analytical result assumes that the vegetation can be modeled by a sparse layer of discrete, randomly oriented particles (leaves, stalks, etc.). The attenuation is given by the effective wave number of the layer obtained from the solution for the mean wave using the effective field approximation. By using the Ulaby-El Rayes formula to relate the dielectric constant of the vegetation to its water content, it can be shown that the attenuation is proportional to water content. The analytical form offers insight into the dependence of the empirical parameters on other variables of the canopy, including plant geometry (i.e. shape and orientation of the leaves and stalks of which the vegetation is comprised), frequency of the measurement and even the physical temperature of the vegetation. Solutions are presented for some special cases including layers consisting of cylinders (stalks) and disks (leaves).
Estimation of effective aerodynamic roughness with altimeter measurements
NASA Technical Reports Server (NTRS)
Menenti, M.; Ritchie, J. C.
1992-01-01
A new method is presented for estimating the aerodynamic roughness length of heterogeneous land surfaces and complex landscapes using elevation measurements performed with an airborne laser altimeter and the Seasat radar altimeter. Land surface structure is characterized at increasing length scales by considering three basic landscape elements: (1) partial to complete canopies of herbaceous vegetation; (2) sparse obstacles (e.g., shrubs and trees); and (3) local relief. Measured parameters of land surface geometry are combined to obtain an effective aerodynamic roughness length which parameterizes the total atmosphere-land surface stress.
Species Composition at the Sub-Meter Level in Discontinuous Permafrost in Subarctic Sweden
NASA Astrophysics Data System (ADS)
Anderson, S. M.; Palace, M. W.; Layne, M.; Varner, R. K.; Crill, P. M.
2013-12-01
Northern latitudes are experiencing rapid warming. Wetlands underlain by permafrost are particularly vulnerable to warming which results in changes in vegetative cover. Specific species have been associated with greenhouse gas emissions therefore knowledge of species compositional shift allows for the systematic change and quantification of emissions and changes in such emissions. Species composition varies on the sub-meter scale based on topography and other microsite environmental parameters. This complexity and the need to scale vegetation to the landscape level proves vital in our estimation of carbon dioxide (CO2) and methane (CH4) emissions and dynamics. Stordalen Mire (68°21'N, 18°49'E) in Abisko and is located at the edge of discontinuous permafrost zone. This provides a unique opportunity to analyze multiple vegetation communities in a close proximity. To do this, we randomly selected 25 1x1 meter plots that were representative of five major cover types: Semi-wet, wet, hummock, tall graminoid, and tall shrub. We used a quadrat with 64 sub plots and measured areal percent cover for 24 species. We collected ground based remote sensing (RS) at each plot to determine species composition using an ADC-lite (near infrared, red, green) and GoPro (red, blue, green). We normalized each image based on a Teflon white chip placed in each image. Textural analysis was conducted on each image for entropy, angular second momentum, and lacunarity. A logistic regression was developed to examine vegetation cover types and remote sensing parameters. We used a multiple linear regression using forwards stepwise variable selection. We found statistical difference in species composition and diversity indices between vegetation cover types. In addition, we were able to build regression model to significantly estimate vegetation cover type as well as percent cover for specific key vegetative species. This ground-based remote sensing allows for quick quantification of vegetation cover and species and also provides the framework for scaling to satellite image data to estimate species composition and shift on the landscape level. To determine diversity within our plots we calculated species richness and Shannon Index. We found that there were statistically different species composition within each vegetation cover type and also determined which species were indicative for cover type. Our logistical regression was able to significantly classify vegetation cover types based on RS parameters. Our multiple regression analysis indicated Betunla nana (Dwarf Birch) (r2= .48, p=<0.0001) and Sphagnum (r2=0.59, p=<0.0001) were statistically significant with respect to RS parameters. We suggest that ground based remote sensing methods may provide a unique and efficient method to quantify vegetation across the landscape in northern latitude wetlands.
Cretini, Kari F.; Visser, Jenneke M.; Krauss, Ken W.; Steyer, Gregory D.
2011-01-01
This document identifies the main objectives of the Coastwide Reference Monitoring System (CRMS) vegetation analytical team, which are to provide (1) collection and development methods for vegetation response variables and (2) the ways in which these response variables will be used to evaluate restoration project effectiveness. The vegetation parameters (that is, response variables) collected in CRMS and other coastal restoration projects funded under the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) are identified, and the field collection methods for these parameters are summarized. Existing knowledge on community and plant responses to changes in environmental drivers (for example, flooding and salinity) from published literature and from the CRMS and CWPPRA monitoring dataset are used to develop a suite of indices to assess wetland condition in coastal Louisiana. Two indices, the floristic quality index (FQI) and a productivity index, are described for herbaceous and forested vegetation. The FQI for herbaceous vegetation is tested with a long-term dataset from a CWPPRA marsh creation project. Example graphics for this index are provided and discussed. The other indices, an FQI for forest vegetation (that is, trees and shrubs) and productivity indices for herbaceous and forest vegetation, are proposed but not tested. New response variables may be added or current response variables removed as data become available and as our understanding of restoration success indicators develops. Once indices are fully developed, each will be used by the vegetation analytical team to assess and evaluate CRMS/CWPPRA project and program effectiveness. The vegetation analytical teams plan to summarize their results in the form of written reports and/or graphics and present these items to CRMS Federal and State sponsors, restoration project managers, landowners, and other data users for their input.
USDA-ARS?s Scientific Manuscript database
Parents may positively influence children's vegetable consumption through effective vegetable parenting practices (VPP). Research has demonstrated three dimensions of effective VPP: Effective Responsiveness, Structure, and Non-Directive Control, but there is limited research investigating each separ...
USDA-ARS?s Scientific Manuscript database
This study reports the modeling of three categories of ineffective vegetable parenting practices (IVPP) separately (responsive, structure, and control vegetable parenting practices). An internet survey was employed for a cross sectional assessment of parenting practices and cognitive-emotional varia...
Predicting Vegetation Condition from ASCAT Soil Water Index over Southwest India
NASA Astrophysics Data System (ADS)
Pfeil, Isabella Maria; Hochstöger, Simon; Amarnath, Giriraj; Pani, Peejush; Enenkel, Markus; Wagner, Wolfgang
2017-04-01
In India, extreme water scarcity events are expected to occur on average every five years. Record-breaking droughts affecting millions of human beings and livestock are common. If the south-west monsoon (summer monsoon) is delayed or brings less rainfall than expected, a season's harvest can be destroyed despite optimal farm management, leading to, in the worst case, life-threatening circumstances for a large number of farmers. Therefore, the monitoring of key drought indicators, such as the healthiness of the vegetation, and subsequent early warning is crucial. The aim of this work is to predict vegetation state from earth observation data instead of relying on models which need a lot of input data, increasing the complexity of error propagation, or seasonal forecasts, that are often too uncertain to be used as a regression component for a vegetation parameter. While precipitation is the main water supply for large parts of India's agricultural areas, vegetation datasets such as the Normalized Difference Vegetation Index (NDVI) provide reliable estimates of vegetation greenness that can be related to vegetation health. Satellite-derived soil moisture represents the missing link between a deficit in rainfall and the response of vegetation. In particular the water available in the root zone plays an important role for near-future vegetation health. Exploiting the added-value of root zone soil moisture is therefore crucial, and its use in vegetation studies presents an added value for drought analyses and decision-support. The soil water index (SWI) dataset derived from the Advanced Scatterometer (ASCAT) on board the Metop satellites represents the water content that is available in the root zone. This dataset shows a strong correlation with NDVI data obtained from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS), which is exploited in this study. A linear regression function is fit to the multi-year SWI and NDVI dataset with a temporal resolution of eight days, returning a set of parameters for every eight-day period of the year. Those parameters are then used to predict vegetation health based on the SWI up to 32 days after the latest available SWI and NDVI observations. In this work, the prediction was carried out for multiple eight-day periods in the year 2015 for three representative districts in India, and then compared to the actually observed NDVI during these periods, showing very similar spatial patterns in most analyzed regions and periods. This approach enables the prediction of vegetation health based on root zone soil moisture instead of relying on agro-meteorological models which often lack crucial input data in remote regions.
Costa, Michel Iskin da Silveira; Meza, Magno Enrique Mendoza
2006-12-01
In a plant-herbivore system, a management strategy called threshold policy is proposed to control grazing intensity where the vegetation dynamics is described by a plant-water interaction model. It is shown that this policy can lead the vegetation density to a previously chosen level under an overgrazing regime. This result is obtained despite both the potential occurrence of vegetation collapse due to overgrazing and the possibility of complex dynamics sensitive to vegetation initial densities and parameter uncertainties.
A test of ecological optimality for semiarid vegetation. M.S. Thesis
NASA Technical Reports Server (NTRS)
Salvucci, Guido D.; Eagleson, Peter S.; Turner, Edmund K.
1992-01-01
Three ecological optimality hypotheses which have utility in parameter reduction and estimation in a climate-soil-vegetation water balance model are reviewed and tested. The first hypothesis involves short term optimization of vegetative canopy density through equilibrium soil moisture maximization. The second hypothesis involves vegetation type selection again through soil moisture maximization, and the third involves soil genesis through plant induced modification of soil hydraulic properties to values which result in a maximum rate of biomass productivity.
Occupancy and abundance of wintering birds in a dynamic agricultural landscape
Miller, Mark W.; Pearlstine, Elise V.; Dorazio, Robert M.; Mazzotti, Frank J.
2011-01-01
Assessing wildlife management action requires monitoring populations, and abundance often is the parameter monitored. Recent methodological advances have enabled estimation of mean abundance within a habitat using presence–absence or count data obtained via repeated visits to a sample of sites. These methods assume populations are closed and intuitively assume habitats within sites change little during a field season. However, many habitats are highly variable over short periods. We developed a variation of existing occupancy and abundance models that allows for extreme spatio-temporal differences in habitat, and resulting changes in wildlife abundance, among sites and among visits to a site within a field season. We conducted our study in sugarcane habitat within the Everglades Agricultural Area southeast of Lake Okeechobee in south Florida. We counted wintering birds, primarily passerines, within 245 sites usually 5 times at each site during December 2006–March 2007. We estimated occupancy and mean abundance of birds in 6 vegetation states during the sugarcane harvest and allowed these parameters to vary temporally or spatially within a vegetation state. Occupancy and mean abundance of the common yellowthroat (Geothlypis trichas) was affected by structure of sugarcane and uncultivated edge vegetation (occupancy=1.00 [95%CĪ=0.96–1.00] and mean abundance=7.9 [95%CĪ=3.2–19.5] in tall sugarcane with tall edge vegetation versus 0.20 [95%CĪ=0.04–0.71] and 0.22 [95%CĪ=0.04–1.2], respectively, in short sugarcane with short edge vegetation in one half of the study area). Occupancy and mean abundance of palm warblers (Dendroica palmarum) were constant (occupancy=1.00, 95%CĪ=0.69–1.00; mean abundance=18, 95%CĪ=1–270). Our model may enable wildlife managers to assess rigorously effects of future edge habitat management on avian distribution and abundance within agricultural landscapes during winter or the breeding season. The model may also help wildlife managers make similar management decisions involving other dynamic habitats such as wetlands, prairies, and even forested areas if forest management or fires occur during the field season.
Occupancy and abundance of wintering birds in a dynamic agricultural landscape
Miller, M.W.; Pearlstine, E.V.; Dorazio, R.M.; Mazzotti, F.J.
2011-01-01
Assessing wildlife management action requires monitoring populations, and abundance often is the parameter monitored. Recent methodological advances have enabled estimation of mean abundance within a habitat using presence-absence or count data obtained via repeated visits to a sample of sites. These methods assume populations are closed and intuitively assume habitats within sites change little during a field season. However, many habitats are highly variable over short periods. We developed a variation of existing occupancy and abundance models that allows for extreme spatio-temporal differences in habitat, and resulting changes in wildlife abundance, among sites and among visits to a site within a field season. We conducted our study in sugarcane habitat within the Everglades Agricultural Area southeast of Lake Okeechobee in south Florida. We counted wintering birds, primarily passerines, within 245 sites usually 5 times at each site during December 2006-March 2007. We estimated occupancy and mean abundance of birds in 6 vegetation states during the sugarcane harvest and allowed these parameters to vary temporally or spatially within a vegetation state. Occupancy and mean abundance of the common yellowthroat (Geothlypis trichas) was affected by structure of sugarcane and uncultivated edge vegetation (occupancy = 1.00 [95%C?? = 0.96-1.00] and mean abundance = 7.9 [95%C?? = 3.2-19.5] in tall sugarcane with tall edge vegetation versus 0.20 [95%C?? = 0.04-0.71] and 0.22 [95%C?? = 0.04-1.2], respectively, in short sugarcane with short edge vegetation in one half of the study area). Occupancy and mean abundance of palm warblers (Dendroica palmarum) were constant (occupancy = 1.00, 95%C?? = 0.69-1.00; mean abundance = 18, 95%C?? = 1-270). Our model may enable wildlife managers to assess rigorously effects of future edge habitat management on avian distribution and abundance within agricultural landscapes during winter or the breeding season. The model may also help wildlife managers make similar management decisions involving other dynamic habitats such as wetlands, prairies, and even forested areas if forest management or fires occur during the field season. ?? 2011 The Wildlife Society.
Stem breakage of salt marsh vegetation under wave forcing: A field and model study
NASA Astrophysics Data System (ADS)
Vuik, Vincent; Suh Heo, Hannah Y.; Zhu, Zhenchang; Borsje, Bas W.; Jonkman, Sebastiaan N.
2018-01-01
One of the services provided by coastal ecosystems is wave attenuation by vegetation, and subsequent reduction of wave loads on flood defense structures. Therefore, stability of vegetation under wave forcing is an important factor to consider. This paper presents a model which determines the wave load that plant stems can withstand before they break or fold. This occurs when wave-induced bending stresses exceed the flexural strength of stems. Flexural strength was determined by means of three-point-bending tests, which were carried out for two common salt marsh species: Spartina anglica (common cord-grass) and Scirpus maritimus (sea club-rush), at different stages in the seasonal cycle. Plant stability is expressed in terms of a critical orbital velocity, which combines factors that contribute to stability: high flexural strength, large stem diameter, low vegetation height, high flexibility and a low drag coefficient. In order to include stem breakage in the computation of wave attenuation by vegetation, the stem breakage model was implemented in a wave energy balance. A model parameter was calibrated so that the predicted stem breakage corresponded with the wave-induced loss of biomass that occurred in the field. The stability of Spartina is significantly higher than that of Scirpus, because of its higher strength, shorter stems, and greater flexibility. The model is validated by applying wave flume tests of Elymus athericus (sea couch), which produced reasonable results with regards to the threshold of folding and overall stem breakage percentage, despite the high flexibility of this species. Application of the stem breakage model will lead to a more realistic assessment of the role of vegetation for coastal protection.
Remote sensing of plant-water relations: An overview and future perspectives.
Damm, A; Paul-Limoges, E; Haghighi, E; Simmer, C; Morsdorf, F; Schneider, F D; van der Tol, C; Migliavacca, M; Rascher, U
2018-04-25
Vegetation is a highly dynamic component of the Earth surface and substantially alters the water cycle. Particularly the process of oxygenic plant photosynthesis determines vegetation connecting the water and carbon cycle and causing various interactions and feedbacks across Earth spheres. While vegetation impacts the water cycle, it reacts to changing water availability via functional, biochemical and structural responses. Unravelling the resulting complex feedbacks and interactions between the plant-water system and environmental change is essential for any modelling approaches and predictions, but still insufficiently understood due to currently missing observations. We hypothesize that an appropriate cross-scale monitoring of plant-water relations can be achieved by combined observational and modelling approaches. This paper reviews suitable remote sensing approaches to assess plant-water relations ranging from pure observational to combined observational-modelling approaches. We use a combined energy balance and radiative transfer model to assess the explanatory power of pure observational approaches focussing on plant parameters to estimate plant-water relations, followed by an outline for a more effective use of remote sensing by their integration into soil-plant-atmosphere continuum (SPAC) models. We apply a mechanistic model simulating water movement in the SPAC to reveal insight into the complexity of relations between soil, plant and atmospheric parameters, and thus plant-water relations. We conclude that future research should focus on strategies combining observations and mechanistic modelling to advance our knowledge on the interplay between the plant-water system and environmental change, e.g. through plant transpiration. Copyright © 2018 Elsevier GmbH. All rights reserved.
Forest Attributes from Radar Interferometric Structure and its Fusion with Optical Remote Sensing
NASA Technical Reports Server (NTRS)
Treuhaft, Robert N.; Law, Beverly E.; Asner, Gregory P.
2004-01-01
The possibility of global, three-dimensional remote sensing of forest structure with interferometric synthetic aperture radar (InSAR) bears on important forest ecological processes, particularly the carbon cycle. InSAR supplements two-dimensional remote sensing with information in the vertical dimension. Its strengths in potential for global coverage complement those of lidar (light detecting and ranging), which has the potential for high-accuracy vertical profiles over small areas. InSAR derives its sensitivity to forest vertical structure from the differences in signals received by two, spatially separate radar receivers. Estimation of parameters describing vertical structure requires multiple-polarization, multiple-frequency, or multiple-baseline InSAR. Combining InSAR with complementary remote sensing techniques, such as hyperspectral optical imaging and lidar, can enhance vertical-structure estimates and consequent biophysical quantities of importance to ecologists, such as biomass. Future InSAR experiments will supplement recent airborne and spaceborne demonstrations, and together with inputs from ecologists regarding structure, they will suggest designs for future spaceborne strategies for measuring global vegetation structure.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Henderson-Sellers, A.
Land-surface schemes developed for incorporation into global climate models include parameterizations that are not yet fully validated and depend upon the specification of a large (20-50) number of ecological and soil parameters, the values of which are not yet well known. There are two methods of investigating the sensitivity of a land-surface scheme to prescribed values: simple one-at-a-time changes or factorial experiments. Factorial experiments offer information about interactions between parameters and are thus a more powerful tool. Here the results of a suite of factorial experiments are reported. These are designed (i) to illustrate the usefulness of this methodology andmore » (ii) to identify factors important to the performance of complex land-surface schemes. The Biosphere-Atmosphere Transfer Scheme (BATS) is used and its sensitivity is considered (a) to prescribed ecological and soil parameters and (b) to atmospheric forcing used in the off-line tests undertaken. Results indicate that the most important atmospheric forcings are mean monthly temperature and the interaction between mean monthly temperature and total monthly precipitation, although fractional cloudiness and other parameters are also important. The most important ecological parameters are vegetation roughness length, soil porosity, and a factor describing the sensitivity of the stomatal resistance of vegetation to the amount of photosynthetically active solar radiation and, to a lesser extent, soil and vegetation albedos. Two-factor interactions including vegetation roughness length are more important than many of the 23 specified single factors. The results of factorial sensitivity experiments such as these could form the basis for intercomparison of land-surface parameterization schemes and for field experiments and satellite-based observation programs aimed at improving evaluation of important parameters.« less
NASA Technical Reports Server (NTRS)
Salmon-Drexler, B. C.
1977-01-01
The premise is the LANDSAT is capable of sensing only a few physical parameters. Much of the contrast provided in LANDSAT data is provided by differences in vegetation cover. Although dominant, vegetation is not the only physical parameter that can be detected with LANDSAT; a ratio of MSS Channel 5 to MSS Channel 4 (R5,4), two visible channels, separates materials by color hue. Additional information is attained by the addition of MSS channels 5 and 4 to approximate brightness, permitting separation of materials by color value. Other spectral combinations may provide correlations with these physical parameters or new ones. An iron absorption in the infrared can also be recognized in LANDSAT data when iron content is present in sufficient percentages, Although by color, limonite-rich soils are distinctive as bright yellow, they are not unique in the R5,4. A fairly strong iron absorption is present in the infrared band MSS Channel 7 for these soils, although the wideband configuration of LANDSAT is not optimal for its enhancement and the effects of vegetation often obscure it.
NASA Astrophysics Data System (ADS)
Jia, S.; Kim, S. H.; Nghiem, S. V.; Kafatos, M.
2017-12-01
Live fuel moisture (LFM) is the water content of live herbaceous plants expressed as a percentage of the oven-dry weight of plant. It is a critical parameter in fire ignition in Mediterranean climate and routinely measured in sites selected by fire agencies across the U.S. Vegetation growing cycle, meteorological metrics, soil type, and topography all contribute to the seasonal and inter-annual variation of LFM, and therefore, the risk of wildfire. The optical remote sensing-based vegetation indices (VIs) have been used to estimate the LFM. Comparing to the VIs, microwave remote sensing products have advantages like less saturation effect in greenness and representing the water content of the vegetation cover. In this study, we established three models to evaluate the predictability of LFM in Southern California using MODIS NDVI, vegetation temperature condition index (VTCI) from downscaled Soil Moisture Active Passive (SMAP) products, and vegetation optical depth (VOD) derived by Land Parameter Retrieval Model. Other ancillary variables, such as topographic factors (aspects and slope) and meteorological metrics (air temperature, precipitation, and relative humidity), are also considered in the models. The model results revealed an improvement of LFM estimation from SMAP products and VOD, despite the uncertainties introduced in the downscaling and parameter retrieval. The estimation of LFM using remote sensing data can provide an assessment of wildfire danger better than current methods using NDVI-based growing seasonal index. Future study will test the VOD estimation from SMAP data using the multi-temporal dual channel algorithm (MT-DCA) and extend the LFM modeling to a regional scale.
Effective Tree Scattering and Opacity at L-Band
NASA Technical Reports Server (NTRS)
Kurum, Mehmet; O'Neill, Peggy E.; Lang, Roger H.; Joseph, Alicia T.; Cosh, Michael H.; Jackson, Thomas J.
2011-01-01
This paper investigates vegetation effects at L-band by using a first-order radiative transfer (RT) model and truck-based microwave measurements over natural conifer stands to assess the applicability of the tau-omega) model over trees. The tau-omega model is a zero-order RT solution that accounts for vegetation effects with effective vegetation parameters (vegetation opacity and single-scattering albedo), which represent the canopy as a whole. This approach inherently ignores multiple-scattering effects and, therefore, has a limited validity depending on the level of scattering within the canopy. The fact that the scattering from large forest components such as branches and trunks is significant at L-band requires that zero-order vegetation parameters be evaluated (compared) along with their theoretical definitions to provide a better understanding of these parameters in the retrieval algorithms as applied to trees. This paper compares the effective vegetation opacities, computed from multi-angular pine tree brightness temperature data, against the results of two independent approaches that provide theoretical and measured optical depths. These two techniques are based on forward scattering theory and radar corner reflector measurements, respectively. The results indicate that the effective vegetation opacity values are smaller than but of similar magnitude to both radar and theoretical estimates. The effective opacity of the zero-order model is thus set equal to the theoretical opacity and an explicit expression for the effective albedo is then obtained from the zero- and first- order RT model comparison. The resultant albedo is found to have a similar magnitude as the effective albedo value obtained from brightness temperature measurements. However, it is less than half of that estimated using the theoretical calculations (0.5 - 0.6 for tree canopies at L-band). This lower observed albedo balances the scattering darkening effect of the large theoretical albedo with a first-order multiple-scattering contribution. The retrieved effective albedo is different from theoretical definitions and not the albedo of single forest elements anymore, but it becomes a global parameter, which depends on all the processes taking place within the canopy, including multiple-scattering.
NASA Astrophysics Data System (ADS)
Xie, Tian; Cui, Baoshan; Bai, Junhong; Li, Shanze; Zhang, Shuyan
2018-02-01
Determining how human disturbance affects plant community persistence and species conservation is one of the most pressing ecological challenges. The large-scale disturbance form defense structures usually have a long-term and potential effect on phytocommunity in coastal saltmarshes. Coastal defense structures usually remove the effect of tidal wave on tidal salt marshes. As a consequence, edaphic factors such as the salinity and moisture contents are disturbed by tidal action blocking. However, few previous studies have explicitly addressed the response of halophyte species persistence and dynamics to the changing edaphic conditions. The understanding of the response of species composition in seed banks and aboveground vegetation to the stress is important to identify ecological effect of coastal defense structures and provide usefully insight into restoration. Here, we conducted a field study to distinguish the density, species composition and relationships of seed bank with aboveground vegetation between tidal flat wetlands with and without coastal defense structures. We also addressed the role of edaphic condition in vegetation degradation caused by coastal defense structures in combination with field monitor and greenhouse experiments. Our results showed the density of the seed bank and aboveground vegetation in the tidal flat without coastal defense structures was significantly lower than the surrounded flat with coastal defense structures. A total of 14 species were founded in the surrounded flat seed bank and 11 species in the tidal flat, but three species were only recorded in aboveground vegetation of the tidal flat which was much lower than 24 aboveground species in the surrounded flat. The absent of species in aboveground vegetation contributed to low germination rate which depend on the edaphic condition. The germination of seeds in the seed bank were inhabited by high soil salinity in the tidal flat and low soil moisture in the surrounded flat. Our study supported the hypothesis that the change of edaphic condition caused by coastal defense structures was the main reason for the difference of the species composition similarity between aboveground vegetation and the soil seed bank between the tidal and surrounded flats. Therefore, mitigating the hydrological disturbance and maintaining the original state of edaphic factors would be useful implications for reducing the ecological effect of defense structure to vegetation communities in coastal salt marshes.
NASA Astrophysics Data System (ADS)
Betbeder, Julie; Fieuzal, Remy; Philippets, Yannick; Ferro-Famil, Laurent; Baup, Frederic
2016-04-01
This paper aims to evaluate the contribution of multitemporal polarimetric synthetic aperture radar (SAR) data for winter wheat and rapeseed crops parameters [height, leaf area index, and dry biomass (DB)] estimation, during their whole vegetation cycles in comparison to backscattering coefficients and optical data. Angular sensitivities and dynamics of polarimetric indicators were also analyzed following the growth stages of these two common crop types using, in total, 14 radar images (Radarsat-2), 16 optical images (Formosat-2, Spot-4/5), and numerous ground data. The results of this study show the importance of correcting the angular effect on SAR signals especially for copolarized signals and polarimetric indicators associated to single-bounce scattering mechanisms. The analysis of the temporal dynamic of polarimetric indicators has shown their high potential to detect crop growth changes. Moreover, this study shows the high interest of using SAR parameters (backscattering coefficients and polarimetric indicators) for crop parameters estimation during the whole vegetation cycle instead of optical vegetation index. They particularly revealed their high potential for rapeseed height and DB monitoring [i.e., Shannon entropy polarimetry (r2=0.70) and radar vegetation index (r2=0.80), respectively].
Wu, Jun-Jun; Gao, Zhi-Hai; Li, Zeng-Yuan; Wang, Hong-Yan; Pang, Yong; Sun, Bin; Li, Chang-Long; Li, Xu-Zhi; Zhang, Jiu-Xing
2014-03-01
In order to estimate the sparse vegetation information accurately in desertification region, taking southeast of Sunite Right Banner, Inner Mongolia, as the test site and Tiangong-1 hyperspectral image as the main data, sparse vegetation coverage and biomass were retrieved based on normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), combined with the field investigation data. Then the advantages and disadvantages between them were compared. Firstly, the correlation between vegetation indexes and vegetation coverage under different bands combination was analyzed, as well as the biomass. Secondly, the best bands combination was determined when the maximum correlation coefficient turned up between vegetation indexes (VI) and vegetation parameters. It showed that the maximum correlation coefficient between vegetation parameters and NDVI could reach as high as 0.7, while that of SAVI could nearly reach 0.8. The center wavelength of red band in the best bands combination for NDVI was 630nm, and that of the near infrared (NIR) band was 910 nm. Whereas, when the center wavelength was 620 and 920 nm respectively, they were the best combination for SAVI. Finally, the linear regression models were established to retrieve vegetation coverage and biomass based on Tiangong-1 VIs. R2 of all models was more than 0.5, while that of the model based on SAVI was higher than that based on NDVI, especially, the R2 of vegetation coverage retrieve model based on SAVI was as high as 0.59. By intersection validation, the standard errors RMSE based on SAVI models were lower than that of the model based on NDVI. The results showed that the abundant spectral information of Tiangong-1 hyperspectral image can reflect the actual vegetaion condition effectively, and SAVI can estimate the sparse vegetation information more accurately than NDVI in desertification region.
NASA Astrophysics Data System (ADS)
Novenko, E. Yu; Tsyganov, A. N.; Olchev, A. V.
2018-01-01
New multi-proxy records (pollen, testate amoebae, and charcoal) were applied to reconstruct the vegetation dynamics in the boreal forest area of the southern part of Valdai Hills (the Central Forest Biosphere Reserve) during the Holocene. The reconstructions of the mean annual temperature and precipitation, the climate moisture index (CMI), peatland surface moisture, and fire activity have shown that climate change has a significant impact on the boreal forests of European Russia. Temperature growth and decreased moistening during the warmest phases of the Holocene Thermal Maximum in 7.0-6.2 ka BP and 6.0-5.5 ka BP and in the relatively warm phase in 3.4-2.5 ka BP led to structural changes in plant communities, specifically an increase in the abundance of broadleaf tree species in forest stands and the suppression of Picea. The frequency of forest fires was higher in that period, and it resulted in the replacement of spruce forests by secondary stands with Betula and Pinus. Despite significant changes in the climatic parameters projected for the 21st century using even the optimistic RCP2.6 scenario, the time lag between climate changes and vegetation responses makes any catastrophic vegetation disturbances (due to natural reasons) in the area in the 21st century unlikely.
Busing, Richard T.; Solomon, Allen M.
2005-01-01
An individual-based model of forest dynamics (FORCLIM) was tested for its ability to simulate forest composition and structure in the Pacific Northwest region of North America. Simulation results across gradients of climate and disturbance were compared to forest survey data from several vegetation zones in western Oregon. Modelled patterns of tree species composition, total basal area and stand height across climate gradients matched those in the forest survey data. However, the density of small stems (<50 cm DBH) was underestimated by the model. Thus actual size-class structure and other density-based parameters of stand structure were not simulated with high accuracy. The addition of partial-stand disturbances at moderate frequencies (<0.01 yr-1) often improved agreement between simulated and actual results. Strengths and weaknesses of the FORCLIM model in simulating forest dynamics and structure in the Pacific Northwest are discussed.
Pinzi, S; Gandía, L M; Arzamendi, G; Ruiz, J J; Dorado, M P
2011-01-01
Presence of unreacted glycerides in biodiesel may reduce drastically its quality. This is why conversion of raw material in biodiesel through transesterification needs to readjust reaction parameter values to complete. In the present work, monitoring of glycerides transformation in biodiesel during the transesterification of vegetable oils was carried out. To check the influence of the chemical composition on glycerides conversion, selected vegetable oils covered a wide range of fatty acid composition. Reactions were carried out under alkali-transesterification in the presence of methanol. In addition, a multiple regression model was proposed. Results showed that kinetics depends on chemical and physical properties of the oils. It was found that the optimal reaction temperature depends on both length and unsaturation degree of vegetable oils fatty acid chains. Vegetable oils with higher degree of unsaturation exhibit faster monoglycerides conversion to biodiesel. It can be concluded that fatty acid composition influences reaction parameters and glycerides conversion, hence biodiesel yield and economic viability. Copyright © 2010 Elsevier Ltd. All rights reserved.
[Soil infiltration characteristics under main vegetation types in Anji County of Zhejiang Province].
Liu, Dao-Ping; Chen, San-Xiong; Zhang, Jin-Chi; Xie, Li; Jiang, Jiang
2007-03-01
The study on the soil infiltration under different main vegetation types in Anji County of Zhejiang Province showed that the characteristics of soil infiltration differed significantly with land use type, and the test eight vegetation types could be classified into four groups, based on soil infiltration capability. The first group, deciduous broadleaved forest, had the strongest soil infiltration capability, and the second group with a stronger soil infiltration capability was composed of grass, pine forest, shrub community and tea bush. Bamboo and evergreen broadleaved forest were classified into the third group with a relatively strong soil infiltration capability, while bare land belonged to the fourth group because of the bad soil structure and poorest soil infiltration capability. The comprehensive parameters of soil infiltration (alpha) and root (beta) were obtained by principal component analysis, and the regression model of alpha and beta could be described as alpha = 0. 1708ebeta -0. 3122. Soil infiltration capability was greatly affected by soil physical and chemical characteristics and root system. Fine roots (< or = 1 mm in diameter) played effective roles on the improvement of soil physical and chemical properties, and the increase of soil infiltration capability was closely related to the amount of the fine roots.
Fisher, R. A.; Muszala, S.; Verteinstein, M.; ...
2015-04-29
We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leafmore » trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fisher, R. A.; Muszala, S.; Verteinstein, M.
We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leafmore » trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.« less
NASA Astrophysics Data System (ADS)
Vescovo, L.; Gianelle, D.; Marcolla, B.; Zaldei, A.; Sakowska, K.
2013-12-01
Linking optical remote sensing with carbon fluxes and biophysical parameters is critical to exploit spatial and temporal extensive information useful for validating model simulations at different scales. Proximal sensing is fundamental to quantify and understand the seasonal dynamics of ecosystems and to upscale the observations carried out at the ground level. In this study, we present the results from an ongoing research project at the FLUXNET eddy covariance site of Monte Bondone (Italy). The site is located at 1550 m a.s.l. on a mountain plateau in the Italian Alps (Viote del Monte Bondone). The area is managed as an extensively-managed meadow, cut once a year, and dominated by Nardus stricta and Festuca nigrescens. The climate of this area is sub-continental (warm and wet summer), with precipitation peaks in spring and autumn. A new hyperspectral system (WhiteRef Box, developed by Fondazione Edmund Mach in collaboration with the Institute of Biometeorology, CNR, Italy) based on the ASD FieldSpec spectrometer (spectral range 350-2500 nm, resolution ~3 nm at 700 nm) was designed to acquire continuous radiometric measurements. The system was installed on the eddy covariance tower at a height of 6 m, with a field of view of 25°. To obtain reflectance values, white panel radiance spectra and canopy radiance spectra were collected every 5 minutes between 10:00 a.m. and 1:00 p.m. (solar time) during the growing season of 2013. In addition, measurements of biophysical parameters such as above-ground biomass, fraction of Absorbed Photosynthetically Active Radiation (fAPAR), Plant Area Index, Canopy Chlorophyll Content, Canopy Water Content and Green Herbage Ratio were performed at weekly intervals within the spectrometer footprint (~5 m2). In this work, we present some preliminary results regarding the potential of spectral vegetation indices - based on VNIR and SWIR spectral bands- for capturing seasonal trends of CO2 fluxes as well as vegetation biophysical parameters dynamics. Spectral vegetation indices sensitive to chlorophyll content (such as Meris Terrestrial ChIorophyll Index, Vogelmann Indices) showed a good linear correlation with fAPAR, daily Gross Primary Production and chlorophyll content (R2> 0.8 for all the three variables). The SWIR-based Vegetation Indices (e.g. Normalised Difference Infrared Index, Moisture Stress Index) confirmed their ability to estimate Canopy Water Content. Most of the analyzed indices showed to be linearly related with Green Herbage Ratio (explaining more than 80% of variance). The Near Infrared Difference Index (Vescovo et al., 2012) confirmed his potential in predicting canopy structural parameters such as Plant Area Index and biomass (R2> 0.90).
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.
Stephenson, N.L.
1998-01-01
Correlative approaches to understanding the climatic controls of vegetation distribution have exhibited at least two important weaknesses: they have been conceptually divorced across spatial scales, and their climatic parameters have not necessarily represented aspects of climate of broad physiological importance to plants. Using examples from the literature and from the Sierra Nevada of California, I argue that two water balance parameters-actual evapotranspiration (AET) and deficit (D)-are biologically meaningful, are well correlated with the distribution of vegetation types, and exhibit these qualities over several orders of magnitude of spatial scale (continental to local). I reach four additional conclusions. (1) Some pairs of climatic parameters presently in use are functionally similar to AET and D; however, AET and D may be easier to interpret biologically. (2) Several well-known climatic parameters are biologically less meaningful or less important than AET and D, and consequently are poorer correlates of the distribution of vegetation types. Of particular interest, AET is a much better correlate of the distributions of coniferous and deciduous forests than minimum temperature. (3) The effects of evaporative demand and water availability on a site's water balance are intrinsically different. For example, the 'dry' experienced by plants on sunward slopes (high evaporative demand) is not comparable to the 'dry' experienced by plants on soils with low water-holding capacities (low water availability), and these differences are reflected in vegetation patterns. (4) Many traditional topographic moisture scalars-those that additively combine measures related to evaporative demand and water availability are not necessarily meaningful for describing site conditions as sensed by plants; the same holds for measured soil moisture. However, using AET and D in place of moisture scalars and measured soil moisture can solve these problems.
Connectivity processes and riparian vegetation of the upper Paraná River, Brazil
NASA Astrophysics Data System (ADS)
Stevaux, José C.; Corradini, Fabrício A.; Aquino, Samia
2013-10-01
In fluvial systems, the relationship between a dominant variable (e.g. flood pulse) and its dependent ones (e.g. riparian vegetation) is called connectivity. This paper analyzes the connectivity elements and processes controlling riparian vegetation for a reach of the upper Paraná River (Brazil) and estimates the future changes in channel-vegetation relationship as a consequence of the managing of a large dam. The studied reach is situated 30 km downstream from the Porto Primavera Dam (construction finished in 1999). Through aerial photography (1:25,000, 1996), RGB-CBERS satellite imagery and a previous field botany survey it was possible to elaborate a map with the five major morpho-vegetation units: 1) Tree-dominated natural levee, 2) Shrubby upper floodplain, 3) Shrub-herbaceous mid floodplain, 4) Grass-herbaceous lower floodplain and 5) Shrub-herbaceous flood runoff channel units. By use of a detailed topographic survey and statistical tools each morpho-vegetation type was analyzed according to its connectivity parameters (frequency, recurrence, permanence, seasonality, potamophase, limnophase and FCQ index) in the pre- and post-dam closure periods of the historical series. Data showed that most of the morpho-vegetation units were predicted to present changes in connectivity parameters values after dam closing and the new regime could affect, in different intensity, the river ecology and particularly the riparian vegetation. The methods used in this study can be useful for dam impact studies in other South American tropical rivers.
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.
NASA Astrophysics Data System (ADS)
Wanthongchai, Dr.; Bauhus, Prof.; Goldammer, Prof.
2009-04-01
Anthropogenic burning in dry dipterocarp forests (DDF) has become a common phenomenon throughout Thailand. It is feared that too frequent fires may affect vegetation structure and composition and thus impact on ecosystem productivity. The aim of this study was to quantify the effects of prescribed fires on sites with different past burning regimes on vegetation structure and composition in the Huay Kha Khaeng Wildlife Sanctuary (HKK), Thailand. Fire frequency was determined from satellite images and ranged from frequent, infrequent, rare and unburned with fire occurrences of 7, 2, 1 and 0 out of the past 10 years, respectively. The pre-burn fuel loads, the overstorey and understorey vegetation structure and composition were determined to investigate the effects of the contrasting past burning regimes. The burning experiment was carried out, applying a three-strip head-fire burning technique. The vegetation structure and composition were sampled again one year after the fire to assess the fire impacts. Aboveground fine fuel loads increased with the length of fire-free interval. The woody plant structures of the frequently burned stand differed from those of the other less frequently burned stands. The species composition of the overstorey on the frequently burned site, in particular that of small sized trees (4.5-10 cm dbh), also differed significantly from that of the other sites. Whilst the ground vegetation including shrubs and herbs did not differ between the past burning regimes, frequent burning obviously promoted the proliferation of graminoid vegetation. There was no clear evidence showing that the prescribed fires affected the mortality of trees (dbh> 4.5 cm) on the sites of the different past burning regimes. The effects of prescribed burning on the understorey vegetation structures varied between the past burning regimes and the understorey vegetation type. Therefore, it is recommended that the DDF at HKK should be subjected to a prescribed fire frequency not shorter than every 6-7 years, or 1-2 fires per decade, to maintain ecosystem structure and function. Variation in time and space in this way, the biodiversity of the landscape may be maintained for the long-term. Keywords: Prescribed burning, burning history, burning frequency, plant species, vegetation structure, dry dipterocarp forest, Huay Kha Khaeng wildlife Sanctuary
Theory of stability, and regulation and control of ecological system in oasis
NASA Astrophysics Data System (ADS)
Pan, Xiaoling; Chao, Jiping
2003-06-01
Starting with analysis on the evolving course of oasis and the characteristics and evolution of transitional zone between oasis and desert, in consideration of ecological elements including plant stomata resistance, area covered by vegetation, and physical elements including albedo of vegetation and bare soil, atmosphere temperature, and humidity, under the condition of the balance among net radiation flux, latent heat flux, and sensible heat flux, the following are calculated: temperatures of vegetation and bare soil in different conditions, as well as the evapotranspiration rate of ecosystem. Analysis on evapotranspiration rate indicates that it depends on both the climate of environment and the physiological and ecological conditions of plants. On certain conditions, the evapotranspiration rate of transitional zone between oasis and desert (i.e. area covered by vegetation less than 20%), in some parameter domains, appears in bifurcation or multiequilibrium state. Meanwhile, in such area, ecosystem is extremely unstable. Any minor change to the balance will cause either increase or reduction of area covered by vegetation in ecosystem, on the basis of discussion on the emergency of these phenomena. This paper is attempting to propose an effective way of destruction and rebuilt ecosystem in transitional zone. The way is to control the evaporation of plant through selecting anti-drought country plant with big stomata resistance, and modify the roughness of the underlying surface in ecosystem by establishing rational interspace structure of plant community, so as to put the degenerative ecosystem into the natural succession track. This primary theory is being verified through observation and analysis on historical data.
NASA Astrophysics Data System (ADS)
Gonzales, H. B.; Ravi, S.; Li, J. J.; Sankey, J. B.
2016-12-01
Hydrological and aeolian processes control the redistribution of soil and nutrients in arid and semi arid environments thereby contributing to the formation of heterogeneous patchy landscapes with nutrient-rich resource islands surrounded by nutrient depleted bare soil patches. The differential trapping of soil particles by vegetation canopies may result in textural changes beneath the vegetation, which, in turn, can alter the hydrological processes such as infiltration and runoff. We conducted infiltration experiments and soil grain size analysis of several shrub (Larrea tridentate) and grass (Bouteloua eriopoda) microsites and in a heterogeneous landscape in the Chihuahuan desert (New Mexico, USA). Our results indicate heterogeneity in soil texture and infiltration patterns under grass and shrub microsites. We assessed the trapping effectiveness of vegetation canopies using a novel computational fluid dynamics (CFD) approach. An open-source software (OpenFOAM) was used to validate the data gathered from particle size distribution (PSD) analysis of soil within the shrub and grass microsites and their porosities (91% for shrub and 68% for grass) determined using terrestrial LiDAR surveys. Three-dimensional architectures of the shrub and grass were created using an open-source computer-aided design (CAD) software (Blender). The readily available solvers within the OpenFOAM architecture were modified to test the validity and optimize input parameters in assessing trapping efficiencies of sparse vegetation against aeolian sediment flux. The results from the numerical simulations explained the observed textual changes under grass and shrub canopies and highlighted the role of sediment trapping by canopies in structuring patch-scale hydrological processes.
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.
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.
Hu, Ning; Li, Hui; Tang, Zheng; Li, Zhongfang; Tian, Jing; Lou, Yilai; Li, Jianwei; Li, Guichun; Hu, Xiaomin
2016-06-17
We examined community diversity, structure and carbon footprint of nematode food web along a chronosequence of T. Sinensis reforestation on degraded Karst. In general, after the reforestation: a serious of diversity parameters and community indices (Shannon-Weinier index (H'), structure index (SI), etc.) were elevated; biomass ratio of fungivores to bacterivores (FFC/BFC), and fungi to bacteria (F/B) were increased, and nematode channel ratio (NCR) were decreased; carbon footprints of all nematode trophic groups, and biomass of bacteria and fungi were increased. Our results indicate that the Karst aboveground vegetation restoration was accompanied with belowground nematode food web development: increasing community complexity, function and fungal dominance in decomposition pathway, and the driving forces included the bottom-up effect (resource control), connectedness of functional groups, as well as soil environments.
Hu, Ning; Li, Hui; Tang, Zheng; Li, Zhongfang; Tian, Jing; Lou, Yilai; Li, Jianwei; Li, Guichun; Hu, Xiaomin
2016-01-01
We examined community diversity, structure and carbon footprint of nematode food web along a chronosequence of T. Sinensis reforestation on degraded Karst. In general, after the reforestation: a serious of diversity parameters and community indices (Shannon-Weinier index (H′), structure index (SI), etc.) were elevated; biomass ratio of fungivores to bacterivores (FFC/BFC), and fungi to bacteria (F/B) were increased, and nematode channel ratio (NCR) were decreased; carbon footprints of all nematode trophic groups, and biomass of bacteria and fungi were increased. Our results indicate that the Karst aboveground vegetation restoration was accompanied with belowground nematode food web development: increasing community complexity, function and fungal dominance in decomposition pathway, and the driving forces included the bottom-up effect (resource control), connectedness of functional groups, as well as soil environments. PMID:27311984
[Green space vegetation quantity in workshop area of Wuhan Iron and Steel Company].
Chen, Fang; Zhou, Zhixiang; Wang, Pengcheng; Li, Haifang; Zhong, Yingfei
2006-04-01
Aimed at the complex community structure and higher fragmentation of urban green space, and based on the investigation of synusia structure and its coverage, this paper studied the vegetation quantity of ornamental green space in the workshop area of Wuhan Iron and Steel Company, with the help of GIS. The results showed that different life forms of ornamental plants in this area had a greater difference in their single leaf area and leaf area index (LAI), and the LAI was not only depended on single leaf area, but also governed by the shape of tree crown and the intensive degree of branches and leaves. The total vegetation quantity was 1 694.2 hm2, with the average LAI being 7.75, and the vegetation quantity of arbor-shrub-herb and arbor-shrub communities accounted for 79.7% and 92.3% of the total, respectively, reflecting that the green space structure was dominated by arbor species and by arbor-shrub-herb and arbor-shrub community types. Single layer-structured lawn had a less percentage, while the vegetation quantity of herb synusia accounted for 22.9% of the total, suggesting an afforestation characteristic of "making use of every bit of space" in the workshop area. The vegetation quantity of urban ornamental green space depended on the area of green space, its synusia structure, and the LAI and coverage of ornamental plants. In enlarging urban green space, ornamental plant species with high LAI should be selected, and community structure should be improved to have a higher vegetation quantity in urban area. To quantify the vegetation quantity of urban ornamental green space more accurately, synusia should be taken as the unit to measure the LAI of typical species, and the synusia structure and its coverage of different community types should be investigated with the help of remote sensing images and GIS.
A Multi-Scale Sampling Strategy for Detecting Physiologically Significant Signals in AVIRIS Imagery
NASA Technical Reports Server (NTRS)
Gamon, John A.; Lee, Lai-Fun; Qiu, Hong-Lie; Davis, Stephen; Roberts, Dar A.; Ustin, Susan L.
1998-01-01
Models of photosynthetic production at ecosystem and global scales require multiple input parameters specifying physical and physiological surface features. While certain physical parameters (e.g., absorbed photosynthetically active radiation) can be derived from current satellite sensors, other physiologically relevant measures (e.g., vegetation type, water status, carboxylation capacity, or photosynthetic light-use efficiency), are not generally directly available from current satellite sensors at the appropriate geographic scale. Consequently, many model parameters must be assumed or derived from independent sources, often at an inappropriate scale. An abundance of ecophysiological studies at the leaf and canopy scales suggests strong physiological control of vegetation-atmosphere CO2 and water vapor fluxes, particularly in evergreen vegetation subjected to diurnal or seasonal stresses. For example hot, dry conditions can lead to stomatal closure, and associated "downregulation" of photosynthetic biochemical processes, a phenomenon often manifested as a "midday photosynthetic depression". A recent study with the revised simple biosphere (SiB2) model demonstrated that photosynthetic downregulation can significantly impact global climate. However, at the global scale, the exact significance of downregulation remains unclear, largely because appropriate physiological measures are generally unavailable at this scale. Clearly, there is a need to develop reliable ways of extracting physiologically relevant information from remote sensing. Narrow-band spectrometers offer many opportunities for deriving physiological parameters needed for ecosystem and global scale photosynthetic models. Experimental studies on the ground at the leaf- to stand-scale have indicated that several narrow-band features can be used to detect plant physiological status. One physiological signal is caused by xanthophyll cycle pigment activity, and is often expressed as the Photochemical Reflectance Index (PRI). Because the xanthophyll cycle pigments are photoregulatory pigments closely linked to photosynthetic function, this index can be used to derive relative photosynthetic rates. An additional signal with physiological significance is the 970 nm water absorption band, which provides a measure of liquid water content. This feature has been quantified both using a simple 2-band ratio (900/970 nm, here referred to as the "Water Band Index" or WBI;), and using the "continuum removal" method. Current atmospheric correction methods for AVIRIS imagery also obtain quantitative expressions of surface liquid water absorption based on the 970 nm water band and may be comparable to ground-based estimates of water content using this feature. However, physiological interpretations of both the PRI and the WBI are best understood at the leaf and canopy scales, where complications of atmospheric interference and complex stand and landscape features can be minimized, and where experimental manipulations can be readily applied. Currently it is not known whether these physiological indices can be used to derive meaningful physiological information from AVIRIS imagery. In addition to the problem of atmospheric interference, another challenge is that any simple physiological index can be confounded by multiple factors unrelated to physiology, and this problem can become more severe at progressively larger spatial scales. For example, previous work has suggested that both the PRI and the WBI, are strongly correlated with other optical measures of canopy structure (e.g., the Normalized Difference Vegetation Index or green vegetation fraction), indicating a confounding effect of structure on physiological signals at the larger, landscape scale. Furthermore, the normal operating mode of most imaging spectrometers does not allow simultaneous, ground truthing at a level of detail needed for physiological sampling. Additionally, manipulative experiments of physiology are difficult to apply at a geographic scale suitable for comparison with remote imagery, which often works at spatial scales that are several orders of magnitude larger than those typically used for physiological studies. These limitations require the consideration of alternative approaches to validating physiological information derived from AVIRIS data. In this report, we present a multi-scale sampling approach to detecting physiologically significant signals in narrow-band spectra. This approach explores the multi-dimensional data space provided by narrow-band spectrometry, and combines AVIRIS imagery at a large scale, with ground spectral sampling at an intermediate scale, and detailed ecophysiological measurements at a fine scale, to examine seasonally and spatially changing relationships between multiple structural and physiological variables. Examples of this approach are provided by simultaneous sampling of the Normalized Difference Vegetation Index (NDVI), an index of fractional PAR interception and green vegetation cover, the Water Band Index (WBI, an index of liquid water absorption, and the Photochemical Reflectance Index (PRI, an index of xanthophyll cycle pigment activity and photosynthetic light-use efficiency. By directly linking changing optical properties sampled on the ground with measurable physiological states, we hope to develop a basis for interpreting similar signals in AVIRIS imagery.
Optimization of lamp spectrum for vegetable growth
NASA Technical Reports Server (NTRS)
Prikupets, L. B.; Tikhomirov, A. A.
1994-01-01
An increase in the demand for and production of vegetables in the winter, mainly in northern and Siberian regions, inevitably leads to mass building of structures for growing plants under completely artificial conditions. An industrial lighting technology is required whose main parameters (spectrum, irradiance, photoperiod) should be assigned carefully and should uniquely determine, along with other important characteristics of the artificial climate, the productivity of the plant-production facility. The most widespread crops grown in our country under indoor conditions are cucumber and tomato plants, which account for more than 98% of the area in greenhouses. These plants are good prospects for growing completely under intense artificial lighting conditions (photocultures). Optimization of the main parameters of optical radiation when growing these plants is the most important task of achieving their profitable production. At present, considerable experience has been gained in studying the dependence of productivity of cucumber and tomato communities on irradiation conditions. Fundamental studies of the Agrophysical Research Institute of the Russian Academy of Sciences, Timiryazev Institute of Plant Physiology of the Russian Academy of Sciences, Timiryazev Agricultural Academy, and other institutes create a good basis for a detailed study of the given problem. Commercial sources of radiation substantially differing in spectral characteristics in the region of photosynthetically active radiation (PAR) were used in the studies.
Hewlette S. Crawford
1976-01-01
The impacts of forest cutting upon understory vegetation were evaluated for Ozark oak-hickory and Appalachian oak-pine stands. These findings were related to similar information from other eastern forest types. Production of understory vegetation is related to stand type, stand structure, stand disturbance, and site. Stand type, structure, and site operate together to...
NASA Astrophysics Data System (ADS)
Wang, X.; Huang, Z.; Zhao, Y.; Hong, M.
2017-12-01
Natural vegetation and artificial plantation are the most important measures for ecological restoration in soil erosion and landslide hazard-prone regions of China. Previous studies have demonstrated that both measures can significantly change the soil structure and decrease soil and water erosion. Few reports have compared the effects of the two contrasting measures on mechanical and hydrological properties and further tested the differentiate responses of soil structure. In the study areas, two vegetation restoration measures-natural vegetation restoration (NVR) and artificial plantation restoration (APR) compared with control site, with similar topographical and geological backgrounds were selected to investigate the different effects on soil structure based on eight-year ecological restoration projects. The results showed that the surface vegetation played an important role in releasing soil erosion and enhance soil structure stability through change the soil aggregates (SA) and total soil porosity (TSP). The SA<0.25mm content in NVR (36.13%) was higher than that in APR (32.14%). The study indicated that SA and TSP were the principal components (PCs) related to soil structure variation. Soil organic carbon, soil water retention, clay and vegetation biomass were more strongly correlated with the PCs in NVR than those in APR. The study indicated that NVR was more beneficial for soil structure stability than APR. These findings will provide a theoretical basis for the decisions around reasonable land use for ecological restoration and conservation in geological hazard-prone regions.
Ecosystem engineering by a colonial mammal: how prairie dogs structure rodent communities.
VanNimwegen, Ron E; Kretzer, Justin; Cully, Jack F
2008-12-01
As ecosystem engineers, prairie dogs (Cynomys spp.) physically alter their environment, but the mechanism by which these alterations affect associated faunal composition is not well known. We examined how rodent and vegetation communities responded to prairie dog colonies and landcover at the Cimarron National Grassland in southwest Kansas, USA. We trapped rodents and measured vegetation structure on and off colonies in 2000 and 2003. We plotted two separate ordinations of trapping grids: one based on rodent counts and a second based on vegetation variables. We regressed three factors on each ordination: (1) colony (on-colony and off-colony), (2) cover (shortgrass and sandsage), and (3) habitat (factorial cross of colony x cover). Rodent communities differed by colony but not cover. Vegetation differed across both gradients. Rodent responses to habitat reflected those of colony and cover, but vegetation was found to differ across cover only in the sandsage prairie. This interaction suggested that rodent composition responded to prairie dog colonies, but independently of vegetation differences. We conclude that burrowing and soil disturbance are more important than vegetation cropping in structuring rodent communities.
Choosing a DIVA: a comparison of emerging digital imagery vegetation analysis techniques
Jorgensen, Christopher F.; Stutzman, Ryan J.; Anderson, Lars C.; Decker, Suzanne E.; Powell, Larkin A.; Schacht, Walter H.; Fontaine, Joseph J.
2013-01-01
Question: What is the precision of five methods of measuring vegetation structure using ground-based digital imagery and processing techniques? Location: Lincoln, Nebraska, USA Methods: Vertical herbaceous cover was recorded using digital imagery techniques at two distinct locations in a mixed-grass prairie. The precision of five ground-based digital imagery vegetation analysis (DIVA) methods for measuring vegetation structure was tested using a split-split plot analysis of covariance. Variability within each DIVA technique was estimated using coefficient of variation of mean percentage cover. Results: Vertical herbaceous cover estimates differed among DIVA techniques. Additionally, environmental conditions affected the vertical vegetation obstruction estimates for certain digital imagery methods, while other techniques were more adept at handling various conditions. Overall, percentage vegetation cover values differed among techniques, but the precision of four of the five techniques was consistently high. Conclusions: DIVA procedures are sufficient for measuring various heights and densities of standing herbaceous cover. Moreover, digital imagery techniques can reduce measurement error associated with multiple observers' standing herbaceous cover estimates, allowing greater opportunity to detect patterns associated with vegetation structure.
Assessing the drivers shaping global patterns of urban vegetation landscape structure.
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.
Remote sensing of solar radiation absorbed and reflected by vegetated land surfaces
NASA Technical Reports Server (NTRS)
Myneni, Ranga B.; Asrar, Ghassem; Tanre, Didier; Choudhury, Bhaskar J.
1992-01-01
1D and 3D radiative-transfer models have been used to investigate the problem of remotely sensed determination of vegetated land surface-absorbed and reflected solar radiation. Calculations were conducted for various illumination conditions to determine surface albedo, soil- and canopy-absorbed photosynthetically active and nonactive radiation, and normalized difference vegetation index. Simple predictive models are developed on the basis of the relationships among these parameters.
Pollen assemblages as paleoenvironmental proxies in the Florida Everglades
Willard, D.A.; Weimer, L.M.; Riegel, W.L.
2001-01-01
Analysis of 170 pollen assemblages from surface samples in eight vegetation types in the Florida Everglades indicates that these wetland sub-environments are distinguishable from the pollen record and that they are useful proxies for hydrologic and edaphic parameters. Vegetation types sampled include sawgrass marshes, cattail marshes, sloughs with floating aquatics, wet prairies, brackish marshes, tree islands, cypress swamps, and mangrove forests. The distribution of these vegetation types is controlled by specific environmental parameters, such as hydrologic regime, nutrient availability, disturbance level, substrate type, and salinity; ecotones between vegetation types may be sharp. Using R-mode cluster analysis of pollen data, we identified diagnostic species groupings; Q-mode cluster analysis was used to differentiate pollen signatures of each vegetation type. Cluster analysis and the modern analog technique were applied to interpret vegetational and environmental trends over the last two millennia at a site in Water Conservation Area 3A. The results show that close modern analogs exist for assemblages in the core and indicate past hydrologic changes at the site, correlated with both climatic and land-use changes. The ability to differentiate marshes with different hydrologic and edaphic requirements using the pollen record facilitates assessment of relative impacts of climatic and anthropogenic changes on this wetland ecosystem on smaller spatial and temporal scales than previously were possible. ?? 2001 Elsevier Science B.V.
NASA Technical Reports Server (NTRS)
Kotada, K.; Nakagawa, S.; Kai, K.; Yoshino, M. M.; Takeda, K.; Seki, K.
1985-01-01
In order to study the distribution of evapotranspiration in the humid region using remote sensing technology, the parameter (alpha) in the Priestley-Taylor model was determined. The daily means of the parameter alpha = 1.14 can be available from summer to autumn and alpha = to approximately 2.0 in winter. The results of the satellite and the airborne sensing done on 21st and 22nd January, 1983, are described. Using the vegetation distribution in the Tsukuba Academic New Town, as well as the radiation temperature obtained by remote sensing and the radiation data observed at the ground surface, the evapotranspiration was calculated for each vegetation type by the Priestley-Taylor method. The daily mean evapotranspiration on 22nd January, 1983, was approximately 0.4 mm/day. The differences in evapotranspiration between the vegetation types were not detectable, because the magnitude of evapotranspiration is very little in winter.
NASA Astrophysics Data System (ADS)
Wohlfahrt, Georg; Hammerle, Albin; Tomelleri, Enrico
2015-04-01
Radiation reflected back from an ecosystem carries a spectral signature resulting from the interaction of radiation with the vegetation canopy and the underlying soil and thus allows drawing conclusions about the structure and functioning of an ecosystem. When this information is linked to a model of the leaf CO2 exchange, the ecosystem-scale CO2 exchange can be simulated. A well-known and very simplistic example for this approach is the light-use efficiency (LUE) model proposed by Monteith which links the flux of absorbed photosynthetically active radiation times a LUE parameter, both of which may be estimated based on remote sensing data, to predict the ecosystem gross photosynthesis. Here we explore the ability of a more elaborate approach by using near-surface remote sensing of hyperspectral reflected radiation, eddy covariance CO2 and energy flux measurements and a coupled radiative transfer and soil-vegetation-atmosphere-transfer (SVAT) model. Our main objective is to understand to what degree the joint assimilation of hyperspectral reflected radiation and eddy covariance flux measurements into the model helps to better constrain model parameters. To this end we use the SCOPE model, a combination of the well-known PROSAIL model and a SVAT model, and the Bayesian inversion algorithm DREAM. In order to explicitly link reflectance in the visible light and the leaf CO2 exchange, a novel parameterisation of the maximum carboxylation capacity parameter (Vcmax) on the leaf a+b chlorophyll content parameter of PROSAIL is introduced. Results are discussed with respect to the additional information content the hyperspectral data yield for simulating canopy photosynthesis.
NASA Astrophysics Data System (ADS)
Meusburger, K.; Konz, N.; Schaub, M.; Alewell, C.
2010-06-01
The focus of soil erosion research in the Alps has been in two categories: (i) on-site measurements, which are rather small scale point measurements on selected plots often constrained to irrigation experiments or (ii) off-site quantification of sediment delivery at the outlet of the catchment. Results of both categories pointed towards the importance of an intact vegetation cover to prevent soil loss. With the recent availability of high-resolution satellites such as IKONOS and QuickBird options for detecting and monitoring vegetation parameters in heterogeneous terrain have increased. The aim of this study is to evaluate the usefulness of QuickBird derived vegetation parameters in soil erosion models for alpine sites by comparison to Cesium-137 (Cs-137) derived soil erosion estimates. The study site (67 km 2) is located in the Central Swiss Alps (Urseren Valley) and is characterised by scarce forest cover and strong anthropogenic influences due to grassland farming for centuries. A fractional vegetation cover (FVC) map for grassland and detailed land-cover maps are available from linear spectral unmixing and supervised classification of QuickBird imagery. The maps were introduced to the Pan-European Soil Erosion Risk Assessment (PESERA) model as well as to the Universal Soil Loss Equation (USLE). Regarding the latter model, the FVC was indirectly incorporated by adapting the C factor. Both models show an increase in absolute soil erosion values when FVC is considered. In contrast to USLE and the Cs-137 soil erosion rates, PESERA estimates are low. For the USLE model also the spatial patterns improved and showed "hotspots" of high erosion of up to 16 t ha -1 a -1. In conclusion field measurements of Cs-137 confirmed the improvement of soil erosion estimates using the satellite-derived vegetation data.
Deciphering structural and temporal interplays during the architectural development of mango trees.
Dambreville, Anaëlle; Lauri, Pierre-Éric; Trottier, Catherine; Guédon, Yann; Normand, Frédéric
2013-05-01
Plant architecture is commonly defined by the adjacency of organs within the structure and their properties. Few studies consider the effect of endogenous temporal factors, namely phenological factors, on the establishment of plant architecture. This study hypothesized that, in addition to the effect of environmental factors, the observed plant architecture results from both endogenous structural and temporal components, and their interplays. Mango tree, which is characterized by strong phenological asynchronisms within and between trees and by repeated vegetative and reproductive flushes during a growing cycle, was chosen as a plant model. During two consecutive growing cycles, this study described vegetative and reproductive development of 20 trees submitted to the same environmental conditions. Four mango cultivars were considered to assess possible cultivar-specific patterns. Integrative vegetative and reproductive development models incorporating generalized linear models as components were built. These models described the occurrence, intensity, and timing of vegetative and reproductive development at the growth unit scale. This study showed significant interplays between structural and temporal components of plant architectural development at two temporal scales. Within a growing cycle, earliness of bud burst was highly and positively related to earliness of vegetative development and flowering. Between growing cycles, flowering growth units delayed vegetative development compared to growth units that did not flower. These interplays explained how vegetative and reproductive phenological asynchronisms within and between trees were generated and maintained. It is suggested that causation networks involving structural and temporal components may give rise to contrasted tree architectures.
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.
NASA Astrophysics Data System (ADS)
Reid, T. D.; Essery, R.; Rutter, N.; Huntley, B.; Baxter, R.; Holden, R.; King, M.; Hancock, S.; Carle, J.
2012-12-01
Boreal forests exert a strong influence on weather and climate by modifying the surface energy and radiation balance. However, global climate and numerical weather prediction models use forest parameter values from simple look-up tables or maps that are derived from limited satellite data, on large grid scales. In reality, Arctic landscapes are inherently heterogeneous, with highly variable land cover types and structures on a variety of spatial scales. There is value in collecting detailed field data for different areas of vegetation cover, to assess the accuracy of large-scale assumptions. To address these issues, a consortium of researchers funded by the UK's Natural Environment Research Council have collected extensive data on radiation, meteorology, snow cover and canopy structure at two contrasting Arctic forest sites. The chosen study sites were an area of boreal birch forest near Abisko, Sweden in March/April 2011 and mixed conifer forest at Sodankylä, Finland in March/April 2012. At both sites, arrays comprising ten shortwave pyranometers and four longwave pyrgeometers were deployed for periods of up to 50 days, under forest plots of varying canopy structures and densities. In addition, downwelling longwave irradiance and global and diffuse shortwave irradiances were recorded at nearby open sites representing the top-of-canopy conditions. Meteorological data were recorded at all sub-canopy and open sites using automatic weather stations. Over the same periods, tree skin temperatures were measured on selected trees using contact thermocouples, infrared thermocouples and thermal imagery. Canopy structure was accurately quantified through manual surveys, extensive hemispherical photography and terrestrial laser scans of every study plot. Sub-canopy snow depth and snow water equivalent were measured on fine-scale grids at each study plot. Regular site maintenance ensured a high quality dataset covering the important Arctic spring period. The data have several applications, for example in forest ecology, canopy radiative transfer models, snow hydrological modelling, and land surface schemes, for a variety of canopy types from sparse, leafless birch to dense pine and spruce. The work also allows the comparison of modern, highly detailed methods such as laser scanning and thermal imagery with older, well-established data collection methods. By combining these data with airborne and satellite remote sensing data, snow-vegetation-atmosphere interactions could be estimated over a wide area of the heterogeneous boreal landscape. This could improve estimates of crucial parameters such as land surface albedo on the grid scales required for global or regional weather and climate models.
Validation of SMAP Radar Vegetation Data Cubes from Agricultural Field Measurements
NASA Astrophysics Data System (ADS)
Tsang, L.; Xu, X.; Liao, T.; Kim, S.; Njoku, E. G.
2012-12-01
The NASA Soil Moisture Active/Passive (SMAP) Mission will be launched in October 2014. The objective of the SMAP mission is to provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. In the active algorithm, the retrieval is performed based on the backscattering data cube, which are characterized by two surface parameters, which are soil moisture and soil surface rms height, and one vegetation parameter, the vegetation water content. We have developed a physical-based forward scattering model to generate the data cube for agricultural fields. To represent the agricultural crops, we include a layer of cylinders and disks on top of the rough surface. The scattering cross section of the vegetation layer and its interaction with the underground soil surface were calculated by the distorted Born approximation, which give explicitly three scattering mechanisms. A) The direct volume scattering B) The double bounce effect as, and C) The double bouncing effects. The direct volume scattering is calculated by using the Body of Revolution code. The double bounce effects, exhibited by the interaction of rough surface with the vegetation layer is considered by modifying the rough surface reflectivity using the coherent wave as computed by Numerical solution of Maxwell equations of 3 Dimensional simulations (NMM3D) of bare soil scattering. The rough surface scattering of the soil was calculated by NMM3D. We have compared the physical scattering models with field measurements. In the field campaign, the measurements were made on soil moisture, rough surface rms heights and vegetation water content as well as geometric parameters of vegetation. The three main crops lands are grassland, cornfield and soybean fields. The corresponding data cubes are validated using SGP99, SMEX02 and SMEX 08 field experiments.
Preliminary assessment of soil moisture over vegetation
NASA Technical Reports Server (NTRS)
Carlson, T. N.
1986-01-01
Modeling of surface energy fluxes was combined with in-situ measurement of surface parameters, specifically the surface sensible heat flux and the substrate soil moisture. A vegetation component was incorporated in the atmospheric/substrate model and subsequently showed that fluxes over vegetation can be very much different than those over bare soil for a given surface-air temperature difference. The temperature signatures measured by a satellite or airborne radiometer should be interpreted in conjunction with surface measurements of modeled parameters. Paradoxically, analyses of the large-scale distribution of soil moisture availability shows that there is a very high correlation between antecedent precipitation and inferred surface moisture availability, even when no specific vegetation parameterization is used in the boundary layer model. Preparatory work was begun in streamlining the present boundary layer model, developing better algorithms for relating surface temperatures to substrate moisture, preparing for participation in the French HAPEX experiment, and analyzing aircraft microwave and radiometric surface temperature data for the 1983 French Beauce experiments.
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.
Experimental and numerical analysis of coastal protection provided by natural ecosystems
NASA Astrophysics Data System (ADS)
Maza, M.; Lara, J. L.; Losada, I. J.; Nepf, H. M.
2016-12-01
The risk of flooding and erosion is increasing for many coastal areas owing to global and regional changes in climate conditions together with increasing exposure and vulnerability. After hurricane Katrina (2005) and Sandy (2012) and the tsunami in Indonesia (2004), coastal managers have become interested in low environmental impact alternatives, or nature-based solutions, to protect the coast. Although capacity for coastal ecosystems to damp flow energy has been widely recognized, they have not been firmly considered in the portfolio of coastal protection options. This is mainly due to the complexity of flow-vegetation interaction and of quantifying the value of coastal protection provided by these ecosystems. This complex problem involves different temporal and spatial scales and disciplines, such as engineering, ecology and economics. This work aims to make a step forward in better understanding the physics involved in flow-vegetation interaction leading to new formulations and parameterizations to address some unsolved questions in literature: the representation of plants and field properties; the influence of wave parameters on the relevant processes; the role of the combined effect of waves and currents and the effect of extreme events on vegetation elements. The three main coastal vegetated ecosystems (seagrasses, saltmarshes and mangroves) are studied with an experimental and numerical approach. Experimental analysis is carried out using mimics and real vegetation, considering different flow and vegetation parameters and characterizing flow energy attenuation for the different scenarios. Numerical simulations are performed using 2-D and 3-D Navier-Stokes models in which the effect of vegetation is implemented and validated. These models are used to extend experimental results by simulating different vegetation distributions and analyzing variables such as high-spatial-resolution free surface and velocity data and forces exerted on vegetation elements.
Relating geomorphic change and grazing to avian communities in riparian forests
Scott, M.L.; Skagen, S.K.; Merligliano, M.F.
2003-01-01
Avian conservation in riparian or bottomland forests requires an understanding of the physical and biotic factors that sustain the structural complexity of riparian vegetation. Riparian forests of western North America are dependent upon flow-related geomorphic processes necessary for establishment of new cottonwood and willow patches. In June 1995, we examined how fluvial geomorphic processes and long-term grazing influence the structural complexity of riparian vegetation and the abundance and diversity of breeding birds along the upper Missouri River in central Montana, a large, flow-regulated, and geomorphically constrained reach. Use by breeding birds was linked to fluvial geomorphic processes that influence the structure of these patches. Species richness and bird diversity increased with increasing structural complexity of vegetation (F1,32 = 75.49, p < 0.0001; F1,32 = 79.76, p < 0.0001, respectively). Bird species composition was significantly correlated with vegetation strata diversity (rs,33 = 0.98, p < 0.0001). Bird abundance in canopy and tall-shrub foraging guilds increased significantly with increasing tree cover and tall-shrub cover (F1,22 = 34.68, p < 0.0001; F1,20 = 22.22, p < 0.0001, respectively). Seventeen bird species, including five species of concern (e.g., Red-eyed Vireo [Vireo olivaceus]), were significantly associated (p < 0.10) with structurally complex forest patches, whereas only six bird species were significantly associated with structurally simple forest patches. We related the structural complexity of 34 riparian vegetation patches to geomorphic change, woody vegetation establishment, and grazing history over a 35-year post-dam period (1953–1988). The structural complexity of habitat patches was positively related to recent sediment accretion (t33 = 3.31, p = 0.002) and vegetation establishment (t20.7 = −3.63, p = 0.002) and negatively related to grazing activity (t19.6 = 3.75, p = 0.001). Avian conservation along rivers like the upper Missouri requires maintenance of the geomorphic processes responsible for tree establishment and management of land-use activities in riparian forests.
NASA Astrophysics Data System (ADS)
Gillies, J. A.; Nield, J. M.; Nickling, W. G.; Furtak-Cole, E.
2014-12-01
Wind erosion and dust emissions occur in many dryland environments from a range of surfaces with different types and amounts of vegetation. Understanding how vegetation modulates these processes remains a research challenge. Here we present results from a study that examines the relationship between an index of shelter (SI=distance from a point to the nearest upwind vegetation/vegetation height) and particle threshold expressed as the ratio of wind speed measured at 0.45 times the mean plant height divided by the wind speed at 17 m when saltation commences, and saltation flux. The results are used to evaluate SI as a parameter to characterize the influence of vegetation on local winds and sediment transport conditions. Wind speed, wind direction, saltation activity and point saltation flux were measured at 35 locations in defined test areas (~13,000 m2) in two vegetation communities: mature streets of mesquite covered nebkhas and incipient nebkhas dominated by low mesquite plants. Measurement positions represent the most open areas, and hence those places most susceptible to wind erosion among the vegetation elements. Shelter index was calculated for each measurement position for each 10° wind direction bin using digital elevation models for each site acquired using terrestrial laser scanning. SI can show the susceptibility to wind erosion at different time scales, i.e., event, seasonal, or annual, but in a supply-limited system it can fail to define actual flux amounts due to a lack of knowledge of the distribution of sediment across the surface of interest with respect to the patterns of SI.
Dominique Bachelet; James M. Lenihan; Christopher Daly; Ronald P. Neilson; Dennis S. Ojima; William J. Parton
2001-01-01
Assessments of vegetation response to climate change have generally been made only by equilibrium vegetation models that predict vegetation composition under steady-state conditions. These models do not simulate either ecosystem biogeochemical processes or changes in ecosystem structure that may, in turn, act as feedbacks in determining the dynamics of vegetation...
Small mammal abundance in Mediterranean post-fire habitats: a role for predators?
NASA Astrophysics Data System (ADS)
Torre, I.; Díaz, M.
2004-05-01
We studied patterns of small mammal abundance and species richness in post-fire habitats by sampling 33 plots (225 m 2 each) representing different stages of vegetation recovery after fire. Small mammal abundance was estimated by live trapping during early spring 1999 and vegetation structure was sampled by visual estimation at the same plots. Recently-burnt areas were characterised by shrubby and herbaceous vegetation with low structural variability, and unburnt areas were characterised by well developed forest cover with high structural complexity. Small mammal abundance and species richness decreased with time elapsed since the last fire (from 5 to at least 50 years), and these differences were associated to the decreasing cover of short shrubs as the post-fire succession of plant communities advanced. However, relationships between vegetation structure and small mammals differed among areas burned in different times, with weak or negative relationship in recently burnt areas and positive and stronger relationship in unburnt areas. Furthermore, the abundance of small mammals was larger than expected from vegetation structure in plots burned recently whereas the contrary pattern was found in unburned areas. We hypothesised that the pattern observed could be related to the responses of small mammal predators to changes in vegetation and landscape structure promoted by fire. Fire-related fragmentation could have promoted the isolation of forest predators (owls and carnivores) in unburned forest patches, a fact that could have produced a higher predation pressure for small mammals. Conversely, small mammal populations would have been enhanced in early post-fire stages by lower predator numbers combined with better predator protection in areas covered by resprouting woody vegetation.
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.
Dimensions of vegetable parenting practices among preschoolers.
Baranowski, Tom; Chen, Tzu-An; O'Connor, Teresia; Hughes, Sheryl; Beltran, Alicia; Frankel, Leslie; Diep, Cassandra; Baranowski, Janice C
2013-10-01
The objective of this study was to determine the factor structure of 31 effective and ineffective vegetable parenting practices used by parents of preschool children based on three theoretically proposed factors: responsiveness, control and structure. The methods employed included both corrected item-total correlations and confirmatory factor analysis. Acceptable fit was obtained only when effective and ineffective parenting practices were analyzed separately. Among effective items the model included one second order factor (effectiveness) and the three proposed first order factors. The same structure was revealed among ineffective items, but required correlated paths be specified among items. A theoretically specified three factor structure was obtained among 31 vegetable parenting practice items, but likely to be effective and ineffective items had to be analyzed separately. Research is needed on how these parenting practices factors predict child vegetable intake. Copyright © 2013 Elsevier Ltd. All rights reserved.
2012-01-01
Background The aim of the paper is to assess by the principal components analysis (PCA) the heavy metal contamination of soil and vegetables widely used as food for people who live in areas contaminated by heavy metals (HMs) due to long-lasting mining activities. This chemometric technique allowed us to select the best model for determining the risk of HMs on the food chain as well as on people's health. Results Many PCA models were computed with different variables: heavy metals contents and some agro-chemical parameters which characterize the soil samples from contaminated and uncontaminated areas, HMs contents of different types of vegetables grown and consumed in these areas, and the complex parameter target hazard quotients (THQ). Results were discussed in terms of principal component analysis. Conclusion There were two major benefits in processing the data PCA: firstly, it helped in optimizing the number and type of data that are best in rendering the HMs contamination of the soil and vegetables. Secondly, it was valuable for selecting the vegetable species which present the highest/minimum risk of a negative impact on the food chain and human health. PMID:23234365
a Hybrid Method in Vegetation Height Estimation Using Polinsar Images of Campaign Biosar
NASA Astrophysics Data System (ADS)
Dehnavi, S.; Maghsoudi, Y.
2015-12-01
Recently, there have been plenty of researches on the retrieval of forest height by PolInSAR data. This paper aims at the evaluation of a hybrid method in vegetation height estimation based on L-band multi-polarized air-borne SAR images. The SAR data used in this paper were collected by the airborne E-SAR system. The objective of this research is firstly to describe each interferometry cross correlation as a sum of contributions corresponding to single bounce, double bounce and volume scattering processes. Then, an ESPIRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm is implemented, to determine the interferometric phase of each local scatterer (ground and canopy). Secondly, the canopy height is estimated by phase differencing method, according to the RVOG (Random Volume Over Ground) concept. The applied model-based decomposition method is unrivaled, as it is not limited to specific type of vegetation, unlike the previous decomposition techniques. In fact, the usage of generalized probability density function based on the nth power of a cosine-squared function, which is characterized by two parameters, makes this method useful for different vegetation types. Experimental results show the efficiency of the approach for vegetation height estimation in the test site.
Estimation of Forest Structure from SRTM correlation data
NASA Astrophysics Data System (ADS)
Chapman, B. D.; Hensley, S.; Siqueira, P.; Simard, M.; Treuhaft, R. N.
2012-12-01
In the year 2000, NASA flew a C-band interferometric SAR mission on the Space Shuttle Endeavour called the NASA Shuttle Radar Topography Mission (SRTM). The objective of this 10 day mission was to measure the topography of the Earth between latitudes of ±60 degrees. The Digital Elevation Model (DEM) obtained by processing the collected interferometric SAR data has been made freely available by NASA for many uses. During SRTM InSAR processing, the interferometric correlation was determined as well. One component of the observed SRTM interferometric correlation is the volumetric correlation. The volumetric correlation contains desired vertical structure information. Therefore, if the other components of the correlation can be determined and removed, the remaining correlation should be related to the along-sight distribution of objects within each image pixel. In the presence of vegetation, where we postulate the radiation is scattering in varying amounts from the top of the vegetation to the ground surface, the decorrelation should be related to thickness of the vegetation layer. If successfully demonstrated, the SRTM data set could be used to derive estimates of year 2000 vegetation structure for a large part of the Earth's land surface. Unfortunately, not all the SRTM data are equally sensitive to vertical structure information. Beam 1, the sub-swath in the near range of the SRTM ScanSAR swath, has the greatest sensitivity. Therefore, this presentation will concentrate on the analysis of data from that sub-swath. First, we will describe the corrections necessary to extract the volumetric correlation from the observed correlation. Second, we will examine methods to model the vegetation structure. Last, vegetation-modeling results based on the SRTM correlation data will be compared with results from other measurements of vegetation structural information. Results for a variety of vegetation types will be examined. This paper was partially written at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.
Arbieu, Ugo; Grünewald, Claudia; Schleuning, Matthias; Böhning-Gaese, Katrin
2017-01-01
Southern African protected areas (PAs) harbour a great diversity of animals, which represent a large potential for wildlife tourism. In this region, global change is expected to result in vegetation changes, such as bush encroachment and increases in vegetation density. However, little is known on the influence of vegetation structure on wildlife tourists' wildlife viewing experience and satisfaction. In this study, we collected data on vegetation structure and perceived mammal densities along 196 road transects (each 5 km long) and conducted a social survey with 651 questionnaires across four PAs in three Southern African countries. Our objectives were 1) to assess visitors' attitude towards vegetation, 2) to test the influence of perceived mammal density and vegetation structure on the easiness to spot animals, and 3) on visitors' satisfaction during their visit to PAs. Using a Boosted Regression Tree procedure, we found mostly negative non-linear relationships between vegetation density and wildlife tourists' experience, and positive relationships between perceived mammal densities and wildlife tourists' experience. In particular, wildlife tourists disliked road transects with high estimates of vegetation density. Similarly, the easiness to spot animals dropped at thresholds of high vegetation density and at perceived mammal densities lower than 46 individuals per road transect. Finally, tourists' satisfaction declined linearly with vegetation density and dropped at mammal densities smaller than 26 individuals per transect. Our results suggest that vegetation density has important impacts on tourists' wildlife viewing experience and satisfaction. Hence, the management of PAs in savannah landscapes should consider how tourists perceive these landscapes and their mammal diversity in order to maintain and develop a sustainable wildlife tourism.
Grünewald, Claudia; Schleuning, Matthias; Böhning-Gaese, Katrin
2017-01-01
Southern African protected areas (PAs) harbour a great diversity of animals, which represent a large potential for wildlife tourism. In this region, global change is expected to result in vegetation changes, such as bush encroachment and increases in vegetation density. However, little is known on the influence of vegetation structure on wildlife tourists’ wildlife viewing experience and satisfaction. In this study, we collected data on vegetation structure and perceived mammal densities along 196 road transects (each 5 km long) and conducted a social survey with 651 questionnaires across four PAs in three Southern African countries. Our objectives were 1) to assess visitors’ attitude towards vegetation, 2) to test the influence of perceived mammal density and vegetation structure on the easiness to spot animals, and 3) on visitors’ satisfaction during their visit to PAs. Using a Boosted Regression Tree procedure, we found mostly negative non-linear relationships between vegetation density and wildlife tourists’ experience, and positive relationships between perceived mammal densities and wildlife tourists’ experience. In particular, wildlife tourists disliked road transects with high estimates of vegetation density. Similarly, the easiness to spot animals dropped at thresholds of high vegetation density and at perceived mammal densities lower than 46 individuals per road transect. Finally, tourists’ satisfaction declined linearly with vegetation density and dropped at mammal densities smaller than 26 individuals per transect. Our results suggest that vegetation density has important impacts on tourists’ wildlife viewing experience and satisfaction. Hence, the management of PAs in savannah landscapes should consider how tourists perceive these landscapes and their mammal diversity in order to maintain and develop a sustainable wildlife tourism. PMID:28957420
Classifying and mapping wetlands and peat resources using digital cartography
Cameron, Cornelia C.; Emery, David A.
1992-01-01
Digital cartography allows the portrayal of spatial associations among diverse data types and is ideally suited for land use and resource analysis. We have developed methodology that uses digital cartography for the classification of wetlands and their associated peat resources and applied it to a 1:24 000 scale map area in New Hampshire. Classifying and mapping wetlands involves integrating the spatial distribution of wetlands types with depth variations in associated peat quality and character. A hierarchically structured classification that integrates the spatial distribution of variations in (1) vegetation, (2) soil type, (3) hydrology, (4) geologic aspects, and (5) peat characteristics has been developed and can be used to build digital cartographic files for resource and land use analysis. The first three parameters are the bases used by the National Wetlands Inventory to classify wetlands and deepwater habitats of the United States. The fourth parameter, geological aspects, includes slope, relief, depth of wetland (from surface to underlying rock or substrate), wetland stratigraphy, and the type and structure of solid and unconsolidated rock surrounding and underlying the wetland. The fifth parameter, peat characteristics, includes the subsurface variation in ash, acidity, moisture, heating value (Btu), sulfur content, and other chemical properties as shown in specimens obtained from core holes. These parameters can be shown as a series of map data overlays with tables that can be integrated for resource or land use analysis.
Kranenburg, Christine J.; Palaseanu-Lovejoy, Monica; Nayegandhi, Amar; Brock, John; Woodman, Robert
2012-01-01
Traditional vegetation maps capture the horizontal distribution of various vegetation properties, for example, type, species and age/senescence, across a landscape. Ecologists have long known, however, that many important forest properties, for example, interior microclimate, carbon capacity, biomass and habitat suitability, are also dependent on the vertical arrangement of branches and leaves within tree canopies. The objective of this study was to use a digital elevation model (DEM) along with tree canopy-structure metrics derived from a lidar survey conducted using the Experimental Advanced Airborne Research Lidar (EAARL) to capture a three-dimensional view of vegetation communities in the Barataria Preserve unit of Jean Lafitte National Historical Park and Preserve, Louisiana. The EAARL instrument is a raster-scanning, full waveform-resolving, small-footprint, green-wavelength (532-nanometer) lidar system designed to map coastal bathymetry, topography and vegetation structure simultaneously. An unsupervised clustering procedure was then applied to the 3-dimensional-based metrics and DEM to produce a vegetation map based on the vertical structure of the park's vegetation, which includes a flotant marsh, scrub-shrub wetland, bottomland hardwood forest, and baldcypress-tupelo swamp forest. This study was completed in collaboration with the National Park Service Inventory and Monitoring Program's Gulf Coast Network. The methods presented herein are intended to be used as part of a cost-effective monitoring tool to capture change in park resources.
USDA-ARS?s Scientific Manuscript database
Soil moisture condition is an important indicator for agricultural drought monitoring. Through the Land Parameter Retrieval Model (LPRM), vegetation optical depth (VOD) as well as surface soil moisture (SM) can be retrieved simultaneously from brightness temperature observations from the Advanced Mi...
NASA Technical Reports Server (NTRS)
Kornilova, L. N.; Cowings, P.; Arlashchenko, N. I.; Korneev, D. Iu; Sagalovich, S. V.; Sarantseva, A. V.; Toscano, W.; Kozlovskaia, I. B.
2003-01-01
The ability of 4 cosmonauts to voluntarily control their physiological parameters during the standing test was evaluated following a series of the adaptive feedback (AF) training sessions. Vegetative status of the cosmonauts during voluntary "relaxation" and "straining" was different when compared with its indices determined before these sessions. In addition, there was a considerable individual variability in the intensity and direction of the AF effects, and the range of parameters responding to AF. It was GCR which was the easiest one for the AF control.
Vaughn, Nicholas R.; Asner, Gregory P.; Smit, Izak P. J.; Riddel, Edward S.
2015-01-01
Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50–450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques. PMID:26660502
Vaughn, Nicholas R; Asner, Gregory P; Smit, Izak P J; Riddel, Edward S
2015-01-01
Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50-450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques.
Parent outcome expectancies for purchasing fruit and vegetables: a validation.
Baranowski, Tom; Watson, Kathy; Missaghian, Mariam; Broadfoot, Alison; Baranowski, Janice; Cullen, Karen; Nicklas, Theresa; Fisher, Jennifer; O'Donnell, Sharon
2007-03-01
To validate four scales -- outcome expectancies for purchasing fruit and for purchasing vegetables, and comparative outcome expectancies for purchasing fresh fruit and for purchasing fresh vegetables versus other forms of fruit and vegetables (F&V). Survey instruments were administered twice, separated by 6 weeks. Recruited in front of supermarkets and grocery stores; interviews conducted by telephone. One hundred and sixty-one food shoppers with children (18 years or younger). Single dimension scales were specified for fruit and for vegetable purchasing outcome expectancies, and for comparative (fresh vs. other) fruit and vegetable purchasing outcome expectancies. Item Response Theory parameter estimates revealed easily interpreted patterns in the sequence of items by difficulty of response. Fruit and vegetable purchasing and fresh fruit comparative purchasing outcome expectancy scales were significantly correlated with home F&V availability, after controlling for social desirability of response. Comparative fresh vegetable outcome expectancy scale was significantly bivariately correlated with home vegetable availability, but not after controlling for social desirability. These scales are available to help better understand family F&V purchasing decisions.
Jennifer L. Long; Melanie Miller; James P. Menakis; Robert E. Keane
2006-01-01
The Landscape Fire and Resource Management Planning Tools Prototype Project, or LANDFIRE Prototype Project, required a system for classifying vegetation composition, biophysical settings, and vegetation structure to facilitate the mapping of vegetation and wildland fuel characteristics and the simulation of vegetation dynamics using landscape modeling. We developed...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Evans, R.D.; Black, R.A.
Growth of vegetative and reproductive structures in Artemisia tridentata is temporally separated during the growing season; vegetative growth occurs during spring and early summer when soil moisture is most abundant, while reproductive growth occurs during summer and fall when soil moisture may be limiting. Vegetative and reproductive structures may exhibit contrasting efficiencies of resource acquisition and investment resulting from temporal differences in resource availability. The effect of water stress on growth, photosynthesis, and resource investment for vegetative and reproductive modules of Artemisia tridentata was examined by applying supplemental water. No differences were observed in vegetative biomass in the two wateringmore » treatments. Growth of vegetative structures occurred in the spring when water was not limiting, and shrubs in both treatments exerted little stomatal control over water loss. Conversely, supplemental watering increased reproductive growth. Shrubs conserved water during summer by abscising leaves and lowering stomatal conductance potential and increases in evaporative demand. In florescences are capable of positive photosynthetic rates comparable to vegetative leaves. Water stress did not alter tissue construction costs or carbon and nitrogen contents for either vegetative or reproductive modules. Resource limitations were reflected in the efficiency of water use during tissue construction; floral leaves and floral heads of shrubs not receiving supplemental water were produced with higher water-use efficiency. Conservative use of water during production of vegetative modules would offer no advantage because neighboring species are also most active at this time. Reproductive growth in A. tridentata occurs during summer when neighboring species are largely dormant, and so efficient use of water may allow development of reproductive structures to continue throughout the summer even with limited supplies of water. 66 refs., 8 figs., 3 tabs.« less
Janet L. Ohmann; Matthew J. Gregory
2002-01-01
Spatially explicit information on the species composition and structure of forest vegetation is needed at broad spatial scales for natural resource policy analysis and ecological research. We present a method for predictive vegetation mapping that applies direct gradient analysis and nearest-neighbor imputation to ascribe detailed ground attributes of vegetation to...
Rapeseed Oil as Renewable Resource for Polyol Synthesis
NASA Astrophysics Data System (ADS)
Stirna, Uldis; Fridrihsone, Anda; Misane, Marija; Vilsone, Dzintra
2011-01-01
Vegetable oils are one of the most important platform chemicals due to their accessibility, specific structure of oils and low price. Rapeseed oil (RO) polyols were prepared by amidization of RO with diethanolamine (DEA). To determine the kinetics of amidization reaction, experiments were carried out. Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), amine (NH) value was determined. Group contribution method by Fedor‵s was used to calculate solubility parameters, van der Waals volume was calculated by Askadskii. Obtained polyol‵s OH and NH value are from 304 up to 415 mg KOH/g. RO polyols synthesis meets the criteria of "green chemistry". In the present study, reaction of RO amidization with DEA was investigated, as well as optimum conditions for polyol synthesis was established to obtain polyols for polyurethane production. Calculations of solubility parameter and cohesion energy density were calculated, as RO polyols will be used as side chains in polymers, and solubility parameter will be used to explain properties of polymers.
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.
IN11B-1621: Quantifying How Climate Affects Vegetation in the Amazon Rainforest
NASA Technical Reports Server (NTRS)
Das, Kamalika; Kodali, Anuradha; Szubert, Marcin; Ganguly, Sangram; Bongard, Joshua
2016-01-01
Amazon droughts in 2005 and 2010 have raised serious concern about the future of the rainforest. Amazon forests are crucial because of their role as the largest carbon sink in the world which would effect the global warming phenomena with decreased photosynthesis activity. Especially, after a decline in plant growth in 1.68 million km2 forest area during the once-in-a-century severe drought in 2010, it is of primary importance to understand the relationship between different climatic variables and vegetation. In an earlier study, we have shown that non-linear models are better at capturing the relation dynamics of vegetation and climate variables such as temperature and precipitation, compared to linear models. In this research, we learn precise models between vegetation and climatic variables (temperature, precipitation) for normal conditions in the Amazon region using genetic programming based symbolic regression. This is done by removing high elevation and drought affected areas and also considering the slope of the region as one of the important factors while building the model. The model learned reveals new and interesting ways historical and current climate variables affect the vegetation at any location. MAIAC data has been used as a vegetation surrogate in our study. For temperature and precipitation, we have used TRMM and MODIS Land Surface Temperature data sets while learning the non-linear regression model. However, to generalize the model to make it independent of the data source, we perform transfer learning where we regress a regularized least squares to learn the parameters of the non-linear model using other data sources such as the precipitation and temperature from the Climatic Research Center (CRU). This new model is very similar in structure and performance compared to the original learned model and verifies the same claims about the nature of dependency between these climate variables and the vegetation in the Amazon region. As a result of this study, we are able to learn, for the very first time how exactly different climate factors influence vegetation at any location in the Amazon rainforests, independent of the specific sources from which the data has been obtained.
NASA Astrophysics Data System (ADS)
Vest, K. R.; Elmore, A. J.; Okin, G. S.
2009-12-01
Desertification is a human induced global phenomenon causing a loss of biodiversity and ecosystem productivity. Semi-arid grasslands are vulnerable to anthropogenic impacts (i.e., groundwater pumping and surface water diversion) that decrease vegetation cover and increase bare soil area leading to a greater probability of soil erosion, potentially enhancing feedback processes associated with desertification. To enhance our understanding of interactions between anthropogenic, physical, and biological factors causing desertification, this study used a combination of modeling and field observations to examine the relationship between chronic groundwater pumping and vegetation cover change and its effects on soil erosion and stability. The work was conducted in Owens Valley California, where a long history of groundwater pumping and surface water diversion has lead to documented vegetation changes. The work examined hydrological, ecological and biogeochemical factors across thirteen sites in Owens Valley. We analyzed soil stability, vegetation and gap size, soil organic carbon, and we also installed Big Spring Number Eight (BSNE) catchers to calculate mass transport of aeolian sediment across sites. Mass transport calculations were used to validate a new wind erosion model that represents the effect of porous vegetation on surface windshear velocity. Results across two field seasons show that the model can be used to predict mass transport, and areas with increased groundwater pumping show a greater susceptibility to erosion. Sediment collected in BSNE catchers was positively correlated with site gap size. Additionally, areas with larger gap sizes have a greater threshold shear velocity and soil stability, yet mass transport was greater at these sites than at sites with smaller gap sizes. Although modeling is complicated by spatial variation in multiple model parameters (e.g., gap size, threshold shear velocity in gaps), our results support the hypothesis that soils with high organic matter are being eroded following the loss of vegetation cover due to groundwater decline leaving behind bare soil surfaces with less fertility hampering vegetation reestablishment. Desertification in this system is apparently easily initiated through groundwater decline due to the high friability of these meadow soils.
Quantifying How Climate Affects Vegetation in the Amazon Rainforest
NASA Astrophysics Data System (ADS)
Das, K.; Kodali, A.; Szubert, M.; Ganguly, S.; Bongard, J.
2016-12-01
Amazon droughts in 2005 and 2010 have raised serious concern about the future of the rainforest. Amazon forests are crucial because of their role as the largest carbon sink in the world which would effect the global warming phenomena with decreased photosynthesis activity. Especially, after a decline in plant growth in 1.68 million km2 forest area during the once-in-a-century severe drought in 2010, it is of primary importance to understand the relationship between different climatic variables and vegetation. In an earlier study, we have shown that non-linear models are better at capturing the relation dynamics of vegetation and climate variables such as temperature and precipitation, compared to linear models. In this research, we learn precise models between vegetation and climatic variables (temperature, precipitation) for normal conditions in the Amazon region using genetic programming based symbolic regression. This is done by removing high elevation and drought affected areas and also considering the slope of the region as one of the important factors while building the model. The model learned reveals new and interesting ways historical and current climate variables affect the vegetation at any location. MAIAC data has been used as a vegetation surrogate in our study. For temperature and precipitation, we have used TRMM and MODIS Land Surface Temperature data sets while learning the non-linear regression model. However, to generalize the model to make it independent of the data source, we perform transfer learning where we regress a regularized least squares to learn the parameters of the non-linear model using other data sources such as the precipitation and temperature from the Climatic Research Center (CRU). This new model is very similar in structure and performance compared to the original learned model and verifies the same claims about the nature of dependency between these climate variables and the vegetation in the Amazon region. As a result of this study, we are able to learn, for the very first time how exactly different climate factors influence vegetation at any location in the Amazon rainforests, independent of the specific sources from which the data has been obtained.
Wavelength selection beyond turing
NASA Astrophysics Data System (ADS)
Zelnik, Yuval R.; Tzuk, Omer
2017-06-01
Spatial patterns arising spontaneously due to internal processes are ubiquitous in nature, varying from periodic patterns of dryland vegetation to complex structures of bacterial colonies. Many of these patterns can be explained in the context of a Turing instability, where patterns emerge due to two locally interacting components that diffuse with different speeds in the medium. Turing patterns are multistable, meaning that many different patterns with different wavelengths are possible for the same set of parameters. Nevertheless, in a given region typically only one such wavelength is dominant. In the Turing instability region, random initial conditions will mostly lead to a wavelength that is similar to that of the leading eigenvector that arises from the linear stability analysis, but when venturing beyond, little is known about the pattern that will emerge. Using dryland vegetation as a case study, we use different models of drylands ecosystems to study the wavelength pattern that is selected in various scenarios beyond the Turing instability region, focusing on the phenomena of localized states and repeated local disturbances.
Early warning and crop condition assessment research
NASA Technical Reports Server (NTRS)
Boatwright, G. O.; Whitehead, V. S.
1986-01-01
The Early Warning Crop Condition Assessment Project of AgRISTARS was a multiagency and multidisciplinary effort. Its mission and objectives were centered around development and testing of remote-sensing techniques that enhance operational methodologies for global crop-condition assessments. The project developed crop stress indicators models that provide data filter and alert capabilities for monitoring global agricultural conditions. The project developed a technique for using NOAA-n satellite advanced very-high-resolution radiometer (AVHRR) data for operational crop-condition assessments. This technology was transferred to the Foreign Agricultural Service of the USDA. The project developed a U.S. Great Plains data base that contains various meteorological parameters and vegetative index numbers (VIN) derived from AVHRR satellite data. It developed cloud screening techniques and scan angle correction models for AVHRR data. It also developed technology for using remotely acquired thermal data for crop water stress indicator modeling. The project provided basic technology including spectral characteristics of soils, water, stressed and nonstressed crop and range vegetation, solar zenith angle, and atmospheric and canopy structure effects.
Morchella tomentosa: a unique belowground structure and a new clade of morels
Franck O.P. Stefani; Serge Sokolski; Trish L. Wurtz; Yves Piché; Richard C. Hamelin; J. André Fortin; Jean A. Bérubé
2010-01-01
Mechanisms involved in post-fire morel fructification remain unclear. A new undescribed belowground vegetative structure of Marchella tomentosa in a burned boreal forest was investigated north of Fairbanks, Alaska. The name "radiscisclerotium" is proposed to define this peculiar and elaborate belowground vegetative structure of ...
A multi-scale approach of fluvial biogeomorphic dynamics using photogrammetry.
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.
Kolosova, T A; Sadovnikova, I V; Belousova, T E
2015-01-01
The results of a survey of school children with chronic gastroduodenitis when applying at an early period the medical rehabilitation with method low-frequency light-magnetotherapy. During treatment of hospital was evaluated vegetative-trophic status with methods of cardiointervalography and thermovision functional tests. In normalizes clinical parameters was correction in dynamics of the vegetative status in children, it confirms the effectiveness of the therapy. It is proved, that the use of low-frequency light-magnetotherapy has a positive effect on the vegetative--trophic provision an organism and normalizes the vegetative dysfunction.
Research on degradation of omethoate with Y2O3:Er3+ and TiO2
NASA Astrophysics Data System (ADS)
Liu, Zhiping; Mai, Yanling; Yan, Aiguo; Fan, Hailu; Yuan, Taidou
2018-06-01
Application of visible light excited photocatalytic degradation reagent of pesticide residues is not only suitable for the farmers, can also be used for city residents for daily use. Up conversion material Y2O3:Er3+ was prepared by sol gel method, then mixed with anatase TiO2 sol solution, to carry out the research of omethoate degradation under visible light. In order to get the higher degradability, it's important to study the technological parameters. Among so many parameters, four parameters were selected. They were vegetable surface omethoate concentration, photocatalytic degradation reagent dosage, pH value and degradation time. Utilizing orthogonal experimental design program, all parameters were optimized. The results showed that: the degradation rate was the largest concerned with the vegetable surface omethoate concentration, and then the degradation time.
Cultivar preference and sensory evaluation of vegetable pigeon pea (Cajanus cajan) in Eastern Kenya
USDA-ARS?s Scientific Manuscript database
Preference and acceptability of twelve vegetable pigeon pea genotypes of medium maturity was evaluated in Eastern Kenya based on six seed cultivar parameters of color, appearance, taste, odor, tenderness and overall seed acceptability. The sensory characteristics were scored by consumers and farmers...
Hyperspectral measurements for estimating biophysical parameters and CO2 exchanges in a rice field
NASA Astrophysics Data System (ADS)
Rossini, M.; Migliavacca, M.; Meroni, M.; Manca, G.; Cogliati, S.; Busetto, L.; Picchi, V.; Galvagno, M.; Colombo, R.; Seufert, G.
2009-04-01
The objective of this work was to monitor the main biophysical and structural parameters as well as the CO2 exchanges between atmosphere and a terrestrial ecosystem from remote and high spectral resolution spectroradiometric measurements. Estimation of photosynthetic rate or gross primary productivity from remotely sensed data is based on the light use efficiency model (LUE), which states that carbon exchange is a function of the photosynthetically active radiation absorbed by vegetation (APAR) and the radiation use efficiency (É) which represents the conversion efficiency of energy to fixed carbon. Hyperspectral data were used in this study in order to derived both the APAR of green vegetation and the É term. The experimental site was a rice paddy field in North Italy equipped with an Eddy Covariance (EC) flux measurement tower (Castellaro IES-JRC site). Intensive field campaigns were conducted during summer 2007 and 2008. In each sampling day, canopy optical properties, canopy structure, biophysical and ecophysiological parameters were measured. EC fluxes were calculated with a time step of 30 minutes according to EUROFLUX methodology. Measured half-hourly net ecosystem exchange (NEE) was partitioned to derive half hourly gross ecosystem production (GEP). Canopy reflectance spectra were collected under clear sky conditions using two portable spectrometers (HR4000, OceanOptics, USA) characterised by different spectral resolutions. A spectrometer characterised by a Full Width at Half Maximum (FWHM) of 0.13 nm was used to estimate steady-state fluorescence (F) and a second one with a FWHM of 2.8 nm was used for the computation of traditional vegetation indices (e.g. NVDI, Normalized Difference Vegetation Index and SAVI, Soil Adjusted Vegetation Index) and PRI (Photochemical Reflectance Index, Gamon et al. 1992). F was estimated by exploiting a variation of the Fraunhofer Line Depth (FLD) principle (Plascyk 1975): the spectral fitting method described in Meroni and Colombo (2006) applied at the 760 nm atmospheric oxygen absorption band. An index of F efficiency, the apparent fluorescence yield (NF760) was also computed as the ratio between F760 and the incident radiation. Results show that Leaf Area Index (LAI), the fraction of absorbed photosynthetically active radiation (fAPAR) and plant height values were well correlated with SAVI (R2 from 0.68 to 0.83) while NDVI was poorly or not correlated. The NDVI-fAPAR relationship, as well as the relationships NDVI-LAI and NDVI-plant height, is very different in the vegetative and ripening stages. The lower correlation with NDVI in this analysis could be explained by the dependence of the relationship on phenology. In contrast, other indices adjusting for background effects (like SAVI) showed highly linear relationships with fAPAR, LAI and plant height for the entire growing period. Furthermore, the use of innovative spectral indices related to physiological processes such as the activation of photoprotective mechanisms and excess energy dissipation via sun-induced passive fluorescence allowed the development of semi-empirical models between radiometric measurements and GEP. The average of half-hourly GEP acquired between 11 a.m. and 1 p.m. (solar time) was related with hyperspectral indices and fluorescence parameters acquired at the same time with the spectrometers. Different LUE models were tested. SAVI was selected to estimate fAPAR because it showed higher correlation than NDVI. Results showed very high coefficient of determination (i.e. R2from 0.88 to 0.98) between GEP and F760 and the product (NF760 x PARi x SAVI) for both years. The regression between GEP and the product (PRI x PARi x SAVI) was instead not significant. The semi-empirical models show high correlation between GEP and chlorophyll fluorescence parameters throughout the two years study period. This result opens up new possibilities for the application of semi-empirical model for the spatial estimation of biophysical parameters and carbon GEP based on aerial and satellite images. References Gamon J.A., Penuelas J., Field C.B. 1992. A Narrow-Waveband Spectral Index That Tracks Diurnal Changes in Photosynthetic Efficiency. Remote Sensing of Environment, 41:35-44. Meroni M., Colombo R. 2006. Leaf level detection of solar induced chlorophyll fluorescence by means of a subnanometer resolution spectroradiometer. Remote Sensing of Environment, 103:438-448. Plascyk J.A. 1975. The MK II Fraunhofer line discriminator (FLD-II) for airborne and orbital remote sensing of solar-stimulated luminescence. Optical Engineering, 14:339-346.
Jakopak, Rhiannon P.; Hall, L. Embere; Chalfoun, Anna D.
2017-01-01
Many mammals create food stores to enhance overwinter survival in seasonal environments. Strategic arrangement of food within caches may facilitate the physical integrity of the cache or improve access to high-quality food to ensure that cached resources meet future nutritional demands. We used the American pika (Ochotona princeps), a food-caching lagomorph, to evaluate variation in haypile (cache) structure (i.e., horizontal layering by plant functional group) in Wyoming, United States. Fifty-five percent of 62 haypiles contained at least 2 discrete layers of vegetation. Adults and juveniles layered haypiles in similar proportions. The probability of layering increased with haypile volume, but not haypile number per individual or nearby forage diversity. Vegetation cached in layered haypiles was also higher in nitrogen compared to vegetation in unlayered piles. We found that American pikas frequently structured their food caches, structured caches were larger, and the cached vegetation in structured piles was of higher nutritional quality. Improving access to stable, high-quality vegetation in haypiles, a critical overwinter food resource, may allow individuals to better persist amidst harsh conditions.
Why we need better predictive models of vegetation phenology
NASA Astrophysics Data System (ADS)
Richardson, Andrew; Migliavacca, Mirco; Keenan, Trevor
2014-05-01
Vegetation phenology is strongly affected by climate change, with warmer temperatures causing earlier spring onset and delayed autumn senescence in most temperate and boreal ecosystems. In arid regions where phenology is driven by the seasonality of soil water availability, shifts in the timing, intensity, and total amount of precipitation are, likewise, affecting the seasonality of vegetation activity. Changes in the duration of the growing season have important implications for ecosystem productivity and uptake of CO2 from the atmosphere, as well as site water balance and runoff, microclimate, ecological interactions within and across trophic levels, and numerous feedbacks to the climate system associated with the surface energy budget. However, an outstanding challenge is that existing phenology sub-models used in ecosystem, land surface, and terrestrial biosphere models fail to adequately represent the seasonality, or sensitivity to environmental drivers, of vegetation phenology. This has two implications. First, these models are therefore likely to perform poorly under future climate scenarios. Second, the seasonality of important ecological processes and interactions, as well as biosphere-atmosphere feedbacks, is likely to be misrepresented as a result. Using data from several recent analyses, and focusing on temperate and boreal ecosystems, we will review current challenges associated with modeling vegetation phenology. We will discuss uncertainties associated with phenology model structure, model parameters, and driver sensitivity (forcing, chilling, and photoperiod). We will show why being able to extrapolate and generalize models (and model parameterization) is essential. We will consider added challenges associated with trying to model autumn phenology. Finally, we will use canopy photosynthesis and uptake of CO2 as an example of why improved understanding of the "rhythm of the seasons" is critically important.
NASA Astrophysics Data System (ADS)
Obriejetan, Michael; Rauch, Hans Peter; Florineth, Florin
2013-04-01
Erosion control systems consisting of technical and biological components are widely accepted and proven to work well if installed properly with regard to site-specific parameters. A wide range of implementation measures for this specific protection purpose is existent and new, in particular technical solutions are constantly introduced into the market. Nevertheless, especially vegetation aspects of erosion control measures are frequently disregarded and should be considered enhanced against the backdrop of the development and realization of adaptation strategies in an altering environment due to climate change associated effects. Technical auxiliaries such as geotextiles typically used for slope protection (nettings, blankets, turf reinforcement mats etc.) address specific features and due to structural and material diversity, differing effects on sediment yield, surface runoff and vegetational development seem evident. Nevertheless there is a knowledge gap concerning the mutual interaction processes between technical and biological components respectively specific comparable data on erosion-reducing effects of technical-biological erosion protection systems are insufficient. In this context, an experimental arrangement was set up to study the correlated influences of geotextiles and vegetation and determine its (combined) effects on surface runoff and soil loss during simulated heavy rainfall events. Sowing vessels serve as testing facilities which are filled with top soil under application of various organic and synthetic geotextiles and by using a reliable drought resistant seed mixture. Regular vegetational monitoring as well as two rainfall simulation runs with four repetitions of each variant were conducted. Therefore a portable rainfall simulator with standardized rainfall intensity of 240 mm h-1 and three minute rainfall duration was used to stress these systems on different stages of plant development at an inclination of 30 degrees. First results show significant differences between the systems referring to sediment yield and runoff amount respectively vegetation development.
Directional Canopy Emissivity Estimation Based on Spectral Invariants
NASA Astrophysics Data System (ADS)
Guo, M.; Cao, B.; Ren, H.; Yongming, D.; Peng, J.; Fan, W.
2017-12-01
Land surface emissivity is a crucial parameter for estimating land surface temperature from remote sensing data and also plays an important role in the physical process of surface energy and water balance from local to global scales. To our knowledge, the emissivity varies with surface type and cover. As for the vegetation, its canopy emissivity is dependent on vegetation types, viewing zenith angle and structure that changes in different growing stages. Lots of previous studies have focused on the emissivity model, but few of them are analytic and suited to different canopy structures. In this paper, a new physical analytic model is proposed to estimate the directional emissivity of homogenous vegetation canopy based on spectral invariants. The initial model counts the directional absorption in six parts: the direct absorption of the canopy and the soil, the absorption of the canopy and soil after a single scattering and after multiple scattering within the canopy-soil system. In order to analytically estimate the emissivity, the pathways of photons absorbed in the canopy-soil system are traced using the re-collision probability in Fig.1. After sensitive analysis on the above six absorptions, the initial complicated model was further simplified as a fixed mathematic expression to estimate the directional emissivity for vegetation canopy. The model was compared with the 4SAIL model, FRA97 model, FRA02 model and DART model in Fig.2, and the results showed that the FRA02 model is significantly underestimated while the FRA97 model is a little underestimated, on basis of the new model. On the contrary, the emissivity difference between the new model with the 4SAIL model and DART model was found to be less than 0.002. In general, since the new model has the advantages of mathematic expression with accurate results and clear physical meaning, the model is promising to be extended to simulate the directional emissivity for the discrete canopy in further study.
NASA Technical Reports Server (NTRS)
Asner, Gregory P. (Principal Investigator)
2003-01-01
Woody encroachment has contributed to documented changes world-wide and locally in the southwestern U.S. Specifically, in North Texas rangelands encroaching mesquite (Prosopis glandulosa var. glandulosa) a known N-fixing species has caused changes in aboveground biomass. While measurements of aboveground plant production are relatively common, measures of soil N availability are scarce and vary widely. N trace gas emissions (nitric and nitrous oxide) flom soils reflect patterns in current N cycling rates and availability as they are stimulated by inputs of organic and inorganic N. Quantification of N oxide emissions from savanna soils may depend upon the spatial distribution of woody plant canopies, and specifically upon the changes in N availability and cycling and subsequent N trace gas production as influenced by the shift from herbaceous to woody vegetation type. The main goal of this research was to determine whether remotely sensible parameters of vegetation structure and soil type could be used to quantify biogeochemical changes in N at local, landscape and regional scales. To accomplish this goal, field-based measurements of N trace gases were carried out between 2000-2001, encompassing the acquisition of imaging spectrometer data from the NASA Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) on September 29, 2001. Both biotic (vegetation type and soil organic N) and abiotic (soil type, soil pH, temperature, soil moisture, and soil inorganic N) controls were analyzed for their contributions to observed spatial and temporal variation in soil N gas fluxes. These plot level studies were used to develop relationships between spatially extensive, field-based measurements of N oxide fluxes and remotely sensible aboveground vegetation and soil properties, and to evaluate the short-term controls over N oxide emissions through intensive field wetting experiments. The relationship between N oxide emissions, remotely-sensed parameters (vegetation cover, and soil type), and physical controls (soil moisture, and temperature) permitted the regional scale quantification of soil N oxides emissions. Landscape scale analysis linking N oxide emissions with cover change revealed an alleviation from N limitation following mesquite invasion. This study demonstrated the advantage of using N trace gases as a measure of ecosystem N availability combined with remote sensing to characterize the spatial heterogeneity in ecosystem parameters at a scale commensurate with field-based measurements of these properties. Woody vegetation encroachment provided an opportunity to capitalize on detection of the remotely-sensible parameter of woody cover as it relates to belowground biogeochemical processes that determine N trace gas production. The first spatially-explicit estimates of NO flux were calculated based on Prosopis fractional cover derived from high resolution remote sensing estimates of fractional woody cover (< 4 m) for a 120 sq km region of North Texas. An assessment of both N stocks and fluxes from the study revealed an alleviation of N limitation at this site experiencing recent woody encroachment. Many arid and semi-arid regions of the world are experiencing woody invasions, often of N-fixing species. The issue of woody encroachment is in the center of an ecological and political debate. Improving the links between biogeochemical processes and remote sensing of ecosystem properties will improve our understanding of biogeochemical processes at the regional scale, thus providing a means to address issues of land-use and land-cover change.
Food structure: Its formation and relationships with other properties.
Joardder, Mohammad U H; Kumar, Chandan; Karim, M A
2017-04-13
Food materials are complex in nature as it has heterogeneous, amorphous, hygroscopic and porous properties. During processing, microstructure of food materials changes which significantly affects other properties of food. An appropriate understanding of the microstructure of the raw food material and its evolution during processing is critical in order to understand and accurately describe dehydration processes and quality anticipation. This review critically assesses the factors that influence the modification of microstructure in the course of drying of fruits and vegetables. The effect of simultaneous heat and mass transfer on microstructure in various drying methods is investigated. Effects of changes in microstructure on other functional properties of dried foods are discussed. After an extensive review of the literature, it is found that development of food structure significantly depends on fresh food properties and process parameters. Also, modification of microstructure influences the other properties of final product. An enhanced understanding of the relationships between food microstructure, drying process parameters and final product quality will facilitate the energy efficient optimum design of the food processor in order to achieve high-quality food.
Yu, Manzhu; Yang, Chaowei
2016-01-01
Dust storms are devastating natural disasters that cost billions of dollars and many human lives every year. Using the Non-Hydrostatic Mesoscale Dust Model (NMM-dust), this research studies how different spatiotemporal resolutions of two input parameters (soil moisture and greenness vegetation fraction) impact the sensitivity and accuracy of a dust model. Experiments are conducted by simulating dust concentration during July 1-7, 2014, for the target area covering part of Arizona and California (31, 37, -118, -112), with a resolution of ~ 3 km. Using ground-based and satellite observations, this research validates the temporal evolution and spatial distribution of dust storm output from the NMM-dust, and quantifies model error using measurements of four evaluation metrics (mean bias error, root mean square error, correlation coefficient and fractional gross error). Results showed that the default configuration of NMM-dust (with a low spatiotemporal resolution of both input parameters) generates an overestimation of Aerosol Optical Depth (AOD). Although it is able to qualitatively reproduce the temporal trend of the dust event, the default configuration of NMM-dust cannot fully capture its actual spatial distribution. Adjusting the spatiotemporal resolution of soil moisture and vegetation cover datasets showed that the model is sensitive to both parameters. Increasing the spatiotemporal resolution of soil moisture effectively reduces model's overestimation of AOD, while increasing the spatiotemporal resolution of vegetation cover changes the spatial distribution of reproduced dust storm. The adjustment of both parameters enables NMM-dust to capture the spatial distribution of dust storms, as well as reproducing more accurate dust concentration.
Satellite observed global variations in ecosystem-scale plant water storage
NASA Astrophysics Data System (ADS)
Tian, F.; Wigneron, J. P.; Brandt, M.; Fensholt, R.
2017-12-01
Plant water storage is a key component in ecohydrological processes and tightly coupled with global carbon and energy budgets. Field measurements of individual trees have revealed diurnal and seasonal variations in plant water storage across different tree species and sizes. However, global estimation of plant water storage is challenged by up-scaling from individual trees to an ecosystem scale. The L-band passive microwaves are sensitive to water stored in the stems, branches and leaves, with dependence on the vegetation structure. Thus, the L-band vegetation optical depth (L-VOD) parameter retrieved from satellite passive microwave observations can be used as a proxy for ecosystem-scale plant water storage. Here, we employ the recently developed SMOS (Soil Moisture and Ocean Salinity) L-VOD dataset to investigate spatial patterns in global plant water storage and its diurnal and seasonal variations. In addition, we compare the spatiotemporal patterns between plant water storage and canopy greenness (i.e., enhanced vegetation indices, EVI) to gain ecohydrological insights among different territorial biomes, including boreal forest and tropical woodland. Generally, seasonal dynamics of plant water storage is much smaller than canopy greenness, yet the temporal coupling of these two traits is totally different between boreal and tropical regions, which could be related to their strategies in plant water regulation.
On Budyko curve as a consequence of climate-soil-vegetation equilibrium hypothesis
NASA Astrophysics Data System (ADS)
Pande, S.
2012-04-01
A hypothesis that Budyko curve is a consequence of stable equilibriums of climate-soil-vegetation co-evolution is tested at biome scale. We assume that i) distribution of vegetation, soil and climate within a biome is a distribution of equilibriums of similar soil-vegetation dynamics and that this dynamics is different across different biomes and ii) soil and vegetation are in dynamic equilibrium with climate while in static equilibrium with each other. In order to test the hypothesis, a two stage regression is considered using MOPEX/Hydrologic Synthesis Project dataset for basins in eastern United States. In the first stage, multivariate regression (Seemingly Unrelated Regression) is performed for each biome with soil (estimated porosity and slope of soil water retention curve) and vegetation characteristics (5-week NDVI gradient) as dependent variables and aridity index, vegetation and soil characteristics as independent variables for respective dependent variables. The regression residuals of the first stage along with aridity index then serve as second stage independent variables while actual vaporization to precipitation ratio (vapor index) serving as dependent variable. Insignificance, if revealed, of a first stage parameter allows us to reject the role of corresponding soil or vegetation characteristics in the co-evolution hypothesis. Meanwhile the significance of second stage regression parameter corresponding to a first stage residual allow us to reject the hypothesis that Budyko curve is a locus "solely" of climate-soil-vegetation co-evolution equilibrium points. Results suggest lack of evidence for soil-vegetation co-evolution in Prairies and Mixed/SouthEast Forests (unlike in Deciduous Forests) though climate plays a dominant role in explaining within biome soil and vegetation characteristics across all the biomes. Preliminary results indicate absence of effects beyond climate-soil-vegetation co-evolution in explaining the ratio of annual total minimum monthly flows to precipitation in Deciduous Forests though other three biome types show presence of effects beyond co-evolutionary. Such an analysis can yield insights into the nature of hydrologic change when assessed along the Budyko curve as well as non co-evolutionary effects such as anthropogenic effects on basin scale annual water balances.
NASA Astrophysics Data System (ADS)
Prescott, C. L.; Dolan, A. M.; Haywood, A. M.; Hunter, S. J.; Tindall, J. C.
2018-02-01
Regional climate and environmental variability in response to orbital forcing during interglacial events within the mid-Piacenzian (Pliocene) Warm Period (mPWP; 3.264-3.025 Ma) has been rarely studied using climate and vegetation models. Here we use climate and vegetation model simulations to predict changes in regional vegetation patterns in response to orbital forcing for four different interglacial events within the mPWP (Marine Isotope Stages (MIS) G17, K1, KM3 and KM5c). The efficacy of model-predicted changes in regional vegetation is assessed by reference to selected high temporal resolution palaeobotanical studies that are theoretically capable of discerning vegetation patterns for the selected interglacial stages. Annual mean surface air temperatures for the studied interglacials are between 0.4 °C to 0.7 °C higher than a comparable Pliocene experiment using modern orbital parameters. Increased spring/summer and reduced autumn/winter insolation in the Northern Hemisphere during MIS G17, K1 and KM3 enhances seasonality in surface air temperature. The two most robust and notable regional responses to this in vegetation cover occur in North America and continental Eurasia, where forests are replaced by more open-types of vegetation (grasslands and shrubland). In these regions our model results appear to be inconsistent with local palaeobotanical data. The orbitally driven changes in seasonal temperature and precipitation lead to a 30% annual reduction in available deep soil moisture (2.0 m from surface), a critical parameter for forest growth, and subsequent reduction in the geographical coverage of forest-type vegetation; a phenomenon not seen in comparable simulations of Pliocene climate and vegetation run with a modern orbital configuration. Our results demonstrate the importance of examining model performance under a range of realistic orbital forcing scenarios within any defined time interval (e.g. mPWP). Additional orbitally resolved records of regional vegetation are needed to further examine the validity of model-predicted regional climate and vegetation responses in greater detail.
A population model of chaparral vegetation response to frequent wildfires.
Lucas, Timothy A; Johns, Garrett; Jiang, Wancen; Yang, Lucie
2013-12-01
The recent increase in wildfire frequency in the Santa Monica Mountains (SMM) may substantially impact plant community structure. Species of Chaparral shrubs represent the dominant vegetation type in the SMM. These species can be divided into three life history types according to their response to wildfires. Nonsprouting species are completely killed by fire and reproduce by seeds that germinate in response to a fire cue, obligate sprouting species survive by resprouting from dormant buds in a root crown because their seeds are destroyed by fire, and facultative sprouting species recover after fire both by seeds and resprouts. Based on these assumptions, we developed a set of nonlinear difference equations to model each life history type. These models can be used to predict species survivorship under varying fire return intervals. For example, frequent fires can lead to localized extinction of nonsprouting species such as Ceanothus megacarpus while several facultative sprouting species such as Ceanothus spinosus and Malosma (Rhus) laurina will persist as documented by a longitudinal study in a biological preserve in the SMM. We estimated appropriate parameter values for several chaparral species using 25 years of data and explored parameter relationships that lead to equilibrium populations. We conclude by looking at the survival strategies of these three species of chaparral shrubs under varying fire return intervals and predict changes in plant community structure under fire intervals of short return. In particular, our model predicts that an average fire return interval of greater than 12 years is required for 50 % of the initial Ceanothus megacarpus population and 25 % of the initial Ceanothus spinosus population to survive. In contrast, we predict that the Malosma laurina population will have 90 % survivorship for an average fire return interval of at least 6 years.
Yanjun Su; Qinghua Guo; Danny L. Fry; Brandon M. Collins; Maggi Kelly; Jacob P. Flanagan; John J. Battles
2016-01-01
Abstract. Accurate vegetation mapping is critical for natural resources management, ecological analysis, and hydrological modeling, among other tasks. Remotely sensed multispectral and hyperspectral imageries have proved to be valuable inputs to the vegetation mapping process, but they can provide only limited vegetation structure...
NASA Astrophysics Data System (ADS)
Gholizadeh, Asa; Kopaekova, Veronika; Rogass, Christian; Mielke, Christian; Misurec, Jan
2016-08-01
Systematic quantification and monitoring of forest biophysical and biochemical variables is required to assess the response of ecosystems to climate change. Remote sensing has been introduced as a time and cost- efficient way to carry out large scale monitoring of vegetation parameters. Red-Edge Position (REP) is a hyperspectrally detectable parameter which is sensitive to vegetation Chl. In the current study, REP was modelled for the Norway spruce forest canopy resampled to HyMap and Sentinel-2 spectral resolution as well as calculated from the real HyMap and Sentinel-2 simulated data. Different REP extraction methods (4PLI, PF, LE, 4PLIH and 4PLIS) were assessed. The study showed the way for effective utilization of the forthcoming hyper and superspectral remote sensing sensors from orbit to monitor vegetation attributes.
Functional and Structural Optimality in Plant Growth: A Crop Modelling Case Study
NASA Astrophysics Data System (ADS)
Caldararu, S.; Purves, D. W.; Smith, M. J.
2014-12-01
Simple mechanistic models of vegetation processes are essential both to our understanding of plant behaviour and to our ability to predict future changes in vegetation. One concept that can take us closer to such models is that of plant optimality, the hypothesis that plants aim to achieve an optimal state. Conceptually, plant optimality can be either structural or functional optimality. A structural constraint would mean that plants aim to achieve a certain structural characteristic such as an allometric relationship or nutrient content that allows optimal function. A functional condition refers to plants achieving optimal functionality, in most cases by maximising carbon gain. Functional optimality conditions are applied on shorter time scales and lead to higher plasticity, making plants more adaptable to changes in their environment. In contrast, structural constraints are optimal given the specific environmental conditions that plants are adapted to and offer less flexibility. We exemplify these concepts using a simple model of crop growth. The model represents annual cycles of growth from sowing date to harvest, including both vegetative and reproductive growth and phenology. Structural constraints to growth are represented as an optimal C:N ratio in all plant organs, which drives allocation throughout the vegetative growing stage. Reproductive phenology - i.e. the onset of flowering and grain filling - is determined by a functional optimality condition in the form of maximising final seed mass, so that vegetative growth stops when the plant reaches maximum nitrogen or carbon uptake. We investigate the plants' response to variations in environmental conditions within these two optimality constraints and show that final yield is most affected by changes during vegetative growth which affect the structural constraint.
Wang, Cong; Li, Jing; Wu, Shanlong; Xia, Chuanfu
2017-01-01
Remote-sensing phenology detection can compensate for deficiencies in field observations and has the advantage of capturing the continuous expression of phenology on a large scale. However, there is some variability in the results of remote-sensing phenology detection derived from different vegetation parameters in satellite time-series data. Since the enhanced vegetation index (EVI) and the leaf area index (LAI) are the most widely used vegetation parameters for remote-sensing phenology extraction, this paper aims to assess the differences in phenological information extracted from EVI and LAI time series and to explore whether either index performs well for all vegetation types on a large scale. To this end, a GLASS (Global Land Surface Satellite Product)-LAI-based phenology product (GLP) was generated using the same algorithm as the MODIS (Moderate Resolution Imaging Spectroradiometer)-EVI phenology product (MLCD) over China from 2001 to 2012. The two phenology products were compared in China for different vegetation types and evaluated using ground observations. The results show that the ratio of missing data is 8.3% for the GLP, which is less than the 22.8% for the MLCD. The differences between the GLP and the MLCD become stronger as the latitude decreases, which also vary among different vegetation types. The start of the growing season (SOS) of the GLP is earlier than that of the MLCD in most vegetation types, and the end of the growing season (EOS) of the GLP is generally later than that of the MLCD. Based on ground observations, it can be suggested that the GLP performs better than the MLCD in evergreen needleleaved forests and croplands, while the MLCD performs better than the GLP in shrublands and grasslands. PMID:28867773
NASA Astrophysics Data System (ADS)
Song, Wanjuan; Mu, Xihan; Ruan, Gaiyan; Gao, Zhan; Li, Linyuan; Yan, Guangjian
2017-06-01
Normalized difference vegetation index (NDVI) of highly dense vegetation (NDVIv) and bare soil (NDVIs), identified as the key parameters for Fractional Vegetation Cover (FVC) estimation, are usually obtained with empirical statistical methods However, it is often difficult to obtain reasonable values of NDVIv and NDVIs at a coarse resolution (e.g., 1 km), or in arid, semiarid, and evergreen areas. The uncertainty of estimated NDVIs and NDVIv can cause substantial errors in FVC estimations when a simple linear mixture model is used. To address this problem, this paper proposes a physically based method. The leaf area index (LAI) and directional NDVI are introduced in a gap fraction model and a linear mixture model for FVC estimation to calculate NDVIv and NDVIs. The model incorporates the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) model parameters product (MCD43B1) and LAI product, which are convenient to acquire. Two types of evaluation experiments are designed 1) with data simulated by a canopy radiative transfer model and 2) with satellite observations. The root-mean-square deviation (RMSD) for simulated data is less than 0.117, depending on the type of noise added on the data. In the real data experiment, the RMSD for cropland is 0.127, for grassland is 0.075, and for forest is 0.107. The experimental areas respectively lack fully vegetated and non-vegetated pixels at 1 km resolution. Consequently, a relatively large uncertainty is found while using the statistical methods and the RMSD ranges from 0.110 to 0.363 based on the real data. The proposed method is convenient to produce NDVIv and NDVIs maps for FVC estimation on regional and global scales.
Territory and nest site selection patterns by Grasshopper Sparrows in southeastern Arizona
Ruth, Janet M.; Skagen, Susan K.
2017-01-01
Grassland bird populations are showing some of the greatest rates of decline of any North American birds, prompting measures to protect and improve important habitat. We assessed how vegetation structure and composition, habitat features often targeted for management, affected territory and nest site selection by Grasshopper Sparrows (Ammodramus savannarum ammolegus) in southeastern Arizona. To identify features important to males establishing territories, we compared vegetation characteristics of known territories and random samples on 2 sites over 5 years. We examined habitat selection patterns of females by comparing characteristics of nest sites with territories over 3 years. Males selected territories in areas of sparser vegetation structure and more tall shrubs (>2 m) than random plots on the site with low shrub densities. Males did not select territories based on the proportion of exotic grasses. Females generally located nest sites in areas with lower small shrub (1–2 m tall) densities than territories overall when possible and preferentially selected native grasses for nest construction. Whether habitat selection was apparent depended upon the range of vegetation structure that was available. We identified an upper threshold above which grass structure seemed to be too high and dense for Grasshopper Sparrows. Our results suggest that some management that reduces vegetative structure may benefit this species in desert grasslands at the nest and territory scale. However, we did not assess initial male habitat selection at a broader landscape scale where their selection patterns may be different and could be influenced by vegetation density and structure outside the range of values sampled in this study.
NASA Astrophysics Data System (ADS)
Bustamante, María; Tajadura, Javier; Gorostiaga, José María; Saiz-Salinas, José Ignacio
2014-06-01
Macroalgae comprise a prominent part of the rocky benthos where many invertebrates develop, and are believed to be undergoing severe declines worldwide. In order to investigate how the vegetation structure (crustose, basal and canopy layers) contributes to the diversity, structure and function of benthic invertebrates, a total of 31 subtidal transects were sampled along the northeast Atlantic coast of Spain. Significant positive relationships were found between the canopy layer and faunal abundance, taxonomic diversity and functional group diversity. Canopy forming algae were also related to epiphytic invertebrates, medium size forms, colonial strategy and suspensivores. By contrast, basal algae showed negative relationships with all variables tested except for detritivores. Multivariate multiple regression analyses (DISTLM) point to crustose as well as canopy layers as the best link between seaweeds and invertebrate assemblage structure. A close relationship was found between taxonomic and functional diversities. In general, low levels of taxonomic redundancy were detected for functional groups correlated with vegetation structure. A conceptual model based on the results is proposed, describing distinct stages of invertebrate assemblages in relation to the vertical structure of vegetation.
NASA Astrophysics Data System (ADS)
Sarkar, S.; Peters-Lidard, C.; Chiu, L.; Kafatos, M.
2005-12-01
Increasing population and urbanization have created stress on developing nations. The quickly shifting patterns of vegetation change in different parts of the world have given rise to the pertinent question of feedback on the climate prevailing on local to regional scales. It is now known with some certainty, that vegetation changes can affect the climate by influencing the heat and water balance. The hydrological cycle particularly is susceptible to changes in vegetation. The Monsoon rainfall forms a vital link in the hydrological cycle prevailing over South East Asia This work examines the variability of vegetation over South East Asia and assesses its impact on the monsoon rainfall. We explain the role of changing vegetation and show how this change has affected the heat and energy balance. We demonstrate the role of vegetation one season earlier in influencing rainfall intensity over specific areas in South East Asia and show the ramification of vegetation change on the summer rainfall behavior. The vegetation variability study specifically focuses on India and China, two of the largest and most populous nations. We have done an assessment to find out the key meteorological and human induced parameters affecting vegetation over the study area through a spatial analysis of monthly NDVI values. This study highlights the role of monsoon rainfall, regional climate dynamics and large scale human induced pollution to be the crucial factors governing the vegetation and vegetation distribution. The vegetation is seen to follow distinct spatial patterns that have been found to be crucial in its eventual impact on monsoon rainfall. We have carried out a series of sensitivity experiments using a land surface hydrologic modeling scheme. The vital energy and water balance parameters are identified and the daily climatological cycles are examined for possible change in behavior for different boundary conditions. It is found that the change from native deciduous forest vegetation to crop land affects monsoon rainfall in two ways: 1) The presence of cropland increases the sensible heat release from ground, increasing the chances for development of forced convection; 2) Large scale irrigation associated with spring crop development creates a moister lower boundary layer thus inducing more moist instability and free convection in the succeeding season.
Calibration of the ``Simplified Simple Biosphere Model—SSiB'' for the Brazilian Northeast Caatinga
NASA Astrophysics Data System (ADS)
do Amaral Cunha, Ana Paula Martins; dos Santos Alvalá, Regina Célia; Correia, Francis Wagner Silva; Kubota, Paulo Yoshio
2009-03-01
The Brazilian Northeast region is covered largely by vegetation adapted to the arid conditions and with varied physiognomy, called caatinga. It occupies an extension of about 800.000 km2 that corresponds to 70% of the region. In recent decades, considerable progress in understanding the micrometeorological processes has been reached, with results that were incorporated into soil-vegetation-atmosphere transfer schemes (SVATS) to study the momentum, energy, water vapor, carbon cycle and vegetation dynamics changes of different ecosystems. Notwithstanding, the knowledge of the parameters and physical or physiological characteristics of the vegetation and soil of the caatinga region is very scarce. So, the objective of this work was performing a calibration of the parameters of the SSiB model for the Brazilian Northeast Caatinga. Micrometeorological and hydrological data collected from July 2004 to June 2005, obtained in the Agricultural Research Center of the Semi-Arid Tropic (CPATSA), were used. Preceding the calibration process, a sensibility study of the SSiB model was performed in order to find the parameters that are sensible to the exchange processes between the surface and atmosphere. The results showed that the B parameter, soil moisture potential at saturation (ψs), hydraulic conductivity of saturated soil (ks) and the volumetric moisture at saturation (θs) present high variations on turbulent fluxes. With the initial parameters, the SSiB model showed best results for net radiation, and the latent heat (sensible heat) flux was over-estimated (under-estimated) for all simulation periods. Considering the calibrated parameters, better values of latent flux and sensible flux were obtained. The calibrated parameters were also used for a validation of the surface fluxes considering data from July 2005 to September 2005. The results showed that the model generated better estimations of latent heat and sensible heat fluxes, with low root mean square error. With better estimations of the turbulent fluxes, it was possible to obtain a more representative energy partitioning for the caatinga. Therefore, it is expected that from this calibrated SSiB model, coupled to the meteorological models, it will be possible to obtain more realistic climate and weather forecasts for the Brazilian Northeast region.
Salazar-Villanea, S; Hendriks, W H; Bruininx, E M A M; Gruppen, H; van der Poel, A F B
2016-06-01
Protein structure influences the accessibility of enzymes for digestion. The proportion of intramolecular β-sheets in the secondary structure of native proteins has been related to a decrease in protein digestibility. Changes to proteins that can be considered positive (for example, denaturation and random coil formation) or negative (for example, aggregation and Maillard reactions) for protein digestibility can occur simultaneously during processing. The final result of these changes on digestibility seems to be a counterbalance of the occurrence of each phenomenon. Occurrence of each phenomenon depends on the conditions applied, but also on the source and type of the protein that is processed. The correlation between denaturation enthalpy after processing and protein digestibility seems to be dependent on the protein source. Heat seems to be the processing parameter with the largest influence on changes in the structure of proteins. The effect of moisture is usually limited to the simultaneous application of heat, but increasing level of moisture during processing usually increases structural changes in proteins. The effect of shear on protein structure is commonly studied using extrusion, although the multifactorial essence of this technology does not allow disentanglement of the separate effects of each processing parameter (for example, heat, shear, moisture). Although most of the available literature on the processing of feed ingredients reports effects on protein digestibility, the mechanisms that explain these effects are usually lacking. Clarifying these mechanisms could aid in the prediction of the nutritional consequences of processing conditions.
A model for microwave emission from vegetation-covered fields
NASA Technical Reports Server (NTRS)
Mo, T.; Choudhury, B. J.; Schmugge, T. J.; Wang, J. R.; Jackson, T. J.
1982-01-01
The measured brightness temperatures over vegetation-covered fields are simulated by a radiative transfer model which treats the vegetation as a uniform canopy with a constant temperature, over a moist soil which emits polarized microwave radiation. The analytic formula for the microwave emission has four parameters: roughness height, polarization mixing factor, effective canopy optical thickness, and single scattering albedo. A good representation has been obtained with the model for both the horizontally and vertically polarized brightness temperatures at 1.4 and 5 GHz frequencies, over fields covered with grass, soybean and corn. A directly proportional relation is found between effective canopy optical thickness and the amount of water present in the vegetation canopy. The effective canopy single scattering albedo depends on vegetation type.
Soil Moisture and Vegetation Effects on GPS Reflectivity From Land
NASA Astrophysics Data System (ADS)
Torres, O.; Grant, M. S.; Bosch, D.
2004-12-01
While originally designed as a navigation system, the GPS signal has been used to achieve a number of useful scientific measurements. One of these measurements utilizes the reflection of the GPS signal from land to determine soil moisture. The study of GPS reflections is based on a bistatic configuration that utilizes forward reflection from the surface. The strength of the GPS signal varies in proportion to surface parameters such as soil moisture, soil type, vegetation cover, and topography. This paper focuses on the effects of soil water content and vegetation cover on the surface based around a reflectivity. A two-part method for calibrating the GPS reflectivity was developed that permits the comparison of the data with surface parameters. The first part of the method relieves the direct signal from any multipath effects, the second part is an over-water calibration that yields a reflectivity independent of the transmitting satellite. The sensitivity of the GPS signal to water in the soil is shown by presenting the increase in reflectivity after rain as compared to before rain. The effect of vegetation on the reflected signal is also presented by the inclusion of leaf area index as a fading parameter in the reflected signal from corn and soy bean fields. The results are compared to extensive surface measurements made as part of the Soil Moisture Experiment 2002 (SMEX 2002) in Iowa and SMEX 2003 in Georgia.
The Impacts of Typical Drought Events on Terrestrial Vegetation in China
NASA Astrophysics Data System (ADS)
Yang, J.; Wu, J.; Zhou, H.; Han, X.
2018-04-01
In our study, according to the statistical results of standardized precipitation evapotranspiration index (SPEI), we chose two drought events which occurred in the North China during 2001 and in the Southwest China from 2009 to 2010. And two of the Global Land Surface Satellite (GLASS) products had been used to evaluate the impacts of drought on vegetation, including the leaf area index (LAI) and the fraction of absorbed photosynthetically active radiation (FAPAR). The results show that: (1) In the development process of a drought event, the anomaly of remote sensing parameters (LAI and FAPAR) usually falls firstly and then rises as the drought changes from moderate to severe and then to moderate. This indicates that the effects of drought on vegetation remote sensing parameters are closely related to the severity of drought disaster. (2) The response of different vegetation types to the drought disaster is different. Compared with the forests, the response of grasslands to drought disaster is earlier. For example, the duration affected by drought disaster in grassland is longer 1/3 than the forests in the Southwest China. (3) Irrigation is an effective measure to mitigate the effects of drought. Irrigated croplands are less affected by drought than non-irrigated croplands and grasslands. In the North China, the decrease amplitude of irrigated croplands' remote sensing parameters is about half of non-irrigated croplands'.
NASA Astrophysics Data System (ADS)
Bergen, K. M.; Goetz, S. J.; Dubayah, R. O.; Henebry, G. M.; Hunsaker, C. T.; Imhoff, M. L.; Nelson, R. F.; Parker, G. G.; Radeloff, V. C.
2009-06-01
Biodiversity and habitat face increasing pressures due to human and natural influences that alter vegetation structure. Because of the inherent difficulty of measuring forested vegetation three-dimensional (3-D) structure on the ground, this important component of biodiversity and habitat has been, until recently, largely restricted to local measurements, or at larger scales to generalizations. New lidar and radar remote sensing instruments such as those proposed for spaceborne missions will provide the capability to fill this gap. This paper reviews the state of the art for incorporatinginformation on vegetation 3-D structure into biodiversity and habitat science and management approaches, with emphasis on use of lidar and radar data. First we review relationships between vegetation 3-D structure, biodiversity and habitat, and metrics commonly used to describe those relationships. Next, we review the technical capabilities of new lidar and radar sensors and their application to biodiversity and habitat studies to date. We then define variables that have been identified as both useful and feasible to retrieve from spaceborne lidar and radar observations and provide their accuracy and precision requirements. We conclude with a brief discussion of implications for spaceborne missions and research programs. The possibility to derive vegetation 3-D measurements from spaceborne active sensors and to integrate them into science and management comes at a critical juncture for global biodiversity conservation and opens new possibilities for advanced scientific analysis of habitat and biodiversity.
New Microwave-Based Missions Applications for Rainfed Crops Characterization
NASA Astrophysics Data System (ADS)
Sánchez, N.; Lopez-Sanchez, J. M.; Arias-Pérez, B.; Valcarce-Diñeiro, R.; Martínez-Fernández, J.; Calvo-Heras, J. M.; Camps, A.; González-Zamora, A.; Vicente-Guijalba, F.
2016-06-01
A multi-temporal/multi-sensor field experiment was conducted within the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS) in Spain, in order to retrieve useful information from satellite Synthetic Aperture Radar (SAR) and upcoming Global Navigation Satellite Systems Reflectometry (GNSS-R) missions. The objective of the experiment was first to identify which radar observables are most sensitive to the development of crops, and then to define which crop parameters the most affect the radar signal. A wide set of radar variables (backscattering coefficients and polarimetric indicators) acquired by Radarsat-2 were analyzed and then exploited to determine variables characterizing the crops. Field measurements were fortnightly taken at seven cereals plots between February and July, 2015. This work also tried to optimize the crop characterization through Landsat-8 estimations, testing and validating parameters such as the leaf area index, the fraction of vegetation cover and the vegetation water content, among others. Some of these parameters showed significant and relevant correlation with the Landsat-derived Normalized Difference Vegetation Index (R>0.60). Regarding the radar observables, the parameters the best characterized were biomass and height, which may be explored for inversion using SAR data as an input. Moreover, the differences in the correlations found for the different crops under study types suggested a way to a feasible classification of crops.
A novel approach for calculating shelf life of minimally processed vegetables.
Corbo, Maria Rosaria; Del Nobile, Matteo Alessandro; Sinigaglia, Milena
2006-01-15
Shelf life of minimally processed vegetables is often calculated by using the kinetic parameters of Gompertz equation as modified by Zwietering et al. [Zwietering, M.H., Jongenburger, F.M., Roumbouts, M., van't Riet, K., 1990. Modelling of the bacterial growth curve. Applied and Environmental Microbiology 56, 1875-1881.] taking 5x10(7) CFU/g as the maximum acceptable contamination value consistent with acceptable quality of these products. As this method does not allow estimation of the standard errors of the shelf life, in this paper the modified Gompertz equation was re-parameterized to directly include the shelf life as a fitting parameter among the Gompertz parameters. Being the shelf life a fitting parameter is possible to determine its confidence interval by fitting the proposed equation to the experimental data. The goodness-of-fit of this new equation was tested by using mesophilic bacteria cell loads from different minimally processed vegetables (packaged fresh-cut lettuce, fennel and shredded carrots) that differed for some process operations or for package atmosphere. The new equation was able to describe the data well and to estimate the shelf life. The results obtained emphasize the importance of using the standard errors for the shelf life value to show significant differences among the samples.
Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices
Ji, Lei; Zhang, Li; Rover, Jennifer R.; Wylie, Bruce K.; Chen, Xuexia
2014-01-01
In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices.
Sukhovol'skiĭ, V G; Ovchinnikova, T M; Baboĭ, S D
2014-01-01
As a description of altitude-belt zonality of wood vegetation, a model of ecological second-order transitions is proposed. Objects of the study have been chosen to be forest cenoses of the northern slope of Kulumyss Ridge (the Sayan Mauntains), while the results are comprised by the altitude profiles of wood vegetation. An ecological phase transition can be considered as the transition of cenoses at different altitudes from the state of presence of certain tree species within the studied territory to the state of their absence. By analogy with the physical model of second-order, phase transitions the order parameter is introduced (i.e., the area portion occupied by a single tree species at the certain altitude) as well as the control variable (i.e., the altitude of the wood vegetation belt). As the formal relation between them, an analog of the Landau's equation for phase transitions in physical systems is obtained. It is shown that the model is in a good accordance with the empirical data. Thus, the model can be used for estimation of upper and lower boundaries of altitude belts for individual tree species (like birch, aspen, Siberian fir, Siberian pine) as well as the breadth of their ecological niches with regard to altitude. The model includes also the parameters that describe numerically the interactions between different species of wood vegetation. The approach versatility allows to simplify description and modeling of wood vegetation altitude zonality, and enables assessment of vegetation cenoses response to climatic changes.
Evaluating high temporal and spatial resolution vegetation index for crop yield prediction
USDA-ARS?s Scientific Manuscript database
Remote sensing data have been widely used in estimating crop yield. Remote sensing derived parameters such as Vegetation Index (VI) were used either directly in building empirical models or by assimilating with crop growth models to predict crop yield. The abilities of remote sensing VI in crop yiel...
MCFire model technical description
David R. Conklin; James M. Lenihan; Dominique Bachelet; Ronald P. Neilson; John B. Kim
2016-01-01
MCFire is a computer program that simulates the occurrence and effects of wildfire on natural vegetation, as a submodel within the MC1 dynamic global vegetation model. This report is a technical description of the algorithms and parameter values used in MCFire, intended to encapsulate its design and features a higher level that is more conceptual than the level...
Impacts of exotic mangroves and mangrove control on tide pool fish assemblages
Richard A. MacKenzie; Cailtin L. Kryss
2013-01-01
Fish were sampled from tide pools in Hawaii to determine how exotic mangroves Rhizophora mangle and the use of herbicides to chemically eradicate them are impacting tide pool fish assemblages. Ecological parameters were compared among mangrove-invaded, native vegetated, and non-vegetated tide pools before and after mangroves had been chemically...
Towards an improved LAI collection protocol via simulated field-based PAR sensing
Yao, Wei; Van Leeuwen, Martin; Romanczyk, Paul; ...
2016-07-14
In support of NASA’s next-generation spectrometer—the Hyperspectral Infrared Imager (HyspIRI)—we are working towards assessing sub-pixel vegetation structure from imaging spectroscopy data. Of particular interest is Leaf Area Index (LAI), which is an informative, yet notoriously challenging parameter to efficiently measure in situ. While photosynthetically-active radiation (PAR) sensors have been validated for measuring crop LAI, there is limited literature on the efficacy of PAR-based LAI measurement in the forest environment. This study (i) validates PAR-based LAI measurement in forest environments, and (ii) proposes a suitable collection protocol, which balances efficiency with measurement variation, e.g., due to sun flecks and various-sized canopymore » gaps. A synthetic PAR sensor model was developed in the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model and used to validate LAI measurement based on first-principles and explicitly-known leaf geometry. Simulated collection parameters were adjusted to empirically identify optimal collection protocols. Furthermore, these collection protocols were then validated in the field by correlating PAR-based LAI measurement to the normalized difference vegetation index (NDVI) extracted from the “classic” Airborne Visible Infrared Imaging Spectrometer (AVIRIS-C) data (R 2 was 0.61). The results indicate that our proposed collecting protocol is suitable for measuring the LAI of sparse forest (LAI < 3–5 ( m 2/m 2)).« less
Glenn, Nancy F.; Neuenschwander, Amy; Vierling, Lee A.; Spaete, Lucas; Li, Aihua; Shinneman, Douglas; Pilliod, David S.; Arkle, Robert; McIlroy, Susan
2016-01-01
To estimate the potential synergies of OLI and ICESat-2 we used simulated ICESat-2 photon data to predict vegetation structure. In a shrubland environment with a vegetation mean height of 1 m and mean vegetation cover of 33%, vegetation photons are able to explain nearly 50% of the variance in vegetation height. These results, and those from a comparison site, suggest that a lower detection threshold of ICESat-2 may be in the range of 30% canopy cover and roughly 1 m height in comparable dryland environments and these detection thresholds could be used to combine future ICESat-2 photon data with OLI spectral data for improved vegetation structure. Overall, the synergistic use of Landsat 8 and ICESat-2 may improve estimates of above-ground biomass and carbon storage in drylands that meet these minimum thresholds, increasing our ability to monitor drylands for fuel loading and the potential to sequester carbon.
Dimensions of vegetable parenting practices among preschoolers
USDA-ARS?s Scientific Manuscript database
The objective of this study was to determine the factor structure of 31 effective and ineffective vegetable parenting practices used by parents of preschool children based on three theoretically proposed factors: responsiveness, control, and structure. The methods employed included both corrected it...
Vegetation Change in Blue Oak Woodlands in California
Barbara A. Holzman; Barbara H. Allen-Diaz
1991-01-01
A preliminary report of a statewide project investigating vegetation change in blue oak (Quercus douglasii) woodlands in California is presented. Vegetation plots taken in the 1930s, as part of a statewide vegetation mapping project, were relocated and surveyed. Species composition, cover and tree stand structure data from the earlier study were...
Predicting local Soil- and Land-units with Random Forest in the Senegalese Sahel
NASA Astrophysics Data System (ADS)
Grau, Tobias; Brandt, Martin; Samimi, Cyrus
2013-04-01
MODIS (MCD12Q1) or Globcover are often the only available global land-cover products, however ground-truthing in the Sahel of Senegal has shown that most classes do have any agreement with actual land-cover making those products unusable in any local application. We suggest a methodology, which models local Wolof land- and soil-types in an area in the Senegalese Ferlo around Linguère at different scales. In a first step, interviews with the local population were conducted to ascertain the local denotation of soil units, as well as their agricultural use and woody vegetation mainly growing on them. "Ndjor" are soft sand soils with mainly Combretum glutinosum trees. They are suitable for groundnuts and beans while millet is grown on hard sand soils ("Bardjen") dominated by Balanites aegyptiaca and Acacia tortilis. "Xur" are clayey depressions with a high diversity of tree species. Lateritic pasture sites with dense woody vegetation (mostly Pterocarpus lucens and Guiera senegalensis) have never been used for cropping and are called "All". In a second step, vegetation and soil parameters of 85 plots (~1 ha) were surveyed in the field. 28 different soil parameters are clustered into 4 classes using the WARD algorithm. Here, 81% agree with the local classification. Then, an ordination (NMDS) with 2 dimensions and a stress-value of 9.13% was calculated using the 28 soil parameters. It shows several significant relationships between the soil classes and the fitted environmental parameters which are derived from field data, a digital elevation model, Landsat and RapidEye imagery as well as TRMM rainfall data. Landsat's band 5 reflectance values (1.55 - 1.75 µm) of mean dry season image (2000-2010) has a R² of 0.42 and is the most important of 9 significant variables (5%-level). A random forest classifier is then used to extrapolate the 4 classes to the whole study area based on the 9 significant environmental parameters. At a resolution of 30 m the OBB (out-of-bag) error rate is 6.55%. At this scale, even small depressions and local discrepancies at field-level can be identified. Scaling to 250, 500 and 1000 m still gives a reliable overview of prevalent soil-units in the region. By relating soil to vegetation parameters we prove, that these maps indicate the potential dominant woody vegetation. Our example demonstrates, that solely the use of native Wolof land-types, which are gathered by interviews, can be used to get a proper scientific classification of (a) the agricultural suitability and (b) the dominant woody vegetation in an area of the Senegalese Sahel region.
Vegetation change detection and quantification: linking Landsat imagery and LIDAR data
Peterson, Birgit E.; Nelson, Kurtis J.
2009-01-01
Measurements of the horizontal and vertical structure of vegetation are helpful for detecting and monitoring change or disturbance on the landscape. Lidar has a unique ability to capture the three-dimensional structure of vegetation canopies. In this preliminary study, we present the results of a series of exploratory data analyses that tested our assumptions about the links between the structural data obtainable from lidar and the change detection products derived from Landsat imagery. Our study area is located in the Sierra National Forest in the Sierra Nevada Mountains of California and covers a wide range of vegetation types. The lidar data used in this study were collected by the Laser Vegetation Imaging System (LVIS) (Blair et al., 1999). LVIS is a largefootprint lidar system optimized to measure canopy structure characteristics. A series of Landsat scenes from 1984 through 2008 was collected for the study area (Path 42, Row 34) and processed to generate maps of disturbance. The preliminary results described here indicate that even simple metrics of height can be useful in assessing changes in structure brought about by disturbance in forest canopies. For example, canopy height values for 2008 were higher on average than those measured for 1999 in undisturbed forest, whereas this trend is not clearly observable for the disturbed forest patches.
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.
Comparison modeling for alpine vegetation distribution in an arid area.
Zhou, Jihua; Lai, Liming; Guan, Tianyu; Cai, Wetao; Gao, Nannan; Zhang, Xiaolong; Yang, Dawen; Cong, Zhentao; Zheng, Yuanrun
2016-07-01
Mapping and modeling vegetation distribution are fundamental topics in vegetation ecology. With the rise of powerful new statistical techniques and GIS tools, the development of predictive vegetation distribution models has increased rapidly. However, modeling alpine vegetation with high accuracy in arid areas is still a challenge because of the complexity and heterogeneity of the environment. Here, we used a set of 70 variables from ASTER GDEM, WorldClim, and Landsat-8 OLI (land surface albedo and spectral vegetation indices) data with decision tree (DT), maximum likelihood classification (MLC), and random forest (RF) models to discriminate the eight vegetation groups and 19 vegetation formations in the upper reaches of the Heihe River Basin in the Qilian Mountains, northwest China. The combination of variables clearly discriminated vegetation groups but failed to discriminate vegetation formations. Different variable combinations performed differently in each type of model, but the most consistently important parameter in alpine vegetation modeling was elevation. The best RF model was more accurate for vegetation modeling compared with the DT and MLC models for this alpine region, with an overall accuracy of 75 % and a kappa coefficient of 0.64 verified against field point data and an overall accuracy of 65 % and a kappa of 0.52 verified against vegetation map data. The accuracy of regional vegetation modeling differed depending on the variable combinations and models, resulting in different classifications for specific vegetation groups.
Automated integration of lidar into the LANDFIRE product suite
Peterson, Birgit; Nelson, Kurtis; Seielstad, Carl; Stoker, Jason M.; Jolly, W. Matt; Parsons, Russell
2015-01-01
Accurate information about three-dimensional canopy structure and wildland fuel across the landscape is necessary for fire behaviour modelling system predictions. Remotely sensed data are invaluable for assessing these canopy characteristics over large areas; lidar data, in particular, are uniquely suited for quantifying three-dimensional canopy structure. Although lidar data are increasingly available, they have rarely been applied to wildland fuels mapping efforts, mostly due to two issues. First, the Landscape Fire and Resource Planning Tools (LANDFIRE) program, which has become the default source of large-scale fire behaviour modelling inputs for the US, does not currently incorporate lidar data into the vegetation and fuel mapping process because spatially continuous lidar data are not available at the national scale. Second, while lidar data are available for many land management units across the US, these data are underutilized for fire behaviour applications. This is partly due to a lack of local personnel trained to process and analyse lidar data. This investigation addresses these issues by developing the Creating Hybrid Structure from LANDFIRE/lidar Combinations (CHISLIC) tool. CHISLIC allows individuals to automatically generate a suite of vegetation structure and wildland fuel parameters from lidar data and infuse them into existing LANDFIRE data sets. CHISLIC will become available for wider distribution to the public through a partnership with the U.S. Forest Service’s Wildland Fire Assessment System (WFAS) and may be incorporated into the Wildland Fire Decision Support System (WFDSS) with additional design and testing. WFAS and WFDSS are the primary systems used to support tactical and strategic wildland fire management decisions.
Yuan, Jiajia; Dong, Wenyi; Sun, Feiyun; Li, Pu; Zhao, Ke
2016-05-01
An environment-friendly decentralized wastewater treatment process that is comprised of activated sludge process (ASP) and wetland vegetation, named as vegetation-activated sludge process (V-ASP), was developed for decentralized wastewater treatment. The long-term experimental results evidenced that the vegetation sequencing batch reactor (V-SBR) process had consistently stable higher removal efficiencies of organic substances and nutrients from domestic wastewater compared with traditional sequencing batch reactor (SBR). The vegetation allocated into V-SBR system could not only remove nutrients through its vegetation transpiration ratio but also provide great surface area for microorganism activity enhancement. This high vegetation transpiration ratio enhanced nutrients removal effectiveness from wastewater mainly by flux enhancement, oxygen and substrate transportation acceleration, and vegetation respiration stimulation. A mathematical model based on ASM2d was successfully established by involving the specific function of vegetation to simulate system performance. The simulation results on the influence of operational parameters on V-ASP treatment effectiveness demonstrated that V-SBR had a high resistance to seasonal temperature fluctuations and influent loading shocking.
Integrated vegetation management (IVM) for INDOT roadsides.
DOT National Transportation Integrated Search
2014-03-01
With over 90,000 miles of road in Indiana, it is important that adjoining vegetation be maintained for safety concerns, road structure : maintenance and aesthetics. Mowing is currently the main form of vegetation management on INDOT (Indiana Departme...
J. Morgan Grove; Mary L. Cadenasso; William R., Jr. Burch; Steward T. Pickett; Kirsten Schwarz; Jarlath O' Neil-Dunne; Matthew Wilson; Austin Troy; Christopher Boone
2006-01-01
Recent advances in remote sensing and the adoption of geographic information systems (GIS) have greatly increased the availibility of high-resolution spatial and attribute data for examing the relationship between social and vegetation structure in urban areas. There are several motivations for understanding this relationship. First, the United States has experienced a...
O'Connor, Teresia; Watson, Kathy; Hughes, Sheryl; Beltran, Alicia; Hingle, Melanie; Baranowski, Janice; Campbell, Karen; Canal, Dolors Juvinyà; Lizaur, Ana Bertha Pérez; Zacarías, Isabel; González, Daniela; Nicklas, Theresa; Baranowski, Tom
2010-07-01
Fruit and vegetable intake may reduce the risk of some chronic diseases. However, many children consume less-than-recommended amounts of fruit and vegetables. Because health professionals and dietetics practitioners often work with parents to increase children's fruit and vegetable intake, assessing their opinions about the effectiveness of parenting practices is an important step in understanding how to promote fruit and vegetable intake among preschool-aged children. Using a cross-sectional design, collaborators from six countries distributed an Internet survey to health and nutrition organization members. A self-selected sample reported their perceptions of the effectiveness of 39 parenting practices intended to promote fruit and vegetable consumption in preschool-aged children from May 18, 2008, to September 16, 2008. A total of 889 participants (55% United States, 22.6% Mexico, 10.9% Australia, 4.4% Spain, 3.3% Chile, 2.2% United Kingdom, and 1.6% other countries) completed the survey. The fruit and vegetable intake-related parenting practices items were categorized into three dimensions (structure, responsiveness, and control) based on a parenting theory conceptual framework and dichotomized as effective/ineffective based on professional perceptions. The theoretically derived factor structures for effective and ineffective parenting practices were evaluated using separate confirmatory factor analyses and demonstrated acceptable fit. Fruit and vegetable intake-related parenting practices that provide external control were perceived as ineffective or counterproductive, whereas fruit and vegetable intake-related parenting practices that provided structure, nondirective control, and were responsive were perceived as effective in getting preschool-aged children to consume fruit and vegetables. Future research needs to develop and validate a parent-reported measure of these fruit and vegetable intake-related parenting practices and to empirically evaluate the effect of parental use of the parenting practices on child fruit and vegetable consumption. Copyright 2010 American Dietetic Association. Published by Elsevier Inc. All rights reserved.
Tropical forest plantation biomass estimation using RADARSAT-SAR and TM data of south china
NASA Astrophysics Data System (ADS)
Wang, Chenli; Niu, Zheng; Gu, Xiaoping; Guo, Zhixing; Cong, Pifu
2005-10-01
Forest biomass is one of the most important parameters for global carbon stock model yet can only be estimated with great uncertainties. Remote sensing, especially SAR data can offers the possibility of providing relatively accurate forest biomass estimations at a lower cost than inventory in study tropical forest. The goal of this research was to compare the sensitivity of forest biomass to Landsat TM and RADARSAT-SAR data and to assess the efficiency of NDVI, EVI and other vegetation indices in study forest biomass based on the field survey date and GIS in south china. Based on vegetation indices and factor analysis, multiple regression and neural networks were developed for biomass estimation for each species of the plantation. For each species, the better relationships between the biomass predicted and that measured from field survey was obtained with a neural network developed for the species. The relationship between predicted and measured biomass derived from vegetation indices differed between species. This study concludes that single band and many vegetation indices are weakly correlated with selected forest biomass. RADARSAT-SAR Backscatter coefficient has a relatively good logarithmic correlation with forest biomass, but neither TM spectral bands nor vegetation indices alone are sufficient to establish an efficient model for biomass estimation due to the saturation of bands and vegetation indices, multiple regression models that consist of spectral and environment variables improve biomass estimation performance. Comparing with TM, a relatively well estimation result can be achieved by RADARSAT-SAR, but all had limitations in tropical forest biomass estimation. The estimation results obtained are not accurate enough for forest management purposes at the forest stand level. However, the approximate volume estimates derived by the method can be useful in areas where no other forest information is available. Therefore, this paper provides a better understanding of relationships of remote sensing data and forest stand parameters used in forest parameter estimation models.
Present-Day Vegetation Helps Quantifying Past Land Cover in Selected Regions of the Czech Republic
Abraham, Vojtěch; Oušková, Veronika; Kuneš, Petr
2014-01-01
The REVEALS model is a tool for recalculating pollen data into vegetation abundances on a regional scale. We explored the general effect of selected parameters by performing simulations and ascertained the best model setting for the Czech Republic using the shallowest samples from 120 fossil sites and data on actual regional vegetation (60 km radius). Vegetation proportions of 17 taxa were obtained by combining the CORINE Land Cover map with forest inventories, agricultural statistics and habitat mapping data. Our simulation shows that changing the site radius for all taxa substantially affects REVEALS estimates of taxa with heavy or light pollen grains. Decreasing the site radius has a similar effect as increasing the wind speed parameter. However, adjusting the site radius to 1 m for local taxa only (even taxa with light pollen) yields lower, more correct estimates despite their high pollen signal. Increasing the background radius does not affect the estimates significantly. Our comparison of estimates with actual vegetation in seven regions shows that the most accurate relative pollen productivity estimates (PPEs) come from Central Europe and Southern Sweden. The initial simulation and pollen data yielded unrealistic estimates for Abies under the default setting of the wind speed parameter (3 m/s). We therefore propose the setting of 4 m/s, which corresponds to the spring average in most regions of the Czech Republic studied. Ad hoc adjustment of PPEs with this setting improves the match 3–4-fold. We consider these values (apart from four exceptions) to be appropriate, because they are within the ranges of standard errors, so they are related to original PPEs. Setting a 1 m radius for local taxa (Alnus, Salix, Poaceae) significantly improves the match between estimates and actual vegetation. However, further adjustments to PPEs exceed the ranges of original values, so their relevance is uncertain. PMID:24936973
[The research on bidirectional reflectance computer simulation of forest canopy at pixel scale].
Song, Jin-Ling; Wang, Jin-Di; Shuai, Yan-Min; Xiao, Zhi-Qiang
2009-08-01
Computer simulation is based on computer graphics to generate the realistic 3D structure scene of vegetation, and to simulate the canopy regime using radiosity method. In the present paper, the authors expand the computer simulation model to simulate forest canopy bidirectional reflectance at pixel scale. But usually, the trees are complex structures, which are tall and have many branches. So there is almost a need for hundreds of thousands or even millions of facets to built up the realistic structure scene for the forest It is difficult for the radiosity method to compute so many facets. In order to make the radiosity method to simulate the forest scene at pixel scale, in the authors' research, the authors proposed one idea to simplify the structure of forest crowns, and abstract the crowns to ellipsoids. And based on the optical characteristics of the tree component and the characteristics of the internal energy transmission of photon in real crown, the authors valued the optical characteristics of ellipsoid surface facets. In the computer simulation of the forest, with the idea of geometrical optics model, the gap model is considered to get the forest canopy bidirectional reflectance at pixel scale. Comparing the computer simulation results with the GOMS model, and Multi-angle Imaging SpectroRadiometer (MISR) multi-angle remote sensing data, the simulation results are in agreement with the GOMS simulation result and MISR BRF. But there are also some problems to be solved. So the authors can conclude that the study has important value for the application of multi-angle remote sensing and the inversion of vegetation canopy structure parameters.
NASA Astrophysics Data System (ADS)
Du, Jinyang; Kimball, John S.; Jones, Lucas A.; Kim, Youngwook; Glassy, Joseph; Watts, Jennifer D.
2017-11-01
Spaceborne microwave remote sensing is widely used to monitor global environmental changes for understanding hydrological, ecological, and climate processes. A new global land parameter data record (LPDR) was generated using similar calibrated, multifrequency brightness temperature (Tb) retrievals from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and the Advanced Microwave Scanning Radiometer 2 (AMSR2). The resulting LPDR provides a long-term (June 2002-December 2015) global record of key environmental observations at a 25 km grid cell resolution, including surface fractional open water (FW) cover, atmosphere precipitable water vapor (PWV), daily maximum and minimum surface air temperatures (Tmx and Tmn), vegetation optical depth (VOD), and surface volumetric soil moisture (VSM). Global mapping of the land parameter climatology means and seasonal variability over the full-year records from AMSR-E (2003-2010) and AMSR2 (2013-2015) observation periods is consistent with characteristic global climate and vegetation patterns. Quantitative comparisons with independent observations indicated favorable LPDR performance for FW (R ≥ 0.75; RMSE ≤ 0.06), PWV (R ≥ 0.91; RMSE ≤ 4.94 mm), Tmx and Tmn (R ≥ 0.90; RMSE ≤ 3.48 °C), and VSM (0.63 ≤ R ≤ 0.84; bias-corrected RMSE ≤ 0.06 cm3 cm-3). The LPDR-derived global VOD record is also proportional to satellite-observed NDVI (GIMMS3g) seasonality (R ≥ 0.88) due to the synergy between canopy biomass structure and photosynthetic greenness. Statistical analysis shows overall LPDR consistency but with small biases between AMSR-E and AMSR2 retrievals that should be considered when evaluating long-term environmental trends. The resulting LPDR and potential updates from continuing AMSR2 operations provide for effective global monitoring of environmental parameters related to vegetation activity, terrestrial water storage, and mobility and are suitable for climate and ecosystem studies. The LPDR dataset is publicly available at http://files.ntsg.umt.edu/data/LPDR_v2/.<
NASA Technical Reports Server (NTRS)
Kerr, Yann H.; Njoku, Eni G.
1990-01-01
A radiative-transfer model for simulating microwave brightness temperatures over land surfaces is described. The model takes into account sensor viewing conditions (spacecraft altitude, viewing angle, frequency, and polarization) and atmospheric parameters over a soil surface characterized by its moisture, roughness, and temperature and covered with a layer of vegetation characterized by its temperature, water content, single scattering albedo, structure, and percent coverage. In order to reduce the influence of atmospheric and surface temperature effects, the brightness temperatures are expressed as polarization ratios that depend primarily on the soil moisture and roughness, canopy water content, and percentage of cover. The sensitivity of the polarization ratio to these parameters is investigated. Simulation of the temporal evolution of the microwave signal over semiarid areas in the African Sahel is presented and compared to actual satellite data from the SMMR instrument on Nimbus-7.
Global assessment of predictability of water availability: A bivariate probabilistic Budyko analysis
NASA Astrophysics Data System (ADS)
Wang, Weiguang; Fu, Jianyu
2018-02-01
Estimating continental water availability is of great importance for water resources management, in terms of maintaining ecosystem integrity and sustaining society development. To more accurately quantify the predictability of water availability, on the basis of univariate probabilistic Budyko framework, a bivariate probabilistic Budyko approach was developed using copula-based joint distribution model for considering the dependence between parameter ω of Wang-Tang's equation and the Normalized Difference Vegetation Index (NDVI), and was applied globally. The results indicate the predictive performance in global water availability is conditional on the climatic condition. In comparison with simple univariate distribution, the bivariate one produces the lower interquartile range under the same global dataset, especially in the regions with higher NDVI values, highlighting the importance of developing the joint distribution by taking into account the dependence structure of parameter ω and NDVI, which can provide more accurate probabilistic evaluation of water availability.
The constructed catchment Chicken Creek as Critical Zone Observatory under transition
NASA Astrophysics Data System (ADS)
Gerwin, Werner; Schaaf, Wolfgang; Elmer, Michael; Hinz, Christoph
2014-05-01
The constructed catchment Chicken Creek was established in 2005 as an experimental landscape laboratory for ecosystem research. The 6 ha area with clearly defined horizontal as well as vertical boundary conditions was left for an unrestricted primary succession. All Critical Zone elements are represented at this site, which allows the study of most processes occurring at the interface of bio-, pedo-, geo- and hydrosphere. It provides outstanding opportunities for investigating interactions and feedbacks between different evolving compartments during ecosystem development. The catchment is extensively instrumented since 2005 in order to detect transition stages of the ecosystem. Data recorded with a high spatial and temporal resolution include hydrological, geomorphological, pedological, limnological as well as biological parameters. In contrast to other Critical Zone Observatories, this site offers the unique situation of an early stage ecosystem with highly dynamic system properties. The first years of development were characterized by a fast formation of geomorphological structures due to massive erosion processes at the initially non-vegetated surface. Hydrological processes led to the establishment of a local groundwater body within 5 years. In the following years the influence of biological structures like vegetation patterns gained an increasing importance. Feedbacks between developing vegetation and e.g. hydrological features became more and more dominant. As a result, different phases of ecosystem development could be distinguished until now. This observatory offers manifold possibilities to identify and disentangle complex interactions between Critical Zone processes in situ under natural conditions. The originally low complexity of the system is growing with time facilitating the identification of influences of newly developing structures on system functions. Thus, it is possible to study effects of small-scale processes on the whole system at the landscape scale. In addition, the highly dynamic initial system properties allow the observation of multifaceted changes of Critical Zone properties and functions within short periods of time. Chicken Creek could complement the existing network of Critical Zone Observatories which are usually established at ecosystems in a mature state.
The Tor Vergata Scattering Model Applied to L Band Backscatter During the Corn Growth Cycle
NASA Astrophysics Data System (ADS)
Joseph, A. T.; van der Velde, R.; Ferrazzoli, P.; Lang, R. H.; Gish, T.
2013-12-01
At the USDA's Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) experimental site in Beltsville (Maryland, USA) a field campaign took place throughout the 2002 corn growth cycle from May 10th (emergence of corn crops) to October 2nd (harvest). One of the microwave instruments deployed was the multi-frequency (X-, C- and L-band) quad-polarized (HH, HV, VV, VH) NASA GSFC / George Washington University (GWU) truck mounted radar. During the field campaign, this radar system provided once a week fully polarized C- and L-band (4.75 and 1.6 GHz) backscatter measurements from incidence angle of 15, 35, and 55 degrees. In support of these microwave observations, an extensive ground characterization took place, which included measurements of surface roughness, soil moisture, vegetation biomass and morphology. The field conditions during the campaign are characterized by several dry downs with a period of drought in the month of August. Peak biomass of the corn canopies was reached at July 24, 2002 with a total biomass of approximately 6.5 kg m-2. This dynamic range in both soil moisture and vegetation conditions within the data set is ideal for the validation of discrete medium vegetation scattering models. In this study, we compare the L band backscatter measurements with simulations by the Tor Vergata model (Bracaglia et al., 1995). The measured soil moisture, vegetation biomass and most reliably measured vegetation morphological parameters (e.g. number of leaves, number of stems and stem height) were used as input for the Tor Vergata model. The more uncertain model parameters (e.g. surface roughness, leaf thickness) and the stem diameter were optimized using a parameter estimation routine based on the Levenberg-Marquardt algorithm. As cost function for this optimization, the HH and VV polarized backscatter measured and simulated by the Tor Vergata model for incidence angle of 15, 35 and 55 degrees were used (6 measurements in total). The calibrated Tor Vergata model simulations are in excellent agreement with the measurements of Root Mean Squared Differences (RMSD's) of 0.8, 0.9 and 1.4 dB for incidences of 15, 35 and 55 degrees, respectively. The results from this study show that a physically based scattering model with the appropriate parameterization can accurately simulate backscatter measurements and, as such, have the potential of being used for the retrieval of biophysical variables (e.g. soil moisture and vegetation biomass). Via calibration of several parameters the Tor Vergata model is able to reproduce the L-band backscatter measured over corn very well. The resulting simulations show that: (1) At 35 degrees: the backscatter is dominated by the surface as well as the vegetation-surface scattering contribution. (2) At 55 degrees: the vegetation and vegetation-surface scattering contributions become dominant.
NASA Astrophysics Data System (ADS)
Miller, D. L.; Roberts, D. A.; Clarke, K. C.; Peters, E. B.; Menzer, O.; Lin, Y.; McFadden, J. P.
2017-12-01
Gross primary productivity (GPP) is commonly estimated with remote sensing techniques over large regions of Earth; however, urban areas are typically excluded due to a lack of light use efficiency (LUE) parameters specific to urban vegetation and challenges stemming from the spatial heterogeneity of urban land cover. In this study, we estimated GPP during the middle of the growing season, both within and among vegetation and land use types, in the Minneapolis-Saint Paul, Minnesota metropolitan region (52.1% vegetation cover). We derived LUE parameters for specific urban vegetation types using estimates of GPP from eddy covariance and tree sap flow-based CO2 flux observations and fraction of absorbed photosynthetically active radiation derived from 2-m resolution WorldView-2 satellite imagery. We produced a pixel-based hierarchical land cover classification of built-up and vegetated urban land cover classes distinguishing deciduous broadleaf trees, evergreen needleleaf trees, turf grass, and golf course grass from impervious and soil surfaces. The overall classification accuracy was 80% (kappa = 0.73). The mapped GPP estimates were within 12% of estimates from independent tall tower eddy covariance measurements. Mean GPP estimates ( ± standard deviation; g C m-2 day-1) for the entire study area from highest to lowest were: golf course grass (11.77 ± 1.20), turf grass (6.05 ± 1.07), evergreen needleleaf trees (5.81 ± 0.52), and deciduous broadleaf trees (2.52 ± 0.25). Turf grass GPP had a larger coefficient of variation (0.18) than the other vegetation classes ( 0.10). Mean land use GPP for the full study area varied as a function of percent vegetation cover. Urban GPP in general, both including and excluding non-vegetated areas, was less than half that of literature estimates for nearby natural forests and grasslands.
Evaluation of a new model of aeolian transport in the presence of vegetation
Li, Junran; Okin, Gregory S.; Herrick, Jeffrey E.; Belnap, Jayne; Miller, Mark E.; Vest, Kimberly; Draut, Amy E.
2013-01-01
Aeolian transport is an important characteristic of many arid and semiarid regions worldwide that affects dust emission and ecosystem processes. The purpose of this paper is to evaluate a recent model of aeolian transport in the presence of vegetation. This approach differs from previous models by accounting for how vegetation affects the distribution of shear velocity on the surface rather than merely calculating the average effect of vegetation on surface shear velocity or simply using empirical relationships. Vegetation, soil, and meteorological data at 65 field sites with measurements of horizontal aeolian flux were collected from the Western United States. Measured fluxes were tested against modeled values to evaluate model performance, to obtain a set of optimum model parameters, and to estimate the uncertainty in these parameters. The same field data were used to model horizontal aeolian flux using three other schemes. Our results show that the model can predict horizontal aeolian flux with an approximate relative error of 2.1 and that further empirical corrections can reduce the approximate relative error to 1.0. The level of error is within what would be expected given uncertainties in threshold shear velocity and wind speed at our sites. The model outperforms the alternative schemes both in terms of approximate relative error and the number of sites at which threshold shear velocity was exceeded. These results lend support to an understanding of the physics of aeolian transport in which (1) vegetation's impact on transport is dependent upon the distribution of vegetation rather than merely its average lateral cover and (2) vegetation impacts surface shear stress locally by depressing it in the immediate lee of plants rather than by changing the bulk surface's threshold shear velocity. Our results also suggest that threshold shear velocity is exceeded more than might be estimated by single measurements of threshold shear stress and roughness length commonly associated with vegetated surfaces, highlighting the variation of threshold shear velocity with space and time in real landscapes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kumar, Jitendra; HargroveJr., William Walter; Norman, Steven P
Vegetation canopy structure is a critically important habit characteristic for many threatened and endangered birds and other animal species, and it is key information needed by forest and wildlife managers for monitoring and managing forest resources, conservation planning and fostering biodiversity. Advances in Light Detection and Ranging (LiDAR) technologies have enabled remote sensing-based studies of vegetation canopies by capturing three-dimensional structures, yielding information not available in two-dimensional images of the landscape pro- vided by traditional multi-spectral remote sensing platforms. However, the large volume data sets produced by airborne LiDAR instruments pose a significant computational challenge, requiring algorithms to identify andmore » analyze patterns of interest buried within LiDAR point clouds in a computationally efficient manner, utilizing state-of-art computing infrastructure. We developed and applied a computationally efficient approach to analyze a large volume of LiDAR data and to characterize and map the vegetation canopy structures for 139,859 hectares (540 sq. miles) in the Great Smoky Mountains National Park. This study helps improve our understanding of the distribution of vegetation and animal habitats in this extremely diverse ecosystem.« less
NASA Technical Reports Server (NTRS)
Deering, D. W.; Haas, R. H. (Principal Investigator)
1980-01-01
The author has identified the following significant results. Relationships between the quantity of mixed prairie rangeland vegetation and LANDSAT MSS response were studied during four growing seasons at test sites throughout the United States Great Plans region. A LANDSAT derived parameter, the normalized difference was developed from theoretical considerations fro statistical estimation of the amount and seasonal condition of rangeland vegetation. This parameter was tested for application to local assessment of green forage biomass and regional monitoring of range feed conditions and drought. Results show that for grasslands in the Great Plains with near continuous vegetative cover and free of heavy brush and forbs, the LANDSAT digital data can provide a useful estimate of the quantity of green forage biomass (within 250 kg/ha), and at least five levels of pasture and range feed conditions can be adequately mapped for extended regions.
Evaluating Vegetation in the National Wetland Condition Assessment
Vegetation is a key biotic indicator of wetland ecological condition and forms a critical element of the USEPA 2011 National Wetland Condition Assessment. Data describing plant species composition and abundance, vegetation structure, and ground surface characteristics were colle...
Conserving herbivorous and predatory insects in urban green spaces.
Mata, Luis; Threlfall, Caragh G; Williams, Nicholas S G; Hahs, Amy K; Malipatil, Mallik; Stork, Nigel E; Livesley, Stephen J
2017-01-19
Insects are key components of urban ecological networks and are greatly impacted by anthropogenic activities. Yet, few studies have examined how insect functional groups respond to changes to urban vegetation associated with different management actions. We investigated the response of herbivorous and predatory heteropteran bugs to differences in vegetation structure and diversity in golf courses, gardens and parks. We assessed how the species richness of these groups varied amongst green space types, and the effect of vegetation volume and plant diversity on trophic- and species-specific occupancy. We found that golf courses sustain higher species richness of herbivores and predators than parks and gardens. At the trophic- and species-specific levels, herbivores and predators show strong positive responses to vegetation volume. The effect of plant diversity, however, is distinctly species-specific, with species showing both positive and negative responses. Our findings further suggest that high occupancy of bugs is obtained in green spaces with specific combinations of vegetation structure and diversity. The challenge for managers is to boost green space conservation value through actions promoting synergistic combinations of vegetation structure and diversity. Tackling this conservation challenge could provide enormous benefits for other elements of urban ecological networks and people that live in cities.
Conserving herbivorous and predatory insects in urban green spaces
Mata, Luis; Threlfall, Caragh G.; Williams, Nicholas S. G.; Hahs, Amy K.; Malipatil, Mallik; Stork, Nigel E.; Livesley, Stephen J.
2017-01-01
Insects are key components of urban ecological networks and are greatly impacted by anthropogenic activities. Yet, few studies have examined how insect functional groups respond to changes to urban vegetation associated with different management actions. We investigated the response of herbivorous and predatory heteropteran bugs to differences in vegetation structure and diversity in golf courses, gardens and parks. We assessed how the species richness of these groups varied amongst green space types, and the effect of vegetation volume and plant diversity on trophic- and species-specific occupancy. We found that golf courses sustain higher species richness of herbivores and predators than parks and gardens. At the trophic- and species-specific levels, herbivores and predators show strong positive responses to vegetation volume. The effect of plant diversity, however, is distinctly species-specific, with species showing both positive and negative responses. Our findings further suggest that high occupancy of bugs is obtained in green spaces with specific combinations of vegetation structure and diversity. The challenge for managers is to boost green space conservation value through actions promoting synergistic combinations of vegetation structure and diversity. Tackling this conservation challenge could provide enormous benefits for other elements of urban ecological networks and people that live in cities. PMID:28102333
Noise-resistant spectral features for retrieving foliar chemical parameters
USDA-ARS?s Scientific Manuscript database
Foliar chemical constituents are important indicators for understanding vegetation growing status and ecosystem functionality. Provided the noncontact and nondestructive traits, the hyperspectral analysis is a superior and efficient method for deriving these parameters. In practical implementation o...
NASA Technical Reports Server (NTRS)
Laymon, Charles A.; Crosson, William L.; Jackson, Thomas J.; Manu, Andrew; Tsegaye, Teferi D.; Soman, V.; Arnold, James E. (Technical Monitor)
2001-01-01
Accurate estimates of spatially heterogeneous algorithm variables and parameters are required in determining the spatial distribution of soil moisture using radiometer data from aircraft and satellites. A ground-based experiment in passive microwave remote sensing of soil moisture was conducted in Huntsville, Alabama from July 1-14, 1996 to study retrieval algorithms and their sensitivity to variable and parameter specification. With high temporal frequency observations at S and L band, we were able to observe large scale moisture changes following irrigation and rainfall events, as well as diurnal behavior of surface moisture among three plots, one bare, one covered with short grass and another covered with alfalfa. The L band emitting depth was determined to be on the order of 0-3 or 0-5 cm below 0.30 cubic centimeter/cubic centimeter with an indication of a shallower emitting depth at higher moisture values. Surface moisture behavior was less apparent on the vegetated plots than it was on the bare plot because there was less moisture gradient and because of difficulty in determining vegetation water content and estimating the vegetation b parameter. Discrepancies between remotely sensed and gravimetric, soil moisture estimates on the vegetated plots point to an incomplete understanding of the requirements needed to correct for the effects of vegetation attenuation. Quantifying the uncertainty in moisture estimates is vital if applications are to utilize remotely-sensed soil moisture data. Computations based only on the real part of the complex dielectric constant and/or an alternative dielectric mixing model contribute a relatively insignificant amount of uncertainty to estimates of soil moisture. Rather, the retrieval algorithm is much more sensitive to soil properties, surface roughness and biomass.
Quantifying Vegetation Structure with Lightweight, Rapid-Scanning Terrestrial Lidar
NASA Astrophysics Data System (ADS)
Paynter, I.; Genest, D.; Saenz, E. J.; Strahler, A. H.; Li, Z.; Peri, F.; Schaaf, C.
2016-12-01
Light Detection and Ranging (lidar) is proving a competent technology for observing vegetation structure. Terrestrial laser scanners (TLS) are ground-based instruments which utilize hundreds of thousands to millions of lidar observations to provide detailed structural and reflective information of their surroundings. TLS has enjoyed initial success as a validation tool for satellite and airborne estimates of vegetation structure, and are producing independent estimates with increasing accuracy. Reconstruction techniques for TLS observations of vegetation have also improved rapidly, especially for trees. However, uncertainties and challenges still remain in TLS modelling of vegetation structure, especially in geometrically complex ecosystems such as tropical forests (where observation extent and density is hampered by occlusion) and highly temporally dynamic coastal ecosystems (such as saltmarshes and mangroves), where observations may be restricted to narrow microstates. Some of these uncertainties can be mitigated, and challenges met, through the use of lidar instruments optimized for favorable deployment logistics through low weight, rapid scanning, and improved durability. We have conducted studies of vegetation structure in temperate and tropical forests, saltmarshes and mangroves, utilizing a highly portable TLS with considerable deployment flexibility, the Compact Biomass Lidar (CBL). We show results from studies in the temperate Long Term Ecological Research site of Harvard Forest (MA, USA); the tropical forested long-term Carbono sites of La Selva Biological Station (Sarapiqui, Costa Rica); and the saltmarsh LTER of Plum Island (MA, USA). These results demonstrate the improvements to observations in these ecosystems which are facilitated by the specifications of the CBL (and similar TLS) which are optimized for favorable deployment logistics and flexibility. We show the benefits of increased numbers of scanning positions, and specialized deployment platforms to meet ecosystem challenges.
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.
NASA Technical Reports Server (NTRS)
Rosero, Enrique; Yang, Zong-Liang; Wagener, Thorsten; Gulden, Lindsey E.; Yatheendradas, Soni; Niu, Guo-Yue
2009-01-01
We use sensitivity analysis to identify the parameters that are most responsible for shaping land surface model (LSM) simulations and to understand the complex interactions in three versions of the Noah LSM: the standard version (STD), a version enhanced with a simple groundwater module (GW), and version augmented by a dynamic phenology module (DV). We use warm season, high-frequency, near-surface states and turbulent fluxes collected over nine sites in the US Southern Great Plains. We quantify changes in the pattern of sensitive parameters, the amount and nature of the interaction between parameters, and the covariance structure of the distribution of behavioral parameter sets. Using Sobol s total and first-order sensitivity indexes, we show that very few parameters directly control the variance of the model output. Significant parameter interaction occurs so that not only the optimal parameter values differ between models, but the relationships between parameters change. GW decreases parameter interaction and appears to improve model realism, especially at wetter sites. DV increases parameter interaction and decreases identifiability, implying it is overparameterized and/or underconstrained. A case study at a wet site shows GW has two functional modes: one that mimics STD and a second in which GW improves model function by decoupling direct evaporation and baseflow. Unsupervised classification of the posterior distributions of behavioral parameter sets cannot group similar sites based solely on soil or vegetation type, helping to explain why transferability between sites and models is not straightforward. This evidence suggests a priori assignment of parameters should also consider climatic differences.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Huang, Shengzhi; Huang, Qiang; Leng, Guoyong
It is of importance to investigate watershed water-energy balance variations and to explore their correlations with vegetation and soil moisture dynamics, which helps better understand the interplays between underlying surface dynamics and the terrestrial water cycle. The heuristic segmentation method was adopted to identify change points in the parameter to series in Fu's equation belonging to the Budyko framework in the Wei River Basin (WRB) and its sub-basins aiming to examine the validity of stationary assumptions. Additionally, the cross wavelet analysis was applied to explore the correlations between vegetation and soil moisture dynamics and to variations. Results indicated that (1)more » the omega variations in the WRB are significant, with some change points identified except for the sub-basin above Zhangjiashan, implying that the stationarity of omega series in the WRB is invalid except for the sub-basin above Zhangjiashan; (2) the correlations between soil moisture series and to series are weaker than those between Normalized Difference Vegetation Index (NDVI) series and omega series; (3) vegetation dynamics show significantly negative correlations with omega variations in 1983-2003 with a 4-8 year signal in the whole WRB, and both vegetation and soil moisture dynamics exert strong impacts on the parameter omega changes. This study helps understanding the interactions between underlying land surface dynamics and watershed water-energy balance. (C) 2017 Elsevier B.V. All rights reserved.« less
Seasonal fecundity and source-sink status of shrub-nesting birds in a southwestern riparian corridor
Brand, L.A.; Noon, B.R.
2011-01-01
Saltcedar (Tamarix spp.) has increasingly dominated riparian floodplains relative to native forests in the southwestern U.S., but little is known about its impacts on avian productivity or population status. We monitored 86 Arizona Bell's Vireo (Vireo bellii arizonae), 147 Abert's Towhee (Melozone aberti), and 154 Yellow-breasted Chat (Icteria virens) nests to assess reproductive parameters in cottonwood-willow (Populus-Salix), saltcedar, and mesquite (Prosopis spp.) stands along the San Pedro River, Arizona during 1999-2001. We also assessed source-sink status for each species in each vegetation type using field data combined with data from the literature. There were no significant differences in reproductive parameters between vegetation types for Abert's Towhee or Yellow-breasted Chat, although seasonal fecundity was quite low across vegetation types for the latter (0.75 ?? 0.14; mean ?? SE). Bell's Vireo had extremely low seasonal fecundity in saltcedar (0.10 ?? 0.09) and significantly fewer fledglings per nest in saltcedar (0.09 ?? 0.09) compared with cottonwood (1.07 ?? 0.32). Point estimates of ?? were substantially <1 for all three focal species in all habitats indicating the entire study area may be performing as a sink; 90% CI of included 1 only for Abert's Towhee across vegetation types and Bell's Vireo in cottonwood vegetation. These results are surprising given the San Pedro is considered to be one of the best remaining occurrences of lowland native riparian vegetation in the southwestern United States. ?? 2011 by the Wilson Ornithological Society.
Soil Structure - A Neglected Component of Land-Surface Models
NASA Astrophysics Data System (ADS)
Fatichi, S.; Or, D.; Walko, R. L.; Vereecken, H.; Kollet, S. J.; Young, M.; Ghezzehei, T. A.; Hengl, T.; Agam, N.; Avissar, R.
2017-12-01
Soil structure is largely absent in most standard sampling and measurements and in the subsequent parameterization of soil hydraulic properties deduced from soil maps and used in Earth System Models. The apparent omission propagates into the pedotransfer functions that deduce parameters of soil hydraulic properties primarily from soil textural information. Such simple parameterization is an essential ingredient in the practical application of any land surface model. Despite the critical role of soil structure (biopores formed by decaying roots, aggregates, etc.) in defining soil hydraulic functions, only a few studies have attempted to incorporate soil structure into models. They mostly looked at the effects on preferential flow and solute transport pathways at the soil profile scale; yet, the role of soil structure in mediating large-scale fluxes remains understudied. Here, we focus on rectifying this gap and demonstrating potential impacts on surface and subsurface fluxes and system wide eco-hydrologic responses. The study proposes a systematic way for correcting the soil water retention and hydraulic conductivity functions—accounting for soil-structure—with major implications for near saturated hydraulic conductivity. Modification to the basic soil hydraulic parameterization is assumed as a function of biological activity summarized by Gross Primary Production. A land-surface model with dynamic vegetation is used to carry out numerical simulations with and without the role of soil-structure for 20 locations characterized by different climates and biomes across the globe. Including soil structure affects considerably the partition between infiltration and runoff and consequently leakage at the base of the soil profile (recharge). In several locations characterized by wet climates, a few hundreds of mm per year of surface runoff become deep-recharge accounting for soil-structure. Changes in energy fluxes, total evapotranspiration and vegetation productivity are less significant but they can reach up to 10% in specific locations. Significance for land-surface and hydrological modeling and implications for distributed domains are discussed.
NASA Astrophysics Data System (ADS)
Stagakis, S.; González-Dugo, V.; Cid, P.; Guillén-Climent, M. L.; Zarco-Tejada, P. J.
2012-07-01
This paper deals with the monitoring of water status and the assessment of the effect of stress on citrus fruit quality using structural and physiological remote sensing indices. Four flights were conducted over a citrus orchard in 2009 using an unmanned aerial vehicle (UAV) carrying a multispectral camera with six narrow spectral bands in the visible and near infrared. Physiological indices such as the Photochemical Reflectance Index (PRI570), a new structurally robust PRI formulation that uses the 515 nm as the reference band (PRI515), and a chlorophyll ratio (R700/R670) were compared against the Normalized Difference Vegetation Index (NDVI), Renormalized Difference Vegetation Index (RDVI) and Modified Triangular Vegetation Index (MTVI) canopy structural indices for their performance in tracking water status and the effects of sustained water stress on fruit quality at harvest. The irrigation setup in the commercial orchard was compared against a treatment scheduled to satisfy full requirements (based on estimated crop evapotranspiration) using two regulated deficit irrigation (RDI) strategies. The water status of the trees throughout the experiment was monitored with frequent field measurements of stem water potential (Ψx), while titratable acidity (TA) and total soluble solids (TSS) were measured at harvest on selected trees from each irrigation treatment. The high spatial resolution of the multispectral imagery (30 cm pixel size) enabled identification of pure tree crown components, extracting the tree reflectance from shaded, sunlit and aggregated pixels. The physiological and structural indices were then calculated from each tree at the following levels: (i) pure sunlit tree crown, (ii) entire crown, aggregating the within-crown shadows, and (iii) simulating a lower resolution pixel, including tree crown, sunlit and shaded soil pixels. The resulting analysis demonstrated that both PRI formulations were able to track water status, except when water stress altered canopy structure. In such cases, PRI570 was more affected than PRI515 by the structural changes caused by sustained water stress throughout the season. Both PRI formulations were proven to serve as pre-visual water stress indicators linked to fruit quality TSS and TA parameters (r2 = 0.69 for PRI515 vs TSS; r2 = 0.58 vs TA). In contrast, the chlorophyll (R700/R670) and structural indices (NDVI, RDVI, MTVI) showed poor relationships with fruit quality and water status levels (r2 = 0.04 for NDVI vs TSS; r2 = 0.19 vs TA). The two PRI formulations showed strong relationships with the field-measured fruit quality parameters in September, the beginning of stage III, which appeared to be the period most sensitive to water stress and the most critical for assessing fruit quality in citrus. Both PRI515 and PRI570 showed similar performance for the two scales assessed (sunlit crown and entire crown), demonstrating that within-crown component separation is not needed in citrus tree crowns where the shaded vegetation component is small. However, the simulation conducted through spatial resampling on tree + soil aggregated pixels revealed that the physiological indices were highly affected by soil reflectance and between-tree shadows, showing that for TSS vs PRI515 the relationship dropped from r2 = 0.69 to r2 = 0.38 when aggregating soil + crown components. This work confirms a previous study that demonstrated the link between PRI570, water stress, and fruit quality, while also making progress in assessing the new PRI formulation (PRI515), the within-crown shadow effects on the physiological indices, and the need for high resolution imagery to target individual tree crowns for the purpose of evaluating the effects of water stress on fruit quality in citrus.
John M. Mulhouse; Diane De Steven; Robert F. Lide; Rebecca R. Sharitz
2005-01-01
Wetland vegetation is strongly dependent upon climate-influenced hydrologic conditions, and plant composition responds in generally consistent ways to droughts. However, the extent of species composition change during drought may be influenced by the pre-existing structure of wetland vegetation. We characterized the vegetation of ten herbaceous Carolina bay wetlands on...
Picotte, Joshua J.; Long, Jordan; Peterson, Birgit; Nelson, Kurtis
2017-01-01
The LANDFIRE Program produces national scale vegetation, fuels, fire regimes, and landscape disturbance data for the entire U.S. These data products have been used to model the potential impacts of fire on the landscape [1], the wildfire risks associated with land and resource management [2, 3], and those near population centers and accompanying Wildland Urban Interface zones [4], as well as many other applications. The initial LANDFIRE National Existing Vegetation Type (EVT) and vegetation structure layers, including vegetation percent cover and height, were mapped circa 2001 and released in 2009 [5]. Each EVT is representative of the dominant plant community within a given area. The EVT layer has since been updated by identifying areas of landscape change and modifying the vegetation types utilizing a series of rules that consider the disturbance type, severity of disturbance, and time since disturbance [6, 7]. Non-disturbed areas were adjusted for vegetation growth and succession. LANDFIRE vegetation structure layers also have been updated by using data modeling techniques [see 6 for a full description]. The subsequent updated versions of LANDFIRE include LANDFIRE 2008, 2010, 2012, and LANDFIRE 2014 is being incrementally released, with all data being released in early 2017. Additionally, a comprehensive remap of the baseline data, LANDFIRE 2015 Remap, is being prototyped, and production is tentatively planned to begin in early 2017 to provide a more current baseline for future updates.
NASA Technical Reports Server (NTRS)
Wang, J. R.; Mcmurtrey, J. E., III; Engman, E. T.; Jackson, T. J.; Schmugge, T. J.; Gould, W. I.; Glazar, W. S.; Fuchs, J. E. (Principal Investigator)
1981-01-01
Microwave emission from bare and vegetated fields was measured with dual polarized radiometers at 1.4 GHz and 5 GHz frequencies. The measured brightness temperatures over bare fields are shown to compare favorably with those calculated from radiative transfer theory with two constant parameters characterizing surface roughness effect. The presence of vegetation cover is found to reduce the sensitivity to soil moisture variation. This sensitivity reduction is generally pronounced the denser, the vegetation cover and the higher the frequency of observation. The effect of vegetation cover is also examined with respect to the measured polarization factor at both frequencies. With the exception of dry corn fields, the measured polarization factor over vegetated fields is found appreciably reduced compared to that over bare fields. A much larger reduction in this factor is found at 5GHz than at 1.4GHz frequency.
Estimation of vegetation parameters such as Leaf Area Index from polarimetric SAR data
NASA Astrophysics Data System (ADS)
Hetz, Marina; Blumberg, Dan G.; Rotman, Stanley R.
2010-05-01
This work presents the analysis of the capability to use the radar backscatter coefficient in semi-arid zones to estimate the vegetation crown in terms of Leaf Area Index (LAI). The research area is characterized by the presence of a pine forest with shrubs as an underlying vegetation layer (understory), olive trees, natural grove areas and eucalyptus trees. The research area was imaged by an airborne RADAR system in L-band during February 2009. The imagery includes multi-look radar images. All the images were fully polarized i.e., HH, VV, HV polarizations. For this research we used the central azimuth angle (113° ). We measured LAI using the ?T Sun Scan Canopy Analysis System. Verification was done by analytic calculations and digital methods for the leaf's and needle's surface area. In addition, we estimated the radar extinction coefficient of the vegetation volume by comparing point calibration targets (trihedral corner reflectors with 150cm side length) within and without the canopy. The radar extinction in co- polarized images was ~26dB and ~24dB for pines and olives respectively, compared to the same calibration target outside the vegetation. We used smaller trihedral corner reflectors (41cm side length) and covered them with vegetation to measure the correlation between vegetation density, LAI and radar backscatter coefficient for pines and olives under known conditions. An inverse correlation between the radar backscatter coefficient of the trihedral corner reflectors covered by olive branches and the LAI of those branches was observed. The correlation between LAI and the optical transmittance was derived using the Beer-Lambert law. In addition, comparing this law's principle to the principle of the radar backscatter coefficient production, we derived the equation that connects between the radar backscatter coefficient and LAI. After extracting the radar backscatter coefficient of forested areas, all the vegetation parameters were used as inputs for the MIMICS model that simulates the radar backscatter coefficient of pines. The model results show a backscatter of -18dB in HV polarization which is 13dB higher than the mean pines backscatter in the radar images, whereas the co-polarized images revealed a backscatter of -10dB which is 23dB higher than the actual backscatter value deriver from the radar images. Therefore, next step in the research will incorporate other vegetation parameters and attempt to understand the discrepancies between the simulation and the actual data.
USDA-ARS?s Scientific Manuscript database
L-band airborne synthetic aperture radar observations were made over California shrublands to better understand the effects by soil and vegetation parameters on backscatter. Temporal changes in radar backscattering coefficient (s0) of up to 3 dB were highly correlated to surface soil moisture but no...
Peilong Liu; Lu Hao; Cen Pan; Decheng Zhou; Yongqiang Liu; Ge Sun
2017-01-01
Leaf area index (LAI) is a key parameter to characterize vegetation dynamics and ecosystemstructure that determines the ecosystem functions and services such as cleanwater supply and carbon sequestration in awatershed. However, linking LAI dynamics and environmental controls (i.e., coupling biosphere, atmosphere, and anthroposphere) remains challenging and such type of...
Solar and Net Radiation for Estimating Potential Evaporation from Three Vegetation Canopies
D.M. Amatya; R.W. Skaggs; G.W. Cheschier; G.P. Fernandez
2000-01-01
Solar and net radiation data are frequent/y used in estimating potential evaporation (PE) from various vegetative surfaces needed for water balance and hydrologic modeling studies. Weather parameters such as air temperature, relative humidity, wind speed, solar radiation, and net radiation have been continuously monitored using automated sensors to estimate PE for...
Percent canopy cover and stand structure statistics from the Forest Vegetation Simulator
Nicholas L. Crookston; Albert R. Stage
1999-01-01
Estimates of percent canopy cover generated by the Forest Vegetation Simulator (FVS) are corrected for crown overlap using an equation presented in this paper. A comparison of the new cover estimate to some others is provided. The cover estimate is one of several describing stand structure. The structure descriptors also include major species, ranges of diameters, tree...
Comparisons of MODIS vegetation index products with biophysical and flux tower measurements
NASA Astrophysics Data System (ADS)
Sirikul, Natthanich
Vegetation indices (VI) play an important role in studies of global climate and biogeochemical cycles, and are also positively related to many biophysical parameters and satellite products, such as leaf area index (LAI), gross primary production (GPP), land surface water index (LSWI) and land surface temperature (LST). In this study we found that VI's had strong relationships with some biophysical products, such as gross primary production, yet were less well correlated with biophysical structural parameters, such as leaf area index. The relationships between MODIS VI's and biophysical field measured LAI showed poor correlation at semi-arid land and broadleaf forest land cover type whereas cropland showed stronger correlations than the other vegetation types. In addition, the relationship between the enhanced vegetation index (EVI)-LAI and normalized difference vegetation index (NDVI)-LAI did not show significant differences. Comparisons of the relationships between the EVI and NDVI with tower-measured GPP from 11 flux towers in North America, showed that MODIS EVI had much stronger relationships with tower-GPP than did NDVI, and EVI was better correlated with the seasonal dynamics of GPP than was NDVI. In addition, there were no significant differences among the 1x1, 3x3 and 7x7 pixel sample sizes. The comparisons of VIs from the 3 MODIS products from which VI's are generated (Standard VI (MOD13)), Nadir Adjusted Surface Reflectance (NBAR (MOD43)), and Surface Reflectance (MOD09)), showed that MODIS NBAR-EVI (MOD43) was best correlated with GPP compared with the other VI products. In addition, the MODIS VI - tower GPP relationships were significantly improved using NBAR-EVI over the more complex canopy structures, such as the broadleaf and needleleaf forests. The relationship of tower-GPP with other MODIS products would be useful in more thorough characterization of some land cover types in which the VI's have encountered problems. The land surface temperature (LST) product were found useful for empirical estimations of GPP in needleleaf forests, but were not useful for the other land cover types, whereas the land surface water index (LSWI) was more sensitive to noise from snowmelt, ground water table levels, and wet soils than to the canopy moisture levels. Also the MODIS EVI was better correlated with LST than was NDVI. Finally, the cross-site comparisons of GPP and multi-products from MODIS showed that the relationships between EVI and GPP were the strongest while LST and GPP was the weakest. EVI may thus be useful in scaling across landscapes, including heterogeneous ones, for regional estimations of GPP, especially if BRDF effects have been taken into account (such as with the NBAR product). Thus, the relationships of EVI-GPP over space and time would potentially provide much useful information for studies of the global carbon cycle.
NASA Astrophysics Data System (ADS)
Liu, P.; Bongiovanni, T. E.; Monsivais-Huertero, A.; Bindlish, R.; Judge, J.
2013-12-01
Accurate estimates of crop yield are important for managing agricultural production and food security. Although the crop growth models, such as the Decision Support System Agrotechnology Transfer (DSSAT), have been used to simulate crop growth and development, the crop yield estimates still diverge from the reality due to different sources of errors in the models and computation. Auxiliary observations may be incorporated into such dynamic models to improve predictions using data assimilation. Active and passive (AP) microwave observations at L-band (1-2 GHz) are sensitive to dielectric and geometric properties of soil and vegetation, including soil moisture (SM), vegetation water content (VWC), surface roughness, and vegetation structure. Because SM and VWC are one of the governing factors in estimating crop yield, microwave observations may be used to improve crop yield estimates. Current studies have shown that active observations are more sensitive to the surface roughness of soil and vegetation structure during the growing season, while the passive observations are more sensitive to the SM. Backscatter and emission models linked with the DSSAT model (DSSAT-A-P) allow assimilation of microwave observations of backscattering coefficient (σ0) and brightness temperature (TB) may provide biophysically realistic estimates of model states and parameters. The present ESA Soil Moisture Ocean Salinity (SMOS) mission provides passive observations at 1.41 GHz at 25 km every 2-3 days, and the NASA/CNDAE Aquarius mission provides L-band AP observations at spatial resolution of 150 km with a repeat coverage of 7 days for global SM products. In 2014, the planned NASA Soil Moisture Active Passive mission will provide AP observations at 1.26 and 1.41 GHz at the spatial resolutions of 3 and 30 km, respectively, with a repeat coverage of 2-3 days. The goal of this study is to understand the impacts of assimilation of asynchronous and synchronous AP observations on crop yield estimates. An Ensemble Kalman Filter-based methodology is implemented to incorporate σ0 and TB from Aquarius and SMOS in the DSSAT-A-P model to improve crop yield for two growing seasons of soybean -a normal and a drought affected season- in the rain-fed region of the Brazilian La Plata Basin, South America. Different scenarios of assimilation, including active only, passive only, and combined AP observations were considered. The elements of the state vector included both model states and parameters related to soil and vegetation. The number of elements included in the state vector changed depending upon different scenarios of assimilation and also upon the growth stages. Crop yield estimates were compared for different scenarios during the two seasons. A synthetic experiment conducted previously showed an improvement of crop estimates in the RMSD by 90 kg/ha using combined AP compared to the openloop and active only assimilation over the region.
Effects of Vegetation Structure on the Location of Lion Kill Sites in African Thicket.
Davies, Andrew B; Tambling, Craig J; Kerley, Graham I H; Asner, Gregory P
2016-01-01
Predator-prey relationships are integral to ecosystem stability and functioning. These relationships are, however, difficult to maintain in protected areas where large predators are increasingly being reintroduced and confined. Where predators make kills has a profound influence on their role in ecosystems, but the relative importance of environmental variables in determining kill sites, and how these might vary across ecosystems is poorly known. We investigated kill sites for lions in South Africa's thicket biome, testing the importance of vegetation structure for kill site locations compared to other environmental variables. Kill sites were located over four years using GPS telemetry and compared to non-kill sites that had been occupied by lions, as well as to random sites within lion ranges. Measurements of 3D vegetation structure obtained from Light Detection and Ranging (LiDAR) were used to calculate the visible area (viewshed) around each site and, along with wind and moonlight data, used to compare kill sites between lion sexes, prey species and prey sexes. Viewshed area was the most important predictor of kill sites (sites in dense vegetation were twice as likely to be kill sites compared to open areas), followed by wind speed and, less so, moonlight. Kill sites for different prey species varied with vegetation structure, and male prey were killed when wind speeds were higher compared to female prey of the same species. Our results demonstrate that vegetation structure is an important component of predator-prey interactions, with varying effects across ecosystems. Such differences require consideration in terms of the ecological roles performed by predators, and in predator and prey conservation.
Dodd, L.E.; Lacki, M.J.; Britzke, E.R.; Buehler, D.A.; Keyser, P.D.; Larkin, J.L.; Rodewald, A.D.; Wigley, T.B.; Wood, P.B.; Rieske, L.K.
2012-01-01
Vertebrate insectivores such as bats are a pervasive top-down force on prey populations in forest ecosystems. Conservation focusing on forest-dwelling bats requires understanding of community-level interactions between these predators and their insect prey. Our study assessed bat activity and insect occurrence (abundance and diversity) across a gradient of forest disturbance and structure (silvicultural treatments) in the Central Appalachian region of North America. We conducted acoustic surveys of bat echolocation concurrent with insect surveys using blacklight and malaise traps over 2 years. Predator activity, prey occurrence and prey biomass varied seasonally and across the region. The number of bat echolocation pulses was positively related with forest disturbance, whereas prey demonstrated varied trends. Lepidopteran abundance was negatively related with disturbance, while dipteran abundance and diversity was positively related with disturbance. Coleoptera were unaffected. Neither bat nor insect response variables differed between plot interiors and edges. Correlations between bat activity and vegetative structure reflected differences in foraging behavior among ensembles. Activity of myotine bats was correlated with variables describing sub-canopy vegetation, whereas activity of lasiurine bats was more closely correlated with canopy-level vegetation. Lepidopteran abundance was correlated with variables describing canopy and sub-canopy vegetation, whereas coleopteran and dipteran occurrence were more closely correlated with canopy-level vegetative structure. Our study demonstrates regional variation in bat activity and prey occurrence across a forested disturbance gradient. Land management and conservation efforts should consider the importance of vegetation structure and plant species richness to sustain forest-dwelling bats and their insect prey.
Community structure and quality after 10 years in two central Ohio mitigation bank wetlands.
Spieles, Douglas J; Coneybeer, Meagan; Horn, Jonathan
2006-11-01
We evaluate two 10-year-old mitigation bank wetlands in central Ohio, one created and one with restored and enhanced components, by analysis of vegetation characteristics and by comparison of the year-10 vegetation and macroinvertebrate communities with reference wetlands. To assess different measures of wetland development, we compare the prevalence of native hydrophytes with an index of floristic quality and we evaluate the predictability of these parameters in year 10, given 5 years of data. Results show that the mitigation wetlands in this study meet vegetation performance criteria of native hydrophyte establishment by year 5 and maintain these characteristics through year 10. Species richness and floristic quality, as well as vegetative similarity with reference wetlands, differ among mitigation wetlands in year 1 and also in their rate of change during the first 10 years. The prevalence of native hydrophytes is reasonably predictable by year 10, but 5 years of monitoring is not sufficient to predict future trends of floristic quality in either the created or restored wetland. By year 10, macroinvertebrate taxa richness does not statistically differ among these wetlands, but mitigation wetlands differ from reference sites by tolerance index and by trophic guild dominance. The created wetland herbivore biomass is significantly smaller than its reference, whereas detritivore biomass is significantly greater in the created wetland and smaller in the restored wetland as compared with respective reference wetlands. These analyses illustrate differences in measures of wetland performance and contrast the monitoring duration necessary for legal compliance with the duration required for development of more complex indicators of ecosystem integrity.
Vegetation Response to Upper Pliocene Glacial/Interglacial Cyclicity in the Central Mediterranean
NASA Astrophysics Data System (ADS)
Combourieu-Nebout, Nathalie
1993-09-01
New detailed pollen analysis of the lower part of the Upper Pliocene Semaforo section (Crotone, Italy) documents cyclic behavior of vegetation at the beginning of the Northern Hemisphere glaciations. The competition between four vegetation units (subtropical humid forest, deciduous temperate forest, altitudinal coniferous forest, and open xeric assemblage) probably reflects modifications of vegetation belts at this montane site. Several increases in herbaceous open vegetation regularly alternate with subtropical humid forest, which expresses rapid climatic oscillations. The complete temporal succession—deciduous forest (rich in Quercus), followed by subtropical humid forest (Taxodiaceae and Cathaya), then altitudinal coniferous forest ( Tsuga, Cedrus, Abies, and Picea), and finally herbaceous open vegetation (Graminae, Compositae, and Artemisia )—displays the climatic evolution from warm and humid interglaciation to cold and dry glaciation. It also suggests an independent variation of temperature and humidity, the two main climatic parameters. The vegetation history of southern Calabria recorded in the Semaforo section have been correlated with the ∂ 18O signal established in the Atlantic Ocean.
NASA Astrophysics Data System (ADS)
Dunn, S. M.; Lilly, A.
2001-10-01
There are now many examples of hydrological models that utilise the capabilities of Geographic Information Systems to generate spatially distributed predictions of behaviour. However, the spatial variability of hydrological parameters relating to distributions of soils and vegetation can be hard to establish. In this paper, the relationship between a soil hydrological classification Hydrology of Soil Types (HOST) and the spatial parameters of a conceptual catchment-scale model is investigated. A procedure involving inverse modelling using Monte-Carlo simulations on two catchments is developed to identify relative values for soil related parameters of the DIY model. The relative values determine the internal variability of hydrological processes as a function of the soil type. For three out of the four soil parameters studied, the variability between HOST classes was found to be consistent across two catchments when tested independently. Problems in identifying values for the fourth 'fast response distance' parameter have highlighted a potential limitation with the present structure of the model. The present assumption that this parameter can be related simply to soil type rather than topography appears to be inadequate. With the exclusion of this parameter, calibrated parameter sets from one catchment can be converted into equivalent parameter sets for the alternate catchment on the basis of their HOST distributions, to give a reasonable simulation of flow. Following further testing on different catchments, and modifications to the definition of the fast response distance parameter, the technique provides a methodology whereby it is possible to directly derive spatial soil parameters for new catchments.
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.
The Uncertainty of Biomass Estimates from Modeled ICESat-2 Returns Across a Boreal Forest Gradient
NASA Technical Reports Server (NTRS)
Montesano, P. M.; Rosette, J.; Sun, G.; North, P.; Nelson, R. F.; Dubayah, R. O.; Ranson, K. J.; Kharuk, V.
2014-01-01
The Forest Light (FLIGHT) radiative transfer model was used to examine the uncertainty of vegetation structure measurements from NASA's planned ICESat-2 photon counting light detection and ranging (LiDAR) instrument across a synthetic Larix forest gradient in the taiga-tundra ecotone. The simulations demonstrate how measurements from the planned spaceborne mission, which differ from those of previous LiDAR systems, may perform across a boreal forest to non-forest structure gradient in globally important ecological region of northern Siberia. We used a modified version of FLIGHT to simulate the acquisition parameters of ICESat-2. Modeled returns were analyzed from collections of sequential footprints along LiDAR tracks (link-scales) of lengths ranging from 20 m-90 m. These link-scales traversed synthetic forest stands that were initialized with parameters drawn from field surveys in Siberian Larix forests. LiDAR returns from vegetation were compiled for 100 simulated LiDAR collections for each 10 Mg · ha(exp -1) interval in the 0-100 Mg · ha(exp -1) above-ground biomass density (AGB) forest gradient. Canopy height metrics were computed and AGB was inferred from empirical models. The root mean square error (RMSE) and RMSE uncertainty associated with the distribution of inferred AGB within each AGB interval across the gradient was examined. Simulation results of the bright daylight and low vegetation reflectivity conditions for collecting photon counting LiDAR with no topographic relief show that 1-2 photons are returned for 79%-88% of LiDAR shots. Signal photons account for approximately 67% of all LiDAR returns, while approximately 50% of shots result in 1 signal photon returned. The proportion of these signal photon returns do not differ significantly (p greater than 0.05) for AGB intervals greater than 20 Mg · ha(exp -1). The 50m link-scale approximates the finest horizontal resolution (length) at which photon counting LiDAR collection provides strong model fits and minimizes forest structure uncertainty in the synthetic Larix stands. At this link-scale AGB greater than 20 Mg · ha(exp -1) has AGB error from 20-50% at the 95% confidence level. These results suggest that the theoretical sensitivity of ICESat-2 photon counting LiDAR measurements alone lack the ability to consistently discern differences in inferred AGB at 10 Mg · ha(exp -1) intervals in sparse forests characteristic of the taiga-tundra ecotone.
NASA Technical Reports Server (NTRS)
Kiang, R.; Adimi, F.; Nigro, J.
2007-01-01
Meteorological and environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. These parameters can most conveniently be obtained using remote sensing. Selected provinces and districts in Thailand and Indonesia are used to illustrate how remotely sensed meteorological and environmental parameters may enhance the capabilities for malaria surveillance and control. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records.
Coherence Effects in L-Band Active and Passive Remote Sensing of Quasi-Periodic Corn Canopies
NASA Technical Reports Server (NTRS)
Utku, Cuneyt; Lang, Roger H.
2011-01-01
Due to their highly random nature, vegetation canopies can be modeled using the incoherent transport theory for active and passive remote sensing applications. Agricultural vegetation canopies however are generally more structured than natural vegetation. The inherent row structure in agricultural canopies induces coherence effects disregarded by the transport theory. The objective of this study is to demonstrate, via Monte-Carlo simulations, these coherence effects on L-band scattering and thermal emission from corn canopies consisting of only stalks.
NASA Astrophysics Data System (ADS)
Blair, J. Bryan; Rabine, David L.; Hofton, Michelle A.
The Laser Vegetation Imaging Sensor (LVIS) is an airborne, scanning laser altimeter, designed and developed at NASA's Goddard Space Flight Center (GSFC). LVIS operates at altitudes up to 10 km above ground, and is capable of producing a data swath up to 1000 m wide nominally with 25-m wide footprints. The entire time history of the outgoing and return pulses is digitised, allowing unambiguous determination of range and return pulse structure. Combined with aircraft position and attitude knowledge, this instrument produces topographic maps with dm accuracy and vertical height and structure measurements of vegetation. The laser transmitter is a diode-pumped Nd:YAG oscillator producing 1064 nm, 10 ns, 5 mJ pulses at repetition rates up to 500 Hz. LVIS has recently demonstrated its ability to determine topography (including sub-canopy) and vegetation height and structure on flight missions to various forested regions in the US and Central America. The LVIS system is the airborne simulator for the Vegetation Canopy Lidar (VCL) mission (a NASA Earth remote sensing satellite due for launch in year 2000), providing simulated data sets and a platform for instrument proof-of-concept studies. The topography maps and return waveforms produced by LVIS provide Earth scientists with a unique data set allowing studies of topography, hydrology, and vegetation with unmatched accuracy and coverage.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kercher, J.R.; Chambers, J.Q.
1995-10-01
We have developed a geographically-distributed ecosystem model for the carbon, nitrogen, and water dynamics of the terrestrial biosphere TERRA. The local ecosystem model of TERRA consists of coupled, modified versions of TEM and DAYTRANS. The ecosystem model in each grid cell calculates water fluxes of evaporation, transpiration, and runoff; carbon fluxes of gross primary productivity, litterfall, and plant and soil respiration; and nitrogen fluxes of vegetation uptake, litterfall, mineralization, immobilization, and system loss. The state variables are soil water content; carbon in live vegetation; carbon in soil; nitrogen in live vegetation; organic nitrogen in soil and fitter; available inorganic nitrogenmore » aggregating nitrites, nitrates, and ammonia; and a variable for allocation. Carbon and nitrogen dynamics are calibrated to specific sites in 17 vegetation types. Eight parameters are determined during calibration for each of the 17 vegetation types. At calibration, the annual average values of carbon in vegetation C, show site differences that derive from the vegetation-type specific parameters and intersite variation in climate and soils. From calibration, we recover the average C{sub v} of forests, woodlands, savannas, grasslands, shrublands, and tundra that were used to develop the model initially. The timing of the phases of the annual variation is driven by temperature and light in the high latitude and moist temperate zones. The dry temperate zones are driven by temperature, precipitation, and light. In the tropics, precipitation is the key variable in annual variation. The seasonal responses are even more clearly demonstrated in net primary production and show the same controlling factors.« less
NASA Astrophysics Data System (ADS)
Pinty, B.; Clerici, M.; Andredakis, I.; Kaminski, T.; Taberner, M.; Verstraete, M. M.; Gobron, N.; Plummer, S.; Widlowski, J.-L.
2011-05-01
The two-stream model parameters and associated uncertainties retrieved by inversion against MODIS broadband visible and near-infrared white sky surface albedos were discussed in a companion paper. The present paper concentrates on the partitioning of the solar radiation fluxes delivered by the Joint Research Centre Two-stream Inversion Package (JRC-TIP). The estimation of the various flux fractions related to the vegetation and the background layers separately capitalizes on the probability density functions of the model parameters discussed in the companion paper. The propagation of uncertainties from the observations to the model parameters is achieved via the Hessian of the cost function and yields a covariance matrix of posterior parameter uncertainties. This matrix is propagated to the radiation fluxes via the model's Jacobian matrix of first derivatives. Results exhibit a rather good spatiotemporal consistency given that the prior values on the model parameters are not specified as a function of land cover type and/or vegetation phenological states. A specific investigation based on a scenario imposing stringent conditions of leaf absorbing and scattering properties highlights the impact of such constraints that are, as a matter of fact, currently adopted in vegetation index approaches. Special attention is also given to snow-covered and snow-contaminated areas since these regions encompass significant reflectance changes that strongly affect land surface processes. A definite asset of the JRC-TIP lies in its capability to control and ultimately relax a number of assumptions that are often implicit in traditional approaches. These features greatly help us understand the discrepancies between the different data sets of land surface properties and fluxes that are currently available. Through a series of selected examples, the inverse procedure implemented in the JRC-TIP is shown to be robust, reliable, and compliant with large-scale processing requirements. Furthermore, this package ensures the physical consistency between the set of observations, the two-stream model parameters, and radiation fluxes. It also documents the retrieval of associated uncertainties.
Zajac, Zuzanna; Stith, Bradley M.; Bowling, Andrea C.; Langtimm, Catherine A.; Swain, Eric D.
2015-01-01
Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low-quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision-making framework will result in better-informed, more robust decisions.
Classification of American metropolitan areas by ecoregion and potential natural vegetation
Ralph A. Sanders; Rowan A. Rowntree
1983-01-01
This publication classifies 279 American metropolitan areas by ecoregion and potential natural vegetation. The classification forms a baseline of expected vegetation structure and composition that can assist scientists and policy makers in making urban forestry generalizations about classes of cities.
Ecological investigations: vegetation studies, preliminary findings
DOE Office of Scientific and Technical Information (OSTI.GOV)
Olgeirson, E.R.; Martin, R.B.
1978-09-01
The objective of the vegetation studies conducted on the research site is to produce a descriptive data base that can be applied to determinations of carrying capacity of the site and surrounding area. Additional information obtained about parameters that influence vegetation growth and maintenance of soil nutrients, and moisture and temperature regimes help define dynamic relationships that must be understood to effect successful revegetation and habitat rehabilitation. The descriptive vegetation baseline also provides a point of departure for design of future monitoring programs, and predictive models and strategies to be used in dealing with impact mitigation; in turn, monitoring programsmore » and predictive modeling form the bases for making distinctions between natural trends and man-induced perturbations.« less
NASA Technical Reports Server (NTRS)
Rouse, J. W., Jr. (Principal Investigator); Haas, R. H.; Deering, D. W.; Schell, J. A.; Harlan, J. C.
1974-01-01
The author has identified the following significant results. The Great Plains Corridor rangeland project successfully utilized natural vegetation systems as phenological indicators of seasonal development and climatic effects upon regional growth conditions. An effective method was developed for quantitative measurement of vegetation conditions, including green biomass estimates, recorded in bands 5 and 6, corrected for sun angle, were used to compute a ratio parameter (TV16) which is shown to be highly correlated with green biomass and vegatation moisture content. Analyses results of ERTS-1 digital data and correlated ground data are summarized. Attention was given to analyzing weather influences and test site variables on vegetation condition measurements with ERTS-1 data.
Ecogeomorphology of Sand Dunes Shaped by Vegetation
NASA Astrophysics Data System (ADS)
Tsoar, H.
2014-12-01
Two dune types associated with vegetation are known: Parabolic and Vegetated Linear Dunes (VLDs), the latters are the dominant dune type in the world deserts. Parabolic dunes are formed in humid, sub-humid and semi-arid environments (rather than arid) where vegetation is nearby. VLDs are known today in semiarid and arid lands where the average yearly rainfall is ≥100 mm, enough to support sparse cover of vegetation. These two dune types are formed by unidirectional winds although they demonstrate a different form and have a distinct dynamics. Conceptual and mathematical models of dunes mobility and stability, based on three control parameters: wind power (DP), average annual precipitation (p), and the human impact parameter (μ) show that where human impact is negligible the effect of wind power (DP) on vegetative cover is substantial. The average yearly rainfall of 60-80 mm is the threshold of annual average rainfall for vegetation growth on dune sand. The model is shown to follow a hysteresis path, which explains the bistability of active and stabilized dunes under the same climatic conditions with respect to wind power. We have discerned formation of parabolic dunes from barchans and transverse dunes in the coastal plain of Israel where a decrease in human activity during the second half of the 20th century caused establishment of vegetation on the crest of the dunes, a process that changed the dynamics of these barchans and transverse dunes and led to a change in the shape of the windward slope from convex to concave. These dunes gradually became parabolic. It seems that VLDs in Australia or the Kalahari have always been vegetated to some degree, though the shrubs were sparser in colder periods when the aeolian erosion was sizeable. Those ancient conditions are characterized by higher wind power and lower rainfall that can reduce, but not completely destroy, the vegetation cover, leading to the formation of lee (shadow) dunes behind each shrub. Formation of such VLDs can occur today in some coasts where the wind is quite strong and the rain can support some shrubs.
Unified Ecoregions of Alaska: 2001
Nowacki, Gregory J.; Spencer, Page; Fleming, Michael; Brock, Terry; Jorgenson, Torre
2003-01-01
Major ecosystems have been mapped and described for the State of Alaska and nearby areas. Ecoregion units are based on newly available datasets and field experience of ecologists, biologists, geologists and regional experts. Recently derived datasets for Alaska included climate parameters, vegetation, surficial geology and topography. Additional datasets incorporated in the mapping process were lithology, soils, permafrost, hydrography, fire regime and glaciation. Thirty two units are mapped using a combination of the approaches of Bailey (hierarchial), and Omernick (integrated). The ecoregions are grouped into two higher levels using a 'tri-archy' based on climate parameters, vegetation response and disturbance processes. The ecoregions are described with text, photos and tables on the published map.
Huang, Qiongyu; Swatantran, Anu; Dubayah, Ralph; Goetz, Scott J
2014-01-01
Avian diversity is under increasing pressures. It is thus critical to understand the ecological variables that contribute to large scale spatial distribution of avian species diversity. Traditionally, studies have relied primarily on two-dimensional habitat structure to model broad scale species richness. Vegetation vertical structure is increasingly used at local scales. However, the spatial arrangement of vegetation height has never been taken into consideration. Our goal was to examine the efficacies of three-dimensional forest structure, particularly the spatial heterogeneity of vegetation height in improving avian richness models across forested ecoregions in the U.S. We developed novel habitat metrics to characterize the spatial arrangement of vegetation height using the National Biomass and Carbon Dataset for the year 2000 (NBCD). The height-structured metrics were compared with other habitat metrics for statistical association with richness of three forest breeding bird guilds across Breeding Bird Survey (BBS) routes: a broadly grouped woodland guild, and two forest breeding guilds with preferences for forest edge and for interior forest. Parametric and non-parametric models were built to examine the improvement of predictability. Height-structured metrics had the strongest associations with species richness, yielding improved predictive ability for the woodland guild richness models (r(2) = ∼ 0.53 for the parametric models, 0.63 the non-parametric models) and the forest edge guild models (r(2) = ∼ 0.34 for the parametric models, 0.47 the non-parametric models). All but one of the linear models incorporating height-structured metrics showed significantly higher adjusted-r2 values than their counterparts without additional metrics. The interior forest guild richness showed a consistent low association with height-structured metrics. Our results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of forest bird species. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness.
Huang, Qiongyu; Swatantran, Anu; Dubayah, Ralph; Goetz, Scott J.
2014-01-01
Avian diversity is under increasing pressures. It is thus critical to understand the ecological variables that contribute to large scale spatial distribution of avian species diversity. Traditionally, studies have relied primarily on two-dimensional habitat structure to model broad scale species richness. Vegetation vertical structure is increasingly used at local scales. However, the spatial arrangement of vegetation height has never been taken into consideration. Our goal was to examine the efficacies of three-dimensional forest structure, particularly the spatial heterogeneity of vegetation height in improving avian richness models across forested ecoregions in the U.S. We developed novel habitat metrics to characterize the spatial arrangement of vegetation height using the National Biomass and Carbon Dataset for the year 2000 (NBCD). The height-structured metrics were compared with other habitat metrics for statistical association with richness of three forest breeding bird guilds across Breeding Bird Survey (BBS) routes: a broadly grouped woodland guild, and two forest breeding guilds with preferences for forest edge and for interior forest. Parametric and non-parametric models were built to examine the improvement of predictability. Height-structured metrics had the strongest associations with species richness, yielding improved predictive ability for the woodland guild richness models (r2 = ∼0.53 for the parametric models, 0.63 the non-parametric models) and the forest edge guild models (r2 = ∼0.34 for the parametric models, 0.47 the non-parametric models). All but one of the linear models incorporating height-structured metrics showed significantly higher adjusted-r2 values than their counterparts without additional metrics. The interior forest guild richness showed a consistent low association with height-structured metrics. Our results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of forest bird species. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. PMID:25101782
Modeling and measuring the visual detection of ecologically relevant motion by an Anolis lizard.
Pallus, Adam C; Fleishman, Leo J; Castonguay, Philip M
2010-01-01
Motion in the visual periphery of lizards, and other animals, often causes a shift of visual attention toward the moving object. This behavioral response must be more responsive to relevant motion (predators, prey, conspecifics) than to irrelevant motion (windblown vegetation). Early stages of visual motion detection rely on simple local circuits known as elementary motion detectors (EMDs). We presented a computer model consisting of a grid of correlation-type EMDs, with videos of natural motion patterns, including prey, predators and windblown vegetation. We systematically varied the model parameters and quantified the relative response to the different classes of motion. We carried out behavioral experiments with the lizard Anolis sagrei and determined that their visual response could be modeled with a grid of correlation-type EMDs with a spacing parameter of 0.3 degrees visual angle, and a time constant of 0.1 s. The model with these parameters gave substantially stronger responses to relevant motion patterns than to windblown vegetation under equivalent conditions. However, the model is sensitive to local contrast and viewer-object distance. Therefore, additional neural processing is probably required for the visual system to reliably distinguish relevant from irrelevant motion under a full range of natural conditions.
The seasonal behaviour of carbon fluxes in the Amazon: fusion of FLUXNET data and the ORCHIDEE model
NASA Astrophysics Data System (ADS)
Verbeeck, H.; Peylin, P.; Bacour, C.; Ciais, P.
2009-04-01
Eddy covariance measurements at the Santarém (km 67) site revealed an unexpected seasonal pattern in carbon fluxes which could not be simulated by existing state-of-the-art global ecosystem models (Saleska et al., Sciece 2003). An unexpected high carbon uptake was measured during dry season. In contrast, carbon release was observed in the wet season. There are several possible (combined) underlying mechanisms of this phenomenon: (1) an increased soil respiration due to soil moisture in the wet season, (2) increased photosynthesis during the dry season due to deep rooting, hydraulic lift, increased radiation and/or a leaf flush. The objective of this study is to optimise the ORCHIDEE model using eddy covariance data in order to be able to mimic the seasonal response of carbon fluxes to dry/wet conditions in tropical forest ecosystems. By doing this, we try to identify the underlying mechanisms of this seasonal response. The ORCHIDEE model is a state of the art mechanistic global vegetation model that can be run at local or global scale. It calculates the carbon and water cycle in the different soil and vegetation pools and resolves the diurnal cycle of fluxes. ORCHIDEE is built on the concept of plant functional types (PFT) to describe vegetation. To bring the different carbon pool sizes to realistic values, spin-up runs are used. ORCHIDEE uses climate variables as drivers together with a number of ecosystem parameters that have been assessed from laboratory and in situ experiments. These parameters are still associated with a large uncertainty and may vary between and within PFTs in a way that is currently not informed or captured by the model. Recently, the development of assimilation techniques allows the objective use of eddy covariance data to improve our knowledge of these parameters in a statistically coherent approach. We use a Bayesian optimisation approach. This approach is based on the minimization of a cost function containing the mismatch between simulated model output and observations as well as the mismatch between a priori and optimized parameters. The parameters can be optimized on different time scales (annually, monthly, daily). For this study the model is optimised at local scale for 5 eddy flux sites: 4 sites in Brazil and one in French Guyana. The seasonal behaviour of C fluxes in response to wet and dry conditions differs among these sites. Key processes that are optimised include: the effect of the soil water on heterotrophic soil respiration, the effect of soil water availability on stomatal conductance and photosynthesis, and phenology. By optimising several key parameters we could improve the simulation of the seasonal pattern of NEE significantly. Nevertheless, posterior parameters should be interpreted with care, because resulting parameter values might compensate for uncertainties on the model structure or other parameters. Moreover, several critical issues appeared during this study e.g. how to assimilate latent and sensible heat data, when the energy balance is not closed in the data? Optimisation of the Q10 parameter showed that on some sites respiration was not sensitive at all to temperature, which show only small variations in this region. Considering this, one could question the reliability of the partitioned fluxes (GPP/Reco) at these sites. This study also tests if there is coherence between optimised parameter values of different sites within the tropical forest PFT and if the forward model response to climate variations is similar between sites.
Does habitat fragmentation influence nest predation in the shortgrass prairie?
Howard, M.N.; Skagen, S.K.; Kennedy, P.L.
2001-01-01
We examined the effects of habitat fragmentation and vegetation structure of shortgrass prairie and Conservation Reserve Program (CRP) lands on predation rates of artificial and natural nests in northeastern Colorado. The CRP provides federal payments to landowners to take highly erodible cropland out of agricultural production. In our study area, CRP lands have been reseeded primarily with non-native grasses, and this vegetation is taller than native shortgrass prairie. We measured three indices of habitat fragmentation (patch size, degree of matrix fragmentation, and distance from edge), none of which influenced mortality rates of artificial or natural nests. Vegetation structure did influence predation rates of artificial nests; daily mortality decreased significantly with increasing vegetation height. Vegetation structure did not influence predation rates of natural nests. CRP lands and shortgrass sites did not differ with respect to mortality rates of artificial nests. Our study area is only moderately fragmented; 62% of the study area is occupied by native grassland. We conclude that the extent of habitat fragmentation in our study area does not result in increased predation in remaining patches of shortgrass prairie habitat.
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.
Victor A. Rudis; Ronald E. Thill; James H. Gramann; Joseph Picone; Nirmala Kalidindi; Philip A. Tappe
1999-01-01
Deciding among cutting practices requires knowledge of forest structure, understory vegetation change, rates of recovery, and resource impacts. The authors used two field devices (a screenometer and a density board) and digital images of 35 mm photographs to compare measures and document the change in understory vegetation structure in forests following reproduction...
Repeatability and implementation of a forest vegetation indicator.
Andrew N. Gray; David L. Azuma
2005-01-01
The composition, diversity, and structure of vascular plants are important indicators of forest health. Changes in species diversity, structural diversity, and the abundance of non-native species are common national concerns, and are part of the international criteria for assessing sustainability of forestry practices. The vegetation indicator for the national Forest...
The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.
Li, Bonan; Wang, Lixin; Kaseke, Kudzai F; Li, Lin; Seely, Mary K
2016-01-01
Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months' continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert.
The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert
Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Li, Lin; Seely, Mary K.
2016-01-01
Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months’ continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert. PMID:27764203
[Object-oriented aquatic vegetation extracting approach based on visible vegetation indices.
Jing, Ran; Deng, Lei; Zhao, Wen Ji; Gong, Zhao Ning
2016-05-01
Using the estimation of scale parameters (ESP) image segmentation tool to determine the ideal image segmentation scale, the optimal segmented image was created by the multi-scale segmentation method. Based on the visible vegetation indices derived from mini-UAV imaging data, we chose a set of optimal vegetation indices from a series of visible vegetation indices, and built up a decision tree rule. A membership function was used to automatically classify the study area and an aquatic vegetation map was generated. The results showed the overall accuracy of image classification using the supervised classification was 53.7%, and the overall accuracy of object-oriented image analysis (OBIA) was 91.7%. Compared with pixel-based supervised classification method, the OBIA method improved significantly the image classification result and further increased the accuracy of extracting the aquatic vegetation. The Kappa value of supervised classification was 0.4, and the Kappa value based OBIA was 0.9. The experimental results demonstrated that using visible vegetation indices derived from the mini-UAV data and OBIA method extracting the aquatic vegetation developed in this study was feasible and could be applied in other physically similar areas.
NASA Astrophysics Data System (ADS)
Yeh, T. Y.; Li, M. H.; Chen, Y. Y.; Ryder, J.; McGrath, M.; Otto, J.; Naudts, K.; Luyssaert, S.; MacBean, N.; Bastrikov, V.
2016-12-01
Dynamic vegetation model ORCHIDEE (Organizing Carbon and Hydrology In Dynamic EcosystEms) is a state of art land surface component of the IPSL (Institute Pierre Simon Laplace) Earth System Model. It has been used world-wide to investigate variations of water, carbon, and energy exchanges between the land surface and the atmosphere. In this study we assessed the applicability of using ORCHIDEE-CAN, a new feature with 3-D CANopy structure (Naudts et al., 2015; Ryder et al., 2016), to simulate surface fluxes measured at tower-based eddy covariance fluxes at the Lien-Hua-Chih experimental watershed in Taiwan. The atmospheric forcing including radiation, air temperature, wind speed, and the dynamics of vertical canopy structure for driving the model were obtained from the observations site. Suitable combinations of default plant function types were examined to meet in-situ observations of soil moisture and leaf area index from 2009 to 2013. The simulated top layer soil moisture was ranging from 0.1 to 0.4 and total leaf area was ranging from 2.2 to 4.4, respectively. A sensitivity analysis was performed to investigate the sensitive of model parameters and model skills of ORCHIDEE-CAN on capturing seasonal variations of surface fluxes. The most sensitive parameters were suggested and calibrated by an automatic data assimilation tool ORCHDAS (ORCHIDEE Data Assimilation Systems; http://orchidas.lsce.ipsl.fr/). Latent heat, sensible heat, and carbon fluxes simulated by the model were compared with long-term observations at the site. ORCHIDEE-CAN by making use of calibrated surface parameters was used to study variations of land-atmosphere interactions on a variety of temporal scale in associations with changes in both land and atmospheric conditions. Ref: Naudts, K., et al.,: A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes, Geoscientific Model Development, 8, 2035-2065, doi:10.5194/gmd-8-2035-2015,2015. Ryder, J., et al. : A multi-layer land surface energy budget model for implicit coupling with global atmospheric simulations, Geoscientific Model Development, 9, 223-245, doi:10.5194/gmd-9-223-2016, 2016.
Gao, Tian; Qiu, Ling; Chen, Cun-gen
2010-09-01
Based on the biotope classification system with vegetation structure as the framework, a modified biotope mapping model integrated with vegetation cover continuity attributes was developed, and applied to the study of the greenbelts in Helsingborg in southern Sweden. An evaluation of the vegetation cover continuity in the greenbelts was carried out by the comparisons of the vascular plant species richness in long- and short-continuity forests, based on the identification of woodland continuity by using ancient woodland indicator species (AWIS). In the test greenbelts, long-continuity woodlands had more AWIS. Among the forests where the dominant trees were more than 30-year-old, the long-continuity ones had a higher biodiversity of vascular plants, compared with the short-continuity ones with the similar vegetation structure. The modified biotope mapping model integrated with the continuity features of vegetation cover could be an important tool in investigating urban biodiversity, and provide corresponding strategies for future urban biodiversity conservation.
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.
[Study of the microwave emissivity characteristics over different land cover types].
Zhang, Yong-Pan; Jiang, Ling-Mei; Qiu, Yu-Bao; Wu, Sheng-Li; Shi, Jian-Cheng; Zhang, Li-Xin
2010-06-01
The microwave emissivity over land is very important for describing the characteristics of the lands, and it is also a key factor for retrieving the parameters of land and atmosphere. Different land covers have their emission behavior as a function of structure, water content, and surface roughness. In the present study the global land surface emissivities were calculated using six month (June, 2003-August, 2003, Dec, 2003-Feb, 2004) AMSR-E L2A brightness temperature, MODIS land surface temperature and the layered atmosphere temperature, and humidity and pressure profiles data retrieved from MODIS/Aqua under clear sky conditions. With the information of IGBP land cover types, "pure" pixels were used, which are defined when the fraction cover of each land type is larger than 85%. Then, the emissivity of sixteen land covers at different frequencies, polarization and their seasonal variation were analyzed respectively. The results show that the emissivity of vegetation including forests, grasslands and croplands is higher than that over bare soil, and the polarization difference of vegetation is smaller than that of bare soil. In summer, the emissivity of vegetation is relatively stable because it is in bloom, therefore the authors can use it as its emissivity in our microwave emissivity database over different land cover types. Furthermore, snow cover can heavily impact the change in land cover emissivity, especially in winter.
Ambiguous dependence of fluorescence intensity of trees on chlorophyll concentration
NASA Astrophysics Data System (ADS)
Zavoruev, Valeriy V.; Zavorueva, Elena N.
2014-11-01
Using fluorimetry Junior PAM (Heinz Walz GmbH, Germany) fluorescence parameters of leaves Prinsepia sinensis, Crataegus chlorocarca M, Acer negúndo, Bétula péndula are studied. It was found that the dependence of maximum fluorescence (Fm) plants on the concentration of chlorophyll depends on the sampling method during of vegetation. The correctness of sampling proves during vegetation is substantiated.
Development of full regeneration establishment models for the forest vegetation simulator
John D. Shaw
2015-01-01
For most simulation modeling efforts, the goal of model developers is to produce simulations that are the best representations of realism as possible. Achieving this goal commonly requires a considerable amount of data to set the initial parameters, followed by validation and model improvement â both of which require even more data. The Forest Vegetation Simulator (FVS...
Amanda L. Fox; Dean E. Eisenhauer; Michael G. Dosskey
2005-01-01
Vegetated filters (buffers) are used to intercept overland runoff and reduce sediment and other contaminant loads to streams (Dosskey, 2001). Filters function by reducing runoff velocity and volume, thus enhancing sedimentation and infiltration. lnfiltration is the main mechanism for soluble contaminant removal, but it also plays a role in suspended particle removal....
Ecological connectivity in the three-dimensional urban green volume using waveform airborne lidar
Casalegno, Stefano; Anderson, Karen; Cox, Daniel T. C.; Hancock, Steven; Gaston, Kevin J.
2017-01-01
The movements of organisms and the resultant flows of ecosystem services are strongly shaped by landscape connectivity. Studies of urban ecosystems have relied on two-dimensional (2D) measures of greenspace structure to calculate connectivity. It is now possible to explore three-dimensional (3D) connectivity in urban vegetation using waveform lidar technology that measures the full 3D structure of the canopy. Making use of this technology, here we evaluate urban greenspace 3D connectivity, taking into account the full vertical stratification of the vegetation. Using three towns in southern England, UK, all with varying greenspace structures, we describe and compare the structural and functional connectivity using both traditional 2D greenspace models and waveform lidar-generated vegetation strata (namely, grass, shrubs and trees). Measures of connectivity derived from 3D greenspace are lower than those derived from 2D models, as the latter assumes that all vertical vegetation strata are connected, which is rarely true. Fragmented landscapes that have more complex 3D vegetation showed greater functional connectivity and we found highest 2D to 3D functional connectivity biases for short dispersal capacities of organisms (6 m to 16 m). These findings are particularly pertinent in urban systems where the distribution of greenspace is critical for delivery of ecosystem services. PMID:28382936
Ecological connectivity in the three-dimensional urban green volume using waveform airborne lidar
NASA Astrophysics Data System (ADS)
Casalegno, Stefano; Anderson, Karen; Cox, Daniel T. C.; Hancock, Steven; Gaston, Kevin J.
2017-04-01
The movements of organisms and the resultant flows of ecosystem services are strongly shaped by landscape connectivity. Studies of urban ecosystems have relied on two-dimensional (2D) measures of greenspace structure to calculate connectivity. It is now possible to explore three-dimensional (3D) connectivity in urban vegetation using waveform lidar technology that measures the full 3D structure of the canopy. Making use of this technology, here we evaluate urban greenspace 3D connectivity, taking into account the full vertical stratification of the vegetation. Using three towns in southern England, UK, all with varying greenspace structures, we describe and compare the structural and functional connectivity using both traditional 2D greenspace models and waveform lidar-generated vegetation strata (namely, grass, shrubs and trees). Measures of connectivity derived from 3D greenspace are lower than those derived from 2D models, as the latter assumes that all vertical vegetation strata are connected, which is rarely true. Fragmented landscapes that have more complex 3D vegetation showed greater functional connectivity and we found highest 2D to 3D functional connectivity biases for short dispersal capacities of organisms (6 m to 16 m). These findings are particularly pertinent in urban systems where the distribution of greenspace is critical for delivery of ecosystem services.
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.
Thompson, C.; Beringer, J.; Chapin, F. S.; McGuire, A.D.
2004-01-01
Question: Current climate changes in the Alaskan Arctic, which are characterized by increases in temperature and length of growing season, could alter vegetation structure, especially through increases in shrub cover or the movement of treeline. These changes in vegetation structure have consequences for the climate system. What is the relationship between structural complexity and partitioning of surface energy along a gradient from tundra through shrub tundra to closed canopy forest? Location: Arctic tundra-boreal forest transition in the Alaskan Arctic. Methods: Along this gradient of increasing canopy complexity, we measured key vegetation characteristics, including community composition, biomass, cover, height, leaf area index and stem area index. We relate these vegetation characteristics to albedo and the partitioning of net radiation into ground, latent, and sensible heating fluxes. Results: Canopy complexity increased along the sequence from tundra to forest due to the addition of new plant functional types. This led to non-linear changes in biomass, cover, and height in the understory. The increased canopy complexity resulted in reduced ground heat fluxes, relatively conserved latent heat fluxes and increased sensible heat fluxes. The localized warming associated with increased sensible heating over more complex canopies may amplify regional warming, causing further vegetation change in the Alaskan Arctic.
Escobar, Indra Elena C; Santos, Vilma M; da Silva, Danielle Karla A; Fernandes, Marcelo F; Cavalcante, Uided Maaze T; Maia, Leonor C
2015-06-01
The aim of this study was to describe the impact of re-vegetation on the restoration of microbial community structure and soil microbiological properties in sand dunes that had been affected by mining activity. Soil samples were collected during the dry and rainy seasons from a chronosequence (1, 9, 21 years) of re-vegetated dunes using a single preserved dune as a reference. The composition of the fatty acid methyl esters and soil microbial properties were evaluated. The results showed that the changes in microbial community structure were related to seasonal variations: biomarkers of Gram-positive bacteria were higher than Gram-negative bacteria during the dry season, showing that this group of organisms is more tolerant to these stressful conditions. The microbial community structure in the natural dune was less affected by seasonal variation compared to the re-vegetated areas, whereas the opposite was observed for microbiological properties. Thus, in general, the proportion of saprobic fungi was higher in the natural dune, whereas Gram-negative bacteria were proportionally more common in the younger areas. Although over time the re-vegetation allows the recovery of the microbial community and the soil functions, these communities and functions are different from those found in the undisturbed areas.
Hogan, Jennifer N.; Daniels, Miles E.; Watson, Fred G.; Oates, Stori C.; Miller, Melissa A.; Conrad, Patricia A.; Shapiro, Karen; Hardin, Dane; Dominik, Clare; Melli, Ann; Jessup, David A.
2013-01-01
Constructed wetland systems are used to reduce pollutants and pathogens in wastewater effluent, but comparatively little is known about pathogen transport through natural wetland habitats. Fecal protozoans, including Cryptosporidium parvum, Giardia lamblia, and Toxoplasma gondii, are waterborne pathogens of humans and animals, which are carried by surface waters from land-based sources into coastal waters. This study evaluated key factors of coastal wetlands for the reduction of protozoal parasites in surface waters using settling column and recirculating mesocosm tank experiments. Settling column experiments evaluated the effects of salinity, temperature, and water type (“pure” versus “environmental”) on the vertical settling velocities of C. parvum, G. lamblia, and T. gondii surrogates, with salinity and water type found to significantly affect settling of the parasites. The mesocosm tank experiments evaluated the effects of salinity, flow rate, and vegetation parameters on parasite and surrogate counts, with increased salinity and the presence of vegetation found to be significant factors for removal of parasites in a unidirectional transport wetland system. Overall, this study highlights the importance of water type, salinity, and vegetation parameters for pathogen transport within wetland systems, with implications for wetland management, restoration efforts, and coastal water quality. PMID:23315738
ECR Plasma Sterilisation, Argon and Nitrogen Treated Plasma
NASA Astrophysics Data System (ADS)
Helhel, Selcuk; Oksuz, Lutfi; Cerezci, Osman; Rad, Abbas Y.
2004-09-01
ECR type plasma system was built to produce plasma in axial direction. Plasma was initiated in a specially designed Nickel - Chrome cylindrical vacuum tube which is being driven through dielectric window by 2.45GHz commercial magnetron source. Tube is also surrounded by a coil driving 150ADC to generate approximately 875Gauss magnetic field at the center. Langmuir probe and ICCD for optical spectrometry were used to characterize internal parameters like electron density, electron temperature and different characteristics of the plasma. Bacillus Subtilis var nigar, bacillus Stearothermophilus, bacillus pumilus E601, Escherichia coli and staphylococcus aureus type bacteria were selected as a reference. Each is resistant for different actions while the Bacilus cereus is the most resistant bacteria for microwave interaction. This study presents the effect of system on used bacteria. Those are gram positive and gram negative bacteria that refers to structure of cell wall. The sterilization efficacy of Argon type ECR plasma was found to be over 99, 5% in Staphylococcus aureus, Staphylococcus epidermidis, Bacillus subtilis (vegetative cell), Bacillus cereus (vegetative cell), Bacillus pumilus and Escherichia coli. System response type is less than 2 minutes.
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.
Surface energy exchanges along a tundra-forest transition and feedbacks to climate
Beringer, J.; Chapin, F. S.; Thompson, Catharine Copass; McGuire, A.D.
2005-01-01
Surface energy exchanges were measured in a sequence of five sites representing the major vegetation types in the transition from arctic tundra to forest. This is the major transition in vegetation structure in northern high latitudes. We examined the influence of vegetation structure on the rates of sensible heating and evapotranspiration to assess the potential feedbacks to climate if high-latitude warming were to change the distribution of these vegetation types. Measurements were made at Council on the Seward Peninsula, Alaska, at representative tundra, low shrub, tall shrub, woodland (treeline), and boreal forest sites. Structural differences across the transition from tundra to forest included an increase in the leaf area index (LAI) from 0.52 to 2.76, an increase in canopy height from 0.1 to 6.1 m, and a general increase in canopy complexity. These changes in vegetation structure resulted in a decrease in albedo from 0.19 to 0.10 as well as changes to the partitioning of energy at the surface. Bulk surface resistance to water vapor flux remained virtually constant across sites, apparently because the combined soil and moss evaporation decreased while transpiration increased along the transect from tundra to forest. In general, sites became relatively warmer and drier along the transect with the convective fluxes being increasingly dominated by sensible heating, as evident by an increasing Bowen ratio from 0.94 to 1.22. The difference in growing season average daily sensible heating between tundra and forest was 21 W m-2. Fluxes changed non-linearly along the transition, with both shrubs and trees substantially enhancing heat transfer to the atmosphere. These changes in vegetation structure that increase sensible heating could feed back to enhance warming at local to regional scales. The magnitude of these vegetation effects on potential high-latitude warming is two to three times greater than suggested by previous modeling studies. ?? 2005 Elsevier B.V. All rights reserved.
Soil and vegetation parameter uncertainty on future terrestrial carbon sinks
NASA Astrophysics Data System (ADS)
Kothavala, Z.; Felzer, B. S.
2013-12-01
We examine the role of the terrestrial carbon cycle in a changing climate at the centennial scale using an intermediate complexity Earth system climate model that includes the effects of dynamic vegetation and the global carbon cycle. We present a series of ensemble simulations to evaluate the sensitivity of simulated terrestrial carbon sinks to three key model parameters: (a) The temperature dependence of soil carbon decomposition, (b) the upper temperature limits on the rate of photosynthesis, and (c) the nitrogen limitation of the maximum rate of carboxylation of Rubisco. We integrated the model in fully coupled mode for a 1200-year spin-up period, followed by a 300-year transient simulation starting at year 1800. Ensemble simulations were conducted varying each parameter individually and in combination with other variables. The results of the transient simulations show that terrestrial carbon uptake is very sensitive to the choice of model parameters. Changes in net primary productivity were most sensitive to the upper temperature limit on the rate of photosynthesis, which also had a dominant effect on overall land carbon trends; this is consistent with previous research that has shown the importance of climatic suppression of photosynthesis as a driver of carbon-climate feedbacks. Soil carbon generally decreased with increasing temperature, though the magnitude of this trend depends on both the net primary productivity changes and the temperature dependence of soil carbon decomposition. Vegetation carbon increased in some simulations, but this was not consistent across all configurations of model parameters. Comparing to global carbon budget observations, we identify the subset of model parameters which are consistent with observed carbon sinks; this serves to narrow considerably the future model projections of terrestrial carbon sink changes in comparison with the full model ensemble.
NASA Astrophysics Data System (ADS)
Cavender-Bares, J.; Schweiger, A. K.; Madritch, M. D.; Gamon, J. A.; Hobbie, S. E.; Montgomery, R.; Townsend, P. A.
2017-12-01
Above-and below-ground plant traits are important for substrate input to the rhizosphere. The substrate composition of the rhizosphere, in turn, affects the diversity of soil organisms, influences soil biochemistry, and water content, and resource availability for plant growth. This has substantial consequences for ecosystem functions, such as above-ground productivity and stability. Above-ground plant chemical and structural traits can be linked to the characteristics of other plant organs, including roots. Airborne imaging spectroscopy has been successfully used to model and predict chemical and structural traits of the above-ground vegetation. However, remotely sensed images capture, almost exclusively, signals from the top of the canopy, providing limited direct information about understory vegetation. Here, we use a data set collected in a savanna ecosystem consisting of spectral measurements gathered at the leaf, the whole plant, and vegetation canopy level to test for hypothesized linkages between above- and below-ground processes that influence root biomass, soil biochemistry, and the diversity of the soil community. In this environment, consisting of herbaceous vegetation intermixed with shrubs and trees growing at variable densities, we investigate the contribution of different vegetation strata to soil characteristics and test the ability of imaging spectroscopy to detect these in plant communities with contrasting vertical structure.
Multi-Frequency Investigation into Scattering from Vegetation over the Growth Cycle
NASA Technical Reports Server (NTRS)
Lang, R. H.; Kurum, M.; O'Neill, P. E.; Joseph, A. T.; Deshpande, M. D.; Cosh, M. H.
2016-01-01
In this investigation, we aim to collect and use time-series multi-frequency microwave data over winter wheat during entire growth cycle to characterize vegetation dynamics and to quantify its effects on soil moisture retrievals. We plan to incorporate C-band radar and VHF receiver within the existing L-band radarradiometer system called ComRAD (SMAPs ground based simulator). With C-bands ability to sense vegetation details and VHFs root-zone soil moisture within ComRADs footprint, we will be able to test our discrete scatterer vegetation models and parameters at various surface conditions. The purpose of this study is to determine optical depth and effective scattering albedo of vegetation of a given type (i.e. winter wheat) at various stages of growth that are need to refine soil moisture retrieval algorithms being developed for the SMAP mission.
J.F. Lehmkuhl; P.F. Hessburg; R.L. Everett; M.H. Huff; R.D. Ottmar
1994-01-01
We analyzed historical and current vegetation composition and structure in 49 sample watersheds, primarily on National Forests, within six river basins in eastern Oregon and Washington. Vegetation patterns were mapped from aerial photographs taken from 1932 to 1959, and from 1985 to 1992. We described vegetation attributes, landscape patterns, the range of historical...
NASA Technical Reports Server (NTRS)
Green, Robert O.; Roberts, Dar A.
1995-01-01
Plant species composition and plant architectural attributes are critical parameters required for the measuring, monitoring, and modeling of terrestrial ecosystems. Remote sensing is commonly cited as an important tool for deriving vegetation properties at an appropriate scale for ecosystem studies, ranging from local to regional and even synoptic scales. Classical approaches rely on vegetation indices such as the normalized difference vegetation index (NDVI) to estimate biophysical parameters such as leaf area index or intercepted photosynthetically active radiation (IPAR). Another approach is to apply a variety of classification schemes to map vegetation and thus extrapolate fine-scale information about specific sites to larger areas of similar composition. Imaging spectrometry provides additional information that is not obtainable through broad-band sensors and that may provide improved inputs both to direct biophysical estimates as well as classification schemes. Some of this capability has been demonstrated through improved discrimination of vegetation, estimates of canopy biochemistry, and liquid water estimates from vegetation. We investigate further the potential of leaf water absorption estimated from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data as a means for discriminating vegetation types and deriving canopy architectural information. We expand our analysis to incorporate liquid water estimates from two spectral regions, the 1000-nm region and the 2200-nm region. The study was conducted in the vicinity of Jasper Ridge, California, which is located on the San Francisco peninsula to the west of the Stanford University campus. AVIRIS data were acquired over Jasper Ridge, CA, on June 2, 1992, at 19:31 UTC. Spectra from three sites in this image were analyzed. These data are from an area of healthy grass, oak woodland, and redwood forest, respectively. For these analyses, the AVIRIS-measured upwelling radiance spectra for the entire Jasper Ridge scene were transformed to apparent surface reflectance using a radiative transfer code-based inversion algorithm.
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.
Effects of Vegetation Structure on the Location of Lion Kill Sites in African Thicket
Davies, Andrew B.; Tambling, Craig J.; Kerley, Graham I. H.; Asner, Gregory P.
2016-01-01
Predator-prey relationships are integral to ecosystem stability and functioning. These relationships are, however, difficult to maintain in protected areas where large predators are increasingly being reintroduced and confined. Where predators make kills has a profound influence on their role in ecosystems, but the relative importance of environmental variables in determining kill sites, and how these might vary across ecosystems is poorly known. We investigated kill sites for lions in South Africa’s thicket biome, testing the importance of vegetation structure for kill site locations compared to other environmental variables. Kill sites were located over four years using GPS telemetry and compared to non-kill sites that had been occupied by lions, as well as to random sites within lion ranges. Measurements of 3D vegetation structure obtained from Light Detection and Ranging (LiDAR) were used to calculate the visible area (viewshed) around each site and, along with wind and moonlight data, used to compare kill sites between lion sexes, prey species and prey sexes. Viewshed area was the most important predictor of kill sites (sites in dense vegetation were twice as likely to be kill sites compared to open areas), followed by wind speed and, less so, moonlight. Kill sites for different prey species varied with vegetation structure, and male prey were killed when wind speeds were higher compared to female prey of the same species. Our results demonstrate that vegetation structure is an important component of predator-prey interactions, with varying effects across ecosystems. Such differences require consideration in terms of the ecological roles performed by predators, and in predator and prey conservation. PMID:26910832
Sitters, Holly; Di Stefano, Julian; Christie, Fiona; Swan, Matthew; York, Alan
2016-01-01
Animal species diversity is often associated with time since disturbance, but the effects of disturbances such as fire on functional diversity are unknown. Functional diversity measures the range, abundance, and distribution of trait values in a community, and links changes in species composition with the consequences for ecosystem function. Improved understanding of the relationship between time since fire (TSF) and functional diversity is critical given that the frequency of both prescribed fire and wildfire is expected to increase. To address this knowledge gap, we examined responses of avian functional diversity to TSF and two direct measures of environmental heterogeneity, plant diversity, and structural heterogeneity. We surveyed birds across a 70-year chronosequence spanning four vegetation types in southeast Australia. Six bird functional traits were used to derive four functional diversity indices (richness, evenness, divergence, and dispersion) and the effects of TSF, plant diversity and structural heterogeneity on species richness and the functional diversity indices were examined using mixed models. We used a regression tree method to identify traits associated with species more common in young vegetation. Functional richness and dispersion were negatively associated with TSF in all vegetation types, suggesting that recent prescribed fire generates heterogeneous vegetation and provides greater opportunities for resource partitioning. Species richness was not significantly associated with TSF, and is probably an unreliable surrogate for functional diversity in fire-prone systems. A positive, relationship between functional evenness and structural heterogeneity was comnon to all vegetation types, suggesting that fine-scale (tens of meters) structural variation can enhance ecosystem function. Species more common in young vegetation were primarily linked by their specialist diets, indicating that ecosystem services such as seed dispersal and insect control are enhanced in more recently burnt vegetation. We suggest that patchy prescribed fire sustains functional diversity, and that controlled use of patchy fire to break up large expanses of mature vegetation will enhance ecosystem function.
NASA Astrophysics Data System (ADS)
Xu, Tao; Liao, Jingjuan
2014-11-01
In order to reveal more deeply the scattering characteristics of wetland vegetation and determine the microwave scattering model suitable for the inversion of wetland vegetation parameters, the comparison and analysis between microwave coherent and incoherent scattering models for wetland vegetation in Poyang Lake area were performed in this paper. In the research, we proposed a coherent scattering model exclusive for wetland vegetation, in which, Generalized Rayleigh-Gans (GRG) approach and infinite-length dielectric cylinder were used to calculate single-scattering matrices of wetland vegetation leaves and stalks. In addition, coherent components produced from interaction among the scattering mechanisms and different scatterers were also considered and this coherent model was compared with Michigan Microwave Canopy Scattering (MIMICS) model. The measured data collected in 2011 in Poyang Lake wetland were used as the input parameters of the coherent and incoherent models. We simulated backscattering coefficients of VV, VH and HH polarization at C band and made a comparison between the simulation results and C-band data from the Radarsat-2 satellite. For both coherent and incoherent scattering model, simulation results for HH and VV polarization were better than the simulation results for HV polarization. In addition, comparisons between coherent and incoherent scattering models proved that the coherence triggered by the scattering mechanism and different scatterers can't be ignored. In the research, we analyzed differences between coherent and incoherent scattering models with change of incident angle. In most instances, the difference between coherent and incoherent scattering models is of the order of several dB.
Hydrology and trout populations of cold-water rivers of Michigan and Wisconsin
Hendrickson, G.E.; Knutilla, R.L.
1974-01-01
Statistical multiple-regression analyses showed significant relationships between trout populations and hydrologic parameters. Parameters showing the higher levels of significance were temperature, hardness of water, percentage of gravel bottom, percentage of bottom vegetation, variability of streamflow, and discharge per unit drainage area. Trout populations increase with lower levels of annual maximum water temperatures, with increase in water hardness, and with increase in percentage of gravel and bottom vegetation. Trout populations also increase with decrease in variability of streamflow, and with increase in discharge per unit drainage area. Most hydrologic parameters were significant when evaluated collectively, but no parameter, by itself, showed a high degree of correlation with trout populations in regression analyses that included all the streams sampled. Regression analyses of stream segments that were restricted to certain limits of hardness, temperature, or percentage of gravel bottom showed improvements in correlation. Analyses of trout populations, in pounds per acre and pounds per mile and hydrologic parameters resulted in regression equations from which trout populations could be estimated with standard errors of 89 and 84 per cent, respectively.
We examined larval and juvenile fish assemblage structure in relation to microhabitat variables within the St. Louis River estuary, a drowned river mouth of Lake Superior. Fish were sampled in vegetated beds throughout the estuary, across a gradient of vegetation types and densit...
Classification and description of world formation types
D. Faber-Langendoen; T. Keeler-Wolf; D. Meidinger; C. Josse; A. Weakley; D. Tart; G. Navarro; B. Hoagland; S. Ponomarenko; G. Fults; Eileen Helmer
2016-01-01
An ecological vegetation classification approach has been developed in which a combination of vegetation attributes (physiognomy, structure, and floristics) and their response to ecological and biogeographic factors are used as the basis for classifying vegetation types. This approach can help support international, national, and subnational classification efforts. The...
NASA Astrophysics Data System (ADS)
Fischer, Christine; Hohenbrink, Tobias; Leimer, Sophia; Roscher, Christiane; Ravenek, Janneke; de Kroon, Hans; Kreutziger, Yvonne; Wirth, Christian; Eisenhauer, Nico; Gleixner, Gerd; Weigelt, Alexandra; Mommer, Liesje; Beßler, Holger; Schröder, Boris; Hildebrandt, Anke
2015-04-01
Soil moisture is the dynamic link between climate, soil and vegetation and the dynamics and variation are affected by several often interrelated factors such as soil texture, soil structural parameters (soil organic carbon) and vegetation parameters (belowground- and aboveground biomass). For the characterization and estimation of soil moisture and its variability and the resulting water fluxes and solute transports, the knowledge of the relative importance of these factors is of major challenge for hydrology and bioclimatology. Because of the heterogeneity of these factors, soil moisture varies strongly over time and space. Our objective was to assess the spatio-temporal variability of soil moisture and factors which could explain that variability, like soil properties and vegetation cover, in in a long term biodiversity experiment (Jena Experiment). The Jena Experiment consist 86 plots on which plant species richness (0, 1, 2, 4, 8, 16, and 60) and functional groups (legumes, grasses, tall herbs, and small herbs) were manipulated in a factorial design Soil moisture measurements were performed weekly April to September 2003-2005 and 2008-2013 using Delta T theta probe. Measurements were integrated to three depth intervals: 0.0 - 0.20, 0.20 - 0.40 and 0.40 - 0.70 m. We analyze the spatio-temporal patterns of soil water content on (i) the normalized time series and (ii) the first components obtained from a principal component analysis (PCA). Both were correlated with the design variables of the Jena Experiment (plant species richness and plant functional groups) and other influencing factors such as soil texture, soil structural variables and vegetation parameters. For the time stability of soil water content, the analysis showed that plots containing grasses was consistently drier than average at the soil surface in all observed years while plots containing legumes comparatively moister, but only up to the year 2008. In 0.40 - 0.70 m soil deep plots presence of small herbs led to higher than average soil moisture in some years (2008, 2012, 2013). Interestingly, plant species richness led to moister than average subsoil at the beginning of the experiment (2003 and 2004), which changed to lower than average up to the year 2010 in all depths. There was no effect of species diversity in the years since 2010, although species diversity generally increases leaf area index and aboveground biomass. The first component from the PCA analysis described the mean behavior in time of all soil moisture time series. The second component reflected the impact of soil depth. The first two components explained 76% of the data set total variance. The third component is linked to plant species richness and explained about 4 % of the total variance of soil moisture data. The fourth component, which explained 2.4 %, showed a high correlation to soil texture. Within this study we investigate the dominant factors controlling spatio-temporal patterns of soil moisture at several soil depths. Although climate and soil depths were the most important drivers, other factors like plant species richness and soil texture affected the temporal variation while certain plant functional groups were important for the spatial variability.
Zavodnik, L B
2003-01-01
Bioflavonoids (polyhydroxyphenols) are ubiquitous components of plants, fruits and vegetables; these compounds are efficient scavengers of free oxygen radicals and peroxides. The aim of this study was to investigate the antioxidant and radioprotective effects of genistein-8-C-glicoside (G8CG), an isoflavone, isolated from the flowers of Lipinus luteusl L. G8CG prevents dose-dependently the destruction of the cytochrome P-450 and its conversion to an inactive form cytochrome P-420, inhibits membrane lipid peroxidation and membrane SH-group oxidation in isolated rat liver microsomal membranes under tert-butylhydroperoxide-induced oxidative stress. Single whole-body gamma-irradiation (1 Gy) of rats results in blood plasma and liver microsomal membrane lipid peroxidation, impairments of microsomal membrane structure and function. Rat treatment with G8CG (75 mg/kg) developed the clear protective effect, stabilized membrane structure and improved the parameters of the monooxygenase function. We can conclude that G8CG can be used as antioxidant and radioprotective agent.
Developmental instability of gynodioecious Teucrium lusitanicum
Alados, C.L.; Navarro, T.; Cabezudo, B.; Emlen, J.M.; Freeman, C.
1998-01-01
Developmental instability was assessed in two geographical races of Teucrium lusitanicum using morphometric measures of vegetative and reproductive structures. T. lusitanicum is a gynodioecious species. Male sterile (female) individuals showed greater developmental instability at all sites. Plants located inland had higher developmental instability of vegetative characters and lower developmental instability of reproductive characters than coastal plants. These results support the contentions that (1) developmental instability is affected more by the disruption of co-adapted gene complexes than by lower heterozygosity, and (2) different habitat characteristics result in the differential response of vegetative and reproductive structures.
2016-01-01
Sagan et al. (1993) used the Galileo space probe data and first principles to find evidence of life on Earth. Here we ask whether Sagan et al. (1993) could also have detected whether life on Earth had three-dimensional structure, based on the Galileo space probe data. We reanalyse the data from this probe to see if structured vegetation could have been detected in regions with abundant photosynthetic pigments through the anisotropy of reflected shortwave radiation. We compare changing brightness of the Amazon forest (a region where Sagan et al. (1993) noted a red edge in the reflectance spectrum, indicative of photosynthesis) as the planet rotates to a common model of reflectance anisotropy and found measured increase of surface reflectance of 0.019 ± 0.003 versus a 0.007 predicted from only anisotropic effects. We hypothesize the difference was due to minor cloud contamination. However, the Galileo dataset had only a small change in phase angle (sun-satellite position) which reduced the observed anisotropy signal and we demonstrate that theoretically if the probe had a variable phase angle between 0–20°, there would have been a much larger predicted change in surface reflectance of 0.1 and under such a scenario three-dimensional vegetation structure on Earth could possibly have been detected. These results suggest that anisotropic effects may be useful to help determine whether exoplanets have three-dimensional vegetation structure in the future, but that further comparisons between empirical and theoretical results are first necessary. PMID:27973530
Doughty, Christopher E; Wolf, Adam
2016-01-01
Sagan et al. (1993) used the Galileo space probe data and first principles to find evidence of life on Earth. Here we ask whether Sagan et al. (1993) could also have detected whether life on Earth had three-dimensional structure, based on the Galileo space probe data. We reanalyse the data from this probe to see if structured vegetation could have been detected in regions with abundant photosynthetic pigments through the anisotropy of reflected shortwave radiation. We compare changing brightness of the Amazon forest (a region where Sagan et al. (1993) noted a red edge in the reflectance spectrum, indicative of photosynthesis) as the planet rotates to a common model of reflectance anisotropy and found measured increase of surface reflectance of 0.019 ± 0.003 versus a 0.007 predicted from only anisotropic effects. We hypothesize the difference was due to minor cloud contamination. However, the Galileo dataset had only a small change in phase angle (sun-satellite position) which reduced the observed anisotropy signal and we demonstrate that theoretically if the probe had a variable phase angle between 0-20°, there would have been a much larger predicted change in surface reflectance of 0.1 and under such a scenario three-dimensional vegetation structure on Earth could possibly have been detected. These results suggest that anisotropic effects may be useful to help determine whether exoplanets have three-dimensional vegetation structure in the future, but that further comparisons between empirical and theoretical results are first necessary.
Coherent structures in wind shear induced wave–turbulence–vegetation interaction in water bodies
Banerjee, Tirtha; Vercauteren, Nikki; Muste, Marian; ...
2017-08-26
Flume experiments with particle imaging velocimetry (PIV) were conducted recently to study a complex flow problem where wind shear acts on the surface of a static water body in presence of flexible emergent vegetation and induces a rich dynamics of wave–turbulence–vegetation interaction inside the water body without any gravitational gradient. The experiments were aimed at mimicking realistic vegetated wetlands and the present work is targeted to improve the understanding of the coherent structures associated with this interaction by employing a combination of techniques such as quadrant analysis, proper orthogonal decomposition (POD), Shannon entropy and mutual information content (MIC). The turbulentmore » transfer of momentum is found to be dominated by organized motions such as sweeps and ejections, while the wave component of vertical momentum transport does not show any such preference. Furthermore, by reducing the data using POD we see that wave energy for large flow depths and turbulent energy for all water depths is concentrated among the top few modes, which can allow development of simple reduced order models. Vegetation flexibility is found to induce several roll type structures, however if the vegetation density is increased, drag effects dominate over flexibility and organize the flow. The interaction between waves and turbulence is also found to be highest among flexible sparse vegetation. But, rapidly evolving parts of the flow such as the air–water interface reduces wave–turbulence interaction.« less
Code of Federal Regulations, 2010 CFR
2010-10-01
... preserve and protect all structures, equipment, and vegetation (such as trees, shrubs, and grass) on or... work required under this contract. The Contractor shall only remove trees when specifically authorized... trees are broken during contract performance, or by the careless operation of equipment, or by workmen...
Native herbivore exerts contrasting effects on fire regime and vegetation structure
Jose L. Hierro; Kenneth L. Clark; Lyn C. Branch; Diego Villarreal
2011-01-01
Although native herbivores can alter fire regimes by consuming herbaceous vegetation that serves as fine fuel and, less commonly, accumulating fuel as nest material and other structures, simultaneous considerations of contrasting effects of herbivores on fire have scarcely been addressed. We proposed that a colonial rodent, vizcacha (Lagostomus maximus...
Vegetation composition and structure in two hemlock stands threatened by the hemlock woolly adelgid
John J. Battles; Natalie Cleavitt; Timothy J. Fahey; Richard A. Evans
2000-01-01
We quantified the vegetation composition and structure of two hemlock (Tsuga canadensis) ravines in the Delaware Water Gap National Recreation Area threatened by the hemlock woolly adelgid (Adelges tsugae). Hemlock accounted for more than 50% of the canopy basal area (ravine mean = 52.3 m² ha-1) and...
Code of Federal Regulations, 2012 CFR
2012-10-01
... preserve and protect all structures, equipment, and vegetation (such as trees, shrubs, and grass) on or... work required under this contract. The Contractor shall only remove trees when specifically authorized... trees are broken during contract performance, or by the careless operation of equipment, or by workmen...
Code of Federal Regulations, 2014 CFR
2014-10-01
... preserve and protect all structures, equipment, and vegetation (such as trees, shrubs, and grass) on or... work required under this contract. The Contractor shall only remove trees when specifically authorized... trees are broken during contract performance, or by the careless operation of equipment, or by workmen...
Code of Federal Regulations, 2013 CFR
2013-10-01
... preserve and protect all structures, equipment, and vegetation (such as trees, shrubs, and grass) on or... work required under this contract. The Contractor shall only remove trees when specifically authorized... trees are broken during contract performance, or by the careless operation of equipment, or by workmen...