Interactive effects of nitrogen addition, warming and invasion across organizational levels in an old-field plant community.

PubMed

Gornish, Elise S

2014-10-08

Response to global change is dependent on the level of biological organization (e.g. the ecologically relevant spatial scale) in which species are embedded. For example, individual responses can affect population-level responses, which, in turn, can affect community-level responses. Although relationships are known to exist among responses to global change across levels of biological organization, formal investigations of these relationships are still uncommon. I conducted an exploratory analysis to identify how nitrogen addition and warming by open top chambers might affect plants across spatial scales by estimating treatment effect size at the leaf level, the plant level and the community level. Moreover, I investigated if the presence of Pityopsis aspera, an experimentally introduced plant species, modified the relationship between spatial scale and effect size across treatments. I found that, overall, the spatial scale significantly contributes to differences in effect size, supporting previous work which suggests that mechanisms driving biotic response to global change are scale dependent. Interestingly, the relationship between spatial scale and effect size in both the absence and presence of experimental invasion is very similar for nitrogen addition and warming treatments. The presence of invasion, however, did not affect the relationship between spatial scale and effect size, suggesting that in this system, invasion may not exacerbate or attenuate climate change effects. This exercise highlights the value of moving beyond integration and scaling to the practice of directly testing for scale effects within single experiments. Published by Oxford University Press on behalf of the Annals of Botany Company.

Downscaling near-surface soil moisture from field to plot scale: A comparative analysis under different environmental conditions

NASA Astrophysics Data System (ADS)

Nasta, Paolo; Penna, Daniele; Brocca, Luca; Zuecco, Giulia; Romano, Nunzio

2018-02-01

Indirect measurements of field-scale (hectometer grid-size) spatial-average near-surface soil moisture are becoming increasingly available by exploiting new-generation ground-based and satellite sensors. Nonetheless, modeling applications for water resources management require knowledge of plot-scale (1-5 m grid-size) soil moisture by using measurements through spatially-distributed sensor network systems. Since efforts to fulfill such requirements are not always possible due to time and budget constraints, alternative approaches are desirable. In this study, we explore the feasibility of determining spatial-average soil moisture and soil moisture patterns given the knowledge of long-term records of climate forcing data and topographic attributes. A downscaling approach is proposed that couples two different models: the Eco-Hydrological Bucket and Equilibrium Moisture from Topography. This approach helps identify the relative importance of two compound topographic indexes in explaining the spatial variation of soil moisture patterns, indicating valley- and hillslope-dependence controlled by lateral flow and radiative processes, respectively. The integrated model also detects temporal instability if the dominant type of topographic dependence changes with spatial-average soil moisture. Model application was carried out at three sites in different parts of Italy, each characterized by different environmental conditions. Prior calibration was performed by using sparse and sporadic soil moisture values measured by portable time domain reflectometry devices. Cross-site comparisons offer different interpretations in the explained spatial variation of soil moisture patterns, with time-invariant valley-dependence (site in northern Italy) and hillslope-dependence (site in southern Italy). The sources of soil moisture spatial variation at the site in central Italy are time-variant within the year and the seasonal change of topographic dependence can be conveniently correlated to a climate indicator such as the aridity index.

Similar Processes but Different Environmental Filters for Soil Bacterial and Fungal Community Composition Turnover on a Broad Spatial Scale

PubMed Central

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P. A.; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

PubMed

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

[Spatial scale effect of land use landscape pattern in Yongdeng County, Gansu Province, China.

PubMed

Liu, Yuan Yuan; Liu, Xue Lu

2016-04-22

Based on "patch-corridor-matrix" pattern, spatial scale effect of landscape pattern was studied in Yongdeng County of Lanzhou City, Gansu Province, China. The results showed that the grassland was the matrix of landscape structure in the studied area, road and river played the corridor role, and the other landscape elements (cultivated land, forest land, garden land, residential land, industrial and mineral land, public management and service land, and the other land) acted as patches. The patch level index and the landscape level index all showed obvious dependence on spatial extent. The scale effect of patch index of different landscape elements existed differently in different extent intervals, so did the scale effect of the landscape level index. Within the extent of 1-20 km, the scale effect showed the most obvious difference between the element types and the index types, while it became smaller in 21-90 km, and disappeared beyond 90 km. 90 km×90 km might be the effective extent to study the dependence of spatial extent of landscape structure.

HIS Design: Big Data that Supports Hydrologic Modeling from Continental to Hillslope Scales

NASA Astrophysics Data System (ADS)

Rasmussen, T. C.; Deemy, J. B.; Younger, S. E.; Kirk, S. E.; Brockman, L. E.

2016-12-01

Analogous to Google Maps, hydrologic data, information, and knowledge resolve differently depending upon the spatial and temporal scales of interest. We show how a multi-scale hydrologic information system (HIS) can be designed and populated for a broad range of spatial (e.g., hillslope, local, regional, continental) and temporal (e.g., current, recent, historic, geologic) scales. Surface and subsurface hydrologic and transport processes are assumed to be scale-dependent, requiring unique governing equations and parameters at each scale. This robust and flexible framework is designed to meet the inventory, monitoring, and management needs of multiple federal agencies (i.e., Forest Service, National Park Service, Fish and Wildlife Service, National Wildlife Reserves). Multi-scale HIS examples are provided using Geographic Information Systems (GIS) for the Southeastern US.

The compositional similarity of urban forests among the world's cities is scale dependent

Treesearch

Jun Yang; Frank A. La Sorte; Petr Pysek; Pengbo Yan; David Nowak; Joe McBride

2015-01-01

Aim We examined species composition of urban forests from local to global scales using occurrence and abundance information to determine how compositional similarity is defined across spatial scales. We predicted that urban forests have become more homogeneous world-wide, which should result in minimal scale dependence that is more pronounced for non-native species,...

Scale dependence of the diversity-stability relationship in a temperate grassland.

PubMed

Zhang, Yunhai; He, Nianpeng; Loreau, Michel; Pan, Qingmin; Han, Xingguo

2018-05-01

A positive relationship between biodiversity and ecosystem stability has been reported in many ecosystems; however, it has yet to be determined whether and how spatial scale affects this relationship. Here, for the first time, we assessed the effects of alpha, beta and gamma diversity on ecosystem stability and the scale dependence of the slope of the diversity-stability relationship.By employing a long-term (33 years) dataset from a temperate grassland, northern China, we calculated the all possible spatial scales with the complete combination from the basic 1-m 2 plots.Species richness was positively associated with ecosystem stability through species asynchrony and overyielding at all spatial scales (1, 2, 3, 4 and 5 m 2 ). Both alpha and beta diversity were positively associated with gamma stability.Moreover, the slope of the diversity-area relationship was significantly higher than that of the stability-area relationship, resulting in a decline of the slope of the diversity-stability relationship with increasing area. Synthesis. With the positive species diversity effect on ecosystem stability from small to large spatial scales, our findings demonstrate the need to maintain a high biodiversity and biotic heterogeneity as insurance against the risks incurred by ecosystems in the face of global environmental changes.

Elevational Gradients in β-Diversity Reflect Variation in the Strength of Local Community Assembly Mechanisms across Spatial Scales

PubMed Central

Tello, J. Sebastián; Myers, Jonathan A.; Macía, Manuel J.; Fuentes, Alfredo F.; Cayola, Leslie; Arellano, Gabriel; Loza, M. Isabel; Torrez, Vania; Cornejo, Maritza; Miranda, Tatiana B.; Jørgensen, Peter M.

2015-01-01

Despite long-standing interest in elevational-diversity gradients, little is known about the processes that cause changes in the compositional variation of communities (β-diversity) across elevations. Recent studies have suggested that β-diversity gradients are driven by variation in species pools, rather than by variation in the strength of local community assembly mechanisms such as dispersal limitation, environmental filtering, or local biotic interactions. However, tests of this hypothesis have been limited to very small spatial scales that limit inferences about how the relative importance of assembly mechanisms may change across spatial scales. Here, we test the hypothesis that scale-dependent community assembly mechanisms shape biogeographic β-diversity gradients using one of the most well-characterized elevational gradients of tropical plant diversity. Using an extensive dataset on woody plant distributions along a 4,000-m elevational gradient in the Bolivian Andes, we compared observed patterns of β-diversity to null-model expectations. β-deviations (standardized differences from null values) were used to measure the relative effects of local community assembly mechanisms after removing sampling effects caused by variation in species pools. To test for scale-dependency, we compared elevational gradients at two contrasting spatial scales that differed in the size of local assemblages and regions by at least an order of magnitude. Elevational gradients in β-diversity persisted after accounting for regional variation in species pools. Moreover, the elevational gradient in β-deviations changed with spatial scale. At small scales, local assembly mechanisms were detectable, but variation in species pools accounted for most of the elevational gradient in β-diversity. At large spatial scales, in contrast, local assembly mechanisms were a dominant force driving changes in β-diversity. In contrast to the hypothesis that variation in species pools alone drives β-diversity gradients, we show that local community assembly mechanisms contribute strongly to systematic changes in β-diversity across elevations. We conclude that scale-dependent variation in community assembly mechanisms underlies these iconic gradients in global biodiversity. PMID:25803846

The scale of landscape fragmentation affects herbivore response to vegetation heterogeneity.

PubMed

Banks, John E

1998-11-01

Using alternating bands of weeds and broccoli I experimentally manipulated vegetation composition and the spatial scale at which the landscape was fragmented in a factorial design. This experimental approach allowed me to distinguish the effect of spatial scale from that of simple crop heterogeneity on crop herbivores. The importance of scale depended on which insect species were examined. Cabbage aphids (Brevicoryne brassicae) were influenced by vegetation composition at all tested scales of fragmentation; cabbage butterflies (Pieris rapae) were not affected by scale or by composition and flea beetles (Phyllotreta cruciferae) revealed a striking dependence on scale of fragmentation as well as an interaction between scale and composition. This approach shows the importance of dissecting out the effects of scale from other aspects of landscape manipulation, and emphasizes the challenge of developing a theory that will enable prediction of species-specific responses to scale.

Scale dependence in habitat selection: The case of the endangered brown bear (Ursus arctos) in the Cantabrian Range (NW Spain)

Treesearch

Maria C. Mateo Sanchez; Samuel A. Cushman; Santiago Saura

2013-01-01

Animals select habitat resources at multiple spatial scales. Thus, explicit attention to scale dependency in species-habitat relationships is critical to understand the habitat suitability patterns as perceived by organisms in complex landscapes. Identification of the scales at which particular environmental variables influence habitat selection may be as important as...

Asynchrony in the inter-annual recruitment of lake whitefish Coregonus clupeaformis in the Great Lakes region

USGS Publications Warehouse

Zischke, Mitchell T.; Bunnell, David B.; Troy, Cary D.; Berglund, Eric K.; Caroffino, David C.; Ebener, Mark P.; He, Ji X.; Sitar, Shawn P.; Hook, Tomas O.

2017-01-01

Spatially separated fish populations may display synchrony in annual recruitment if the factors that drive recruitment success, particularly abiotic factors such as temperature, are synchronised across broad spatial scales. We examined inter-annual variation in recruitment among lake whitefish (Coregonus clupeaformis) populations in lakes Huron, Michigan and Superior using fishery-dependent and -independent data from 1971 to 2014. Relative year-class strength (RYCS) was calculated from catch-curve residuals for each year class across multiple sampling years. Pairwise comparison of RYCS among datasets revealed no significant associations either within or between lakes, suggesting that recruitment of lake whitefish is spatially asynchronous. There was no consistent correlation between pairwise agreement and the distance between datasets, and models to estimate the spatial scale of recruitment synchrony did not fit well to these data. This suggests that inter-annual recruitment variation of lake whitefish is asynchronous across broad spatial scales in the Great Lakes. While our method primarily evaluated year-to-year recruitment variation, it is plausible that recruitment of lake whitefish varies at coarser temporal scales (e.g. decadal). Nonetheless, our findings differ from research on some other Coregonus species and suggest that local biotic or density-dependent factors may contribute strongly to lake whitefish recruitment rather than inter-annual variability in broad-scale abiotic factors.

The effects of habitat connectivity and regional heterogeneity on artificial pond metacommunities.

PubMed

Pedruski, Michael T; Arnott, Shelley E

2011-05-01

Habitat connectivity and regional heterogeneity represent two factors likely to affect biodiversity across different spatial scales. We performed a 3 × 2 factorial design experiment to investigate the effects of connectivity, heterogeneity, and their interaction on artificial pond communities of freshwater invertebrates at the local (α), among-community (β), and regional (γ) scales. Despite expectations that the effects of connectivity would depend on levels of regional heterogeneity, no significant interactions were found for any diversity index investigated at any spatial scale. While observed responses of biodiversity to connectivity and heterogeneity depended to some extent on the diversity index and spatial partitioning formula used, the general pattern shows that these factors largely act at the β scale, as opposed to the α or γ scales. We conclude that the major role of connectivity in aquatic invertebrate communities is to act as a homogenizing force with relatively little effect on diversity at the α or γ levels. Conversely, heterogeneity acts as a force maintaining differences between communities.

Cross-scale feedbacks and scale mismatches as influences on cultural services and the resilience of protected areas.

PubMed

Maciejewski, Kristine; De Vos, Alta; Cumming, Graeme S; Moore, Christine; Biggs, Duan

2015-01-01

Protected areas are a central strategy for achieving global conservation goals, but their continued existence depends heavily on maintaining sufficient social and political support to outweigh economic interests or other motives for land conversion. Thus, the resilience of protected areas can be considered a function of their perceived benefits to society. Nature-based tourism (NBT), a cultural ecosystem service, provides a key source of income to protected areas, facilitating a sustainable solution to conservation. The ability of tourism to generate income depends, however, on both the scales at which this cultural service is provided and the scales at which tourists respond to services on offer. This observation raises a set of location-, context-, and scale-related questions that need to be confronted before we can understand and value cultural service provision appropriately. We combine elements of resilience analysis with a systems ecology framework and apply this to NBT in protected areas to investigate cross-scale interactions and scale mismatches. We postulate that cross-scale effects can either have a positive effect on protected area resilience or lead to scale mismatches, depending on their interactions with cross-scale feedbacks. To demonstrate this, we compare spatial scales and nested levels of institutions to develop a typology of scale mismatches for common scenarios in NBT. In our new typology, the severity of a scale mismatch is expressed as the ratio of spatial scale to institutional level, producing 25 possible outcomes with differing consequences for system resilience. We predict that greater differences between interacting scales and levels, and greater magnitudes of cross-scale interactions, will lead to greater magnitudes of scale mismatch. Achieving a better understanding of feedbacks and mismatches, and finding ways of aligning spatial and institutional scales, will be critical for strengthening the resilience of protected areas that depend on NBT.

An Investigation on the Spatial Variability of Manning Roughness Coefficients in Continental-scale River Routing Simulations

NASA Astrophysics Data System (ADS)

Luo, X.; Hong, Y.; Lei, X.; Leung, L. R.; Li, H. Y.; Getirana, A.

2017-12-01

As one essential component of the Earth system modeling, the continental-scale river routing computation plays an important role in applications of Earth system models, such as evaluating the impacts of the global change on water resources and flood hazards. The streamflow timing, which depends on the modeled flow velocities, can be an important aspect of the model results. River flow velocities have been estimated by using the Manning's equation where the Manning roughness coefficient is a key and sensitive parameter. In some early continental-scale studies, the Manning coefficient was determined with simplified methods, such as using a constant value for the entire basin. However, large spatial variability is expected in the Manning coefficients for the numerous channels composing the river network in distributed continental-scale hydrologic modeling. In the application of a continental-scale river routing model in the Amazon Basin, we use spatially varying Manning coefficients dependent on channel sizes and attempt to represent the dominant spatial variability of Manning coefficients. Based on the comparisons of simulation results with in situ streamflow records and remotely sensed river stages, we investigate the comparatively optimal Manning coefficients and explicitly demonstrate the advantages of using spatially varying Manning coefficients. The understanding obtained in this study could be helpful in the modeling of surface hydrology at regional to continental scales.

Frequency-dependent scaling from mesoscale to macroscale in viscoelastic random composites

PubMed Central

Zhang, Jun

2016-01-01

This paper investigates the scaling from a statistical volume element (SVE; i.e. mesoscale level) to representative volume element (RVE; i.e. macroscale level) of spatially random linear viscoelastic materials, focusing on the quasi-static properties in the frequency domain. Requiring the material statistics to be spatially homogeneous and ergodic, the mesoscale bounds on the RVE response are developed from the Hill–Mandel homogenization condition adapted to viscoelastic materials. The bounds are obtained from two stochastic initial-boundary value problems set up, respectively, under uniform kinematic and traction boundary conditions. The frequency and scale dependencies of mesoscale bounds are obtained through computational mechanics for composites with planar random chessboard microstructures. In general, the frequency-dependent scaling to RVE can be described through a complex-valued scaling function, which generalizes the concept originally developed for linear elastic random composites. This scaling function is shown to apply for all different phase combinations on random chessboards and, essentially, is only a function of the microstructure and mesoscale. PMID:27274689

Agent-based modeling of malaria vectors: the importance of spatial simulation.

PubMed

Bomblies, Arne

2014-07-03

The modeling of malaria vector mosquito populations yields great insight into drivers of malaria transmission at the village scale. Simulation of individual mosquitoes as "agents" in a distributed, dynamic model domain may be greatly beneficial for simulation of spatial relationships of vectors and hosts. In this study, an agent-based model is used to simulate the life cycle and movement of individual malaria vector mosquitoes in a Niger Sahel village, with individual simulated mosquitoes interacting with their physical environment as well as humans. Various processes that are known to be epidemiologically important, such as the dependence of parity on flight distance between developmental habitat and blood meal hosts and therefore spatial relationships of pools and houses, are readily simulated using this modeling paradigm. Impacts of perturbations can be evaluated on the basis of vectorial capacity, because the interactions between individuals that make up the population- scale metric vectorial capacity can be easily tracked for simulated mosquitoes and human blood meal hosts, without the need to estimate vectorial capacity parameters. As expected, model results show pronounced impacts of pool source reduction from larvicide application and draining, but with varying degrees of impact depending on the spatial relationship between pools and human habitation. Results highlight the importance of spatially-explicit simulation that can model individuals such as in an agent-based model. The impacts of perturbations on village scale malaria transmission depend on spatial locations of individual mosquitoes, as well as the tracking of relevant life cycle events and characteristics of individual mosquitoes. This study demonstrates advantages of using an agent-based approach for village-scale mosquito simulation to address questions in which spatial relationships are known to be important.

Scale-dependent effects of land cover on water physico-chemistry and diatom-based metrics in a major river system, the Adour-Garonne basin (South Western France).

PubMed

Tudesque, Loïc; Tisseuil, Clément; Lek, Sovan

2014-01-01

The scale dependence of ecological phenomena remains a central issue in ecology. Particularly in aquatic ecology, the consideration of the accurate spatial scale in assessing the effects of landscape factors on stream condition is critical. In this context, our study aimed at assessing the relationships between multi-spatial scale land cover patterns and a variety of water quality and diatom metrics measured at the stream reach level. This investigation was conducted in a major European river system, the Adour-Garonne river basin, characterized by a wide range of ecological conditions. Redundancy analysis (RDA) and variance partitioning techniques were used to disentangle the different relationships between land cover, water-chemistry and diatom metrics. Our results revealed a top-down "cascade effect" indirectly linking diatom metrics to land cover patterns through water physico-chemistry, which occurred at the largest spatial scales. In general, the strength of the relationships between land cover, physico-chemistry, and diatoms was shown to increase with the spatial scale, from the local to the basin scale, emphasizing the importance of continuous processes of accumulation throughout the river gradient. Unexpectedly, we established that the influence of land cover on the diatom metric was of primary importance both at the basin and local scale, as a result of discontinuous but not necessarily antagonist processes. The most detailed spatial grain of the Corine land cover classification appeared as the most relevant spatial grain to relate land cover to water chemistry and diatoms. Our findings provide suitable information to improve the implementation of effective diatom-based monitoring programs, especially within the scope of the European Water Framework Directive. © 2013 Elsevier B.V. All rights reserved.

Spatial Structure of Seagrass Suggests That Size-Dependent Plant Traits Have a Strong Influence on the Distribution and Maintenance of Tropical Multispecies Meadows

PubMed Central

Ooi, Jillian L. S.; Van Niel, Kimberly P.; Kendrick, Gary A.; Holmes, Karen W.

2014-01-01

Background Seagrass species in the tropics occur in multispecies meadows. How these meadows are maintained through species co-existence and what their ecological drivers may be has been an overarching question in seagrass biogeography. In this study, we quantify the spatial structure of four co-existing species and infer potential ecological processes from these structures. Methods and Results Species presence/absence data were collected using underwater towed and dropped video cameras in Pulau Tinggi, Malaysia. The geostatistical method, utilizing semivariograms, was used to describe the spatial structure of Halophila spp, Halodule uninervis, Syringodium isoetifolium and Cymodocea serrulata. Species had spatial patterns that were oriented in the along-shore and across-shore directions, nested with larger species in meadow interiors, and consisted of multiple structures that indicate the influence of 2–3 underlying processes. The Linear Model of Coregionalization (LMC) was used to estimate the amount of variance contributing to the presence of a species at specific spatial scales. These distances were <2.5 m (micro-scale), 2.5–50 m (fine-scale) and >50 m (broad-scale) in the along-shore; and <2.5 m (micro-scale), 2.5–140 m (fine-scale) and >140 m (broad-scale) in the across-shore. The LMC suggests that smaller species (Halophila spp and H. uninervis) were most influenced by broad-scale processes such as hydrodynamics and water depth whereas large, localised species (S. isoetifolium and C. serrulata) were more influenced by finer-scale processes such as sediment burial, seagrass colonization and growth, and physical disturbance. Conclusion In this study, we provide evidence that spatial structure is distinct even when species occur in well-mixed multispecies meadows, and we suggest that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical marine plant communities. This study offers a contrast from previous spatial models of seagrasses which have largely focused on monospecific temperate meadows. PMID:24497978

Spatial structure of seagrass suggests that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical multispecies meadows.

PubMed

Ooi, Jillian L S; Van Niel, Kimberly P; Kendrick, Gary A; Holmes, Karen W

2014-01-01

Seagrass species in the tropics occur in multispecies meadows. How these meadows are maintained through species co-existence and what their ecological drivers may be has been an overarching question in seagrass biogeography. In this study, we quantify the spatial structure of four co-existing species and infer potential ecological processes from these structures. Species presence/absence data were collected using underwater towed and dropped video cameras in Pulau Tinggi, Malaysia. The geostatistical method, utilizing semivariograms, was used to describe the spatial structure of Halophila spp, Halodule uninervis, Syringodium isoetifolium and Cymodocea serrulata. Species had spatial patterns that were oriented in the along-shore and across-shore directions, nested with larger species in meadow interiors, and consisted of multiple structures that indicate the influence of 2-3 underlying processes. The Linear Model of Coregionalization (LMC) was used to estimate the amount of variance contributing to the presence of a species at specific spatial scales. These distances were <2.5 m (micro-scale), 2.5-50 m (fine-scale) and >50 m (broad-scale) in the along-shore; and <2.5 m (micro-scale), 2.5-140 m (fine-scale) and >140 m (broad-scale) in the across-shore. The LMC suggests that smaller species (Halophila spp and H. uninervis) were most influenced by broad-scale processes such as hydrodynamics and water depth whereas large, localised species (S. isoetifolium and C. serrulata) were more influenced by finer-scale processes such as sediment burial, seagrass colonization and growth, and physical disturbance. In this study, we provide evidence that spatial structure is distinct even when species occur in well-mixed multispecies meadows, and we suggest that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical marine plant communities. This study offers a contrast from previous spatial models of seagrasses which have largely focused on monospecific temperate meadows.

Optimal configurations of spatial scale for grid cell firing under noise and uncertainty

PubMed Central

Towse, Benjamin W.; Barry, Caswell; Bush, Daniel; Burgess, Neil

2014-01-01

We examined the accuracy with which the location of an agent moving within an environment could be decoded from the simulated firing of systems of grid cells. Grid cells were modelled with Poisson spiking dynamics and organized into multiple ‘modules’ of cells, with firing patterns of similar spatial scale within modules and a wide range of spatial scales across modules. The number of grid cells per module, the spatial scaling factor between modules and the size of the environment were varied. Errors in decoded location can take two forms: small errors of precision and larger errors resulting from ambiguity in decoding periodic firing patterns. With enough cells per module (e.g. eight modules of 100 cells each) grid systems are highly robust to ambiguity errors, even over ranges much larger than the largest grid scale (e.g. over a 500 m range when the maximum grid scale is 264 cm). Results did not depend strongly on the precise organization of scales across modules (geometric, co-prime or random). However, independent spatial noise across modules, which would occur if modules receive independent spatial inputs and might increase with spatial uncertainty, dramatically degrades the performance of the grid system. This effect of spatial uncertainty can be mitigated by uniform expansion of grid scales. Thus, in the realistic regimes simulated here, the optimal overall scale for a grid system represents a trade-off between minimizing spatial uncertainty (requiring large scales) and maximizing precision (requiring small scales). Within this view, the temporary expansion of grid scales observed in novel environments may be an optimal response to increased spatial uncertainty induced by the unfamiliarity of the available spatial cues. PMID:24366144

When Local Extinction and Colonization of River Fishes Can Be Predicted by Regional Occupancy: the Role of Spatial Scales

PubMed Central

Bergerot, Benjamin; Hugueny, Bernard; Belliard, Jérôme

2013-01-01

Background Predicting which species are likely to go extinct is perhaps one of the most fundamental yet challenging tasks for conservation biologists. This is particularly relevant for freshwater ecosystems which tend to have the highest proportion of species threatened with extinction. According to metapopulation theories, local extinction and colonization rates of freshwater subpopulations can depend on the degree of regional occupancy, notably due to rescue effects. However, relationships between extinction, colonization, regional occupancy and the spatial scales at which they operate are currently poorly known. Methods And Findings: We used a large dataset of freshwater fish annual censuses in 325 stream reaches to analyse how annual extinction/colonization rates of subpopulations depend on the regional occupancy of species. For this purpose, we modelled the regional occupancy of 34 fish species over the whole French river network and we tested how extinction/colonization rates could be predicted by regional occupancy described at five nested spatial scales. Results show that extinction and colonization rates depend on regional occupancy, revealing existence a rescue effect. We also find that these effects are scale dependent and their absolute contribution to colonization and extinction tends to decrease from river section to larger basin scales. Conclusions In terms of management, we show that regional occupancy quantification allows the evaluation of local species extinction/colonization dynamics and reduction of local extinction risks for freshwater fish species implies the preservation of suitable habitats at both local and drainage basin scales. PMID:24367636

When local extinction and colonization of river fishes can be predicted by regional occupancy: the role of spatial scales.

PubMed

Bergerot, Benjamin; Hugueny, Bernard; Belliard, Jérôme

2013-01-01

Predicting which species are likely to go extinct is perhaps one of the most fundamental yet challenging tasks for conservation biologists. This is particularly relevant for freshwater ecosystems which tend to have the highest proportion of species threatened with extinction. According to metapopulation theories, local extinction and colonization rates of freshwater subpopulations can depend on the degree of regional occupancy, notably due to rescue effects. However, relationships between extinction, colonization, regional occupancy and the spatial scales at which they operate are currently poorly known. And Findings: We used a large dataset of freshwater fish annual censuses in 325 stream reaches to analyse how annual extinction/colonization rates of subpopulations depend on the regional occupancy of species. For this purpose, we modelled the regional occupancy of 34 fish species over the whole French river network and we tested how extinction/colonization rates could be predicted by regional occupancy described at five nested spatial scales. Results show that extinction and colonization rates depend on regional occupancy, revealing existence a rescue effect. We also find that these effects are scale dependent and their absolute contribution to colonization and extinction tends to decrease from river section to larger basin scales. In terms of management, we show that regional occupancy quantification allows the evaluation of local species extinction/colonization dynamics and reduction of local extinction risks for freshwater fish species implies the preservation of suitable habitats at both local and drainage basin scales.

Effects of spatial scale on the perception and assessment of risk of natural disturbance in forested ecosystems: examples from northeastern Oregon

Treesearch

R. James Barbour; Miles Hemstrom; Alan Ager; Jane L. Hayes

2005-01-01

The perception and measurement of the risk of natural disturbances often varies depending on the spatial and temporal scales over which information is collected or analyzed. This can lead to conflicting conclusions about severity of current or past disturbances or the risk of future ones. Failure to look across scales also complicates local implementation of policies...

Scale dependence of the diversity–stability relationship in a temperate grassland

PubMed Central

Zhang, Yunhai; He, Nianpeng; Loreau, Michel; Pan, Qingmin; Han, Xingguo

2018-01-01

A positive relationship between biodiversity and ecosystem stability has been reported in many ecosystems; however, it has yet to be determined whether and how spatial scale affects this relationship. Here, for the first time, we assessed the effects of alpha, beta and gamma diversity on ecosystem stability and the scale dependence of the slope of the diversity–stability relationship.By employing a long-term (33 years) dataset from a temperate grassland, northern China, we calculated the all possible spatial scales with the complete combination from the basic 1-m2 plots.Species richness was positively associated with ecosystem stability through species asynchrony and overyielding at all spatial scales (1, 2, 3, 4 and 5 m2). Both alpha and beta diversity were positively associated with gamma stability.Moreover, the slope of the diversity–area relationship was significantly higher than that of the stability–area relationship, resulting in a decline of the slope of the diversity–stability relationship with increasing area.Synthesis. With the positive species diversity effect on ecosystem stability from small to large spatial scales, our findings demonstrate the need to maintain a high biodiversity and biotic heterogeneity as insurance against the risks incurred by ecosystems in the face of global environmental changes. PMID:29725139

Speciation has a spatial scale that depends on levels of gene flow.

PubMed

Kisel, Yael; Barraclough, Timothy G

2010-03-01

Area is generally assumed to affect speciation rates, but work on the spatial context of speciation has focused mostly on patterns of range overlap between emerging species rather than on questions of geographical scale. A variety of geographical theories of speciation predict that the probability of speciation occurring within a given region should (1) increase with the size of the region and (2) increase as the spatial extent of intraspecific gene flow becomes smaller. Using a survey of speciation events on isolated oceanic islands for a broad range of taxa, we find evidence for both predictions. The probability of in situ speciation scales with island area in bats, carnivorous mammals, birds, flowering plants, lizards, butterflies and moths, and snails. Ferns are an exception to these findings, but they exhibit high frequencies of polyploid and hybrid speciation, which are expected to be scale independent. Furthermore, the minimum island size for speciation correlates across groups with the strength of intraspecific gene flow, as is estimated from a meta-analysis of published population genetic studies. These results indicate a general geographical model of speciation rates that are dependent on both area and gene flow. The spatial scale of population divergence is an important but neglected determinant of broad-scale diversity patterns.

Meta-ecosystem dynamics and functioning on finite spatial networks

PubMed Central

Marleau, Justin N.; Guichard, Frédéric; Loreau, Michel

2014-01-01

The addition of spatial structure to ecological concepts and theories has spurred integration between sub-disciplines within ecology, including community and ecosystem ecology. However, the complexity of spatial models limits their implementation to idealized, regular landscapes. We present a model meta-ecosystem with finite and irregular spatial structure consisting of local nutrient–autotrophs–herbivores ecosystems connected through spatial flows of materials and organisms. We study the effect of spatial flows on stability and ecosystem functions, and provide simple metrics of connectivity that can predict these effects. Our results show that high rates of nutrient and herbivore movement can destabilize local ecosystem dynamics, leading to spatially heterogeneous equilibria or oscillations across the meta-ecosystem, with generally increased meta-ecosystem primary and secondary production. However, the onset and the spatial scale of these emergent dynamics depend heavily on the spatial structure of the meta-ecosystem and on the relative movement rate of the autotrophs. We show how this strong dependence on finite spatial structure eludes commonly used metrics of connectivity, but can be predicted by the eigenvalues and eigenvectors of the connectivity matrix that describe the spatial structure and scale. Our study indicates the need to consider finite-size ecosystems in meta-ecosystem theory. PMID:24403323

Quantifying drivers of wild pig movement across multiple spatial and temporal scales

USGS Publications Warehouse

Kay, Shannon L.; Fischer, Justin W.; Monaghan, Andrew J.; Beasley, James C; Boughton, Raoul; Campbell, Tyler A; Cooper, Susan M; Ditchkoff, Stephen S.; Hartley, Stephen B.; Kilgo, John C; Wisely, Samantha M; Wyckoff, A Christy; Vercauteren, Kurt C.; Pipen, Kim M

2017-01-01

The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau.

PubMed

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-08-24

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau

NASA Astrophysics Data System (ADS)

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-08-01

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau

PubMed Central

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-01-01

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302–480 km, while the annual precipitation showed smaller scales of 111–182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions. PMID:27553388

Simulating spatial and temporally related fire weather

Treesearch

Isaac C. Grenfell; Mark Finney; Matt Jolly

2010-01-01

Use of fire behavior models has assumed an increasingly important role for managers of wildfire incidents to make strategic decisions. For fire risk assessments and danger rating at very large spatial scales, these models depend on fire weather variables or fire danger indices. Here, we describe a method to simulate fire weather at a national scale that captures the...

Scale-dependent variation in forest structures in naturally dynamic boreal forest landscapes

NASA Astrophysics Data System (ADS)

Kulha, Niko; Pasanen, Leena; De Grandpré, Louis; Kuuluvainen, Timo; Aakala, Tuomas

2017-04-01

Natural forest structures vary at multiple spatial scales. This variation reflects the occurrence of driving factors, such as disturbances and variation in soil or topography. To explore and understand the linkages of forest structural characteristics and factors driving their variation, we need to recognize how the structural characteristics vary in relation to spatial scale. This can be achieved by identifying scale-dependent features in forest structure within unmanaged forest landscapes. By identifying these features and examining their relationship with potential driving factors, we can better understand the dynamics of forest structural development. Here, we examine the spatial variation in forest structures at multiple spatial scales, utilizing data from old-growth boreal forests in two regions with contrasting disturbance regimes: northern Finland and north-eastern Québec, Canada ( 67° 45'N, 29° 36'E, 49° 39'N, 67° 55'W, respectively). The three landscapes (4 km2 each) in Finland are dominated by Pinus sylvestris and Picea abies, whereas the two landscapes in Québec are dominated by Abies balsamea and Picea mariana. Québec's forests are a subject to cyclic outbreaks of the eastern spruce budworm, causing extensive mortality especially in A. balsamea-dominated stands. In the Finnish landscapes, gap- to patch-scale disturbances due to tree senescence, fungi and wind, as well as infrequent surface fires in areas dominated by P. sylvestris, prevail. Owing to the differences in the species compositions and the disturbance regimes, we expect differing scales of variation between the landscapes. To quantify patterns of variation, we visually interpret stereopairs of recent aerial photographs. From the photographs, we collect information on forest canopy coverage, species composition and dead wood. For the interpretation, each 4 km2 plot is divided into 0.1ha square cells (4096 per plot). Interpretations are validated against field observations and compiled to raster maps. We analyze the raster maps with Bayesian scale space approach (iBSiZer), which aims in capturing credible variations at different spatial scales. As a result, we can detect structural entities (e.g. patches with higher canopy cover), which deviate credibly from their surroundings. The detected entities can further be linked to specific drivers. Our results show that the role of a particular driving factor varies in relation to spatial scale. For example, in the Finnish landscapes, topoedaphic factors exerted a stronger control on broad-scale forest structural characteristics, whereas recent disturbances (quantified as the amount of dead wood) appeared to play an important role in explaining the smaller scale variation of forest structures. Here, we showcase the methodology used in the detection of scale-dependent forest structural entities and present the results of our analysis of the spatial scales of variation in the natural boreal forest structures.

Economic analysis of fuel treatments

Treesearch

D. Evan Mercer; Jeffrey P. Prestemon

2012-01-01

The economics of wildfire is complicated because wildfire behavior depends on the spatial and temporal scale at which management decisions made, and because of uncertainties surrounding the results of management actions. Like the wildfire processes they seek to manage, interventions through fire prevention programs, suppression, and fuels management are scale dependent...

Multi-scale habitat selection modeling: A review and outlook

Treesearch

Kevin McGarigal; Ho Yi Wan; Kathy A. Zeller; Brad C. Timm; Samuel A. Cushman

2016-01-01

Scale is the lens that focuses ecological relationships. Organisms select habitat at multiple hierarchical levels and at different spatial and/or temporal scales within each level. Failure to properly address scale dependence can result in incorrect inferences in multi-scale habitat selection modeling studies.

Phase-dependent outbreak dynamics of geometrid moth linked to host plant phenology.

PubMed

Jepsen, Jane U; Hagen, Snorre B; Karlsen, Stein-Rune; Ims, Rolf A

2009-12-07

Climatically driven Moran effects have often been invoked as the most likely cause of regionally synchronized outbreaks of insect herbivores without identifying the exact mechanism. However, the degree of match between host plant and larval phenology is crucial for the growth and survival of many spring-feeding pest insects, suggesting that a phenological match/mismatch-driven Moran effect may act as a synchronizing agent. We analyse the phase-dependent spatial dynamics of defoliation caused by cyclically outbreaking geometrid moths in northern boreal birch forest in Fennoscandia through the most recent massive outbreak (2000-2008). We use satellite-derived time series of the prevalence of moth defoliation and the onset of the growing season for the entire region to investigate the link between the patterns of defoliation and outbreak spread. In addition, we examine whether a phase-dependent coherence in the pattern of spatial synchrony exists between defoliation and onset of the growing season, in order to evaluate if the degree of matching phenology between the moth and their host plant could be the mechanism behind a Moran effect. The strength of regional spatial synchrony in defoliation and the pattern of defoliation spread were both highly phase-dependent. The incipient phase of the outbreak was characterized by high regional synchrony in defoliation and long spread distances, compared with the epidemic and crash phase. Defoliation spread was best described using a two-scale stratified spread model, suggesting that defoliation spread is governed by two processes operating at different spatial scale. The pattern of phase-dependent spatial synchrony was coherent in both defoliation and onset of the growing season. This suggests that the timing of spring phenology plays a role in the large-scale synchronization of birch forest moth outbreaks.

Phase-dependent outbreak dynamics of geometrid moth linked to host plant phenology

PubMed Central

Jepsen, Jane U.; Hagen, Snorre B.; Karlsen, Stein-Rune; Ims, Rolf A.

2009-01-01

Climatically driven Moran effects have often been invoked as the most likely cause of regionally synchronized outbreaks of insect herbivores without identifying the exact mechanism. However, the degree of match between host plant and larval phenology is crucial for the growth and survival of many spring-feeding pest insects, suggesting that a phenological match/mismatch-driven Moran effect may act as a synchronizing agent. We analyse the phase-dependent spatial dynamics of defoliation caused by cyclically outbreaking geometrid moths in northern boreal birch forest in Fennoscandia through the most recent massive outbreak (2000–2008). We use satellite-derived time series of the prevalence of moth defoliation and the onset of the growing season for the entire region to investigate the link between the patterns of defoliation and outbreak spread. In addition, we examine whether a phase-dependent coherence in the pattern of spatial synchrony exists between defoliation and onset of the growing season, in order to evaluate if the degree of matching phenology between the moth and their host plant could be the mechanism behind a Moran effect. The strength of regional spatial synchrony in defoliation and the pattern of defoliation spread were both highly phase-dependent. The incipient phase of the outbreak was characterized by high regional synchrony in defoliation and long spread distances, compared with the epidemic and crash phase. Defoliation spread was best described using a two-scale stratified spread model, suggesting that defoliation spread is governed by two processes operating at different spatial scale. The pattern of phase-dependent spatial synchrony was coherent in both defoliation and onset of the growing season. This suggests that the timing of spring phenology plays a role in the large-scale synchronization of birch forest moth outbreaks. PMID:19740876

Multiscale Structure of UXO Site Characterization: Spatial Estimation and Uncertainty Quantification

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

Ostrouchov, George; Doll, William E.; Beard, Les P.

2009-01-01

Unexploded ordnance (UXO) site characterization must consider both how the contamination is generated and how we observe that contamination. Within the generation and observation processes, dependence structures can be exploited at multiple scales. We describe a conceptual site characterization process, the dependence structures available at several scales, and consider their statistical estimation aspects. It is evident that most of the statistical methods that are needed to address the estimation problems are known but their application-specific implementation may not be available. We demonstrate estimation at one scale and propose a representation for site contamination intensity that takes full account of uncertainty,more » is flexible enough to answer regulatory requirements, and is a practical tool for managing detailed spatial site characterization and remediation. The representation is based on point process spatial estimation methods that require modern computational resources for practical application. These methods have provisions for including prior and covariate information.« less

Metacommunity versus Biogeography: A Case Study of Two Groups of Neotropical Vegetation-Dwelling Arthropods

PubMed Central

Gonçalves-Souza, Thiago; Romero, Gustavo Q.; Cottenie, Karl

2014-01-01

Biogeography and metacommunity ecology provide two different perspectives on species diversity. Both are spatial in nature but their spatial scales do not necessarily match. With recent boom of metacommunity studies, we see an increasing need for clear discrimination of spatial scales relevant for both perspectives. This discrimination is a necessary prerequisite for improved understanding of ecological phenomena across scales. Here we provide a case study to illustrate some spatial scale-dependent concepts in recent metacommunity studies and identify potential pitfalls. We presented here the diversity patterns of Neotropical lepidopterans and spiders viewed both from metacommunity and biogeographical perspectives. Specifically, we investigated how the relative importance of niche- and dispersal-based processes for community assembly change at two spatial scales: metacommunity scale, i.e. within a locality, and biogeographical scale, i.e. among localities widely scattered along a macroclimatic gradient. As expected, niche-based processes dominated the community assembly at metacommunity scale, while dispersal-based processes played a major role at biogeographical scale for both taxonomical groups. However, we also observed small but significant spatial effects at metacommunity scale and environmental effects at biogeographical scale. We also observed differences in diversity patterns between the two taxonomical groups corresponding to differences in their dispersal modes. Our results thus support the idea of continuity of processes interactively shaping diversity patterns across scales and emphasize the necessity of integration of metacommunity and biogeographical perspectives. PMID:25549332

Soil moisture dynamics and dominant controls at different spatial scales over semiarid and semi-humid areas

NASA Astrophysics Data System (ADS)

Suo, Lizhu; Huang, Mingbin; Zhang, Yongkun; Duan, Liangxia; Shan, Yan

2018-07-01

Soil moisture dynamics plays an active role in ecological and hydrological processes, and it depends on a large number of environmental factors, such as topographic attributes, soil properties, land use types, and precipitation. However, studies must still clarify the relative significance of these environmental factors at different soil depths and at different spatial scales. This study aimed: (1) to characterize temporal and spatial variations in soil moisture content (SMC) at four soil layers (0-40, 40-100, 100-200, and 200-500 cm) and three spatial scales (plot, hillslope, and region); and (2) to determine their dominant controls in diverse soil layers at different spatial scales over semiarid and semi-humid areas of the Loess Plateau, China. Given the high co-dependence of environmental factors, partial least squares regression (PLSR) was used to detect relative significance among 15 selected environmental factors that affect SMC. Temporal variation in SMC decreased with increasing soil depth, and vertical changes in the 0-500 cm soil profile were divided into a fast-changing layer (0-40 cm), an active layer (40-100 cm), a sub-active layer (100-200 cm), and a relatively stable layer (200-500 cm). PLSR models simulated SMC accurately in diverse soil layers at different scales; almost all values for variation in response (R2) and goodness of prediction (Q2) were >0.5 and >0.0975, respectively. Upper and lower layer SMCs were the two most important factors that influenced diverse soil layers at three scales, and these SMC variables exhibited the highest importance in projection (VIP) values. The 7-day antecedent precipitation and 7-day antecedent potential evapotranspiration contributed significantly to SMC only at the 0-40 cm soil layer. VIP of soil properties, especially sand and silt content, which influenced SMC strongly, increased significantly after increasing the measured scale. Mean annual precipitation and potential evapotranspiration also influenced SMC at the regional scale significantly. Overall, this study indicated that dominant controls of SMC varied among three spatial scales on the Loess Plateau, and VIP was a function of spatial scale and soil depth.

Ecological effects of the Hayman Fire - Part 8: Effects on species of concern

Treesearch

Natasha B. Kotliar; Sara Simonson; Geneva Chong; Dave Theobald

2003-01-01

Conclusions about the effects of fire on species of concern will depend on the temporal and spatial scales of analysis. Populations of some species may decline in abundance immediately postfire due to alteration or destruction of habitat, but over larger spatial and temporal scales, fire contributes to a shifting mosaic of habitat conditions across the landscape....

Invasive plants have scale-dependent effects on diversity by altering species-area relationships.

PubMed

Powell, Kristin I; Chase, Jonathan M; Knight, Tiffany M

2013-01-18

Although invasive plant species often reduce diversity, they rarely cause plant extinctions. We surveyed paired invaded and uninvaded plant communities from three biomes. We reconcile the discrepancy in diversity loss from invaders by showing that invaded communities have lower local richness but steeper species accumulation with area than that of uninvaded communities, leading to proportionately fewer species loss at broader spatial scales. We show that invaders drive scale-dependent biodiversity loss through strong neutral sampling effects on the number of individuals in a community. We also show that nonneutral species extirpations are due to a proportionately larger effect of invaders on common species, suggesting that rare species are buffered against extinction. Our study provides a synthetic perspective on the threat of invasions to biodiversity loss across spatial scales.

Exploring the effect of the spatial scale of fishery management.

PubMed

Takashina, Nao; Baskett, Marissa L

2016-02-07

For any spatially explicit management, determining the appropriate spatial scale of management decisions is critical to success at achieving a given management goal. Specifically, managers must decide how much to subdivide a given managed region: from implementing a uniform approach across the region to considering a unique approach in each of one hundred patches and everything in between. Spatially explicit approaches, such as the implementation of marine spatial planning and marine reserves, are increasingly used in fishery management. Using a spatially explicit bioeconomic model, we quantify how the management scale affects optimal fishery profit, biomass, fishery effort, and the fraction of habitat in marine reserves. We find that, if habitats are randomly distributed, the fishery profit increases almost linearly with the number of segments. However, if habitats are positively autocorrelated, then the fishery profit increases with diminishing returns. Therefore, the true optimum in management scale given cost to subdivision depends on the habitat distribution pattern. Copyright © 2015 Elsevier Ltd. All rights reserved.

How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

NASA Astrophysics Data System (ADS)

Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

2017-12-01

Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

Scale Dependence of Oak Woodland Historical Fire Intervals: Contrasting the Barrens of Tennessee and Cross Timbers of Oklahoma, USA

Treesearch

Michael C. Stambaugh; Richard P. Guyette; Joseph M. Marschall; Daniel C. Dey

2016-01-01

Characterization of scale dependence of fire intervals could inform interpretations of fire history and improve fire prescriptions that aim to mimic historical fire regime conditions. We quantified the temporal variability in fire regimes and described the spatial dependence of fire intervals through the analysis of multi-century fire scar records (8 study sites, 332...

Concepts of scale and scaling

Treesearch

Jianguo Wu; Harbin Li

2006-01-01

The relationship between pattern and process is of great interest in all natural and social sciences, and scale is an integral part of this relationship. It is now well documented that biophysical and socioeconomic patterns and processes operate on a wide range of spatial and temporal scales. In particular, the scale multiplicity and scale dependence of pattern,...

Spatial Analysis of Rice Blast in China at Three Different Scales.

PubMed

Guo, Fangfang; Chen, Xinglong; Lu, Minghong; Yang, Li; Wang, Shi Wei; Wu, Bo Ming

2018-05-22

In this study, spatial analyses were conducted at three different scales to better understand the epidemiology of rice blast, a major rice disease caused by Magnaporthe oryzae. At regional scale, across the major rice production regions in China, rice blast incidence was monitored on 101 dates at 193 stations from June 10 th to Sep. 10 th during 2009-2014, and surveyed in 143 fields in September, 2016; at county scale, 3 surveys were done covering 1-5 counties in 2015-2016; and at field scale, blast was evaluated in 6 fields in 2015-2016. Spatial cluster and hot spot analyses were conducted in GIS on the geographical pattern of the disease at regional scale, and geostatistical analysis performed at all the three scales. Cluster and hot spot analyses revealed that high-disease areas were clustered in mountainous areas in China. Geostatistical analyses detected spatial dependence of blast incidence with influence ranges of 399 to 1080 km at regional scale, and 5 to 10 m at field scale, but not at county scale. The spatial patterns at different scales might be determined by inherent properties of rice blast and environmental driving forces, and findings from this study provide helpful information to sampling and management of rice blast.

Scale-Dependence of Processes Structuring Dung Beetle Metacommunities Using Functional Diversity and Community Deconstruction Approaches

PubMed Central

da Silva, Pedro Giovâni; Hernández, Malva Isabel Medina

2015-01-01

Community structure is driven by mechanisms linked to environmental, spatial and temporal processes, which have been successfully addressed using metacommunity framework. The relative importance of processes shaping community structure can be identified using several different approaches. Two approaches that are increasingly being used are functional diversity and community deconstruction. Functional diversity is measured using various indices that incorporate distinct community attributes. Community deconstruction is a way to disentangle species responses to ecological processes by grouping species with similar traits. We used these two approaches to determine whether they are improvements over traditional measures (e.g., species composition, abundance, biomass) for identification of the main processes driving dung beetle (Scarabaeinae) community structure in a fragmented mainland-island landscape in southern Brazilian Atlantic Forest. We sampled five sites in each of four large forest areas, two on the mainland and two on the island. Sampling was performed in 2012 and 2013. We collected abundance and biomass data from 100 sampling points distributed over 20 sampling sites. We studied environmental, spatial and temporal effects on dung beetle community across three spatial scales, i.e., between sites, between areas and mainland-island. The γ-diversity based on species abundance was mainly attributed to β-diversity as a consequence of the increase in mean α- and β-diversity between areas. Variation partitioning on abundance, biomass and functional diversity showed scale-dependence of processes structuring dung beetle metacommunities. We identified two major groups of responses among 17 functional groups. In general, environmental filters were important at both local and regional scales. Spatial factors were important at the intermediate scale. Our study supports the notion of scale-dependence of environmental, spatial and temporal processes in the distribution and functional organization of Scarabaeinae beetles. We conclude that functional diversity may be used as a complementary approach to traditional measures, and that community deconstruction allows sufficient disentangling of responses of different trait-based groups. PMID:25822150

Spatial distribution of limited resources and local density regulation in juvenile Atlantic salmon.

PubMed

Finstad, Anders G; Einum, Sigurd; Ugedal, Ola; Forseth, Torbjørn

2009-01-01

1. Spatial heterogeneity of resources may influence competition among individuals and thus have a fundamental role in shaping population dynamics and carrying capacity. In the present study, we identify shelter opportunities as a limiting resource for juvenile Atlantic salmon (Salmo salar L.). Experimental and field studies are combined in order to demonstrate how the spatial distribution of shelters may influence population dynamics on both within and among population scales. 2. In closed experimental streams, fish performance scaled negatively with decreasing shelter availability and increasing densities. In contrast, the fish in open stream channels dispersed according to shelter availability and performance of fish remaining in the streams did not depend on initial density or shelters. 3. The field study confirmed that spatial variation in densities of 1-year-old juveniles was governed both by initial recruit density and shelter availability. Strength of density-dependent population regulation, measured as carrying capacity, increased with decreasing number of shelters. 4. Nine rivers were surveyed for spatial variation in shelter availability and increased shelter heterogeneity tended to decrease maximum observed population size (measured using catch statistics of adult salmon as a proxy). 5. Our studies highlight the importance of small-scale within-population spatial structure in population dynamics and demonstrate that not only the absolute amount of limiting resources but also their spatial arrangement can be an important factor influencing population carrying capacity.

Modelling Soil-Landscapes in Coastal California Hills Using Fine Scale Terrestrial Lidar

NASA Astrophysics Data System (ADS)

Prentice, S.; Bookhagen, B.; Kyriakidis, P. C.; Chadwick, O.

2013-12-01

Digital elevation models (DEMs) are the dominant input to spatially explicit digital soil mapping (DSM) efforts due to their increasing availability and the tight coupling between topography and soil variability. Accurate characterization of this coupling is dependent on DEM spatial resolution and soil sampling density, both of which may limit analyses. For example, DEM resolution may be too coarse to accurately reflect scale-dependent soil properties yet downscaling introduces artifactual uncertainty unrelated to deterministic or stochastic soil processes. We tackle these limitations through a DSM effort that couples moderately high density soil sampling with a very fine scale terrestrial lidar dataset (20 cm) implemented in a semiarid rolling hillslope domain where terrain variables change rapidly but smoothly over short distances. Our guiding hypothesis is that in this diffusion-dominated landscape, soil thickness is readily predicted by continuous terrain attributes coupled with catenary hillslope segmentation. We choose soil thickness as our keystone dependent variable for its geomorphic and hydrologic significance, and its tendency to be a primary input to synthetic ecosystem models. In defining catenary hillslope position we adapt a logical rule-set approach that parses common terrain derivatives of curvature and specific catchment area into discrete landform elements (LE). Variograms and curvature-area plots are used to distill domain-scale terrain thresholds from short range order noise characteristic of very fine-scale spatial data. The revealed spatial thresholds are used to condition LE rule-set inputs, rendering a catenary LE map that leverages the robustness of fine-scale terrain data to create a generalized interpretation of soil geomorphic domains. Preliminary regressions show that continuous terrain variables alone (curvature, specific catchment area) only partially explain soil thickness, and only in a subset of soils. For example, at spatial scales up 20, curvature explains 40% of soil thickness variance among soils <3 m deep, while soils >3 m deep show no clear relation to curvature. To further demonstration our geomorphic segmentation approach, we apply it to DEM domains where diffusion processes are less dominant than in our primary study area. Classified landform map derived from fine scale terrestrial lidar. Color classes depict hydrogeomorphic process domains in zero order watersheds.

Application of spatial and non-spatial data analysis in determination of the factors that impact municipal solid waste generation rates in Turkey

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

Keser, Saniye; Duzgun, Sebnem; Department of Geodetic and Geographic Information Technologies, Middle East Technical University, 06800 Ankara

Highlights: Black-Right-Pointing-Pointer Spatial autocorrelation exists in municipal solid waste generation rates for different provinces in Turkey. Black-Right-Pointing-Pointer Traditional non-spatial regression models may not provide sufficient information for better solid waste management. Black-Right-Pointing-Pointer Unemployment rate is a global variable that significantly impacts the waste generation rates in Turkey. Black-Right-Pointing-Pointer Significances of global parameters may diminish at local scale for some provinces. Black-Right-Pointing-Pointer GWR model can be used to create clusters of cities for solid waste management. - Abstract: In studies focusing on the factors that impact solid waste generation habits and rates, the potential spatial dependency in solid waste generation datamore » is not considered in relating the waste generation rates to its determinants. In this study, spatial dependency is taken into account in determination of the significant socio-economic and climatic factors that may be of importance for the municipal solid waste (MSW) generation rates in different provinces of Turkey. Simultaneous spatial autoregression (SAR) and geographically weighted regression (GWR) models are used for the spatial data analyses. Similar to ordinary least squares regression (OLSR), regression coefficients are global in SAR model. In other words, the effect of a given independent variable on a dependent variable is valid for the whole country. Unlike OLSR or SAR, GWR reveals the local impact of a given factor (or independent variable) on the waste generation rates of different provinces. Results show that provinces within closer neighborhoods have similar MSW generation rates. On the other hand, this spatial autocorrelation is not very high for the exploratory variables considered in the study. OLSR and SAR models have similar regression coefficients. GWR is useful to indicate the local determinants of MSW generation rates. GWR model can be utilized to plan waste management activities at local scale including waste minimization, collection, treatment, and disposal. At global scale, the MSW generation rates in Turkey are significantly related to unemployment rate and asphalt-paved roads ratio. Yet, significances of these variables may diminish at local scale for some provinces. At local scale, different factors may be important in affecting MSW generation rates.« less

Homogenization techniques for population dynamics in strongly heterogeneous landscapes.

PubMed

Yurk, Brian P; Cobbold, Christina A

2018-12-01

An important problem in spatial ecology is to understand how population-scale patterns emerge from individual-level birth, death, and movement processes. These processes, which depend on local landscape characteristics, vary spatially and may exhibit sharp transitions through behavioural responses to habitat edges, leading to discontinuous population densities. Such systems can be modelled using reaction-diffusion equations with interface conditions that capture local behaviour at patch boundaries. In this work we develop a novel homogenization technique to approximate the large-scale dynamics of the system. We illustrate our approach, which also generalizes to multiple species, with an example of logistic growth within a periodic environment. We find that population persistence and the large-scale population carrying capacity is influenced by patch residence times that depend on patch preference, as well as movement rates in adjacent patches. The forms of the homogenized coefficients yield key theoretical insights into how large-scale dynamics arise from the small-scale features.

Influences of land use on leaf breakdown in Southern Appalachian headwater streams: a multiple-scale analysis

Treesearch

R.A. Sponseller; E.F. Benfield

2001-01-01

Stream ecosystems can be strongly influenced by land use within watersheds. The extent of this influence may depend on the spatial distribution of developed land and the scale at which it is evaluated. Effects of land-cover patterns on leaf breakdown were studied in 8 Southern Appalachian headwater streams. Using a GIS, land cover was evaluated at several spatial...

A Bayesian method for assessing multiscalespecies-habitat relationships

USGS Publications Warehouse

Stuber, Erica F.; Gruber, Lutz F.; Fontaine, Joseph J.

2017-01-01

ContextScientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multi-scale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large.ObjectivesOur objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance.MethodsWe introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA.ResultsOur method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%.ConclusionsGiven the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships.

Ecological feedbacks. Termite mounds can increase the robustness of dryland ecosystems to climatic change.

PubMed

Bonachela, Juan A; Pringle, Robert M; Sheffer, Efrat; Coverdale, Tyler C; Guyton, Jennifer A; Caylor, Kelly K; Levin, Simon A; Tarnita, Corina E

2015-02-06

Self-organized spatial vegetation patterning is widespread and has been described using models of scale-dependent feedback between plants and water on homogeneous substrates. As rainfall decreases, these models yield a characteristic sequence of patterns with increasingly sparse vegetation, followed by sudden collapse to desert. Thus, the final, spot-like pattern may provide early warning for such catastrophic shifts. In many arid ecosystems, however, termite nests impart substrate heterogeneity by altering soil properties, thereby enhancing plant growth. We show that termite-induced heterogeneity interacts with scale-dependent feedbacks to produce vegetation patterns at different spatial grains. Although the coarse-grained patterning resembles that created by scale-dependent feedback alone, it does not indicate imminent desertification. Rather, mound-field landscapes are more robust to aridity, suggesting that termites may help stabilize ecosystems under global change. Copyright © 2015, American Association for the Advancement of Science.

Plasmon mass scale in two-dimensional classical nonequilibrium gauge theory

NASA Astrophysics Data System (ADS)

Lappi, T.; Peuron, J.

2018-02-01

We study the plasmon mass scale in classical gluodynamics in a two-dimensional configuration that mimics the boost-invariant initial color fields in a heavy-ion collision. We numerically measure the plasmon mass scale using three different methods: a hard thermal loop (HTL) expression involving the quasiparticle spectrum constructed from Coulomb gauge field correlators, an effective dispersion relation, and the measurement of oscillations between electric and magnetic energies after introducing a spatially uniform perturbation to the electric field. We find that the HTL expression and the uniform electric field measurement are in rough agreement. The effective dispersion relation agrees with other methods within a factor of 2. We also study the dependence on time and occupation number, observing similar trends as in three spatial dimensions, where a power-law dependence sets in after an occupation-number-dependent transient time. We observe a decrease of the plasmon mass squared as t-1 / 3 at late times.

Range-wide wetland associations of the King Rail: A multi-scale approach

USGS Publications Warehouse

Glisson, Wesley J.; Conway, Courtney J.; Nadeau, Christopher P.; Borgmann, Kathi L.; Laxson, Thomas A.

2015-01-01

King Rail populations have declined and identifying wetland features that influence King Rail occupancy can help prevent further population declines. We integrated continent-wide marsh bird survey data with spatial wetland data from the National Wetland Inventory (NWI) to examine wetland features that influenced King Rail occupancy throughout the species’ range. We analyzed wetland data at 7 spatial scales to examine the scale(s) at which 68 wetland features were most strongly related to King Rail occupancy. Occupancy was most strongly associated with estuarine features and brackish and tidal saltwater regimes. King Rail occupancy was positively associated with emergent and scrub-shrub wetlands and negatively associated with forested wetlands. The best spatial scale for assessing King Rail occupancy differed among wetland features; we could not identify one spatial scale (among all wetland features) that best explained variation in occupancy. Future research on King Rail habitat that includes multiple spatial scales is more likely to identify the suite of features that influence occupancy. Our results indicate that NWI data may be useful for predicting occupancy based on broad habitat features across the King Rail’s range, which may help inform management decisions for this and other wetland-dependent birds.

Investigating the dependence of SCM simulated precipitation and clouds on the spatial scale of large-scale forcing at SGP [Investigating the scale dependence of SCM simulated precipitation and cloud by using gridded forcing data at SGP

DOE PAGES

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

2017-08-05

Large-scale forcing data, such as vertical velocity and advective tendencies, are required to drive single-column models (SCMs), cloud-resolving models, and large-eddy simulations. Previous studies suggest that some errors of these model simulations could be attributed to the lack of spatial variability in the specified domain-mean large-scale forcing. This study investigates the spatial variability of the forcing and explores its impact on SCM simulated precipitation and clouds. A gridded large-scale forcing data during the March 2000 Cloud Intensive Operational Period at the Atmospheric Radiation Measurement program's Southern Great Plains site is used for analysis and to drive the single-column version ofmore » the Community Atmospheric Model Version 5 (SCAM5). When the gridded forcing data show large spatial variability, such as during a frontal passage, SCAM5 with the domain-mean forcing is not able to capture the convective systems that are partly located in the domain or that only occupy part of the domain. This problem has been largely reduced by using the gridded forcing data, which allows running SCAM5 in each subcolumn and then averaging the results within the domain. This is because the subcolumns have a better chance to capture the timing of the frontal propagation and the small-scale systems. As a result, other potential uses of the gridded forcing data, such as understanding and testing scale-aware parameterizations, are also discussed.« less

Multi-scale evaluation of the environmental controls on burn probability in a southern Sierra Nevada landscape

Treesearch

Sean A. Parks; Marc-Andre Parisien; Carol Miller

2011-01-01

We examined the scale-dependent relationship between spatial fire likelihood or burn probability (BP) and some key environmental controls in the southern Sierra Nevada, California, USA. Continuous BP estimates were generated using a fire simulation model. The correspondence between BP (dependent variable) and elevation, ignition density, fuels and aspect was evaluated...

Modeling fluid injection induced microseismicity in shales

NASA Astrophysics Data System (ADS)

Carcione, José M.; Currenti, Gilda; Johann, Lisa; Shapiro, Serge

2018-02-01

Hydraulic fracturing in shales generates a cloud of seismic—tensile and shear—events that can be used to evaluate the extent of the fracturing (event clouds) and obtain the hydraulic properties of the medium, such as the degree of anisotropy and the permeability. Firstly, we investigate the suitability of novel semi-analytical reference solutions for pore pressure evolution around a well after fluid injection in anisotropic media. To do so, we use cylindrical coordinates in the presence of a formation (a layer) and spherical coordinates for a homogeneous and unbounded medium. The involved differential equations are transformed to an isotropic diffusion equation by means of pseudo-spatial coordinates obtained from the spatial variables re-scaled by the permeability components. We consider pressure-dependent permeability components, which are independent of the spatial direction. The analytical solutions are compared to numerical solutions to verify their applicability. The comparison shows that the solutions are suitable for a limited permeability range and moderate to minor pressure dependences of the permeability. Once the pressure evolution around the well has been established, we can model the microseismic events. Induced seismicity by failure due to fluid injection in a porous rock depends on the properties of the hydraulic and elastic medium and in situ stress conditions. Here, we define a tensile threshold pressure above which there is tensile emission, while the shear threshold is obtained by using the octahedral stress criterion and the in situ rock properties and conditions. Subsequently, we generate event clouds for both cases and study the spatio-temporal features. The model considers anisotropic permeability and the results are spatially re-scaled to obtain an effective isotropic medium representation. For a 3D diffusion in spherical coordinates and exponential pressure dependence of the permeability, the results differ from those of the classical diffusion equation. Use of the classical front to fit cloud events spatially, provides good results but with a re-scaled value of these components. Modeling is required to evaluate the scaling constant in real cases.

Effect of land use on the spatial variability of organic matter and nutrient status in an Oxisol

NASA Astrophysics Data System (ADS)

Paz-Ferreiro, Jorge; Alves, Marlene Cristina; Vidal Vázquez, Eva

2013-04-01

Heterogeneity is now considered as an inherent soil property. Spatial variability of soil attributes in natural landscapes results mainly from soil formation factors. In cultivated soils much heterogeneity can additionally occur as a result of land use, agricultural systems and management practices. Organic matter content (OMC) and nutrients associated to soil exchange complex are key attribute in the maintenance of a high quality soil. Neglecting spatial heterogeneity in soil OMC and nutrient status at the field scale might result in reduced yield and in environmental damage. We analyzed the impact of land use on the pattern of spatial variability of OMC and soil macronutrients at the stand scale. The study was conducted in São Paulo state, Brazil. Land uses were pasture, mango orchard and corn field. Soil samples were taken at 0-10 cm and 10-20 cm depth in 84 points, within 100 m x 100 m plots. Texture, pH, OMC, cation exchange capacity (CEC), exchangeable cations (Ca, Mg, K, H, Al) and resin extractable phosphorus were analyzed.. Statistical variability was found to be higher in parameters defining the soil nutrient status (resin extractable P, K, Ca and Mg) than in general soil properties (OMC, CEC, base saturation and pH). Geostatistical analysis showed contrasting patterns of spatial dependence for the different soil uses, sampling depths and studied properties. Most of the studied data sets collected at two different depths exhibited spatial dependence at the sampled scale and their semivariograms were modeled by a nugget effect plus a structure. The pattern of soil spatial variability was found to be different between the three study soil uses and at the two sampling depths, as far as model type, nugget effect or ranges of spatial dependence were concerned. Both statistical and geostatistical results pointed out the importance of OMC as a driver responsible for the spatial variability of soil nutrient status.

Determination of the Time-Space Magnetic Correlation Functions in the Solar Wind

NASA Astrophysics Data System (ADS)

Weygand, J. M.; Matthaeus, W. H.; Kivelson, M.; Dasso, S.

2013-12-01

Magnetic field data from many different intervals and 7 different solar wind spacecraft are employed to estimate the scale-dependent time decorrelation function in the interplanetary magnetic field in both the slow and fast solar wind. This estimation requires correlations varying with both space and time lags. The two point correlation function with no time lag is determined by correlating time series data from multiple spacecraft separated in space and for complete coverage of length scales relies on many intervals with different spacecraft spatial separations. In addition we employ single spacecraft time-lagged correlations, and two spacecraft time lagged correlations to access different spatial and temporal correlation data. Combining these data sets gives estimates of the scale-dependent time decorrelation function, which in principle tells us how rapidly time decorrelation occurs at a given wavelength. For static fields the scale-dependent time decorrelation function is trivially unity, but in turbulence the nonlinear cascade process induces time-decorrelation at a given length scale that occurs more rapidly with decreasing scale. The scale-dependent time decorrelation function is valuable input to theories as well as various applications such as scattering, transport, and study of predictability. It is also a fundamental element of formal turbulence theory. Our results are extension of the Eulerian correlation functions estimated in Matthaeus et al. [2010], Weygand et al [2012; 2013].

Coexistence and relative abundance in plant communities are determined by feedbacks when the scale of feedback and dispersal is local.

PubMed

Mack, Keenan M L; Bever, James D

2014-09-01

1. Negative plant-soil feedback occurs when the presence of an individual of a particular species at a particular site decreases the relative success of individuals of the same species compared to those other species at that site. This effect favors heterospecifics thereby facilitating coexistence and maintaining diversity. Empirical work has demonstrated that the average strengths of these feedbacks correlate with the relative abundance of species within a community, suggesting that feedbacks are an important driver of plant community composition. Understanding what factors contribute to the generation of this relationship is necessary for diagnosing the dynamic forces that maintain diversity in plant communities. 2. We used a spatially explicit, individual-based computer simulation to test the effects of dispersal distance, the size of feedback neighbourhoods, the strength of pairwise feedbacks and community wide variation of feedbacks, community richness, as well as life-history differences on the dependence of relative abundance on strength of feedback. 3. We found a positive dependence of relative abundance of a species on its average feedback for local scale dispersal and feedback. However, we found that the strength of this dependence decreased as either the spatial scale of dispersal and/or the spatial scale of feedback increased. We also found that for spatially local (i.e. relatively small) scale interaction and dispersal, as the mean strength of feedbacks in the community becomes less negative, the greater the increase in abundance produced by a comparable increase in species-specific average feedback. We found that life-history differences such as mortality rate did not generate a pattern with abundance, nor did they affect the relationship between abundance and average feedback. 4. Synthesis . Our results support the claim that empirical observations of a positive correlation between relative abundance and strength of average feedback serves as evidence that local scale negative feedbacks play a prominent role in structuring plant communities. We also identify that this relationship depends upon local scale plant dispersal and feedback which generates clumping and magnifies the negative feedbacks.

Spatially dependent responses of a large-river fish assemblage to bank stabilization and side channels

USGS Publications Warehouse

Reinhold, Ann Marie; Bramblett, Robert G.; Zale, Alexander V.; Poole, Geoffrey C.; Roberts, David W.

2017-01-01

The alteration of rivers by anthropogenic bank stabilization to prevent the erosion of economically valuable lands and structures has become commonplace. However, such alteration has ambiguous consequences for fish assemblages, especially in large rivers. Because most large, temperate rivers have impoundments, it can be difficult to separate the influences of bank stabilization structures from those of main-stem impoundments, especially because both stabilization structures and impoundments can cause side-channel loss. Few large rivers are free flowing and retain extensive side channels, but the Yellowstone River (our study area) is one such river. We hypothesized that in this river (1) bank stabilization has changed fish assemblage structure by altering habitats, (2) side-channel availability has influenced fish assemblage structure by providing habitat heterogeneity, and (3) the influences of bank stabilization and side channels on fish assemblages were spatially scale dependent. We developed a spatially explicit framework to test these hypotheses. Fish assemblage structure varied with the extent of bank stabilization and the availability of side channels; however, not all assemblage subsets were influenced. Nevertheless, bank stabilization and side channels had different and sometimes opposite influences on the fish assemblage. The effects of side channels on fish were more consistent and widespread than those of bank stabilization; the catches of more fishes were positively correlated with side-channel availability than with the extent of bank stabilization. The influences of bank stabilization and side channels on the relative abundances of fish also varied, depending on species and river bend geomorphology. The variation in river morphology probably contributed to the assemblage differences between stabilized and reference river bends; stabilized alluvial pools were deeper than reference alluvial pools, but the depths of stabilized and reference bluff pools did not differ. The strengths of the relationships among fish assemblages, bank stabilization, and side channels were spatially scale dependent; optimum spatial scales ranged from less than 200 m to 3,200 m up- and downstream, suggesting that bank stabilization and side channels influenced fish assemblages across multiple spatial scales.

Spatial distribution of enzyme driven reactions at micro-scales

NASA Astrophysics Data System (ADS)

Kandeler, Ellen; Boeddinghaus, Runa; Nassal, Dinah; Preusser, Sebastian; Marhan, Sven; Poll, Christian

2017-04-01

Studies of microbial biogeography can often provide key insights into the physiologies, environmental tolerances, and ecological strategies of soil microorganisms that dominate in natural environments. In comparison with aquatic systems, soils are particularly heterogeneous. Soil heterogeneity results from the interaction of a hierarchical series of interrelated variables that fluctuate at many different spatial and temporal scales. Whereas spatial dependence of chemical and physical soil properties is well known at scales ranging from decimetres to several hundred metres, the spatial structure of soil enzymes is less clear. Previous work has primarily focused on spatial heterogeneity at a single analytical scale using the distribution of individual cells, specific types of organisms or collective parameters such as bacterial abundance or total microbial biomass. There are fewer studies that have considered variations in community function and soil enzyme activities. This presentation will give an overview about recent studies focusing on spatial pattern of different soil enzymes in the terrestrial environment. Whereas zymography allows the visualization of enzyme pattern in the close vicinity of roots, micro-sampling strategies followed by MUF analyses clarify micro-scale pattern of enzymes associated to specific microhabitats (micro-aggregates, organo-mineral complexes, subsoil compartments).

Characterizing Spatial Organization of Cell Surface Receptors in Human Breast Cancer with STORM

NASA Astrophysics Data System (ADS)

Lyall, Evan; Chapman, Matthew R.; Sohn, Lydia L.

2012-02-01

Regulation and control of complex biological functions are dependent upon spatial organization of biological structures at many different length scales. For instance Eph receptors and their ephrin ligands bind when opposing cells come into contact during development, resulting in spatial organizational changes on the nanometer scale that lead to changes on the macro scale, in a process known as organ morphogenesis. One technique able to probe this important spatial organization at both the nanometer and micrometer length scales, including at cell-cell junctions, is stochastic optical reconstruction microscopy (STORM). STORM is a technique that localizes individual fluorophores based on the centroids of their point spread functions and then reconstructs a composite image to produce super resolved structure. We have applied STORM to study spatial organization of the cell surface of human breast cancer cells, specifically the organization of tyrosine kinase receptors and chemokine receptors. A better characterization of spatial organization of breast cancer cell surface proteins is necessary to fully understand the tumorigenisis pathways in the most common malignancy in United States women.

The spatial scale for cisco recruitment dynamics in Lake Superior during 1978-2007

USGS Publications Warehouse

Rook, Benjamin J.; Hansen, Michael J.; Gorman, Owen T.

2012-01-01

The cisco Coregonus artedi was once the most abundant fish species in the Great Lakes, but currently cisco populations are greatly reduced and management agencies are attempting to restore the species throughout the basin. To increase understanding of the spatial scale at which density‐independent and density‐dependent factors influence cisco recruitment dynamics in the Great Lakes, we used a Ricker stock–recruitment model to identify and quantify the appropriate spatial scale for modeling age‐1 cisco recruitment dynamics in Lake Superior. We found that the recruitment variation of ciscoes in Lake Superior was best described by a five‐parameter regional model with separate stock–recruitment relationships for the western, southern, eastern, and northern regions. The spatial scale for modeling was about 260 km (range = 230–290 km). We also found that the density‐independent recruitment rate and the rate of compensatory density dependence varied among regions at different rates. The density‐independent recruitment rate was constant among regions (3.6 age‐1 recruits/spawner), whereas the rate of compensatory density dependence varied 16‐fold among regions (range = −0.2 to −2.9/spawner). Finally, we found that peak recruitment and the spawning stock size that produced peak recruitment varied among regions. Both peak recruitment (0.5–7.1 age‐1 recruits/ha) and the spawning stock size that produced peak recruitment (0.3–5.3 spawners/ha) varied 16‐fold among regions. Our findings support the hypothesis that the factors driving cisco recruitment operate within four different regions of Lake Superior, suggest that large‐scale abiotic factors are more important than small‐scale biotic factors in influencing cisco recruitment, and suggest that fishery managers throughout Lake Superior and the entire Great Lakes basin should address cisco restoration and management efforts on a regional scale in each lake.

How large is large enough for insects? Forest fragmentation effects at three spatial scales

NASA Astrophysics Data System (ADS)

Ribas, C. R.; Sobrinho, T. G.; Schoereder, J. H.; Sperber, C. F.; Lopes-Andrade, C.; Soares, S. M.

2005-02-01

Several mechanisms may lead to species loss in fragmented habitats, such as edge and shape effects, loss of habitat and heterogeneity. Ants and crickets were sampled in 18 forest remnants in south-eastern Brazil, to test whether a group of small remnants maintains the same insect species richness as similar sized large remnants, at three spatial scales. We tested hypotheses about alpha and gamma diversity to explain the results. Groups of remnants conserve as many species of ants as a single one. Crickets, however, showed a scale-dependent pattern: at small scales there was no significant or important difference between groups of remnants and a single one, while at the larger scale the group of remnants maintained more species. Alpha diversity (local species richness) was similar in a group of remnants and in a single one, at the three spatial scales, both for ants and crickets. Gamma diversity, however, varied both with taxa (ants and crickets) and spatial scale, which may be linked to insect mobility, remnant isolation, and habitat heterogeneity. Biological characteristics of the organisms involved have to be considered when studying fragmentation effects, as well as spatial scale at which it operates. Mobility of the organisms influences fragmentation effects, and consequently conservation strategies.

Multivariate analysis of scale-dependent associations between bats and landscape structure

USGS Publications Warehouse

Gorresen, P.M.; Willig, M.R.; Strauss, R.E.

2005-01-01

The assessment of biotic responses to habitat disturbance and fragmentation generally has been limited to analyses at a single spatial scale. Furthermore, methods to compare responses between scales have lacked the ability to discriminate among patterns related to the identity, strength, or direction of associations of biotic variables with landscape attributes. We present an examination of the relationship of population- and community-level characteristics of phyllostomid bats with habitat features that were measured at multiple spatial scales in Atlantic rain forest of eastern Paraguay. We used a matrix of partial correlations between each biotic response variable (i.e., species abundance, species richness, and evenness) and a suite of landscape characteristics to represent the multifaceted associations of bats with spatial structure. Correlation matrices can correspond based on either the strength (i.e., magnitude) or direction (i.e., sign) of association. Therefore, a simulation model independently evaluated correspondence in the magnitude and sign of correlations among scales, and results were combined via a meta-analysis to provide an overall test of significance. Our approach detected both species-specific differences in response to landscape structure and scale dependence in those responses. This matrix-simulation approach has broad applicability to ecological situations in which multiple intercorrelated factors contribute to patterns in space or time. ?? 2005 by the Ecological Society of America.

Spatial variability of macrobenthic zonation on exposed sandy beaches

NASA Astrophysics Data System (ADS)

Veiga, Puri; Rubal, Marcos; Cacabelos, Eva; Maldonado, Cristina; Sousa-Pinto, Isabel

2014-07-01

We analysed the consistence of vertical patterns of distribution (i.e. zonation) for macrofauna at different spatial scales on four intermediate exposed beaches in the North of Portugal. We tested the hypothesis that biological zonation on exposed sandy beaches would vary at the studied spatial scales. For this aim, abundance, diversity and structure of macrobenthic assemblages were examined at the scales of transect and beach. Moreover, the main environmental factors that could potentially drive zonation patterns were investigated. Univariate and multivariate analyses revealed that the number of biological zones ranged from two to three depending on the beach and from indistinct zonation to three zones at the scale of transect. Therefore, results support our working hypothesis because zonation patterns were not consistent at the studied spatial scales. The median particle size, sorting coefficient and water content were significantly correlated with zonation patterns of macrobenthic assemblages. However, a high degree of correlation was not reached when the total structure of the assemblage was considered.

Spatial dependence of predictions from image segmentation: a methods to determine appropriate scales for producing land-management information

USDA-ARS?s Scientific Manuscript database

A challenge in ecological studies is defining scales of observation that correspond to relevant ecological scales for organisms or processes. Image segmentation has been proposed as an alternative to pixel-based methods for scaling remotely-sensed data into ecologically-meaningful units. However, to...

Spatial patterns of frequent floods in Switzerland

NASA Astrophysics Data System (ADS)

Schneeberger, Klaus; Rössler, Ole; Weingartner, Rolf

2017-04-01

Information about the spatial characteristics of high and extreme streamflow is often needed for an accurate analysis of flood risk and effective co-ordination of flood related activities, such as flood defence planning. In this study we analyse the spatial dependence of frequent floods in Switzerland across different scales. Firstly, we determine the average length of high and extreme flow events for 56 runoff time series of Swiss rivers. Secondly, a dependence measure expressing the probability that streamflow peaks are as high as peaks at a conditional site is used to describe and map the spatial extend of joint occurrence of frequent floods across Switzerland. Thirdly, we apply a cluster analysis to identify groups of sites that are likely to react similarly in terms of joint occurrence of high flow events. The results indicate that a time interval with a length of 3 days seems to be most appropriate to characterise the average length of high streamflow events across spatial scales. In the main Swiss basins, high and extreme streamflows were found to be asymptotically independent. In contrast, at the meso-scale distinct flood regions, which react similarly in terms of occurrence of frequent flood, were found. The knowledge about these regions can help to optimise flood defence planning or to estimate regional flood risk properly.

Restricted cross-scale habitat selection by American beavers.

PubMed

Francis, Robert A; Taylor, Jimmy D; Dibble, Eric; Strickland, Bronson; Petro, Vanessa M; Easterwood, Christine; Wang, Guiming

2017-12-01

Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis (hereafter, beaver) has been studied at singular spatial scales, but to date no research addresses multi-scale selection. Our objectives were to determine if beaver habitat selection was specialized to semiaquatic habitats and if variables explaining habitat selection are consistent between landscape and fine spatial scales. We built maximum entropy (MaxEnt) models to relate landscape-scale presence-only data to landscape variables, and used generalized linear mixed models to evaluate fine spatial scale habitat selection using global positioning system (GPS) relocation data. Explanatory variables between the landscape and fine spatial scale were compared for consistency. Our findings suggested that beaver habitat selection at coarse (study area) and fine (within home range) scales was congruent, and was influenced by increasing amounts of woody wetland edge density and shrub edge density, and decreasing amounts of open water edge density. Habitat suitability at the landscape scale also increased with decreasing amounts of grass frequency. As territorial, central-place foragers, beavers likely trade-off open water edge density (i.e., smaller non-forested wetlands or lodges closer to banks) for defense and shorter distances to forage and obtain construction material. Woody plants along edges and expanses of open water for predator avoidance may limit beaver fitness and subsequently determine beaver habitat selection.

Restricted cross-scale habitat selection by American beavers

PubMed Central

Taylor, Jimmy D; Dibble, Eric; Strickland, Bronson; Petro, Vanessa M; Easterwood, Christine; Wang, Guiming

2017-01-01

Abstract Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis (hereafter, beaver) has been studied at singular spatial scales, but to date no research addresses multi-scale selection. Our objectives were to determine if beaver habitat selection was specialized to semiaquatic habitats and if variables explaining habitat selection are consistent between landscape and fine spatial scales. We built maximum entropy (MaxEnt) models to relate landscape-scale presence-only data to landscape variables, and used generalized linear mixed models to evaluate fine spatial scale habitat selection using global positioning system (GPS) relocation data. Explanatory variables between the landscape and fine spatial scale were compared for consistency. Our findings suggested that beaver habitat selection at coarse (study area) and fine (within home range) scales was congruent, and was influenced by increasing amounts of woody wetland edge density and shrub edge density, and decreasing amounts of open water edge density. Habitat suitability at the landscape scale also increased with decreasing amounts of grass frequency. As territorial, central-place foragers, beavers likely trade-off open water edge density (i.e., smaller non-forested wetlands or lodges closer to banks) for defense and shorter distances to forage and obtain construction material. Woody plants along edges and expanses of open water for predator avoidance may limit beaver fitness and subsequently determine beaver habitat selection. PMID:29492032

Dissecting the multi-scale spatial relationship of earthworm assemblages with soil environmental variability.

PubMed

Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre

2014-12-05

Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the spatial variation did not depend on the soil environmental variability for certain species. This finding could indicate the influence of contagious biotic interactions, stochastic factors, or unmeasured relevant soil environmental variables.

Evolution of scaling emergence in large-scale spatial epidemic spreading.

PubMed

Wang, Lin; Li, Xiang; Zhang, Yi-Qing; Zhang, Yan; Zhang, Kan

2011-01-01

Zipf's law and Heaps' law are two representatives of the scaling concepts, which play a significant role in the study of complexity science. The coexistence of the Zipf's law and the Heaps' law motivates different understandings on the dependence between these two scalings, which has still hardly been clarified. In this article, we observe an evolution process of the scalings: the Zipf's law and the Heaps' law are naturally shaped to coexist at the initial time, while the crossover comes with the emergence of their inconsistency at the larger time before reaching a stable state, where the Heaps' law still exists with the disappearance of strict Zipf's law. Such findings are illustrated with a scenario of large-scale spatial epidemic spreading, and the empirical results of pandemic disease support a universal analysis of the relation between the two laws regardless of the biological details of disease. Employing the United States domestic air transportation and demographic data to construct a metapopulation model for simulating the pandemic spread at the U.S. country level, we uncover that the broad heterogeneity of the infrastructure plays a key role in the evolution of scaling emergence. The analyses of large-scale spatial epidemic spreading help understand the temporal evolution of scalings, indicating the coexistence of the Zipf's law and the Heaps' law depends on the collective dynamics of epidemic processes, and the heterogeneity of epidemic spread indicates the significance of performing targeted containment strategies at the early time of a pandemic disease.

Floodplain complexity and surface metrics: influences of scale and geomorphology

USGS Publications Warehouse

Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.

2015-01-01

Many studies of fluvial geomorphology and landscape ecology examine a single river or landscape, thus lack generality, making it difficult to develop a general understanding of the linkages between landscape patterns and larger-scale driving variables. We examined the spatial complexity of eight floodplain surfaces in widely different geographic settings and determined how patterns measured at different scales relate to different environmental drivers. Floodplain surface complexity is defined as having highly variable surface conditions that are also highly organised in space. These two components of floodplain surface complexity were measured across multiple sampling scales from LiDAR-derived DEMs. The surface character and variability of each floodplain were measured using four surface metrics; namely, standard deviation, skewness, coefficient of variation, and standard deviation of curvature from a series of moving window analyses ranging from 50 to 1000 m in radius. The spatial organisation of each floodplain surface was measured using spatial correlograms of the four surface metrics. Surface character, variability, and spatial organisation differed among the eight floodplains; and random, fragmented, highly patchy, and simple gradient spatial patterns were exhibited, depending upon the metric and window size. Differences in surface character and variability among the floodplains became statistically stronger with increasing sampling scale (window size), as did their associations with environmental variables. Sediment yield was consistently associated with differences in surface character and variability, as were flow discharge and variability at smaller sampling scales. Floodplain width was associated with differences in the spatial organization of surface conditions at smaller sampling scales, while valley slope was weakly associated with differences in spatial organisation at larger scales. A comparison of floodplain landscape patterns measured at different scales would improve our understanding of the role that different environmental variables play at different scales and in different geomorphic settings.

Scale-dependent CMB power asymmetry from primordial speed of sound and a generalized δ N formalism

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

Wang, Dong-Gang; Cai, Yi-Fu; Zhao, Wen

2016-02-01

We explore a plausible mechanism that the hemispherical power asymmetry in the CMB is produced by the spatial variation of the primordial sound speed parameter. We suggest that in a generalized approach of the δ N formalism the local e-folding number may depend on some other primordial parameters besides the initial values of inflaton. Here the δ N formalism is extended by considering the effects of a spatially varying sound speed parameter caused by a super-Hubble perturbation of a light field. Using this generalized δ N formalism, we systematically calculate the asymmetric primordial spectrum in the model of multi-speed inflation by taking intomore » account the constraints of primordial non-Gaussianities. We further discuss specific model constraints, and the corresponding asymmetry amplitudes are found to be scale-dependent, which can accommodate current observations of the power asymmetry at different length scales.« less

Implementation of a flow-dependent background error correlation length scale formulation in the NEMOVAR OSTIA system

NASA Astrophysics Data System (ADS)

Fiedler, Emma; Mao, Chongyuan; Good, Simon; Waters, Jennifer; Martin, Matthew

2017-04-01

OSTIA is the Met Office's Operational Sea Surface Temperature (SST) and Ice Analysis system, which produces L4 (globally complete, gridded) analyses on a daily basis. Work is currently being undertaken to replace the original OI (Optimal Interpolation) data assimilation scheme with NEMOVAR, a 3D-Var data assimilation method developed for use with the NEMO ocean model. A dual background error correlation length scale formulation is used for SST in OSTIA, as implemented in NEMOVAR. Short and long length scales are combined according to the ratio of the decomposition of the background error variances into short and long spatial correlations. The pre-defined background error variances vary spatially and seasonally, but not on shorter time-scales. If the derived length scales applied to the daily analysis are too long, SST features may be smoothed out. Therefore a flow-dependent component to determining the effective length scale has also been developed. The total horizontal gradient of the background SST field is used to identify regions where the length scale should be shortened. These methods together have led to an improvement in the resolution of SST features compared to the previous OI analysis system, without the introduction of spurious noise. This presentation will show validation results for feature resolution in OSTIA using the OI scheme, the dual length scale NEMOVAR scheme, and the flow-dependent implementation.

Seed harvesting by a generalist consumer is context-dependent: Interactive effects across multiple spatial scales

USGS Publications Warehouse

Ostoja, Steven M.; Schupp, Eugene W.; Klinger, Rob

2013-01-01

Granivore foraging decisions affect consumer success and determine the quantity and spatial pattern of seed survival. These decisions are influenced by environmental variation at spatial scales ranging from landscapes to local foraging patches. In a field experiment, the effects of seed patch variation across three spatial scales on seed removal by western harvester ants Pogonomyrmex occidentalis were evaluated. At the largest scale we assessed harvesting in different plant communities, at the intermediate scale we assessed harvesting at different distances from ant mounds, and at the smallest scale we assessed the effects of interactions among seed species in local seed neighborhoods on seed harvesting (i.e. resource–consumer interface). Selected seed species were presented alone (monospecific treatment) and in mixture with Bromus tectorum (cheatgrass; mixture treatment) at four distances from P. occidentalis mounds in adjacent intact sagebrush and non-native cheatgrass-dominated communities in the Great Basin, Utah, USA. Seed species differed in harvest, with B. tectorum being least preferred. Large and intermediate scale variation influenced harvest. More seeds were harvested in sagebrush than in cheatgrass-dominated communities (largest scale), and the quantity of seed harvested varied with distance from mounds (intermediate-scale), although the form of the distance effect differed between plant communities. At the smallest scale, seed neighborhood affected harvest, but the patterns differed among seed species considered. Ants harvested fewer seeds from mixed-seed neighborhoods than from monospecific neighborhoods, suggesting context dependence and potential associational resistance. Further, the effects of plant community and distance from mound on seed harvest in mixtures differed from their effects in monospecific treatments. Beyond the local seed neighborhood, selection of seed resources is better understood by simultaneously evaluating removal at multiple scales. Associational effects provide a useful theoretical basis for better understanding harvester ant foraging decisions. These results demonstrate the importance of ecological context for seed removal, which has implications for seed pools, plant populations and communities.

Effect of spatial and temporal scales on habitat suitability modeling: A case study of Ommastrephes bartramii in the northwest pacific ocean

NASA Astrophysics Data System (ADS)

Gong, Caixia; Chen, Xinjun; Gao, Feng; Tian, Siquan

2014-12-01

Temporal and spatial scales play important roles in fishery ecology, and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution. The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling, with the western stock of winter-spring cohort of neon flying squid ( Ommastrephes bartramii) in the northwest Pacific Ocean as an example. In this study, the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature (SST) from remote sensing during August to October of 2003-2008 were used. We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales (0.5°, 1° and 2°), four longitude scales (0.5°, 1°, 2° and 4°), and three temporal scales (week, fortnight, and month). The coefficients of variation (CV) of the weekly, biweekly and monthly suitability index (SI) were compared to determine which temporal and spatial scales of SI model are more precise. This study shows that the optimal temporal and spatial scales with the lowest CV are month, and 0.5° latitude and 0.5° longitude for O. bartramii in the northwest Pacific Ocean. This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts. We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.

Can basin land use effects on physical characteristics of streams be determined at broad geographic scales?

USGS Publications Warehouse

Goldstein, R.M.; Carlisle, D.M.; Meador, M.R.; Short, T.M.

2007-01-01

The environmental setting (e.g., climate, topography, geology) and land use affect stream physical characteristics singly and cumulatively. At broad geographic scales, we determined the importance of environmental setting and land use in explaining variation in stream physical characteristics. We hypothesized that as the spatial scale decreased from national to regional, land use would explain more of the variation in stream physical characteristics because environmental settings become more homogeneous. At a national scale, stepwise linear regression indicated that environmental setting was more important in explaining variability in stream physical characteristics. Although statistically discernible, the amount of variation explained by land use was not remarkable due to low partial correlations. At level II ecoregion spatial scales (southeastern USA plains, central USA plains, and a combination of the western Cordillera and the western interior basins and ranges), environmental setting variables were again more important predictors of stream physical characteristics, however, as the spatial scale decreased from national to regional, the portion of variability in stream physical characteristics explained by basin land use increased. Development of stream habitat indicators of land use will depend upon an understanding of relations between stream physical characteristics and environmental factors at multiple spatial scales. Smaller spatial scales will be necessary to reduce the confounding effects of variable environmental settings before the effects of land use can be reliably assessed. ?? Springer Science+Business Media B.V. 2006.

Sensitivity of landscape metrics to changing scale of remote sensing data in spatial pattern analysis: effect, criticality and scaling.

NASA Astrophysics Data System (ADS)

Xu, C.; Zhao, S.; Zhao, B.

2017-12-01

Spatial heterogeneity is scale-dependent, that is, the quantification and representation of spatial pattern vary with the resolution and extent. Overwhelming practices focused on scale effect of landscape metrics, and predicable scaling relationships found among some of them are thought to be the most effective and precise way to quantify multi-scale characteristics. However, previous studies tended to consider a narrow range of scales, and few focused on the critical threshold of scaling function. Here we examine the scalograms of 38 widely-used landscape-level metrics in a more integral spectrum of grain size among 96 landscapes with various extent (i.e. from 25km2 up towards to 221 km2), which sampled randomly from NLCD product. Our goal is to explore the existence of scaling domain and whether the response of metrics to changing resolution would be influenced by spatial extent. Results clearly show the existence of scaling domain for 13 of them (Type II), while the behaviors of other 13 (Type I) exhibit simple scaling functions and the rest (Type III) demonstrate various forms like no obvious change or fluctuation across the integral spectrum of grain size. In addition, an invariant power law scaling relationship was found between critical resolution and spatial extent for metrics falling into Type II, as the critical resolution is proportional to Eρ (ρ is a constant, and E is the extent). All the scaling exponents (ρ) are positive, suggesting that the critical resolutions for these characteristics of landscape structure can be relaxed as the spatial extent expands. This agrees well with empirical perception that coarser grain size might be allowed for spatial data with larger extent. Furthermore, the parameters of scaling functions for metrics falling into Type I and Type II vary with spatial extent, and power law or logarithmic relationships could be identified between them for some metrics. Our finding support the existence of self-organized criticality for a hierarchically-structured landscape. Although the underlying mechanism driving the scaling relationship remains unclear, it could provide guidance toward general principles in spatial pattern analysis and on selecting the proper resolution to avoid the misrepresentation of spatial pattern and profound biases in further ecological progress research.

The relative influence of habitat amount and configuration on genetic structure across multiple spatial scales

PubMed Central

Millette, Katie L; Keyghobadi, Nusha

2015-01-01

Despite strong interest in understanding how habitat spatial structure shapes the genetics of populations, the relative importance of habitat amount and configuration for patterns of genetic differentiation remains largely unexplored in empirical systems. In this study, we evaluate the relative influence of, and interactions among, the amount of habitat and aspects of its spatial configuration on genetic differentiation in the pitcher plant midge, Metriocnemus knabi. Larvae of this species are found exclusively within the water-filled leaves of pitcher plants (Sarracenia purpurea) in a system that is naturally patchy at multiple spatial scales (i.e., leaf, plant, cluster, peatland). Using generalized linear mixed models and multimodel inference, we estimated effects of the amount of habitat, patch size, interpatch distance, and patch isolation, measured at different spatial scales, on genetic differentiation (FST) among larval samples from leaves within plants, plants within clusters, and clusters within peatlands. Among leaves and plants, genetic differentiation appears to be driven by female oviposition behaviors and is influenced by habitat isolation at a broad (peatland) scale. Among clusters, gene flow is spatially restricted and aspects of both the amount of habitat and configuration at the focal scale are important, as is their interaction. Our results suggest that both habitat amount and configuration can be important determinants of genetic structure and that their relative influence is scale dependent. PMID:25628865

The relative influence of habitat amount and configuration on genetic structure across multiple spatial scales.

PubMed

Millette, Katie L; Keyghobadi, Nusha

2015-01-01

Despite strong interest in understanding how habitat spatial structure shapes the genetics of populations, the relative importance of habitat amount and configuration for patterns of genetic differentiation remains largely unexplored in empirical systems. In this study, we evaluate the relative influence of, and interactions among, the amount of habitat and aspects of its spatial configuration on genetic differentiation in the pitcher plant midge, Metriocnemus knabi. Larvae of this species are found exclusively within the water-filled leaves of pitcher plants (Sarracenia purpurea) in a system that is naturally patchy at multiple spatial scales (i.e., leaf, plant, cluster, peatland). Using generalized linear mixed models and multimodel inference, we estimated effects of the amount of habitat, patch size, interpatch distance, and patch isolation, measured at different spatial scales, on genetic differentiation (F ST) among larval samples from leaves within plants, plants within clusters, and clusters within peatlands. Among leaves and plants, genetic differentiation appears to be driven by female oviposition behaviors and is influenced by habitat isolation at a broad (peatland) scale. Among clusters, gene flow is spatially restricted and aspects of both the amount of habitat and configuration at the focal scale are important, as is their interaction. Our results suggest that both habitat amount and configuration can be important determinants of genetic structure and that their relative influence is scale dependent.

Multiscale spatial and temporal estimation of the b-value

NASA Astrophysics Data System (ADS)

García-Hernández, R.; D'Auria, L.; Barrancos, J.; Padilla, G.

2017-12-01

The estimation of the spatial and temporal variations of the Gutenberg-Richter b-value is of great importance in different seismological applications. One of the problems affecting its estimation is the heterogeneous distribution of the seismicity which makes its estimate strongly dependent upon the selected spatial and/or temporal scale. This is especially important in volcanoes where dense clusters of earthquakes often overlap the background seismicity. Proposed solutions for estimating temporal variations of the b-value include considering equally spaced time intervals or variable intervals having an equal number of earthquakes. Similar approaches have been proposed to image the spatial variations of this parameter as well.We propose a novel multiscale approach, based on the method of Ogata and Katsura (1993), allowing a consistent estimation of the b-value regardless of the considered spatial and/or temporal scales. Our method, named MUST-B (MUltiscale Spatial and Temporal characterization of the B-value), basically consists in computing estimates of the b-value at multiple temporal and spatial scales, extracting for a give spatio-temporal point a statistical estimator of the value, as well as and indication of the characteristic spatio-temporal scale. This approach includes also a consistent estimation of the completeness magnitude (Mc) and of the uncertainties over both b and Mc.We applied this method to example datasets for volcanic (Tenerife, El Hierro) and tectonic areas (Central Italy) as well as an example application at global scale.

Network analysis reveals multiscale controls on streamwater chemistry

USGS Publications Warehouse

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

Network analysis reveals multiscale controls on streamwater chemistry

PubMed Central

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks. PMID:24753575

Network analysis reveals multiscale controls on streamwater chemistry.

PubMed

McGuire, Kevin J; Torgersen, Christian E; Likens, Gene E; Buso, Donald C; Lowe, Winsor H; Bailey, Scott W

2014-05-13

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

Spatial dependence of predictions from image segmentation: A variogram-based method to determine appropriate scales for producing land-management information

USDA-ARS?s Scientific Manuscript database

A significant challenge in ecological studies has been defining scales of observation that correspond to the relevant ecological scales for organisms or processes of interest. Remote sensing has become commonplace in ecological studies and management, but the default resolution of imagery often used...

Capturing subregional variability in regional-scale climate change vulnerability assessments of natural resources

Treesearch

Polly C. Buotte; David L. Peterson; Kevin S. McKelvey; Jeffrey A. Hicke

2016-01-01

Natural resource vulnerability to climate change can depend on the climatology and ecological conditions at a particular site. Here we present a conceptual framework for incorporating spatial variability in natural resource vulnerability to climate change in a regional-scale assessment. The framework was implemented in the first regional-scale vulnerability...

Different modelling approaches to evaluate nitrogen transport and turnover at the watershed scale

NASA Astrophysics Data System (ADS)

Epelde, Ane Miren; Antiguedad, Iñaki; Brito, David; Jauch, Eduardo; Neves, Ramiro; Garneau, Cyril; Sauvage, Sabine; Sánchez-Pérez, José Miguel

2016-08-01

This study presents the simulation of hydrological processes and nutrient transport and turnover processes using two integrated numerical models: Soil and Water Assessment Tool (SWAT) (Arnold et al., 1998), an empirical and semi-distributed numerical model; and Modelo Hidrodinâmico (MOHID) (Neves, 1985), a physics-based and fully distributed numerical model. This work shows that both models reproduce satisfactorily water and nitrate exportation at the watershed scale at annual and daily basis, MOHID providing slightly better results. At the watershed scale, both SWAT and MOHID simulated similarly and satisfactorily the denitrification amount. However, as MOHID numerical model was the only one able to reproduce adequately the spatial variation of the soil hydrological conditions and water table level fluctuation, it proved to be the only model able of reproducing the spatial variation of the nutrient cycling processes that are dependent to the soil hydrological conditions such as the denitrification process. This evidences the strength of the fully distributed and physics-based models to simulate the spatial variability of nutrient cycling processes that are dependent to the hydrological conditions of the soils.

Multi-scale variation in spatial heterogeneity for microbial community structure in an eastern Virginia agricultural field

NASA Technical Reports Server (NTRS)

Franklin, Rima B.; Mills, Aaron L.

2003-01-01

To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of community structure in a wheat field in eastern Virginia (USA). Nearly 200 soil samples were collected at a variety of separation distances ranging from 2.5 cm to 11 m. Whole-community DNA was extracted from each sample, and community structure was compared using amplified fragment length polymorphism (AFLP) DNA fingerprinting. Relative similarity was calculated between each pair of samples and compared using geostatistical variogram analysis to study autocorrelation as a function of separation distance. Spatial autocorrelation was found at scales ranging from 30 cm to more than 6 m, depending on the sampling extent considered. In some locations, up to four different correlation length scales were detected. The presence of nested scales of variability suggests that the environmental factors regulating the development of the communities in this soil may operate at different scales. Kriging was used to generate maps of the spatial organization of communities across the plot, and the results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot, and this is thought to be due to the variable response of individual populations to spatial heterogeneity associated with soil properties. c2003 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

NASA Astrophysics Data System (ADS)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are weak, especially when more stringent conditions are imposed (i.e. when T is very high), except at the monthly scale.

Evolution of Scaling Emergence in Large-Scale Spatial Epidemic Spreading

PubMed Central

Wang, Lin; Li, Xiang; Zhang, Yi-Qing; Zhang, Yan; Zhang, Kan

2011-01-01

Background Zipf's law and Heaps' law are two representatives of the scaling concepts, which play a significant role in the study of complexity science. The coexistence of the Zipf's law and the Heaps' law motivates different understandings on the dependence between these two scalings, which has still hardly been clarified. Methodology/Principal Findings In this article, we observe an evolution process of the scalings: the Zipf's law and the Heaps' law are naturally shaped to coexist at the initial time, while the crossover comes with the emergence of their inconsistency at the larger time before reaching a stable state, where the Heaps' law still exists with the disappearance of strict Zipf's law. Such findings are illustrated with a scenario of large-scale spatial epidemic spreading, and the empirical results of pandemic disease support a universal analysis of the relation between the two laws regardless of the biological details of disease. Employing the United States domestic air transportation and demographic data to construct a metapopulation model for simulating the pandemic spread at the U.S. country level, we uncover that the broad heterogeneity of the infrastructure plays a key role in the evolution of scaling emergence. Conclusions/Significance The analyses of large-scale spatial epidemic spreading help understand the temporal evolution of scalings, indicating the coexistence of the Zipf's law and the Heaps' law depends on the collective dynamics of epidemic processes, and the heterogeneity of epidemic spread indicates the significance of performing targeted containment strategies at the early time of a pandemic disease. PMID:21747932

Spatial multi-scale variability of soil nutrients in relation to environmental factors in a typical agricultural region, eastern China.

PubMed

Liu, Yang; Lv, Jianshu; Zhang, Bing; Bi, Jun

2013-04-15

Identifying the sources of spatial variability and deficiency risk of soil nutrients is a crucial issue for soil and agriculture management. A total of 1247 topsoil samples (0-20 cm) were collected at the nodes of a 2×2 km grid in Rizhao City and the contents of soil organic carbon (OC), total nitrogen (TN), and total phosphorus (TP) were determined. Factorial kriging analysis (FKA), stepwise multiple regression, and indicator kriging (IK) were appled to investigate the scale dependent correlations among soil nutrients, identify the sources of spatial variability at each spatial scale, and delineate the potential risk of soil nutrient deficiency. Linear model of co-regionalization (LMC) fitting indicated that the presence of multi-scale variation was comprised of nugget effect, an exponential structure with a range of 12 km (local scale), and a spherical structure with a range of 84 km (regional scale). The short-range variation of OC and TN was mainly dominated by land use types, and TP was controlled by terrain. At long-range scale, spatial variation of OC, TN, and TP was dominated by parent material. Indicator kriging maps depicted the probability of soil nutrient deficiency compared with the background values in eastern Shandong province. The high deficiency risk area of all nutrient integration was mainly located in eastern and northwestern parts. Copyright © 2013 Elsevier B.V. All rights reserved.

Theories of Simplification and Scaling of Spatially Distributed Processes. Chapter 12

NASA Technical Reports Server (NTRS)

Levin, Simon A.; Pacala, Stephen W.

1997-01-01

The problem of scaling is at the heart of ecological theory, the essence of understanding and of the development of a predictive capability. The description of any system depends on the spatial, temporal, and organizational perspective chosen; hence it is essential to understand not only how patterns and dynamics vary with scale, but also how patterns at one scale are manifestations of processes operating at other scales. Evolution has shaped the characteristics of species in ways that result in scale displacement: Each species experiences the environment at its own unique set of spatial and temporal scales and interfaces the biota through unique assemblages of phenotypes. In this way, coexistence becomes possible, and biodiversity is enhanced. By averaging over space, time, and biological interactions, a genotype filters variation at fine scales and selects the arena in which it will face the vicissitudes of nature. Variation at finer scales is then noise, of minor importance to the survival and dynamics of the species, and consequently of minor importance in any attempt at description. In attempting to model ecological interactions in space, contributors throughout this book have struggled with a trade-off between simplification and "realistic" complexity and detail. Although the challenge of simplification is widely recognized in ecology, less appreciated is the intertwining of scaling questions and scaling laws with the process of simplification. In the context of this chapter simplification will in general mean the use of spatial or ensemble means and low-order moments to capture more detailed interactions by integrating over given areas. In this way, one can derive descriptions of the system at different spatial scales, which provides the essentials for the extraction of scaling laws by examination of how system properties vary with scale.

Thermal maps of Jupiter - Spatial organization and time dependence of stratospheric temperatures, 1980 to 1990

NASA Technical Reports Server (NTRS)

Orton, Glenn S.; Friedson, A. James; Baines, Kevin H.; Martin, Terry Z.; West, Robert A.; Caldwell, John; Hammel, Heidi B.; Bergstralh, Jay T.; Malcolm, Michael E.

1991-01-01

The spatial organization and time dependence of Jupiter's stratospheric temperatures have been measured by observing thermal emission from the 7.8-micrometer CH4 band. These temperatures, observed through the greater part of a Jovian year, exhibit the influence of seasonal radiative forcing. Distinct bands of high temperature are located at the poles and midlatitudes, while the equator alternates between warm and cold with a period of approximately 4 years. Substantial longitudinal variability is often observed within the warm midlatitude bands, and occasionally elsewhere on the planet. This variability includes small, localized structures, as well as large-scale waves with wavelengths longer than about 30,000 kilometers. The amplitudes of the waves vary on a time scale of about 1 month; structures on a smaller scale may have lifetimes of only days. Waves observed in 1985, 1987, and 1988 propagated with group velocities less than + or - 30 meters/sec.

Facing the scaling problem: A multi-methodical approach to simulate soil erosion at hillslope and catchment scale

NASA Astrophysics Data System (ADS)

Schmengler, A. C.; Vlek, P. L. G.

2012-04-01

Modelling soil erosion requires a holistic understanding of the sediment dynamics in a complex environment. As most erosion models are scale-dependent and their parameterization is spatially limited, their application often requires special care, particularly in data-scarce environments. This study presents a hierarchical approach to overcome the limitations of a single model by using various quantitative methods and soil erosion models to cope with the issues of scale. At hillslope scale, the physically-based Water Erosion Prediction Project (WEPP)-model is used to simulate soil loss and deposition processes. Model simulations of soil loss vary between 5 to 50 t ha-1 yr-1 dependent on the spatial location on the hillslope and have only limited correspondence with the results of the 137Cs technique. These differences in absolute soil loss values could be either due to internal shortcomings of each approach or to external scale-related uncertainties. Pedo-geomorphological soil investigations along a catena confirm that estimations by the 137Cs technique are more appropriate in reflecting both the spatial extent and magnitude of soil erosion at hillslope scale. In order to account for sediment dynamics at a larger scale, the spatially-distributed WaTEM/SEDEM model is used to simulate soil erosion at catchment scale and to predict sediment delivery rates into a small water reservoir. Predicted sediment yield rates are compared with results gained from a bathymetric survey and sediment core analysis. Results show that specific sediment rates of 0.6 t ha-1 yr-1 by the model are in close agreement with observed sediment yield calculated from stratigraphical changes and downcore variations in 137Cs concentrations. Sediment erosion rates averaged over the entire catchment of 1 to 2 t ha-1 yr-1 are significantly lower than results obtained at hillslope scale confirming an inverse correlation between the magnitude of erosion rates and the spatial scale of the model. The study has shown that the use of multiple methods facilitates the calibration and validation of models and might provide a more accurate measure for soil erosion rates in ungauged catchments. Moreover, the approach could be used to identify the most appropriate working and operational scales for soil erosion modelling.

Two-particle microrheology of quasi-2D viscous systems.

PubMed

Prasad, V; Koehler, S A; Weeks, Eric R

2006-10-27

We study the spatially correlated motions of colloidal particles in a quasi-2D system (human serum albumin protein molecules at an air-water interface) for different surface viscosities eta s. We observe a transition in the behavior of the correlated motion, from 2D interface dominated at high eta s to bulk fluid dependent at low eta s. The correlated motions can be scaled onto a master curve which captures the features of this transition. This master curve also characterizes the spatial dependence of the flow field of a viscous interface in response to a force. The scale factors used for the master curve allow for the calculation of the surface viscosity eta s that can be compared to one-particle measurements.

On the effects of scale for ecosystem services mapping

USGS Publications Warehouse

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

On the Effects of Scale for Ecosystem Services Mapping

PubMed Central

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability. PMID:25549256

On the effects of scale for ecosystem services mapping.

PubMed

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

An intercomparison of remotely sensed soil moisture products at various spatial scales over the Iberian penisula

USDA-ARS?s Scientific Manuscript database

Soil moisture (SM) can be retrieved from active microwave (AM)-, passive microwave (PM)- and thermal infrared (TIR)-observations, each having their unique spatial- and temporal-coverage. A limitation of TIR-based SM retrievals is its dependency on cloud-free conditions, while microwave retrievals ar...

Spatial dynamics of large-scale, multistage crab (Callinectes sapidus) dispersal: Determinants and consequences for recruitment

USGS Publications Warehouse

Etherington, L.L.; Eggleston, D.B.

2003-01-01

We assessed determinants and consequences of multistage dispersal on spatial recruitment of the blue crab, Callinectes sapidus, within the Croatan, Albemarle, Pamlico Estuarine System (CAPES), North Carolina, U.S.A. Large-scale sampling of early juvenile crabs over 4 years indicated that spatial abundance patterns were size-dependent and resulted from primary post-larval dispersal (pre-settlement) and secondary juvenile dispersal (early post-settlement). In general, primary dispersal led to high abundances within more seaward habitats, whereas secondary dispersal (which was relatively consistent) expanded the distribution of juveniles, potentially increasing the estuarine nursery capacity. There were strong relationships between juvenile crab density and specific wind characteristics; however, these patterns were spatially explicit. Various physical processes (e.g., seasonal wind events, timing and magnitude of tropical cyclones) interacted to influence dispersal during multiple stages and determined crab recruitment patterns. Our results suggest that the nursery value of different habitats is highly dependent on the dispersal potential (primary and secondary dispersal) to and from these areas, which is largely determined by the relative position of habitats within the estuarine landscape.

Combining participatory and socioeconomic approaches to map fishing effort in small-scale fisheries.

PubMed

Thiault, Lauric; Collin, Antoine; Chlous, Frédérique; Gelcich, Stefan; Claudet, Joachim

2017-01-01

Mapping the spatial allocation of fishing effort while including key stakeholders in the decision making process is essential for effective fisheries management but is difficult to implement in complex small-scale fisheries that are diffuse, informal and multifaceted. Here we present a standardized but flexible approach that combines participatory mapping approaches (fishers' spatial preference for fishing grounds, or fishing suitability) with socioeconomic approaches (spatial extrapolation of social surrogates, or fishing capacity) to generate a comprehensive map of predicted fishing effort. Using a real world case study, in Moorea, French Polynesia, we showed that high predicted fishing effort is not simply located in front of, or close to, main fishing villages with high dependence on marine resources; it also occurs where resource dependency is moderate and generally in near-shore areas and reef passages. The integrated approach we developed can contribute to addressing the recurrent lack of fishing effort spatial data through key stakeholders' (i.e., resource users) participation. It can be tailored to a wide range of social, ecological and data availability contexts, and should help improve place-based management of natural resources.

Combining participatory and socioeconomic approaches to map fishing effort in small-scale fisheries

PubMed Central

Collin, Antoine; Chlous, Frédérique; Gelcich, Stefan; Claudet, Joachim

2017-01-01

Mapping the spatial allocation of fishing effort while including key stakeholders in the decision making process is essential for effective fisheries management but is difficult to implement in complex small-scale fisheries that are diffuse, informal and multifaceted. Here we present a standardized but flexible approach that combines participatory mapping approaches (fishers’ spatial preference for fishing grounds, or fishing suitability) with socioeconomic approaches (spatial extrapolation of social surrogates, or fishing capacity) to generate a comprehensive map of predicted fishing effort. Using a real world case study, in Moorea, French Polynesia, we showed that high predicted fishing effort is not simply located in front of, or close to, main fishing villages with high dependence on marine resources; it also occurs where resource dependency is moderate and generally in near-shore areas and reef passages. The integrated approach we developed can contribute to addressing the recurrent lack of fishing effort spatial data through key stakeholders' (i.e., resource users) participation. It can be tailored to a wide range of social, ecological and data availability contexts, and should help improve place-based management of natural resources. PMID:28486509

Spatial correlations of Diceroprocta apache and its host plants: Evidence for a negative impact from Tamarix invasion

USGS Publications Warehouse

Ellingson, A.R.; Andersen, D.C.

2002-01-01

1. The hypothesis that the habitat-scale spatial distribution of the, Apache cicada Diceroprocta apache Davis is unaffected by the presence of the invasive exotic saltcedar Tamarix ramosissima was tested using data from 205 1-m2 quadrats placed within the flood-plain of the Bill Williams River, Arizona, U.S.A. Spatial dependencies within and between cicada density and habitat variables were estimated using Moran's I and its bivariate analogue to discern patterns and associations at spatial scales from 1 to 30 m. 2. Apache cicadas were spatially aggregated in high-density clusters averaging 3m in diameter. A positive association between cicada density, estimated by exuvial density, and the per cent canopy cover of a native tree, Goodding's willow Salix gooddingii, was detected in a non-spatial correlation analysis. No non-spatial association between cicada density and saltcedar canopy cover was detected. 3. Tests for spatial cross-correlation using the bivariate IYZ indicated the presence of a broad-scale negative association between cicada density and saltcedar canopy cover. This result suggests that large continuous stands of saltcedar are associated with reduced cicada density. In contrast, positive associations detected at spatial scales larger than individual quadrats suggested a spill-over of high cicada density from areas featuring Goodding's willow canopy into surrounding saltcedar monoculture. 4. Taken together and considered in light of the Apache cicada's polyphagous habits, the observed spatial patterns suggest that broad-scale factors such as canopy heterogeneity affect cicada habitat use more than host plant selection. This has implications for management of lower Colorado River riparian woodlands to promote cicada presence and density through maintenance or creation of stands of native trees as well as manipulation of the characteristically dense and homogeneous saltcedar canopies.

Spatial correlations of Diceroprocta apache and its host plants: Evidence for a negative impact from Tamarix invasion

USGS Publications Warehouse

Ellingson, A.R.; Andersen, D.C.

2002-01-01

1. The hypothesis that the habitat-scale spatial distribution of the Apache cicada Diceroprocta apache Davis is unaffected by the presence of the invasive exotic saltcedar Tamarix ramosissima was tested using data from 205 1-m2 quadrats placed within the flood-plain of the Bill Williams River, Arizona, U.S.A. Spatial dependencies within and between cicada density and habitat variables were estimated using Moran's I and its bivariate analogue to discern patterns and associations at spatial scales from 1 to 30 m.2. Apache cicadas were spatially aggregated in high-density clusters averaging 3 m in diameter. A positive association between cicada density, estimated by exuvial density, and the per cent canopy cover of a native tree, Goodding's willow Salix gooddingii, was detected in a non-spatial correlation analysis. No non-spatial association between cicada density and saltcedar canopy cover was detected.3. Tests for spatial cross-correlation using the bivariate IYZ indicated the presence of a broad-scale negative association between cicada density and saltcedar canopy cover. This result suggests that large continuous stands of saltcedar are associated with reduced cicada density. In contrast, positive associations detected at spatial scales larger than individual quadrats suggested a spill-over of high cicada density from areas featuring Goodding's willow canopy into surrounding saltcedar monoculture.4. Taken together and considered in light of the Apache cicada's polyphagous habits, the observed spatial patterns suggest that broad-scale factors such as canopy heterogeneity affect cicada habitat use more than host plant selection. This has implications for management of lower Colorado River riparian woodlands to promote cicada presence and density through maintenance or creation of stands of native trees as well as manipulation of the characteristically dense and homogeneous saltcedar canopies.

Spectral Dimensionality and Scale of Urban Radiance

NASA Technical Reports Server (NTRS)

Small, Christopher

2001-01-01

Characterization of urban radiance and reflectance is important for understanding the effects of solar energy flux on the urban environment as well as for satellite mapping of urban settlement patterns. Spectral mixture analyses of Landsat and Ikonos imagery suggest that the urban radiance field can very often be described with combinations of three or four spectral endmembers. Dimensionality estimates of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) radiance measurements of urban areas reveal the existence of 30 to 60 spectral dimensions. The extent to which broadband imagery collected by operational satellites can represent the higher dimensional mixing space is a function of both the spatial and spectral resolution of the sensor. AVIRIS imagery offers the spatial and spectral resolution necessary to investigate the scale dependence of the spectral dimensionality. Dimensionality estimates derived from Minimum Noise Fraction (MNF) eigenvalue distributions show a distinct scale dependence for AVIRIS radiance measurements of Milpitas, California. Apparent dimensionality diminishes from almost 40 to less than 10 spectral dimensions between scales of 8000 m and 300 m. The 10 to 30 m scale of most features in urban mosaics results in substantial spectral mixing at the 20 m scale of high altitude AVIRIS pixels. Much of the variance at pixel scales is therefore likely to result from actual differences in surface reflectance at pixel scales. Spatial smoothing and spectral subsampling of AVIRIS spectra both result in substantial loss of information and reduction of apparent dimensionality, but the primary spectral endmembers in all cases are analogous to those found in global analyses of Landsat and Ikonos imagery of other urban areas.

Spatial distribution and optimal harvesting of an age-structured population in a fluctuating environment.

PubMed

Engen, Steinar; Lee, Aline Magdalena; Sæther, Bernt-Erik

2018-02-01

We analyze a spatial age-structured model with density regulation, age specific dispersal, stochasticity in vital rates and proportional harvesting. We include two age classes, juveniles and adults, where juveniles are subject to logistic density dependence. There are environmental stochastic effects with arbitrary spatial scales on all birth and death rates, and individuals of both age classes are subject to density independent dispersal with given rates and specified distributions of dispersal distances. We show how to simulate the joint density fields of the age classes and derive results for the spatial scales of all spatial autocovariance functions for densities. A general result is that the squared scale has an additive term equal to the squared scale of the environmental noise, corresponding to the Moran effect, as well as additive terms proportional to the dispersal rate and variance of dispersal distance for the age classes and approximately inversely proportional to the strength of density regulation. We show that the optimal harvesting strategy in the deterministic case is to harvest only juveniles when their relative value (e.g. financial) is large, and otherwise only adults. With increasing environmental stochasticity there is an interval of increasing length of values of juveniles relative to adults where both age classes should be harvested. Harvesting generally tends to increase all spatial scales of the autocovariances of densities. Copyright © 2017. Published by Elsevier Inc.

When at what scale will trends in European mean and heavy precipitation emerge

NASA Astrophysics Data System (ADS)

Maraun, Douglas

2013-04-01

A multi-model ensemble of regional climate projections for Europe is employed to investigate how the time of emergence (TOE) for seasonal sums and maxima of daily precipitation depends on spatial scale. The TOE is redefined for emergence from internal variability only, the spread of the TOE due to imperfect climate model formulation is used as a measure of uncertainty in the TOE itself. Thereby the TOE becomes a fundamentally limiting time scale and translates into a minimum spatial scale on which robust conclusions can be drawn about precipitation trends. Thus also minimum temporal and spatial scales for adaptation planning are given. In northern Europe, positive winter trends in mean and heavy precipitation, in southwestern and southeastern Europe summer trends in mean precipitation emerge already within the next decades. Yet across wide areas, especially for heavy summer precipitation, the local trend emerges only late in the 21st century or later. For precipitation averaged to larger scales, the trend in general emerges earlier. Douglas Maraun, When at what scale will trends in European mean and heavy precipitation emerge? Env. Res. Lett., in press, 2013.

Disentangling Puzzles of Spatial Scales and Participation in Environmental Governance—The Case of Governance Re-scaling Through the European Water Framework Directive

NASA Astrophysics Data System (ADS)

Newig, Jens; Schulz, Daniel; Jager, Nicolas W.

2016-12-01

This article attempts to shed new light on prevailing puzzles of spatial scales in multi-level, participatory governance as regards the democratic legitimacy and environmental effectiveness of governance systems. We focus on the governance re-scaling by the European Water Framework Directive, which introduced new governance scales (mandated river basin management) and demands consultation of citizens and encourages `active involvement' of stakeholders. This allows to examine whether and how re-scaling through deliberate governance interventions impacts on democratic legitimacy and effective environmental policy delivery. To guide the enquiry, this article organizes existing—partly contradictory—claims on the relation of scale, democratic legitimacy, and environmental effectiveness into three clusters of mechanisms, integrating insights from multi-level governance, social-ecological systems, and public participation. We empirically examine Water Framework Directive implementation in a comparative case study of multi-level systems in the light of the suggested mechanisms. We compare two planning areas in Germany: North Rhine Westphalia and Lower Saxony. Findings suggest that the Water Framework Directive did have some impact on institutionalizing hydrological scales and participation. Local participation appears generally both more effective and legitimate than on higher levels, pointing to the need for yet more tailored multi-level governance approaches, depending on whether environmental knowledge or advocacy is sought. We find mixed results regarding the potential of participation to bridge spatial `misfits' between ecological and administrative scales of governance, depending on the historical institutionalization of governance on ecological scales. Polycentricity, finally, appeared somewhat favorable in effectiveness terms with some distinct differences regarding polycentricity in planning vs. polycentricity in implementation.

Disentangling Puzzles of Spatial Scales and Participation in Environmental Governance-The Case of Governance Re-scaling Through the European Water Framework Directive.

PubMed

Newig, Jens; Schulz, Daniel; Jager, Nicolas W

2016-12-01

This article attempts to shed new light on prevailing puzzles of spatial scales in multi-level, participatory governance as regards the democratic legitimacy and environmental effectiveness of governance systems. We focus on the governance re-scaling by the European Water Framework Directive, which introduced new governance scales (mandated river basin management) and demands consultation of citizens and encourages 'active involvement' of stakeholders. This allows to examine whether and how re-scaling through deliberate governance interventions impacts on democratic legitimacy and effective environmental policy delivery. To guide the enquiry, this article organizes existing-partly contradictory-claims on the relation of scale, democratic legitimacy, and environmental effectiveness into three clusters of mechanisms, integrating insights from multi-level governance, social-ecological systems, and public participation. We empirically examine Water Framework Directive implementation in a comparative case study of multi-level systems in the light of the suggested mechanisms. We compare two planning areas in Germany: North Rhine Westphalia and Lower Saxony. Findings suggest that the Water Framework Directive did have some impact on institutionalizing hydrological scales and participation. Local participation appears generally both more effective and legitimate than on higher levels, pointing to the need for yet more tailored multi-level governance approaches, depending on whether environmental knowledge or advocacy is sought. We find mixed results regarding the potential of participation to bridge spatial 'misfits' between ecological and administrative scales of governance, depending on the historical institutionalization of governance on ecological scales. Polycentricity, finally, appeared somewhat favorable in effectiveness terms with some distinct differences regarding polycentricity in planning vs. polycentricity in implementation.

MODELING SCALE-DEPENDENT LANDSCAPE PATTERN, DISPERSAL, AND CONNECTIVITY FROM THE PERSPECTIVE OF THE ORGANISM

EPA Science Inventory

Effects of fine- to broad-scale patterns of landscape heterogeneity on dispersal success were examined for organisms varying in life history traits. To systematically control spatial pattern, a landscape model was created by merging physiographically-based maps of simulated land...

[Spatial scale effect of urban land use landscape pattern in Shanghai City].

PubMed

Xu, Li-Hua; Yue, Wen Ze; Cao, Yu

2007-12-01

Based on geographic information system (GIS) and remote sensing (RS) techniques, the landscape classes of urban land use in Shanghai City were extracted from SPOT images with 5 m spatial resolution in 2002, and then, the classified data were applied to quantitatively explore the change patterns of several basic landscape metrics at different scales. The results indicated that landscape metrics were sensitive to grain- and extent variance. Urban landscape pattern was spatially dependent. In other words, different landscape metrics showed different responses to scale. The resolution of 40 m was an intrinsic observing scale for urban landscape in Shanghai City since landscape metrics showed random characteristics while the grain was less than 40 m. The extent of 24 km was a symbol scale in a series of extents, which was consistent with the boundary between urban built-up area and suburban area in Shanghai City. As a result, the extent of 12 km away from urban center would be an intrinsic handle scale for urban landscape in Shanghai City. However, due to the complexity of urban structure and asymmetry of urban spatial expansion, the intrinsic handle scale was not regular extent, and the square with size of 24 km was just an approximate intrinsic extent for Shanghai City.

Coronal energy distribution and X-ray activity in the small scale magnetic field of the quiet sun

NASA Technical Reports Server (NTRS)

Habbal, S. R.

1992-01-01

The energy distribution in the small-scale magnetic field that pervades the solar surface, and its relationship to X-ray/coronal activity are discussed. The observed emission from the small scale structures, at temperatures characteristic of the chromosphere, transition region and corona, emanates from the boundaries of supergranular cells, within coronal bright points. This emission is characterized by a strong temporal and spatial variability with no definite pattern. The analysis of simultaneous, multiwavelength EUV observations shows that the spatial density of the enhanced as well as variable emission from the small scale structures exhibits a pronounced temperature dependence with significant maxima at 100,000 and 1,000,000 K. Within the limits of the spatial (1-5 arcsec) and temporal (1-5 min) resolution of data available at present, the observed variability in the small scale structure cannot account for the coroal heating of the quiet sun. The characteristics of their emission are more likely to be an indicator of the coronal heating mechanisms.

Pattern-based, multi-scale segmentation and regionalization of EOSD land cover

NASA Astrophysics Data System (ADS)

Niesterowicz, Jacek; Stepinski, Tomasz F.

2017-10-01

The Earth Observation for Sustainable Development of Forests (EOSD) map is a 25 m resolution thematic map of Canadian forests. Because of its large spatial extent and relatively high resolution the EOSD is difficult to analyze using standard GIS methods. In this paper we propose multi-scale segmentation and regionalization of EOSD as new methods for analyzing EOSD on large spatial scales. Segments, which we refer to as forest land units (FLUs), are delineated as tracts of forest characterized by cohesive patterns of EOSD categories; we delineated from 727 to 91,885 FLUs within the spatial extent of EOSD depending on the selected scale of a pattern. Pattern of EOSD's categories within each FLU is described by 1037 landscape metrics. A shapefile containing boundaries of all FLUs together with an attribute table listing landscape metrics make up an SQL-searchable spatial database providing detailed information on composition and pattern of land cover types in Canadian forest. Shapefile format and extensive attribute table pertaining to the entire legend of EOSD are designed to facilitate broad range of investigations in which assessment of composition and pattern of forest over large areas is needed. We calculated four such databases using different spatial scales of pattern. We illustrate the use of FLU database for producing forest regionalization maps of two Canadian provinces, Quebec and Ontario. Such maps capture the broad scale variability of forest at the spatial scale of the entire province. We also demonstrate how FLU database can be used to map variability of landscape metrics, and thus the character of landscape, over the entire Canada.

Spatiotemporal correlation structure of the Earth's surface temperature

NASA Astrophysics Data System (ADS)

Fredriksen, Hege-Beate; Rypdal, Kristoffer; Rypdal, Martin

2015-04-01

We investigate the spatiotemporal temperature variability for several gridded instrumental and climate model data sets. The temporal variability is analysed by estimating the power spectral density and studying the differences between local and global temperatures, land and sea, and among local temperature records at different locations. The spatiotemporal correlation structure is analysed through cross-spectra that allow us to compute frequency-dependent spatial autocorrelation functions (ACFs). Our results are then compared to theoretical spectra and frequency-dependent spatial ACFs derived from a fractional stochastic-diffusive energy balance model (FEBM). From the FEBM we expect both local and global temperatures to have a long-range persistent temporal behaviour, and the spectral exponent (β) is expected to increase by a factor of two when going from local to global scales. Our comparison of the average local spectrum and the global spectrum shows good agreement with this model, although the FEBM has so far only been studied for a pure land planet and a pure ocean planet, respectively, with no seasonal forcing. Hence it cannot capture the substantial variability among the local spectra, in particular between the spectra for land and sea, and for equatorial and non-equatorial temperatures. Both models and observation data show that land temperatures in general have a low persistence, while sea surface temperatures show a higher, and also more variable degree of persistence. Near the equator the spectra deviate from the power-law shape expected from the FEBM. Instead we observe large variability at time scales of a few years due to ENSO, and a flat spectrum at longer time scales, making the spectrum more reminiscent of that of a red noise process. From the frequency-dependent spatial ACFs we observe that the spatial correlation length increases with increasing time scale, which is also consistent with the FEBM. One consequence of this is that longer-lasting structures must also be wider in space. The spatial correlation length is also observed to be longer for land than for sea. The climate model simulations studied are mainly CMIP5 control runs of length 500-1000 yr. On time scales up to several centuries we do not observe that the difference between the local and global spectral exponents vanish. This also follows from the FEBM and shows that the dynamics is spatiotemporal (not just temporal) even on these time scales.

Spatial Variability of Snowpack Properties On Small Slopes

NASA Astrophysics Data System (ADS)

Pielmeier, C.; Kronholm, K.; Schneebeli, M.; Schweizer, J.

The spatial variability of alpine snowpacks is created by a variety of parameters like deposition, wind erosion, sublimation, melting, temperature, radiation and metamor- phism of the snow. Spatial variability is thought to strongly control the avalanche initi- ation and failure propagation processes. Local snowpack measurements are currently the basis for avalanche warning services and there exist contradicting hypotheses about the spatial continuity of avalanche active snow layers and interfaces. Very little about the spatial variability of the snowpack is known so far, therefore we have devel- oped a systematic and objective method to measure the spatial variability of snowpack properties, layering and its relation to stability. For a complete coverage, the analysis of the spatial variability has to entail all scales from mm to km. In this study the small to medium scale spatial variability is investigated, i.e. the range from centimeters to tenths of meters. During the winter 2000/2001 we took systematic measurements in lines and grids on a flat snow test field with grid distances from 5 cm to 0.5 m. Fur- thermore, we measured systematic grids with grid distances between 0.5 m and 2 m in undisturbed flat fields and on small slopes above the tree line at the Choerbschhorn, in the region of Davos, Switzerland. On 13 days we measured the spatial pattern of the snowpack stratigraphy with more than 110 snow micro penetrometer measure- ments at slopes and flat fields. Within this measuring grid we placed 1 rutschblock and 12 stuffblock tests to measure the stability of the snowpack. With the large num- ber of measurements we are able to use geostatistical methods to analyse the spatial variability of the snowpack. Typical correlation lengths are calculated from semivari- ograms. Discerning the systematic trends from random spatial variability is analysed using statistical models. Scale dependencies are shown and recurring scaling patterns are outlined. The importance of the small and medium scale spatial variability for the larger (kilometer) scale spatial variability as well as for the avalanche formation are discussed. Finally, an outlook on spatial models for the snowpack variability is given.

Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2013-08-01

Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.

Community shifts under climate change: mechanisms at multiple scales.

PubMed

Gornish, Elise S; Tylianakis, Jason M

2013-07-01

Processes that drive ecological dynamics differ across spatial scales. Therefore, the pathways through which plant communities and plant-insect relationships respond to changing environmental conditions are also expected to be scale-dependent. Furthermore, the processes that affect individual species or interactions at single sites may differ from those affecting communities across multiple sites. We reviewed and synthesized peer-reviewed literature to identify patterns in biotic or abiotic pathways underpinning changes in the composition and diversity of plant communities under three components of climate change (increasing temperature, CO2, and changes in precipitation) and how these differ across spatial scales. We also explored how these changes to plants affect plant-insect interactions. The relative frequency of biotic vs. abiotic pathways of climate effects at larger spatial scales often differ from those at smaller scales. Local-scale studies show variable responses to climate drivers, often driven by biotic factors. However, larger scale studies identify changes to species composition and/or reduced diversity as a result of abiotic factors. Differing pathways of climate effects can result from different responses of multiple species, habitat effects, and differing effects of invasions at local vs. regional to global scales. Plant community changes can affect higher trophic levels as a result of spatial or phenological mismatch, foliar quality changes, and plant abundance changes, though studies on plant-insect interactions at larger scales are rare. Climate-induced changes to plant communities will have considerable effects on community-scale trophic exchanges, which may differ from the responses of individual species or pairwise interactions.

Spatial Interpretation of Tower, Chamber and Modelled Terrestrial Fluxes in a Tropical Forest Plantation

NASA Astrophysics Data System (ADS)

Whidden, E.; Roulet, N.

2003-04-01

Interpretation of a site average terrestrial flux may be complicated in the presence of inhomogeneities. Inhomogeneity may invalidate the basic assumptions of aerodynamic flux measurement. Chamber measurement may miss or misinterpret important temporal or spatial anomalies. Models may smooth over important nonlinearities depending on the scale of application. Although inhomogeneity is usually seen as a design problem, many sites have spatial variance that may have a large impact on net flux, and in many cases a large homogeneous surface is unrealistic. The sensitivity and validity of a site average flux are investigated in the presence of an inhomogeneous site. Directional differences are used to evaluate the validity of aerodynamic methods and the computation of a site average tower flux. Empirical and modelling methods are used to interpret the spatial controls on flux. An ecosystem model, Ecosys, is used to assess spatial length scales appropriate to the ecophysiologic controls. A diffusion model is used to compare tower, chamber, and model data, by spatially weighting contributions within the tower footprint. Diffusion model weighting is also used to improve tower flux estimates by producing footprint averaged ecological parameters (soil moisture, soil temperature, etc.). Although uncertainty remains in the validity of measurement methods and the accuracy of diffusion models, a detailed spatial interpretation is required at an inhomogeneous site. Flux estimation between methods improves with spatial interpretation, showing the importance to an estimation of a site average flux. Small-scale temporal and spatial anomalies may be relatively unimportant to overall flux, but accounting for medium-scale differences in ecophysiological controls is necessary. A combination of measurements and modelling can be used to define the appropriate time and length scales of significant non-linearity due to inhomogeneity.

Terrestrial habitat selection and strong density-dependent mortality in recently metamorphosed amphibians.

PubMed

Patrick, David A; Harper, Elizabeth B; Hunter, Malcolm L; Calhoun, Aram J K

2008-09-01

To predict the effects of terrestrial habitat change on amphibian populations, we need to know how amphibians respond to habitat heterogeneity, and whether habitat choice remains consistent throughout the life-history cycle. We conducted four experiments to evaluate how the spatial distribution of juvenile wood frogs, Rana sylvatica (including both overall abundance and localized density), was influenced by habitat choice and habitat structure, and how this relationship changed with spatial scale and behavioral phase. The four experiments included (1) habitat manipulation on replicated 10-ha landscapes surrounding breeding pools; (2) short-term experiments with individual frogs emigrating through a manipulated landscape of 1 m wide hexagonal patches; and habitat manipulations in (3) small (4-m2); and (4) large (100-m2) enclosures with multiple individuals to compare behavior both during and following emigration. The spatial distribution of juvenile wood frogs following emigration resulted from differences in the scale at which juvenile amphibians responded to habitat heterogeneity during active vs. settled behavioral phases. During emigration, juvenile wood frogs responded to coarse-scale variation in habitat (selection between 2.2-ha forest treatments) but not to fine-scale variation. After settling, however, animals showed habitat selection at much smaller scales (2-4 m2). This resulted in high densities of animals in small patches of suitable habitat where they experienced rapid mortality. No evidence of density-dependent habitat selection was seen, with juveniles typically choosing to remain at extremely high densities in high-quality habitat, rather than occupying low-quality habitat. These experiments demonstrate how prediction of the terrestrial distribution of juvenile amphibians requires understanding of the complex behavioral responses to habitat heterogeneity. Understanding these patterns is important, given that human alterations to amphibian habitats may generate extremely high densities of animals, resulting in high density-dependent mortality.

Physicochemical heterogeneity controls on uranium bioreduction rates at the field scale.

PubMed

Li, Li; Gawande, Nitin; Kowalsky, Michael B; Steefel, Carl I; Hubbard, Susan S

2011-12-01

It has been demonstrated in laboratory systems that U(VI) can be reduced to immobile U(IV) by bacteria in natural environments. The ultimate efficacy of bioreduction at the field scale, however, is often challenging to quantify and depends on site characteristics. In this work, uranium bioreduction rates at the field scale are quantified, for the first time, using an integrated approach. The approach combines field data, inverse and forward hydrological and reactive transport modeling, and quantification of reduction rates at different spatial scales. The approach is used to explore the impact of local scale (tens of centimeters) parameters and processes on field scale (tens of meters) system responses to biostimulation treatments and the controls of physicochemical heterogeneity on bioreduction rates. Using the biostimulation experiments at the Department of Energy Old Rifle site, our results show that the spatial distribution of hydraulic conductivity and solid phase mineral (Fe(III)) play a critical role in determining the field-scale bioreduction rates. Due to the dependence on Fe-reducing bacteria, field-scale U(VI) bioreduction rates were found to be largely controlled by the abundance of Fe(III) minerals at the vicinity of the injection wells and by the presence of preferential flow paths connecting injection wells to down gradient Fe(III) abundant areas.

Role Of Spatial Scale In Sub-Area Prioritization To Reduce Impact Of Planned Land Use/Cover Alternations Of Watershed Responses

EPA Science Inventory

An index based methodology is presented that rank the sub-areas in a watershed based on their relative impacts on watershed response to anticipated land developments. We argue in this paper that the spatial locations of such critical areas are dependent on the extent of watershed...

Non-monotonic changes in performance with eccentricity modeled by multiple eccentricity-dependent limitations.

PubMed

Poirier, Frédéric J A M; Gurnsey, Rick

2005-08-01

Eccentricity-dependent resolution losses are sometimes compensated for in psychophysical experiments by magnifying (scaling) stimuli at each eccentricity. The use of either pre-selected scaling factors or unscaled stimuli sometimes leads to non-monotonic changes in performance as a function of eccentricity. We argue that such non-monotonic changes arise when performance is limited by more than one type of constraint at each eccentricity. Building on current methods developed to investigate peripheral perception [e.g., Watson, A. B. (1987). Estimation of local spatial scale. Journal of the Optical Society of America A, 4 (8), 1579-1582; Poirier, F. J. A. M., & Gurnsey, R. (2002). Two eccentricity dependent limitations on subjective contour discrimination. Vision Research, 42, 227-238; Strasburger, H., Rentschler, I., & Harvey Jr., L. O. (1994). Cortical magnification theory fails to predict visual recognition. European Journal of Neuroscience, 6, 1583-1588], we show how measured scaling can deviate from a linear function of eccentricity in a grating acuity task [Thibos, L. N., Still, D. L., & Bradley, A. (1996). Characterization of spatial aliasing and contrast sensitivity in peripheral vision. Vision Research, 36(2), 249-258]. This framework can also explain the central performance drop [Kehrer, L. (1989). Central performance drop on perceptual segregation tasks. Spatial Vision, 4, 45-62] and a case of "reverse scaling" of the integration window in symmetry [Tyler, C. W. (1999). Human symmetry detection exhibits reverse eccentricity scaling. Visual Neuroscience, 16, 919-922]. These cases of non-monotonic performance are shown to be consistent with multiple sources of resolution loss, each of which increases linearly with eccentricity. We conclude that most eccentricity research, including "oddities", can be explained by multiple-scaling theory as extended here, where the receptive field properties of all underlying mechanisms in a task increase in size with eccentricity, but not necessarily at the same rate.

Demographic controls of aboveground forest biomass across North America.

PubMed

Vanderwel, Mark C; Zeng, Hongcheng; Caspersen, John P; Kunstler, Georges; Lichstein, Jeremy W

2016-04-01

Ecologists have limited understanding of how geographic variation in forest biomass arises from differences in growth and mortality at continental to global scales. Using forest inventories from across North America, we partitioned continental-scale variation in biomass growth and mortality rates of 49 tree species groups into (1) species-independent spatial effects and (2) inherent differences in demographic performance among species. Spatial factors that were separable from species composition explained 83% and 51% of the respective variation in growth and mortality. Moderate additional variation in mortality (26%) was attributable to differences in species composition. Age-dependent biomass models showed that variation in forest biomass can be explained primarily by spatial gradients in growth that were unrelated to species composition. Species-dependent patterns of mortality explained additional variation in biomass, with forests supporting less biomass when dominated by species that are highly susceptible to competition (e.g. Populus spp.) or to biotic disturbances (e.g. Abies balsamea). © 2016 John Wiley & Sons Ltd/CNRS.

Comparison of Multivariate Spatial Dependence Structures of DPIL and Flowmeter Hydraulic Conductivity Data Sets at the MADE Site

NASA Astrophysics Data System (ADS)

Xiao, B.; Haslauer, C. P.; Bohling, G. C.; Bárdossy, A.

2017-12-01

The spatial arrangement of hydraulic conductivity (K) determines water flow and solute transport behaviour in groundwater systems. This presentation demonstrates three advances over commonly used geostatistical methods by integrating measurements from novel measurement techniques and novel multivariate non-Gaussian dependence models: The spatial dependence structure of K was analysed using both data sets of K. Previously encountered similarities were confirmed in low-dimensional dependence. These similarities become less stringent and deviate more from symmetric Gaussian dependence in dimensions larger than two. Measurements of small and large K values are more uncertain than medium K values due to decreased sensitivity of the measurement devices at both ends of the K scale. Nevertheless, these measurements contain useful information that we include in the estimation of the marginal distribution and the spatial dependence structure as ``censored measurements'' that are estimated jointly without the common assumption of independence. The spatial dependence structure of the two data sets and their cross-covariances are used to infer the spatial dependence and the amount of the bias between the two data sets. By doing so, one spatial model for K is constructed that is used for simulation and that reflects the characteristics of both measurement techniques. The concept of the presented methodology is to use all available information for the estimation of a stochastic model of the primary parameter (K) at the highly heterogeneous Macrodispersion Experiment (MADE) site. The primary parameter has been measured by two independent measurement techniques whose sets of locations do not overlap. This site offers the unique opportunity of large quantities of measurements of K (31123 direct push injection logging based measurements and 2611 flowmeter based measurements). This improved dependence structure of K will be included into the estimated non-Gaussian dependence models and is expected to reproduce observed solute concentrations at the site better than existing dependence models of K.

Temporal scaling and spatial statistical analyses of groundwater level fluctuations

NASA Astrophysics Data System (ADS)

Sun, H.; Yuan, L., Sr.; Zhang, Y.

2017-12-01

Natural dynamics such as groundwater level fluctuations can exhibit multifractionality and/or multifractality due likely to multi-scale aquifer heterogeneity and controlling factors, whose statistics requires efficient quantification methods. This study explores multifractionality and non-Gaussian properties in groundwater dynamics expressed by time series of daily level fluctuation at three wells located in the lower Mississippi valley, after removing the seasonal cycle in the temporal scaling and spatial statistical analysis. First, using the time-scale multifractional analysis, a systematic statistical method is developed to analyze groundwater level fluctuations quantified by the time-scale local Hurst exponent (TS-LHE). Results show that the TS-LHE does not remain constant, implying the fractal-scaling behavior changing with time and location. Hence, we can distinguish the potentially location-dependent scaling feature, which may characterize the hydrology dynamic system. Second, spatial statistical analysis shows that the increment of groundwater level fluctuations exhibits a heavy tailed, non-Gaussian distribution, which can be better quantified by a Lévy stable distribution. Monte Carlo simulations of the fluctuation process also show that the linear fractional stable motion model can well depict the transient dynamics (i.e., fractal non-Gaussian property) of groundwater level, while fractional Brownian motion is inadequate to describe natural processes with anomalous dynamics. Analysis of temporal scaling and spatial statistics therefore may provide useful information and quantification to understand further the nature of complex dynamics in hydrology.

Spatio-Temporal Variability of Groundwater Storage in India

NASA Technical Reports Server (NTRS)

Bhanja, Soumendra; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2016-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Ground water storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent).In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Spatio-temporal variability of groundwater storage in India.

PubMed

Bhanja, Soumendra N; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2017-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Groundwater storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent). In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Interactions across spatial scales among forest dieback, fire, and erosion in northern New Mexico landscapes

USGS Publications Warehouse

Allen, Craig D.

2007-01-01

Ecosystem patterns and disturbance processes at one spatial scale often interact with processes at another scale, and the result of such cross-scale interactions can be nonlinear dynamics with thresholds. Examples of cross-scale pattern-process relationships and interactions among forest dieback, fire, and erosion are illustrated from northern New Mexico (USA) landscapes, where long-term studies have recently documented all of these disturbance processes. For example, environmental stress, operating on individual trees, can cause tree death that is amplified by insect mortality agents to propagate to patch and then landscape or even regional-scale forest dieback. Severe drought and unusual warmth in the southwestern USA since the late 1990s apparently exceeded species-specific physiological thresholds for multiple tree species, resulting in substantial vegetation mortality across millions of hectares of woodlands and forests in recent years. Predictions of forest dieback across spatial scales are constrained by uncertainties associated with: limited knowledge of species-specific physiological thresholds; individual and site-specific variation in these mortality thresholds; and positive feedback loops between rapidly-responding insect herbivore populations and their stressed plant hosts, sometimes resulting in nonlinear “pest” outbreak dynamics. Fire behavior also exhibits nonlinearities across spatial scales, illustrated by changes in historic fire regimes where patch-scale grazing disturbance led to regional-scale collapse of surface fire activity and subsequent recent increases in the scale of extreme fire events in New Mexico. Vegetation dieback interacts with fire activity by modifying fuel amounts and configurations at multiple spatial scales. Runoff and erosion processes are also subject to scale-dependent threshold behaviors, exemplified by ecohydrological work in semiarid New Mexico watersheds showing how declines in ground surface cover lead to non-linear increases in bare patch connectivity and thereby accelerated runoff and erosion at hillslope and watershed scales. Vegetation dieback, grazing, and fire can change land surface properties and cross-scale hydrologic connectivities, directly altering ecohydrological patterns of runoff and erosion. The interactions among disturbance processes across spatial scales can be key drivers in ecosystem dynamics, as illustrated by these studies of recent landscape changes in northern New Mexico. To better anticipate and mitigate accelerating human impacts to the planetary ecosystem at all spatial scales, improvements are needed in our conceptual and quantitative understanding of cross-scale interactions among disturbance processes.

High-resolution Statistics of Solar Wind Turbulence at Kinetic Scales Using the Magnetospheric Multiscale Mission

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

Chasapis, Alexandros; Matthaeus, W. H.; Parashar, T. N.

Using data from the Magnetospheric Multiscale (MMS) and Cluster missions obtained in the solar wind, we examine second-order and fourth-order structure functions at varying spatial lags normalized to ion inertial scales. The analysis includes direct two-spacecraft results and single-spacecraft results employing the familiar Taylor frozen-in flow approximation. Several familiar statistical results, including the spectral distribution of energy, and the sale-dependent kurtosis, are extended down to unprecedented spatial scales of ∼6 km, approaching electron scales. The Taylor approximation is also confirmed at those small scales, although small deviations are present in the kinetic range. The kurtosis is seen to attain verymore » high values at sub-proton scales, supporting the previously reported suggestion that monofractal behavior may be due to high-frequency plasma waves at kinetic scales.« less

Mismatch between herbivore behavior and demographics contributes to scale-dependence of host susceptibility in two pine species

Treesearch

Tiina Ylioja; Daniel H. Slone; Matthew P. Ayres

2005-01-01

The impacts on forests of tree-killing bark beetles can depend on the species composition of potential host trees. Host susceptibility might be an intrinsic property of tree species, or it might depend on spatial patterning of alternative host species. We compared the susceptibility of loblolly pine (Pinus taeda) and Virginia pine (P. ...

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds

PubMed Central

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

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds.

PubMed

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.

The spatial sensitivity of the spectral diversity-biodiversity relationship: an experimental test in a prairie grassland.

PubMed

Wang, Ran; Gamon, John A; Cavender-Bares, Jeannine; Townsend, Philip A; Zygielbaum, Arthur I

2018-03-01

Remote sensing has been used to detect plant biodiversity in a range of ecosystems based on the varying spectral properties of different species or functional groups. However, the most appropriate spatial resolution necessary to detect diversity remains unclear. At coarse resolution, differences among spectral patterns may be too weak to detect. In contrast, at fine resolution, redundant information may be introduced. To explore the effect of spatial resolution, we studied the scale dependence of spectral diversity in a prairie ecosystem experiment at Cedar Creek Ecosystem Science Reserve, Minnesota, USA. Our study involved a scaling exercise comparing synthetic pixels resampled from high-resolution images within manipulated diversity treatments. Hyperspectral data were collected using several instruments on both ground and airborne platforms. We used the coefficient of variation (CV) of spectral reflectance in space as the indicator of spectral diversity and then compared CV at different scales ranging from 1 mm 2 to 1 m 2 to conventional biodiversity metrics, including species richness, Shannon's index, Simpson's index, phylogenetic species variation, and phylogenetic species evenness. In this study, higher species richness plots generally had higher CV. CV showed higher correlations with Shannon's index and Simpson's index than did species richness alone, indicating evenness contributed to the spectral diversity. Correlations with species richness and Simpson's index were generally higher than with phylogenetic species variation and evenness measured at comparable spatial scales, indicating weaker relationships between spectral diversity and phylogenetic diversity metrics than with species diversity metrics. High resolution imaging spectrometer data (1 mm 2 pixels) showed the highest sensitivity to diversity level. With decreasing spatial resolution, the difference in CV between diversity levels decreased and greatly reduced the optical detectability of biodiversity. The optimal pixel size for distinguishing α diversity in these prairie plots appeared to be around 1 mm to 10 cm, a spatial scale similar to the size of an individual herbaceous plant. These results indicate a strong scale-dependence of the spectral diversity-biodiversity relationships, with spectral diversity best able to detect a combination of species richness and evenness, and more weakly detecting phylogenetic diversity. These findings can be used to guide airborne studies of biodiversity and develop more effective large-scale biodiversity sampling methods. ©2018 The Authors Ecological Applications published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.

Dependence of Snowmelt Simulations on Scaling of the Forcing Processes (Invited)

NASA Astrophysics Data System (ADS)

Winstral, A. H.; Marks, D. G.; Gurney, R. J.

2009-12-01

The spatial organization and scaling relationships of snow distribution in mountain environs is ultimately dependent on the controlling processes. These processes include interactions between weather, topography, vegetation, snow state, and seasonally-dependent radiation inputs. In large scale snow modeling it is vital to know these dependencies to obtain accurate predictions while reducing computational costs. This study examined the scaling characteristics of the forcing processes and the dependency of distributed snowmelt simulations to their scaling. A base model simulation characterized these processes with 10m resolution over a 14.0 km2 basin with an elevation range of 1474 - 2244 masl. Each of the major processes affecting snow accumulation and melt - precipitation, wind speed, solar radiation, thermal radiation, temperature, and vapor pressure - were independently degraded to 1 km resolution. Seasonal and event-specific results were analyzed. Results indicated that scale effects on melt vary by process and weather conditions. The dependence of melt simulations on the scaling of solar radiation fluxes also had a seasonal component. These process-based scaling characteristics should remain static through time as they are based on physical considerations. As such, these results not only provide guidance for current modeling efforts, but are also well suited to predicting how potential climate changes will affect the heterogeneity of mountain snow distributions.

How beta diversity and the underlying causes vary with sampling scales in the Changbai mountain forests.

PubMed

Tan, Lingzhao; Fan, Chunyu; Zhang, Chunyu; von Gadow, Klaus; Fan, Xiuhua

2017-12-01

This study aims to establish a relationship between the sampling scale and tree species beta diversity temperate forests and to identify the underlying causes of beta diversity at different sampling scales. The data were obtained from three large observational study areas in the Changbai mountain region in northeastern China. All trees with a dbh ≥1 cm were stem-mapped and measured. The beta diversity was calculated for four different grain sizes, and the associated variances were partitioned into components explained by environmental and spatial variables to determine the contributions of environmental filtering and dispersal limitation to beta diversity. The results showed that both beta diversity and the causes of beta diversity were dependent on the sampling scale. Beta diversity decreased with increasing scales. The best-explained beta diversity variation was up to about 60% which was discovered in the secondary conifer and broad-leaved mixed forest (CBF) study area at the 40 × 40 m scale. The variation partitioning result indicated that environmental filtering showed greater effects at bigger grain sizes, while dispersal limitation was found to be more important at smaller grain sizes. What is more, the result showed an increasing explanatory ability of environmental effects with increasing sampling grains but no clearly trend of spatial effects. The study emphasized that the underlying causes of beta diversity variation may be quite different within the same region depending on varying sampling scales. Therefore, scale effects should be taken into account in future studies on beta diversity, which is critical in identifying different relative importance of spatial and environmental drivers on species composition variation.

Linking the influence and dependence of people on biodiversity across scales.

PubMed

Isbell, Forest; Gonzalez, Andrew; Loreau, Michel; Cowles, Jane; Díaz, Sandra; Hector, Andy; Mace, Georgina M; Wardle, David A; O'Connor, Mary I; Duffy, J Emmett; Turnbull, Lindsay A; Thompson, Patrick L; Larigauderie, Anne

2017-05-31

Biodiversity enhances many of nature's benefits to people, including the regulation of climate and the production of wood in forests, livestock forage in grasslands and fish in aquatic ecosystems. Yet people are now driving the sixth mass extinction event in Earth's history. Human dependence and influence on biodiversity have mainly been studied separately and at contrasting scales of space and time, but new multiscale knowledge is beginning to link these relationships. Biodiversity loss substantially diminishes several ecosystem services by altering ecosystem functioning and stability, especially at the large temporal and spatial scales that are most relevant for policy and conservation.

The significance of spatial variability of rainfall on streamflow: A synthetic analysis at the Upper Lee catchment, UK

NASA Astrophysics Data System (ADS)

Pechlivanidis, Ilias; McIntyre, Neil; Wheater, Howard

2017-04-01

Rainfall, one of the main inputs in hydrological modeling, is a highly heterogeneous process over a wide range of scales in space, and hence the ignorance of the spatial rainfall information could affect the simulated streamflow. Calibration of hydrological model parameters is rarely a straightforward task due to parameter equifinality and parameters' 'nature' to compensate for other uncertainties, i.e. structural and forcing input. In here, we analyse the significance of spatial variability of rainfall on streamflow as a function of catchment scale and type, and antecedent conditions using the continuous time, semi-distributed PDM hydrological model at the Upper Lee catchment, UK. The impact of catchment scale and type is assessed using 11 nested catchments ranging in scale from 25 to 1040 km2, and further assessed by artificially changing the catchment characteristics and translating these to model parameters with uncertainty using model regionalisation. Synthetic rainfall events are introduced to directly relate the change in simulated streamflow to the spatial variability of rainfall. Overall, we conclude that the antecedent catchment wetness and catchment type play an important role in controlling the significance of the spatial distribution of rainfall on streamflow. Results show a relationship between hydrograph characteristics (streamflow peak and volume) and the degree of spatial variability of rainfall for the impermeable catchments under dry antecedent conditions, although this decreases at larger scales; however this sensitivity is significantly undermined under wet antecedent conditions. Although there is indication that the impact of spatial rainfall on streamflow varies as a function of catchment scale, the variability of antecedent conditions between the synthetic catchments seems to mask this significance. Finally, hydrograph responses to different spatial patterns in rainfall depend on assumptions used for model parameter estimation and also the spatial variation in parameters indicating the need of an uncertainty framework in such investigation.

Tensor perturbations during inflation in a spatially closed Universe

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

Bonga, Béatrice; Gupt, Brajesh; Yokomizo, Nelson, E-mail: bpb165@psu.edu, E-mail: bgupt@gravity.psu.edu, E-mail: yokomizo@gravity.psu.edu

2017-05-01

In a recent paper [1], we studied the evolution of the background geometry and scalar perturbations in an inflationary, spatially closed Friedmann-Lemaȋtre-Robertson-Walker (FLRW) model having constant positive spatial curvature and spatial topology S{sup 3}. Due to the spatial curvature, the early phase of slow-roll inflation is modified, leading to suppression of power in the scalar power spectrum at large angular scales. In this paper, we extend the analysis to include tensor perturbations. We find that, similarly to the scalar perturbations, the tensor power spectrum also shows suppression for long wavelength modes. The correction to the tensor spectrum is limited tomore » the very long wavelength modes, therefore the resulting observable CMB B-mode polarization spectrum remains practically the same as in the standard scenario with flat spatial sections. However, since both the tensor and scalar power spectra are modified, there are scale dependent corrections to the tensor-to-scalar ratio that leads to violation of the standard slow-roll consistency relation.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

NASA Technical Reports Server (NTRS)

Meng, Ran; Wu, Jin; Schwager, Kathy L.; Zhao, Feng; Dennison, Philip E.; Cook, Bruce D.; Brewster, Kristen; Green, Timothy M.; Serbin, Shawn P.

2017-01-01

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

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

Meng, Ran; Wu, Jin; Schwager, Kathy L.

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

DOE PAGES

Meng, Ran; Wu, Jin; Schwager, Kathy L.; ...

2017-01-21

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Scale-dependency of LiDAR derived terrain attributes in quantitative soil-landscape modeling: Effects of grid resolution vs. neighborhood extent

EPA Science Inventory

Quantifying the spatial distribution of soil properties is essential for ecological and environmental modeling at the landscape scale. Terrain attributes are one of the primary covariates in soil-landscape models due to their control on energy and mass fluxes, which in turn contr...

Defensive effects of extrafloral nectaries in quaking aspen differ with scale

Treesearch

Brent Mortensen; Diane Wagner; Patricia Doak

2010-01-01

The effects of plant defenses on herbivory can differ among spatial scales. This may be particularly common with indirect defenses, such as extrafloral nectarines (EFNs), that attract predatory arthropods and are dependent on predator distribution, abundance, and behavior. We tested the defensive effects of EFNs in quaking aspen (Populus tremuloides...

California spotted owl habitat characteristics and use

Treesearch

Susan L. Roberts

2017-01-01

California spotted owls (Strix occidentalis occidentalis) establish large home ranges averaging about 1279 ha (3,160 ac) (table 3-1), and within these home ranges individual owls select habitat at different scales, depending on their activity. At the smallest spatial scale, the nest tree, it appears there is very limited flexibility in the...

Large-scale phenomena, chapter 3, part D

NASA Technical Reports Server (NTRS)

1975-01-01

Oceanic phenomena with horizontal scales from approximately 100 km up to the widths of the oceans themselves are examined. Data include: shape of geoid, quasi-stationary anomalies due to spatial variations in sea density and steady current systems, and the time dependent variations due to tidal and meteorological forces and to varying currents.

Fractal Characterization of Multitemporal Scaled Remote Sensing Data

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Lam, Nina Siu-Ngan; Qiu, Hong-lie

1998-01-01

Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the ingestion, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust software and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISS. Scale is fundamental to the characterization of geo-spatial data as represented in GISS, but we have relatively little insight on the effects of, or how to measure the effects of, scale in representing multiscaled data; i.e., data that are acquired in different formats (e.g., map, digital) and exist in varying spatial, temporal, and in the case of remote sensing data, radiometric, configurations. This is particularly true in the emerging era of Integrated GISs (IGIS), wherein spatial data in a variety of formats (e.g., raster, vector) are combined with multiscaled remote sensing data, capable of performing highly sophisticated space-time data analyses and modeling. Moreover, the complexities associated with the integration of multiscaled data sets in a multitude of formats are exacerbated by the confusion of what the term "scale" is from a multidisciplinary perspective; i.e., "scale" takes on significantly different meanings depending upon one's disciplinary background and spatial perspective which can lead to substantive confusion in the input, manipulation, analyses, and output of IGISs (Quattrochi, 1993). Hence, we must begin to look at the universality of scale and begin to develop the theory, methods, and techniques necessary to advance knowledge on the "Science of Scale" across a wide number of spatial disciplines that use GISs.

Global shape recognition is modulated by the spatial distance of local elements--evidence from simultanagnosia.

PubMed

Huberle, Elisabeth; Karnath, Hans-Otto

2006-01-01

Simultanagnosia is a rare deficit that impairs individuals in perceiving several objects at the same time. It is usually observed following bilateral parieto-occipital brain damage. Despite the restrictions in perceiving the global aspect of a scene, processing of individual objects remains unaffected. The mechanisms underlying simultanagnosia are not well understood. Previous findings indicated that the integration of multiple objects into a holistic representation of the environment is not impossible per se, but might depend on the spatial relationship between individual objects. The present study examined the influence of inter-element distances between individual objects on the recognition of global shapes in two patients with simultanagnosia. We presented Navon hierarchical letter stimuli with different inter-element distances between letters at the Local Scale. Improved recognition at the Global Scale was observed in both patients by reducing the inter-element distance. Global shape recognition in simultanagnosia thus seems to be modulated by the spatial distance of local elements and does not appear to be an all-or-nothing phenomenon depending on spatial continuity. The findings seem to argue against a deficit in visual working memory capacity as the primary deficit in simultanagnosia. However, further research is necessary to investigate alternative interpretations.

Saturation of the turbulent dynamo.

PubMed

Schober, J; Schleicher, D R G; Federrath, C; Bovino, S; Klessen, R S

2015-08-01

The origin of strong magnetic fields in the Universe can be explained by amplifying weak seed fields via turbulent motions on small spatial scales and subsequently transporting the magnetic energy to larger scales. This process is known as the turbulent dynamo and depends on the properties of turbulence, i.e., on the hydrodynamical Reynolds number and the compressibility of the gas, and on the magnetic diffusivity. While we know the growth rate of the magnetic energy in the linear regime, the saturation level, i.e., the ratio of magnetic energy to turbulent kinetic energy that can be reached, is not known from analytical calculations. In this paper we present a scale-dependent saturation model based on an effective turbulent resistivity which is determined by the turnover time scale of turbulent eddies and the magnetic energy density. The magnetic resistivity increases compared to the Spitzer value and the effective scale on which the magnetic energy spectrum is at its maximum moves to larger spatial scales. This process ends when the peak reaches a characteristic wave number k☆ which is determined by the critical magnetic Reynolds number. The saturation level of the dynamo also depends on the type of turbulence and differs for the limits of large and small magnetic Prandtl numbers Pm. With our model we find saturation levels between 43.8% and 1.3% for Pm≫1 and between 2.43% and 0.135% for Pm≪1, where the higher values refer to incompressible turbulence and the lower ones to highly compressible turbulence.

Spatial averaging of a dissipative particle dynamics model for active suspensions

NASA Astrophysics Data System (ADS)

Panchenko, Alexander; Hinz, Denis F.; Fried, Eliot

2018-03-01

Starting from a fine-scale dissipative particle dynamics (DPD) model of self-motile point particles, we derive meso-scale continuum equations by applying a spatial averaging version of the Irving-Kirkwood-Noll procedure. Since the method does not rely on kinetic theory, the derivation is valid for highly concentrated particle systems. Spatial averaging yields stochastic continuum equations similar to those of Toner and Tu. However, our theory also involves a constitutive equation for the average fluctuation force. According to this equation, both the strength and the probability distribution vary with time and position through the effective mass density. The statistics of the fluctuation force also depend on the fine scale dissipative force equation, the physical temperature, and two additional parameters which characterize fluctuation strengths. Although the self-propulsion force entering our DPD model contains no explicit mechanism for aligning the velocities of neighboring particles, our averaged coarse-scale equations include the commonly encountered cubically nonlinear (internal) body force density.

When will trends in European mean and heavy daily precipitation emerge?

NASA Astrophysics Data System (ADS)

Maraun, Douglas

2013-03-01

A multi-model ensemble of regional climate projections for Europe is employed to investigate how the time of emergence (TOE) for seasonal sums and maxima of daily precipitation depends on spatial scale. The TOE is redefined for emergence from internal variability only; the spread of the TOE due to imperfect climate model formulation is used as a measure of uncertainty in the TOE itself. Thereby, the TOE becomes a fundamentally limiting timescale and translates into a minimum spatial scale on which robust conclusions can be drawn about precipitation trends. Thus, minimum temporal and spatial scales for adaptation planning are also given. In northern Europe, positive winter trends in mean and heavy precipitation, and in southwestern and southeastern Europe, summer trends in mean precipitation already emerge within the next few decades. However, across wide areas, especially for heavy summer precipitation, the local trend emerges only late in the 21st century or later. For precipitation averaged to larger scales, the trend, in general, emerges earlier.

Density-dependent nest predation in waterfowl: the relative importance of nest density versus nest dispersion

USGS Publications Warehouse

Ackerman, Joshua T.; Ringelman, Kevin M.; Eadie, J.M.

2012-01-01

When nest predation levels are very high or very low, the absolute range of observable nest success is constrained (a floor/ceiling effect), and it may be more difficult to detect density-dependent nest predation. Density-dependent nest predation may be more detectable in years with moderate predation rates, simply because there can be a greater absolute difference in nest success between sites. To test this, we replicated a predation experiment 10 years after the original study, using both natural and artificial nests, comparing a year when overall rates of nest predation were high (2000) to a year with moderate nest predation (2010). We found no evidence for density-dependent predation on artificial nests in either year, indicating that nest predation is not density-dependent at the spatial scale of our experimental replicates (1-ha patches). Using nearest-neighbor distances as a measure of nest dispersion, we also found little evidence for “dispersion-dependent” predation on artificial nests. However, when we tested for dispersion-dependent predation using natural nests, we found that nest survival increased with shorter nearest-neighbor distances, and that neighboring nests were more likely to share the same nest fate than non-adjacent nests. Thus, at small spatial scales, density-dependence appears to operate in the opposite direction as predicted: closer nearest neighbors are more likely to be successful. We suggest that local nest dispersion, rather than larger-scale measures of nest density per se, may play a more important role in density-dependent nest predation.

Flexible hydrological modeling - Disaggregation from lumped catchment scale to higher spatial resolutions

NASA Astrophysics Data System (ADS)

Tran, Quoc Quan; Willems, Patrick; Pannemans, Bart; Blanckaert, Joris; Pereira, Fernando; Nossent, Jiri; Cauwenberghs, Kris; Vansteenkiste, Thomas

2015-04-01

Based on an international literature review on model structures of existing rainfall-runoff and hydrological models, a generalized model structure is proposed. It consists of different types of meteorological components, storage components, splitting components and routing components. They can be spatially organized in a lumped way, or on a grid, spatially interlinked by source-to-sink or grid-to-grid (cell-to-cell) routing. The grid size of the model can be chosen depending on the application. The user can select/change the spatial resolution depending on the needs and/or the evaluation of the accuracy of the model results, or use different spatial resolutions in parallel for different applications. Major research questions addressed during the study are: How can we assure consistent results of the model at any spatial detail? How can we avoid strong or sudden changes in model parameters and corresponding simulation results, when one moves from one level of spatial detail to another? How can we limit the problem of overparameterization/equifinality when we move from the lumped model to the spatially distributed model? The proposed approach is a step-wise one, where first the lumped conceptual model is calibrated using a systematic, data-based approach, followed by a disaggregation step where the lumped parameters are disaggregated based on spatial catchment characteristics (topography, land use, soil characteristics). In this way, disaggregation can be done down to any spatial scale, and consistently among scales. Only few additional calibration parameters are introduced to scale the absolute spatial differences in model parameters, but keeping the relative differences as obtained from the spatial catchment characteristics. After calibration of the spatial model, the accuracies of the lumped and spatial models were compared for peak, low and cumulative runoff total and sub-flows (at downstream and internal gauging stations). For the distributed models, additional validation on spatial results was done for the groundwater head values at observation wells. To ensure that the lumped model can produce results as accurate as the spatially distributed models or close regardless to the number of parameters and implemented physical processes, it was checked whether the structure of the lumped models had to be adjusted. The concept has been implemented in a PCRaster - Python platform and tested for two Belgian case studies (catchments of the rivers Dijle and Grote Nete). So far, use is made of existing model structures (NAM, PDM, VHM and HBV). Acknowledgement: These results were obtained within the scope of research activities for the Flemish Environment Agency (VMM) - division Operational Water Management on "Next Generation hydrological modeling", in cooperation with IMDC consultants, and for Flanders Hydraulics Research (Waterbouwkundig Laboratorium) on "Effect of climate change on the hydrological regime of navigable watercourses in Belgium".

How does the connectivity of open-framework conglomerates within multi-scale hierarchical fluvial architecture affect oil-sweep efficiency in waterflooding?

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

Gershenzon, Naum I.; Soltanian, Mohamad Reza; Ritzi, Robert W.

Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multiphase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations andmore » probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We further analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound- bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.« less

How does the connectivity of open-framework conglomerates within multi-scale hierarchical fluvial architecture affect oil-sweep efficiency in waterflooding?

DOE PAGES

Gershenzon, Naum I.; Soltanian, Mohamad Reza; Ritzi, Robert W.; ...

2015-10-23

Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multiphase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations andmore » probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We further analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound- bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.« less

Effects of Time-Dependent Inflow Perturbations on Turbulent Flow in a Street Canyon

NASA Astrophysics Data System (ADS)

Duan, G.; Ngan, K.

2017-12-01

Urban flow and turbulence are driven by atmospheric flows with larger horizontal scales. Since building-resolving computational fluid dynamics models typically employ steady Dirichlet boundary conditions or forcing, the accuracy of numerical simulations may be limited by the neglect of perturbations. We investigate the sensitivity of flow within a unit-aspect-ratio street canyon to time-dependent perturbations near the inflow boundary. Using large-eddy simulation, time-periodic perturbations to the streamwise velocity component are incorporated via the nudging technique. Spatial averages of pointwise differences between unperturbed and perturbed velocity fields (i.e., the error kinetic energy) show a clear dependence on the perturbation period, though spatial structures are largely insensitive to the time-dependent forcing. The response of the error kinetic energy is maximized for perturbation periods comparable to the time scale of the mean canyon circulation. Frequency spectra indicate that this behaviour arises from a resonance between the inflow forcing and the mean motion around closed streamlines. The robustness of the results is confirmed using perturbations derived from measurements of roof-level wind speed.

Confronting the Paradox of Enrichment to the Metacommunity Perspective

PubMed Central

Hauzy, Céline; Nadin, Grégoire; Canard, Elsa; Gounand, Isabelle; Mouquet, Nicolas; Ebenman, Bo

2013-01-01

Resource enrichment can potentially destabilize predator-prey dynamics. This phenomenon historically referred as the "paradox of enrichment" has mostly been explored in spatially homogenous environments. However, many predator-prey communities exchange organisms within spatially heterogeneous networks called metacommunities. This heterogeneity can result from uneven distribution of resources among communities and thus can lead to the spreading of local enrichment within metacommunities. Here, we adapted the original Rosenzweig-MacArthur predator-prey model, built to study the paradox of enrichment, to investigate the effect of regional enrichment and of its spatial distribution on predator-prey dynamics in metacommunities. We found that the potential for destabilization was depending on the connectivity among communities and the spatial distribution of enrichment. In one hand, we found that at low dispersal regional enrichment led to the destabilization of predator-prey dynamics. This destabilizing effect was more pronounced when the enrichment was uneven among communities. In the other hand, we found that high dispersal could stabilize the predator-prey dynamics when the enrichment was spatially heterogeneous. Our results illustrate that the destabilizing effect of enrichment can be dampened when the spatial scale of resource enrichment is lower than that of organismss movements (heterogeneous enrichment). From a conservation perspective, our results illustrate that spatial heterogeneity could decrease the regional extinction risk of species involved in specialized trophic interactions. From the perspective of biological control, our results show that the heterogeneous distribution of pest resource could favor or dampen outbreaks of pests and of their natural enemies, depending on the spatial scale of heterogeneity. PMID:24358242

Spatial scaling of core and dominant forest cover in the Upper Mississippi and Illinois River floodplains, USA

USGS Publications Warehouse

De Jager, Nathan R.; Rohweder, Jason J.

2011-01-01

Different organisms respond to spatial structure in different terms and across different spatial scales. As a consequence, efforts to reverse habitat loss and fragmentation through strategic habitat restoration ought to account for the different habitat density and scale requirements of various taxonomic groups. Here, we estimated the local density of floodplain forest surrounding each of ~20 million 10-m forested pixels of the Upper Mississippi and Illinois River floodplains by using moving windows of multiple sizes (1–100 ha). We further identified forest pixels that met two local density thresholds: 'core' forest pixels were nested in a 100% (unfragmented) forested window and 'dominant' forest pixels were those nested in a >60% forested window. Finally, we fit two scaling functions to declines in the proportion of forest cover meeting these criteria with increasing window length for 107 management-relevant focal areas: a power function (i.e. self-similar, fractal-like scaling) and an exponential decay function (fractal dimension depends on scale). The exponential decay function consistently explained more variation in changes to the proportion of forest meeting both the 'core' and 'dominant' criteria with increasing window length than did the power function, suggesting that elevation, soil type, hydrology, and human land use constrain these forest types to a limited range of scales. To examine these scales, we transformed the decay constants to measures of the distance at which the probability of forest meeting the 'core' and 'dominant' criteria was cut in half (S 1/2, m). S 1/2 for core forest was typically between ~55 and ~95 m depending on location along the river, indicating that core forest cover is restricted to extremely fine scales. In contrast, half of all dominant forest cover was lost at scales that were typically between ~525 and 750 m, but S 1/2 was as long as 1,800 m. S 1/2 is a simple measure that (1) condenses information derived from multi-scale analyses, (2) allows for comparisons of the amount of forest habitat available to species with different habitat density and scale requirements, and (3) can be used as an index of the spatial continuity of habitat types that do not scale fractally.

Evaluation of normalization methods for cDNA microarray data by k-NN classification

PubMed Central

Wu, Wei; Xing, Eric P; Myers, Connie; Mian, I Saira; Bissell, Mina J

2005-01-01

Background Non-biological factors give rise to unwanted variations in cDNA microarray data. There are many normalization methods designed to remove such variations. However, to date there have been few published systematic evaluations of these techniques for removing variations arising from dye biases in the context of downstream, higher-order analytical tasks such as classification. Results Ten location normalization methods that adjust spatial- and/or intensity-dependent dye biases, and three scale methods that adjust scale differences were applied, individually and in combination, to five distinct, published, cancer biology-related cDNA microarray data sets. Leave-one-out cross-validation (LOOCV) classification error was employed as the quantitative end-point for assessing the effectiveness of a normalization method. In particular, a known classifier, k-nearest neighbor (k-NN), was estimated from data normalized using a given technique, and the LOOCV error rate of the ensuing model was computed. We found that k-NN classifiers are sensitive to dye biases in the data. Using NONRM and GMEDIAN as baseline methods, our results show that single-bias-removal techniques which remove either spatial-dependent dye bias (referred later as spatial effect) or intensity-dependent dye bias (referred later as intensity effect) moderately reduce LOOCV classification errors; whereas double-bias-removal techniques which remove both spatial- and intensity effect reduce LOOCV classification errors even further. Of the 41 different strategies examined, three two-step processes, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, all of which removed intensity effect globally and spatial effect locally, appear to reduce LOOCV classification errors most consistently and effectively across all data sets. We also found that the investigated scale normalization methods do not reduce LOOCV classification error. Conclusion Using LOOCV error of k-NNs as the evaluation criterion, three double-bias-removal normalization strategies, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, outperform other strategies for removing spatial effect, intensity effect and scale differences from cDNA microarray data. The apparent sensitivity of k-NN LOOCV classification error to dye biases suggests that this criterion provides an informative measure for evaluating normalization methods. All the computational tools used in this study were implemented using the R language for statistical computing and graphics. PMID:16045803

Evaluation of normalization methods for cDNA microarray data by k-NN classification.

PubMed

Wu, Wei; Xing, Eric P; Myers, Connie; Mian, I Saira; Bissell, Mina J

2005-07-26

Non-biological factors give rise to unwanted variations in cDNA microarray data. There are many normalization methods designed to remove such variations. However, to date there have been few published systematic evaluations of these techniques for removing variations arising from dye biases in the context of downstream, higher-order analytical tasks such as classification. Ten location normalization methods that adjust spatial- and/or intensity-dependent dye biases, and three scale methods that adjust scale differences were applied, individually and in combination, to five distinct, published, cancer biology-related cDNA microarray data sets. Leave-one-out cross-validation (LOOCV) classification error was employed as the quantitative end-point for assessing the effectiveness of a normalization method. In particular, a known classifier, k-nearest neighbor (k-NN), was estimated from data normalized using a given technique, and the LOOCV error rate of the ensuing model was computed. We found that k-NN classifiers are sensitive to dye biases in the data. Using NONRM and GMEDIAN as baseline methods, our results show that single-bias-removal techniques which remove either spatial-dependent dye bias (referred later as spatial effect) or intensity-dependent dye bias (referred later as intensity effect) moderately reduce LOOCV classification errors; whereas double-bias-removal techniques which remove both spatial- and intensity effect reduce LOOCV classification errors even further. Of the 41 different strategies examined, three two-step processes, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, all of which removed intensity effect globally and spatial effect locally, appear to reduce LOOCV classification errors most consistently and effectively across all data sets. We also found that the investigated scale normalization methods do not reduce LOOCV classification error. Using LOOCV error of k-NNs as the evaluation criterion, three double-bias-removal normalization strategies, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, outperform other strategies for removing spatial effect, intensity effect and scale differences from cDNA microarray data. The apparent sensitivity of k-NN LOOCV classification error to dye biases suggests that this criterion provides an informative measure for evaluating normalization methods. All the computational tools used in this study were implemented using the R language for statistical computing and graphics.

Scaling range sizes to threats for robust predictions of risks to biodiversity.

PubMed

Keith, David A; Akçakaya, H Resit; Murray, Nicholas J

2018-04-01

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range-size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red-list assessments for decades, appropriate spatial scales of AOO for predicting risks of species' extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale-sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1-1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer-scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid-measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape-scale threats to species and ecosystems. © 2017 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Grassland productivity in response to nutrient additions and herbivory is scale-dependent

PubMed Central

Baldwin, Douglas C.; Naithani, Kusum J.

2016-01-01

Vegetation response to nutrient addition can vary across space, yet studies that explicitly incorporate spatial pattern into experimental approaches are rare. To explore whether there are unique spatial scales (grains) at which grass response to nutrients and herbivory is best expressed, we imposed a large (∼3.75 ha) experiment in a South African coastal grassland ecosystem. In two of six 60 × 60 m grassland plots, we imposed a scaled sampling design in which fertilizer was added in replicated sub-plots (1 × 1 m, 2 × 2 m, and 4 × 4 m). The remaining plots either received no additions or were fertilized evenly across the entire area. Three of the six plots were fenced to exclude herbivory. We calculated empirical semivariograms for all plots one year following nutrient additions to determine whether the scale of grass response (biomass and nutrient concentrations) corresponded to the scale of the sub-plot additions and compared these results to reference plots (unfertilized or unscaled) and to plots with and without herbivory. We compared empirical semivariogram parameters to parameters from semivariograms derived from a set of simulated landscapes (neutral models). Empirical semivariograms showed spatial structure in plots that received multi-scaled nutrient additions, particularly at the 2 × 2 m grain. The level of biomass response was predicted by foliar P concentration and, to a lesser extent, N, with the treatment effect of herbivory having a minimal influence. Neutral models confirmed the length scale of the biomass response and indicated few differences due to herbivory. Overall, we conclude that interpretation of nutrient limitation in grasslands is dependent on the grain used to measure grass response and that herbivory had a secondary effect. PMID:27920956

Probing Mantle Heterogeneity Across Spatial Scales

NASA Astrophysics Data System (ADS)

Hariharan, A.; Moulik, P.; Lekic, V.

2017-12-01

Inferences of mantle heterogeneity in terms of temperature, composition, grain size, melt and crystal structure may vary across local, regional and global scales. Probing these scale-dependent effects require quantitative comparisons and reconciliation of tomographic models that vary in their regional scope, parameterization, regularization and observational constraints. While a range of techniques like radial correlation functions and spherical harmonic analyses have revealed global features like the dominance of long-wavelength variations in mantle heterogeneity, they have limited applicability for specific regions of interest like subduction zones and continental cratons. Moreover, issues like discrepant 1-D reference Earth models and related baseline corrections have impeded the reconciliation of heterogeneity between various regional and global models. We implement a new wavelet-based approach that allows for structure to be filtered simultaneously in both the spectral and spatial domain, allowing us to characterize heterogeneity on a range of scales and in different geographical regions. Our algorithm extends a recent method that expanded lateral variations into the wavelet domain constructed on a cubed sphere. The isolation of reference velocities in the wavelet scaling function facilitates comparisons between models constructed with arbitrary 1-D reference Earth models. The wavelet transformation allows us to quantify the scale-dependent consistency between tomographic models in a region of interest and investigate the fits to data afforded by heterogeneity at various dominant wavelengths. We find substantial and spatially varying differences in the spectrum of heterogeneity between two representative global Vp models constructed using different data and methodologies. Applying the orthonormality of the wavelet expansion, we isolate detailed variations in velocity from models and evaluate additional fits to data afforded by adding such complexities to long-wavelength variations. Our method provides a way to probe and evaluate localized features in a multi-scale description of mantle heterogeneity.

Environmental analysis using integrated GIS and remotely sensed data - Some research needs and priorities

NASA Technical Reports Server (NTRS)

Davis, Frank W.; Quattrochi, Dale A.; Ridd, Merrill K.; Lam, Nina S.-N.; Walsh, Stephen J.

1991-01-01

This paper discusses some basic scientific issues and research needs in the joint processing of remotely sensed and GIS data for environmental analysis. Two general topics are treated in detail: (1) scale dependence of geographic data and the analysis of multiscale remotely sensed and GIS data, and (2) data transformations and information flow during data processing. The discussion of scale dependence focuses on the theory and applications of spatial autocorrelation, geostatistics, and fractals for characterizing and modeling spatial variation. Data transformations during processing are described within the larger framework of geographical analysis, encompassing sampling, cartography, remote sensing, and GIS. Development of better user interfaces between image processing, GIS, database management, and statistical software is needed to expedite research on these and other impediments to integrated analysis of remotely sensed and GIS data.

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

Domènech, Guillem; Hiramatsu, Takashi; Lin, Chunshan

We consider a cosmological model in which the tensor mode becomes massive during inflation, and study the Cosmic Microwave Background (CMB) temperature and polarization bispectra arising from the mixing between the scalar mode and the massive tensor mode during inflation. The model assumes the existence of a preferred spatial frame during inflation. The local Lorentz invariance is already broken in cosmology due to the existence of a preferred rest frame. The existence of a preferred spatial frame further breaks the remaining local SO(3) invariance and in particular gives rise to a mass in the tensor mode. At linear perturbation level,more » we minimize our model so that the vector mode remains non-dynamical, while the scalar mode is the same as the one in single-field slow-roll inflation. At non-linear perturbation level, this inflationary massive graviton phase leads to a sizeable scalar-scalar-tensor coupling, much greater than the scalar-scalar-scalar one, as opposed to the conventional case. This scalar-scalar-tensor interaction imprints a scale dependent feature in the CMB temperature and polarization bispectra. Very intriguingly, we find a surprizing similarity between the predicted scale dependence and the scale-dependent non-Gaussianities at low multipoles hinted in the WMAP and Planck results.« less

Application Perspective of 2D+SCALE Dimension

NASA Astrophysics Data System (ADS)

Karim, H.; Rahman, A. Abdul

2016-09-01

Different applications or users need different abstraction of spatial models, dimensionalities and specification of their datasets due to variations of required analysis and output. Various approaches, data models and data structures are now available to support most current application models in Geographic Information System (GIS). One of the focuses trend in GIS multi-dimensional research community is the implementation of scale dimension with spatial datasets to suit various scale application needs. In this paper, 2D spatial datasets that been scaled up as the third dimension are addressed as 2D+scale (or 3D-scale) dimension. Nowadays, various data structures, data models, approaches, schemas, and formats have been proposed as the best approaches to support variety of applications and dimensionality in 3D topology. However, only a few of them considers the element of scale as their targeted dimension. As the scale dimension is concerned, the implementation approach can be either multi-scale or vario-scale (with any available data structures and formats) depending on application requirements (topology, semantic and function). This paper attempts to discuss on the current and new potential applications which positively could be integrated upon 3D-scale dimension approach. The previous and current works on scale dimension as well as the requirements to be preserved for any given applications, implementation issues and future potential applications forms the major discussion of this paper.

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

PubMed

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

2017-11-01

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

Mapping multi-scale vascular plant richness in a forest landscape with integrated LiDAR and hyperspectral remote-sensing.

PubMed

Hakkenberg, C R; Zhu, K; Peet, R K; Song, C

2018-02-01

The central role of floristic diversity in maintaining habitat integrity and ecosystem function has propelled efforts to map and monitor its distribution across forest landscapes. While biodiversity studies have traditionally relied largely on ground-based observations, the immensity of the task of generating accurate, repeatable, and spatially-continuous data on biodiversity patterns at large scales has stimulated the development of remote-sensing methods for scaling up from field plot measurements. One such approach is through integrated LiDAR and hyperspectral remote-sensing. However, despite their efficiencies in cost and effort, LiDAR-hyperspectral sensors are still highly constrained in structurally- and taxonomically-heterogeneous forests - especially when species' cover is smaller than the image resolution, intertwined with neighboring taxa, or otherwise obscured by overlapping canopy strata. In light of these challenges, this study goes beyond the remote characterization of upper canopy diversity to instead model total vascular plant species richness in a continuous-cover North Carolina Piedmont forest landscape. We focus on two related, but parallel, tasks. First, we demonstrate an application of predictive biodiversity mapping, using nonparametric models trained with spatially-nested field plots and aerial LiDAR-hyperspectral data, to predict spatially-explicit landscape patterns in floristic diversity across seven spatial scales between 0.01-900 m 2 . Second, we employ bivariate parametric models to test the significance of individual, remotely-sensed predictors of plant richness to determine how parameter estimates vary with scale. Cross-validated results indicate that predictive models were able to account for 15-70% of variance in plant richness, with LiDAR-derived estimates of topography and forest structural complexity, as well as spectral variance in hyperspectral imagery explaining the largest portion of variance in diversity levels. Importantly, bivariate tests provide evidence of scale-dependence among predictors, such that remotely-sensed variables significantly predict plant richness only at spatial scales that sufficiently subsume geolocational imprecision between remotely-sensed and field data, and best align with stand components including plant size and density, as well as canopy gaps and understory growth patterns. Beyond their insights into the scale-dependent patterns and drivers of plant diversity in Piedmont forests, these results highlight the potential of remotely-sensible essential biodiversity variables for mapping and monitoring landscape floristic diversity from air- and space-borne platforms. © 2017 by the Ecological Society of America.

Magnetic small-angle neutron scattering on bulk metallic glasses: A feasibility study for imaging displacement fields

NASA Astrophysics Data System (ADS)

Mettus, Denis; Deckarm, Michael; Leibner, Andreas; Birringer, Rainer; Stolpe, Moritz; Busch, Ralf; Honecker, Dirk; Kohlbrecher, Joachim; Hautle, Patrick; Niketic, Nemanja; Fernández, Jesús Rodríguez; Barquín, Luis Fernández; Michels, Andreas

2017-12-01

Magnetic-field-dependent small-angle neutron scattering (SANS) has been utilized to study the magnetic microstructure of bulk metallic glasses (BMGs). In particular, the magnetic scattering from soft magnetic Fe70Mo5Ni5P12.5B2.5C5 and hard magnetic (Nd60Fe30Al10) 92Ni8 alloys in the as-prepared, aged, and mechanically deformed state is compared. While the soft magnetic BMGs exhibit a large field-dependent SANS response with perturbations originating predominantly from spatially varying magnetic anisotropy fields, the SANS cross sections of the hard magnetic BMGs are only weakly dependent on the field, and their angular anisotropy indicates the presence of scattering contributions due to spatially dependent saturation magnetization. Moreover, we observe an unusual increase in the magnetization of the rare-earth-based alloy after deformation. Analysis of the SANS cross sections in terms of the correlation function of the spin misalignment reveals the existence of field-dependent anisotropic long-wavelength magnetization fluctuations on a scale of a few tens of nanometers. We also give a detailed account of how the SANS technique relates to unraveling displacement fields on a mesoscopic length scale in disordered magnetic materials.

Grizzly bear habitat selection is scale dependent.

PubMed

Ciarniello, Lana M; Boyce, Mark S; Seip, Dale R; Heard, Douglas C

2007-07-01

The purpose of our study is to show how ecologists' interpretation of habitat selection by grizzly bears (Ursus arctos) is altered by the scale of observation and also how management questions would be best addressed using predetermined scales of analysis. Using resource selection functions (RSF) we examined how variation in the spatial extent of availability affected our interpretation of habitat selection by grizzly bears inhabiting mountain and plateau landscapes. We estimated separate models for females and males using three spatial extents: within the study area, within the home range, and within predetermined movement buffers. We employed two methods for evaluating the effects of scale on our RSF designs. First, we chose a priori six candidate models, estimated at each scale, and ranked them using Akaike Information Criteria. Using this method, results changed among scales for males but not for females. For female bears, models that included the full suite of covariates predicted habitat use best at each scale. For male bears that resided in the mountains, models based on forest successional stages ranked highest at the study-wide and home range extents, whereas models containing covariates based on terrain features ranked highest at the buffer extent. For male bears on the plateau, each scale estimated a different highest-ranked model. Second, we examined differences among model coefficients across the three scales for one candidate model. We found that both the magnitude and direction of coefficients were dependent upon the scale examined; results varied between landscapes, scales, and sexes. Greenness, reflecting lush green vegetation, was a strong predictor of the presence of female bears in both landscapes and males that resided in the mountains. Male bears on the plateau were the only animals to select areas that exposed them to a high risk of mortality by humans. Our results show that grizzly bear habitat selection is scale dependent. Further, the selection of resources can be dependent upon the availability of a particular vegetation type on the landscape. From a management perspective, decisions should be based on a hierarchical process of habitat selection, recognizing that selection patterns vary across scales.

Groundwater-fed irrigation impacts spatially distributed temporal scaling behavior of the natural system: a spatio-temporal framework for understanding water management impacts

NASA Astrophysics Data System (ADS)

Condon, Laura E.; Maxwell, Reed M.

2014-03-01

Regional scale water management analysis increasingly relies on integrated modeling tools. Much recent work has focused on groundwater-surface water interactions and feedbacks. However, to our knowledge, no study has explicitly considered impacts of management operations on the temporal dynamics of the natural system. Here, we simulate twenty years of hourly moisture dependent, groundwater-fed irrigation using a three-dimensional, fully integrated, hydrologic model (ParFlow-CLM). Results highlight interconnections between irrigation demand, groundwater oscillation frequency and latent heat flux variability not previously demonstrated. Additionally, the three-dimensional model used allows for novel consideration of spatial patterns in temporal dynamics. Latent heat flux and water table depth both display spatial organization in temporal scaling, an important finding given the spatial homogeneity and weak scaling observed in atmospheric forcings. Pumping and irrigation amplify high frequency (sub-annual) variability while attenuating low frequency (inter-annual) variability. Irrigation also intensifies scaling within irrigated areas, essentially increasing temporal memory in both the surface and the subsurface. These findings demonstrate management impacts that extend beyond traditional water balance considerations to the fundamental behavior of the system itself. This is an important step to better understanding groundwater’s role as a buffer for natural variability and the impact that water management has on this capacity.

Mapping fuels at multiple scales: landscape application of the fuel characteristic classification system.

Treesearch

D. McKenzie; C.L. Raymond; L.-K.B. Kellogg; R.A. Norheim; A.G. Andreu; A.C. Bayard; K.E. Kopper; E. Elman

2007-01-01

Fuel mapping is a complex and often multidisciplinary process, involving remote sensing, ground-based validation, statistical modeling, and knowledge-based systems. The scale and resolution of fuel mapping depend both on objectives and availability of spatial data layers. We demonstrate use of the Fuel Characteristic Classification System (FCCS) for fuel mapping at two...

Assessments of habitat preferences and quality depend on spatial scale and metrics of fitness

USGS Publications Warehouse

Chalfoun, A.D.; Martin, T.E.

2007-01-01

1. Identifying the habitat features that influence habitat selection and enhance fitness is critical for effective management. Ecological theory predicts that habitat choices should be adaptive, such that fitness is enhanced in preferred habitats. However, studies often report mismatches between habitat preferences and fitness consequences across a wide variety of taxa based on a single spatial scale and/or a single fitness component. 2. We examined whether habitat preferences of a declining shrub steppe songbird, the Brewer's sparrow Spizella breweri, were adaptive when multiple reproductive fitness components and spatial scales (landscape, territory and nest patch) were considered. 3. We found that birds settled earlier and in higher densities, together suggesting preference, in landscapes with greater shrub cover and height. Yet nest success was not higher in these landscapes; nest success was primarily determined by nest predation rates. Thus landscape preferences did not match nest predation risk. Instead, nestling mass and the number of nesting attempts per pair increased in preferred landscapes, raising the possibility that landscapes were chosen on the basis of food availability rather than safe nest sites. 4. At smaller spatial scales (territory and nest patch), birds preferred different habitat features (i.e. density of potential nest shrubs) that reduced nest predation risk and allowed greater season-long reproductive success. 5. Synthesis and applications. Habitat preferences reflect the integration of multiple environmental factors across multiple spatial scales, and individuals may have more than one option for optimizing fitness via habitat selection strategies. Assessments of habitat quality for management prescriptions should ideally include analysis of diverse fitness consequences across multiple ecologically relevant spatial scales. ?? 2007 The Authors.

The Use of Scale-Dependent Precision to Increase Forecast Accuracy in Earth System Modelling

NASA Astrophysics Data System (ADS)

Thornes, Tobias; Duben, Peter; Palmer, Tim

2016-04-01

At the current pace of development, it may be decades before the 'exa-scale' computers needed to resolve individual convective clouds in weather and climate models become available to forecasters, and such machines will incur very high power demands. But the resolution could be improved today by switching to more efficient, 'inexact' hardware with which variables can be represented in 'reduced precision'. Currently, all numbers in our models are represented as double-precision floating points - each requiring 64 bits of memory - to minimise rounding errors, regardless of spatial scale. Yet observational and modelling constraints mean that values of atmospheric variables are inevitably known less precisely on smaller scales, suggesting that this may be a waste of computer resources. More accurate forecasts might therefore be obtained by taking a scale-selective approach whereby the precision of variables is gradually decreased at smaller spatial scales to optimise the overall efficiency of the model. To study the effect of reducing precision to different levels on multiple spatial scales, we here introduce a new model atmosphere developed by extending the Lorenz '96 idealised system to encompass three tiers of variables - which represent large-, medium- and small-scale features - for the first time. In this chaotic but computationally tractable system, the 'true' state can be defined by explicitly resolving all three tiers. The abilities of low resolution (single-tier) double-precision models and similar-cost high resolution (two-tier) models in mixed-precision to produce accurate forecasts of this 'truth' are compared. The high resolution models outperform the low resolution ones even when small-scale variables are resolved in half-precision (16 bits). This suggests that using scale-dependent levels of precision in more complicated real-world Earth System models could allow forecasts to be made at higher resolution and with improved accuracy. If adopted, this new paradigm would represent a revolution in numerical modelling that could be of great benefit to the world.

Space and time scales of shoreline change at Cape Cod National Seashore, MA, USA

USGS Publications Warehouse

Allen, J.R.; LaBash, C.L.; List, J.H.; Kraus, Nicholas C.; McDougal, William G.

1999-01-01

Different processes cause patterns of shoreline change which are exhibited at different magnitudes and nested into different spatial and time scale hierarchies. The 77-km outer beach at Cape Cod National Seashore offers one of the few U.S. federally owned portions of beach to study shoreline change within the full range of sediment source and sink relationships, and barely affected by human intervention. 'Mean trends' of shoreline changes are best observed at long time scales but contain much spatial variation thus many sites are not equal in response. Long-term, earlier-noted trends are confirmed but the added quantification and resolution improves greatly the understanding of appropriate spatial and time scales of those processes driving bluff retreat and barrier island changes in both north and south depocenters. Shorter timescales allow for comparison of trends and uncertainty in shoreline change at local scales but are dependent upon some measure of storm intensity and seasonal frequency. Single-event shoreline survey results for one storm at daily intervals after the erosional phase suggest a recovery time for the system of six days, identifies three sites with abnormally large change, and that responses at these sites are spatially coherent for now unknown reasons. Areas near inlets are the most variable at all time scales. Hierarchies in both process and form are suggested.

Context-dependent colonization dynamics: Regional reward contagion drives local compression in aquatic beetles.

PubMed

Pintar, Matthew R; Resetarits, William J

2017-09-01

Habitat selection by colonizing organisms is an important factor in determining species abundance and community dynamics at multiple spatial scales. Many organisms select habitat patches based on intrinsic patch quality, but patches exist in complex landscapes linked by dispersal and colonization, forming metapopulations and metacommunities. Perceived patch quality can be influenced by neighbouring patches through spatial contagion, wherein perceived quality of one patch can extend beyond its borders and either increase or decrease the colonization of neighbouring patches and localities. These spatially explicit colonization dynamics can result in habitat compression, wherein more colonists occupy a patch or locality than in the absence of spatial context dependence. Previous work on contagion/compression focused primarily on the role of predators in driving colonization patterns. Our goal was to determine whether resource abundance can drive multi-scale colonization dynamics of aquatic beetles through the processes of contagion and compression in naturally colonized experimental pools. We established two levels (high/low quality) of within-patch resource abundances (leaf litter) using an experimental landscape of mesocosms, and assayed colonization by 35 species of aquatic beetles. Patches were arranged in localities (sets of two patches), which consisted of a combination of two patch-level resource levels in a 2 × 2 factorial design, allowing us to assay colonization at both locality and patch levels. We demonstrate that patterns of species abundance and richness of colonizing aquatic beetles are determined by patch quality and context-dependent processes at multiple spatial scales. Localities that consisted of at least one high-quality patch were colonized at equivalent rates that were higher than localities containing only low-quality patches, displaying regional reward contagion. In localities that consisted of one high- and one low-quality patch, reward contagion produced by higher leaf litter levels resulted in greater abundance of beetles in such localities, which then compressed into the highest quality patches. Our results provide further support for the critical roles of habitat selection and spatial context, particularly the quality of neighbouring habitat patches, in generating patterns of species abundances and community structure across landscapes. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Evaluating Water Budget Closure Across Spatial Scales: An Observational Approach through Texas Water Observatory

NASA Astrophysics Data System (ADS)

Gaur, N.; Jaimes, A.; Vaughan, S.; Morgan, C.; Moore, G. W.; Miller, G. R.; Everett, M. E.; Lawing, M.; Mohanty, B.

2017-12-01

Applications varying from improving water conservation practices at the field scale to predicting global hydrology under a changing climate depend upon our ability to achieve water budget closure. 1) Prevalent heterogeneity in soils, geology and land-cover, 2) uncertainties in observations and 3) space-time scales of our control volume and available data are the main factors affecting the percentage of water budget closure that we can achieve. The Texas Water Observatory presents a unique opportunity to observe the major components of the water cycle (namely precipitation, evapotranspiration, root zone soil moisture, streamflow and groundwater) in varying eco-hydrological regions representative of the lower Brazos River basin at multiple scales. The soils in these regions comprise of heavy clays that swell and shrink to create complex preferential pathways in the sub-surface, thus, making the hydrology in this region difficult to quantify. This work evaluates the water budget of the region by varying the control volume in terms of 3 temporal (weekly, monthly and seasonal) and 3 different spatial scales. The spatial scales are 1) Point scale - that is typical for process understanding of water dynamics, 2) Eddy Covariance footprint scale - that is typical of most eco-hydrological applications at the field scale and, 3) Satellite footprint scale- that is typically used in regional and global hydrological analysis. We employed a simple water balance model to evaluate the water budget at all scales. The point scale water budget was assessed using direct observations from hydro-geo-thematically located observation locations within different eddy covariance footprints. At the eddy covariance footprint scale, the sub-surface of each eddy covariance footprint was intensively characterized using electromagnetic induction (EM 38) and the resultant data was used to calculate the inter-point variability to upscale the sub-surface storage while the satellite scale water budget was evaluated using SMAP satellite observations supplemented with reanalysis products. At the point scale, we found differences in sub-surface storage in the same land-cover depending on the landscape position of the observation point while land-cover significantly affected water budget at the larger scales.

Spatially explicit modeling in ecology: A review

USGS Publications Warehouse

DeAngelis, Donald L.; Yurek, Simeon

2017-01-01

The use of spatially explicit models (SEMs) in ecology has grown enormously in the past two decades. One major advancement has been that fine-scale details of landscapes, and of spatially dependent biological processes, such as dispersal and invasion, can now be simulated with great precision, due to improvements in computer technology. Many areas of modeling have shifted toward a focus on capturing these fine-scale details, to improve mechanistic understanding of ecosystems. However, spatially implicit models (SIMs) have played a dominant role in ecology, and arguments have been made that SIMs, which account for the effects of space without specifying spatial positions, have an advantage of being simpler and more broadly applicable, perhaps contributing more to understanding. We address this debate by comparing SEMs and SIMs in examples from the past few decades of modeling research. We argue that, although SIMs have been the dominant approach in the incorporation of space in theoretical ecology, SEMs have unique advantages for addressing pragmatic questions concerning species populations or communities in specific places, because local conditions, such as spatial heterogeneities, organism behaviors, and other contingencies, produce dynamics and patterns that usually cannot be incorporated into simpler SIMs. SEMs are also able to describe mechanisms at the local scale that can create amplifying positive feedbacks at that scale, creating emergent patterns at larger scales, and therefore are important to basic ecological theory. We review the use of SEMs at the level of populations, interacting populations, food webs, and ecosystems and argue that SEMs are not only essential in pragmatic issues, but must play a role in the understanding of causal relationships on landscapes.

Linking the influence and dependence of people on biodiversity across scales

PubMed Central

Isbell, Forest; Gonzalez, Andrew; Loreau, Michel; Cowles, Jane; Díaz, Sandra; Hector, Andy; Mace, Georgina M.; Wardle, David A.; O’Connor, Mary I.; Duffy, J. Emmett; Turnbull, Lindsay A.; Thompson, Patrick L.; Larigauderie, Anne

2017-01-01

Biodiversity enhances many of nature’s benefits to people, including the regulation of climate and the production of wood in forests, livestock forage in grasslands and fish in aquatic ecosystems. Yet people are now driving the sixth mass extinction event in Earth’s history. Human dependence and influence on biodiversity have mainly been studied separately and at contrasting scales of space and time, but new multiscale knowledge is beginning to link these relationships. Biodiversity loss substantially diminishes several ecosystem services by altering ecosystem functioning and stability, especially at the large temporal and spatial scales that are most relevant for policy and conservation. PMID:28569811

Complex-ordered patterns in shaken convection.

PubMed

Rogers, Jeffrey L; Pesch, Werner; Brausch, Oliver; Schatz, Michael F

2005-06-01

We report and analyze complex patterns observed in a combination of two standard pattern forming experiments. These exotic states are composed of two distinct spatial scales, each displaying a different temporal dependence. The system is a fluid layer experiencing forcing from both a vertical temperature difference and vertical time-periodic oscillations. Depending on the parameters these forcing mechanisms produce fluid motion with either a harmonic or a subharmonic temporal response. Over a parameter range where these mechanisms have comparable influence the spatial scales associated with both responses are found to coexist, resulting in complex, yet highly ordered patterns. Phase diagrams of this region are reported and criteria to define the patterns as quasiperiodic crystals or superlattices are presented. These complex patterns are found to satisfy four-mode (resonant tetrad) conditions. The qualitative difference between the present formation mechanism and the resonant triads ubiquitously used to explain complex-ordered patterns in other nonequilibrium systems is discussed. The only exception to quantitative agreement between our analysis based on Boussinesq equations and laboratory investigations is found to be the result of breaking spatial symmetry in a small parameter region near onset.

Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh.

PubMed

Bi, Qifang; Azman, Andrew S; Satter, Syed Moinuddin; Khan, Azharul Islam; Ahmed, Dilruba; Riaj, Altaf Ahmed; Gurley, Emily S; Lessler, Justin

2016-02-01

Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets) near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs) to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98), type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00), and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00) exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a cholera endemic population suggests a possible role for highly targeted interventions. Studies with cluster designs in areas with strong spatial clustering of exposures should increase sample size to account for the correlation of these exposures.

Scale dependence of disease impacts on quaking aspen (Populus tremuloides) mortality in the southwestern United States

USGS Publications Warehouse

Bell, David M.; Bradford, John B.; Lauenroth, William K.

2015-01-01

By examining variation in disease prevalence, mortality of healthy trees, and mortality of diseased trees, we showed that the role of disease in aspen tree mortality depended on the scale of inference. For variation among individuals in diameter, disease tended to expose intermediate-size trees experiencing moderate risk to greater risk. For spatial variation in summer temperature, disease exposed lower risk populations to greater mortality probabilities, but the magnitude of this exposure depended on summer precipitation. Furthermore, the importance of diameter and slenderness in mediating responses to climate supports the increasing emphasis on trait variation in studies of ecological responses to global change.

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

LaGory, K. E.; Walston, L. J.; Goulet, C

The decline of many snake populations is attributable to habitat loss, and knowledge of habitat use is critical to their conservation. Resource characteristics (e.g., relative availability of different habitat types, soils, and slopes) within a landscape are scale-dependent and may not be equal across multiple spatial scales. Thus, it is important to identify the relevant spatial scales at which resource selection occurs. We conducted a radiotelemetry study of eastern hognose snake (Heterodon platirhinos) home range size and resource use at different hierarchical spatial scales. We present the results for 8 snakes radiotracked during a 2-year study at New Boston Airmore » Force Station (NBAFS) in southern New Hampshire, USA, where the species is listed by the state as endangered. Mean home range size (minimum convex polygon) at NBAFS (51.7 {+-} 14.7 ha) was similar to that reported in other parts of the species range. Radiotracked snakes exhibited different patterns of resource use at different spatial scales. At the landscape scale (selection of locations within the landscape), snakes overutilized old-field and forest edge habitats and underutilized forested habitats and wetlands relative to availability. At this scale, snakes also overutilized areas containing sandy loam soils and areas with lower slope (mean slope = 5.2% at snake locations vs. 6.7% at random locations). We failed to detect some of these patterns of resource use at the home range scale (i.e., within the home range). Our ability to detect resource selection by the snakes only at the landscape scale is likely the result of greater heterogeneity in macrohabitat features at the broader landscape scale. From a management perspective, future studies of habitat selection for rare species should include measurement of available habitat at spatial scales larger than the home range. We suggest that the maintenance of open early successional habitats as a component of forested landscapes will be critical for the persistence of eastern hognose snake populations in the northeastern United States.« less

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

PubMed

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

2017-02-01

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

Scale-Dependent Habitat Selection and Size-Based Dominance in Adult Male American Alligators

PubMed Central

Strickland, Bradley A.; Vilella, Francisco J.; Belant, Jerrold L.

2016-01-01

Habitat selection is an active behavioral process that may vary across spatial and temporal scales. Animals choose an area of primary utilization (i.e., home range) then make decisions focused on resource needs within patches. Dominance may affect the spatial distribution of conspecifics and concomitant habitat selection. Size-dependent social dominance hierarchies have been documented in captive alligators, but evidence is lacking from wild populations. We studied habitat selection for adult male American alligators (Alligator mississippiensis; n = 17) on the Pearl River in central Mississippi, USA, to test whether habitat selection was scale-dependent and individual resource selectivity was a function of conspecific body size. We used K-select analysis to quantify selection at the home range scale and patches within the home range to determine selection congruency and important habitat variables. In addition, we used linear models to determine if body size was related to selection patterns and strengths. Our results indicated habitat selection of adult male alligators was a scale-dependent process. Alligators demonstrated greater overall selection for habitat variables at the patch level and less at the home range level, suggesting resources may not be limited when selecting a home range for animals in our study area. Further, diurnal habitat selection patterns may depend on thermoregulatory needs. There was no relationship between resource selection or home range size and body size, suggesting size-dependent dominance hierarchies may not have influenced alligator resource selection or space use in our sample. Though apparent habitat suitability and low alligator density did not manifest in an observed dominance hierarchy, we hypothesize that a change in either could increase intraspecific interactions, facilitating a dominance hierarchy. Due to the broad and diverse ecological roles of alligators, understanding the factors that influence their social dominance and space use can provide great insight into their functional role in the ecosystem. PMID:27588947

Scale-dependent habitat selection and size-based dominance in adult male American alligators

USGS Publications Warehouse

Strickland, Bradley A.; Vilella, Francisco; Belant, Jerrold L.

2016-01-01

Habitat selection is an active behavioral process that may vary across spatial and temporal scales. Animals choose an area of primary utilization (i.e., home range) then make decisions focused on resource needs within patches. Dominance may affect the spatial distribution of conspecifics and concomitant habitat selection. Size-dependent social dominance hierarchies have been documented in captive alligators, but evidence is lacking from wild populations. We studied habitat selection for adult male American alligators (Alligator mississippiensis; n = 17) on the Pearl River in central Mississippi, USA, to test whether habitat selection was scale-dependent and individual resource selectivity was a function of conspecific body size. We used K-select analysis to quantify selection at the home range scale and patches within the home range to determine selection congruency and important habitat variables. In addition, we used linear models to determine if body size was related to selection patterns and strengths. Our results indicated habitat selection of adult male alligators was a scale-dependent process. Alligators demonstrated greater overall selection for habitat variables at the patch level and less at the home range level, suggesting resources may not be limited when selecting a home range for animals in our study area. Further, diurnal habitat selection patterns may depend on thermoregulatory needs. There was no relationship between resource selection or home range size and body size, suggesting size-dependent dominance hierarchies may not have influenced alligator resource selection or space use in our sample. Though apparent habitat suitability and low alligator density did not manifest in an observed dominance hierarchy, we hypothesize that a change in either could increase intraspecific interactions, facilitating a dominance hierarchy. Due to the broad and diverse ecological roles of alligators, understanding the factors that influence their social dominance and space use can provide great insight into their functional role in the ecosystem.

Wave actions and topography determine the small-scale spatial distribution of newly settled Asari clams Ruditapes philippinarum on a tidal flat

NASA Astrophysics Data System (ADS)

Nambu, Ryogen; Saito, Hajime; Tanaka, Yoshio; Higano, Junya; Kuwahara, Hisami

2012-03-01

There are many studies on spatial distributions of Asari clam Ruditapes philippinarum adults on tidal flats but few have dealt with spatial distributions of newly settled Asari clam (<0.3 mm shell length, indicative of settlement patterns) in relation to physical/topographical conditions on tidal flats. We examined small-scale spatial distributions of newly settled individuals on the Matsunase tidal flat, central Japan, during the low spring tides on two days 29th-30th June 2007, together with the shear stress from waves and currents on the flat. The characteristics of spatial distribution of newly settled Asari clam markedly varied depending on both of hydrodynamic and topographical conditions on the tidal flat. Using generalized linear models (GLMs), factors responsible for affecting newly settled Asari clam density and its spatial distribution were distinguished between sampling days, with "crest" sites always having a negative influence each on the density and the distribution on both sampling days. The continuously recorded data for the wave-current flows at the "crest" site on the tidal flat showed that newly settled Asari clam, as well as bottom sediment particles, at the "crest" site to be easily displaced. Small-scale spatial distributions of newly settled Asari clam changed with more advanced benthic stages in relation to the wave shear stress.

Multi-Scale and Object-Oriented Analysis for Mountain Terrain Segmentation and Geomorphological Assessment

NASA Astrophysics Data System (ADS)

Marston, B. K.; Bishop, M. P.; Shroder, J. F.

2009-12-01

Digital terrain analysis of mountain topography is widely utilized for mapping landforms, assessing the role of surface processes in landscape evolution, and estimating the spatial variation of erosion. Numerous geomorphometry techniques exist to characterize terrain surface parameters, although their utility to characterize the spatial hierarchical structure of the topography and permit an assessment of the erosion/tectonic impact on the landscape is very limited due to scale and data integration issues. To address this problem, we apply scale-dependent geomorphometric and object-oriented analyses to characterize the hierarchical spatial structure of mountain topography. Specifically, we utilized a high resolution digital elevation model to characterize complex topography in the Shimshal Valley in the Western Himalaya of Pakistan. To accomplish this, we generate terrain objects (geomorphological features and landform) including valley floors and walls, drainage basins, drainage network, ridge network, slope facets, and elemental forms based upon curvature. Object-oriented analysis was used to characterize object properties accounting for object size, shape, and morphometry. The spatial overlay and integration of terrain objects at various scales defines the nature of the hierarchical organization. Our results indicate that variations in the spatial complexity of the terrain hierarchical organization is related to the spatio-temporal influence of surface processes and landscape evolution dynamics. Terrain segmentation and the integration of multi-scale terrain information permits further assessment of process domains and erosion, tectonic impact potential, and natural hazard potential. We demonstrate this with landform mapping and geomorphological assessment examples.

Classification of Farmland Landscape Structure in Multiple Scales

NASA Astrophysics Data System (ADS)

Jiang, P.; Cheng, Q.; Li, M.

2017-12-01

Farmland is one of the basic terrestrial resources that support the development and survival of human beings and thus plays a crucial role in the national security of every country. Pattern change is the intuitively spatial representation of the scale and quality variation of farmland. Through the characteristic development of spatial shapes as well as through changes in system structures, functions and so on, farmland landscape patterns may indicate the landscape health level. Currently, it is still difficult to perform positioning analyses of landscape pattern changes that reflect the landscape structure variations of farmland with an index model. Depending on a number of spatial properties such as locations and adjacency relations, distance decay, fringe effect, and on the model of patch-corridor-matrix that is applied, this study defines a type system of farmland landscape structure on the national, provincial, and city levels. According to such a definition, the classification model of farmland landscape-structure type at the pixel scale is developed and validated based on mathematical-morphology concepts and on spatial-analysis methods. Then, the laws that govern farmland landscape-pattern change in multiple scales are analyzed from the perspectives of spatial heterogeneity, spatio-temporal evolution, and function transformation. The result shows that the classification model of farmland landscape-structure type can reflect farmland landscape-pattern change and its effects on farmland production function. Moreover, farmland landscape change in different scales displayed significant disparity in zonality, both within specific regions and in urban-rural areas.

Spatial variation in the climatic predictors of species compositional turnover and endemism.

PubMed

Di Virgilio, Giovanni; Laffan, Shawn W; Ebach, Malte C; Chapple, David G

2014-08-01

Previous research focusing on broad-scale or geographically invariant species-environment dependencies suggest that temperature-related variables explain more of the variation in reptile distributions than precipitation. However, species-environment relationships may exhibit considerable spatial variation contingent upon the geographic nuances that vary between locations. Broad-scale, geographically invariant analyses may mask this local variation and their findings may not generalize to different locations at local scales. We assess how reptile-climatic relationships change with varying spatial scale, location, and direction. Since the spatial distributions of diversity and endemism hotspots differ for other species groups, we also assess whether reptile species turnover and endemism hotspots are influenced differently by climatic predictors. Using New Zealand reptiles as an example, the variation in species turnover, endemism and turnover in climatic variables was measured using directional moving window analyses, rotated through 360°. Correlations between the species turnover, endemism and climatic turnover results generated by each rotation of the moving window were analysed using multivariate generalized linear models applied at national, regional, and local scales. At national-scale, temperature turnover consistently exhibited the greatest influence on species turnover and endemism, but model predictive capacity was low (typically r (2) = 0.05, P < 0.001). At regional scales the relative influence of temperature and precipitation turnover varied between regions, although model predictive capacity was also generally low. Climatic turnover was considerably more predictive of species turnover and endemism at local scales (e.g., r (2) = 0.65, P < 0.001). While temperature turnover had the greatest effect in one locale (the northern North Island), there was substantial variation in the relative influence of temperature and precipitation predictors in the remaining four locales. Species turnover and endemism hotspots often occurred in different locations. Climatic predictors had a smaller influence on endemism. Our results caution against assuming that variability in temperature will always be most predictive of reptile biodiversity across different spatial scales, locations and directions. The influence of climatic turnover on the species turnover and endemism of other taxa may exhibit similar patterns of spatial variation. Such intricate variation might be discerned more readily if studies at broad scales are complemented by geographically variant, local-scale analyses.

The scale dependence of optical diversity in a prairie ecosystem

NASA Astrophysics Data System (ADS)

Gamon, J. A.; Wang, R.; Stilwell, A.; Zygielbaum, A. I.; Cavender-Bares, J.; Townsend, P. A.

2015-12-01

Biodiversity loss, one of the most crucial challenges of our time, endangers ecosystem services that maintain human wellbeing. Traditional methods of measuring biodiversity require extensive and costly field sampling by biologists with extensive experience in species identification. Remote sensing can be used for such assessment based upon patterns of optical variation. This provides efficient and cost-effective means to determine ecosystem diversity at different scales and over large areas. Sampling scale has been described as a "fundamental conceptual problem" in ecology, and is an important practical consideration in both remote sensing and traditional biodiversity studies. On the one hand, with decreasing spatial and spectral resolution, the differences among different optical types may become weak or even disappear. Alternately, high spatial and/or spectral resolution may introduce redundant or contradictory information. For example, at high resolution, the variation within optical types (e.g., between leaves on a single plant canopy) may add complexity unrelated to specie richness. We studied the scale-dependence of optical diversity in a prairie ecosystem at Cedar Creek Ecosystem Science Reserve, Minnesota, USA using a variety of spectrometers from several platforms on the ground and in the air. Using the coefficient of variation (CV) of spectra as an indicator of optical diversity, we found that high richness plots generally have a higher coefficient of variation. High resolution imaging spectrometer data (1 mm pixels) showed the highest sensitivity to richness level. With decreasing spatial resolution, the difference in CV between richness levels decreased, but remained significant. These findings can be used to guide airborne studies of biodiversity and develop more effective large-scale biodiversity sampling methods.

Multi-scale approaches for high-speed imaging and analysis of large neural populations

PubMed Central

Ahrens, Misha B.; Yuste, Rafael; Peterka, Darcy S.; Paninski, Liam

2017-01-01

Progress in modern neuroscience critically depends on our ability to observe the activity of large neuronal populations with cellular spatial and high temporal resolution. However, two bottlenecks constrain efforts towards fast imaging of large populations. First, the resulting large video data is challenging to analyze. Second, there is an explicit tradeoff between imaging speed, signal-to-noise, and field of view: with current recording technology we cannot image very large neuronal populations with simultaneously high spatial and temporal resolution. Here we describe multi-scale approaches for alleviating both of these bottlenecks. First, we show that spatial and temporal decimation techniques based on simple local averaging provide order-of-magnitude speedups in spatiotemporally demixing calcium video data into estimates of single-cell neural activity. Second, once the shapes of individual neurons have been identified at fine scale (e.g., after an initial phase of conventional imaging with standard temporal and spatial resolution), we find that the spatial/temporal resolution tradeoff shifts dramatically: after demixing we can accurately recover denoised fluorescence traces and deconvolved neural activity of each individual neuron from coarse scale data that has been spatially decimated by an order of magnitude. This offers a cheap method for compressing this large video data, and also implies that it is possible to either speed up imaging significantly, or to “zoom out” by a corresponding factor to image order-of-magnitude larger neuronal populations with minimal loss in accuracy or temporal resolution. PMID:28771570

Deciphering the Costs of Reproduction in Mango – Vegetative Growth Matters

PubMed Central

Capelli, Mathilde; Lauri, Pierre-Éric; Normand, Frédéric

2016-01-01

Irregular fruit production across successive years is a major issue that limits the profitability of most temperate and tropical fruit crops. It is particularly affected by the reciprocal relationships between vegetative and reproductive growth. The concept of the costs of reproduction is defined in terms of losses in the potential future reproductive success caused by current investment in reproduction. This concept, developed in ecology and evolutionary biology, could provide a methodological framework to analyze irregular bearing in fruit crops, especially in relation to the spatial scale at which studies are done. The objective of this study was to investigate the direct effects of reproduction during a growing cycle on reproduction during the following growing cycle and the indirect effects through vegetative growth between these two reproductive events, for four mango cultivars and during two growing cycles. Two spatial scales were considered: the growth unit (GU) and the scaffold branch. Costs of reproduction were detected between two successive reproductive events and between reproduction and vegetative growth. These costs were scale-dependent, generally detected at the GU scale and infrequently at the scaffold branch scale, suggesting partial branch autonomy with respect to processes underlying the effects of reproduction on vegetative growth. In contrast, the relationships between vegetative growth and reproduction were positive at the GU scale and at the scaffold branch scale in most cases, suggesting branch autonomy for the processes, mainly local, underlying flowering and fruiting. The negative effect of reproduction on vegetative growth prevailed over the positive effect of vegetative growth on the subsequent reproduction. The costs of reproduction were also cultivar-dependent. Those revealed at the GU scale were related to the bearing behavior of each cultivar. Our results put forward the crucial role of vegetative growth occurring between two reproductive events. They are discussed in the context of irregular bearing considering both the spatial scale and the various bearing habits of the mango cultivars, in order to formulate new hypotheses about this issue. PMID:27818665

Addressing scale dependence in roughness and morphometric statistics derived from point cloud data.

NASA Astrophysics Data System (ADS)

Buscombe, D.; Wheaton, J. M.; Hensleigh, J.; Grams, P. E.; Welcker, C. W.; Anderson, K.; Kaplinski, M. A.

2015-12-01

The heights of natural surfaces can be measured with such spatial density that almost the entire spectrum of physical roughness scales can be characterized, down to the morphological form and grain scales. With an ability to measure 'microtopography' comes a demand for analytical/computational tools for spatially explicit statistical characterization of surface roughness. Detrended standard deviation of surface heights is a popular means to create continuous maps of roughness from point cloud data, using moving windows and reporting window-centered statistics of variations from a trend surface. If 'roughness' is the statistical variation in the distribution of relief of a surface, then 'texture' is the frequency of change and spatial arrangement of roughness. The variance in surface height as a function of frequency obeys a power law. In consequence, roughness is dependent on the window size through which it is examined, which has a number of potential disadvantages: 1) the choice of window size becomes crucial, and obstructs comparisons between data; 2) if windows are large relative to multiple roughness scales, it is harder to discriminate between those scales; 3) if roughness is not scaled by the texture length scale, information on the spacing and clustering of roughness `elements' can be lost; and 4) such practice is not amenable to models describing the scattering of light and sound from rough natural surfaces. We discuss the relationship between roughness and texture. Some useful parameters which scale vertical roughness to characteristic horizontal length scales are suggested, with examples of bathymetric point clouds obtained using multibeam from two contrasting riverbeds, namely those of the Colorado River in Grand Canyon, and the Snake River in Hells Canyon. Such work, aside from automated texture characterization and texture segmentation, roughness and grain size calculation, might also be useful for feature detection and classification from point clouds.

Verifying the Dependence of Fractal Coefficients on Different Spatial Distributions

NASA Astrophysics Data System (ADS)

Gospodinov, Dragomir; Marekova, Elisaveta; Marinov, Alexander

2010-01-01

A fractal distribution requires that the number of objects larger than a specific size r has a power-law dependence on the size N(r) = C/rD∝r-D where D is the fractal dimension. Usually the correlation integral is calculated to estimate the correlation fractal dimension of epicentres. A `box-counting' procedure could also be applied giving the `capacity' fractal dimension. The fractal dimension can be an integer and then it is equivalent to a Euclidean dimension (it is zero of a point, one of a segment, of a square is two and of a cube is three). In general the fractal dimension is not an integer but a fractional dimension and there comes the origin of the term `fractal'. The use of a power-law to statistically describe a set of events or phenomena reveals the lack of a characteristic length scale, that is fractal objects are scale invariant. Scaling invariance and chaotic behavior constitute the base of a lot of natural hazards phenomena. Many studies of earthquakes reveal that their occurrence exhibits scale-invariant properties, so the fractal dimension can characterize them. It has first been confirmed that both aftershock rate decay in time and earthquake size distribution follow a power law. Recently many other earthquake distributions have been found to be scale-invariant. The spatial distribution of both regional seismicity and aftershocks show some fractal features. Earthquake spatial distributions are considered fractal, but indirectly. There are two possible models, which result in fractal earthquake distributions. The first model considers that a fractal distribution of faults leads to a fractal distribution of earthquakes, because each earthquake is characteristic of the fault on which it occurs. The second assumes that each fault has a fractal distribution of earthquakes. Observations strongly favour the first hypothesis. The fractal coefficients analysis provides some important advantages in examining earthquake spatial distribution, which are:—Simple way to quantify scale-invariant distributions of complex objects or phenomena by a small number of parameters.—It is becoming evident that the applicability of fractal distributions to geological problems could have a more fundamental basis. Chaotic behaviour could underlay the geotectonic processes and the applicable statistics could often be fractal. The application of fractal distribution analysis has, however, some specific aspects. It is usually difficult to present an adequate interpretation of the obtained values of fractal coefficients for earthquake epicenter or hypocenter distributions. That is why in this paper we aimed at other goals—to verify how a fractal coefficient depends on different spatial distributions. We simulated earthquake spatial data by generating randomly points first in a 3D space - cube, then in a parallelepiped, diminishing one of its sides. We then continued this procedure in 2D and 1D space. For each simulated data set we calculated the points' fractal coefficient (correlation fractal dimension of epicentres) and then checked for correlation between the coefficients values and the type of spatial distribution. In that way one can obtain a set of standard fractal coefficients' values for varying spatial distributions. These then can be used when real earthquake data is analyzed by comparing the real data coefficients values to the standard fractal coefficients. Such an approach can help in interpreting the fractal analysis results through different types of spatial distributions.

Orientation decoding depends on maps, not columns

PubMed Central

Freeman, Jeremy; Brouwer, Gijs Joost; Heeger, David J.; Merriam, Elisha P.

2011-01-01

The representation of orientation in primary visual cortex (V1) has been examined at a fine spatial scale corresponding to the columnar architecture. We present functional magnetic resonance imaging (fMRI) measurements providing evidence for a topographic map of orientation preference in human V1 at a much coarser scale, in register with the angular-position component of the retinotopic map of V1. This coarse-scale orientation map provides a parsimonious explanation for why multivariate pattern analysis methods succeed in decoding stimulus orientation from fMRI measurements, challenging the widely-held assumption that decoding results reflect sampling of spatial irregularities in the fine-scale columnar architecture. Decoding stimulus attributes and cognitive states from fMRI measurements has proven useful for a number of applications, but our results demonstrate that the interpretation cannot assume decoding reflects or exploits columnar organization. PMID:21451017

Fractals and Spatial Methods for Mining Remote Sensing Imagery

NASA Technical Reports Server (NTRS)

Lam, Nina; Emerson, Charles; Quattrochi, Dale

2003-01-01

The rapid increase in digital remote sensing and GIS data raises a critical problem -- how can such an enormous amount of data be handled and analyzed so that useful information can be derived quickly? Efficient handling and analysis of large spatial data sets is central to environmental research, particularly in global change studies that employ time series. Advances in large-scale environmental monitoring and modeling require not only high-quality data, but also reliable tools to analyze the various types of data. A major difficulty facing geographers and environmental scientists in environmental assessment and monitoring is that spatial analytical tools are not easily accessible. Although many spatial techniques have been described recently in the literature, they are typically presented in an analytical form and are difficult to transform to a numerical algorithm. Moreover, these spatial techniques are not necessarily designed for remote sensing and GIS applications, and research must be conducted to examine their applicability and effectiveness in different types of environmental applications. This poses a chicken-and-egg problem: on one hand we need more research to examine the usability of the newer techniques and tools, yet on the other hand, this type of research is difficult to conduct if the tools to be explored are not accessible. Another problem that is fundamental to environmental research are issues related to spatial scale. The scale issue is especially acute in the context of global change studies because of the need to integrate remote-sensing and other spatial data that are collected at different scales and resolutions. Extrapolation of results across broad spatial scales remains the most difficult problem in global environmental research. There is a need for basic characterization of the effects of scale on image data, and the techniques used to measure these effects must be developed and implemented to allow for a multiple scale assessment of the data before any useful process-oriented modeling involving scale-dependent data can be conducted. Through the support of research grants from NASA, we have developed a software module called ICAMS (Image Characterization And Modeling System) to address the need to develop innovative spatial techniques and make them available to the broader scientific communities. ICAMS provides new spatial techniques, such as fractal analysis, geostatistical functions, and multiscale analysis that are not easily available in commercial GIS/image processing software. By bundling newer spatial methods in a user-friendly software module, researchers can begin to test and experiment with the new spatial analysis methods and they can gauge scale effects using a variety of remote sensing imagery. In the following, we describe briefly the development of ICAMS and present application examples.

Describing a multitrophic plant-herbivore-parasitoid system at four spatial scales

NASA Astrophysics Data System (ADS)

Cuautle, M.; Parra-Tabla, V.

2014-02-01

Herbivore-parasitoid interactions must be studied using a multitrophic and multispecies approach. The strength and direction of multiple effects through trophic levels may change across spatial scales. In this work, we use the herbaceous plant Ruellia nudiflora, its moth herbivore Tripudia quadrifera, and several parasitoid morphospecies that feed on the herbivore to answer the following questions: Do herbivore and parasitoid attack levels vary depending on the spatial scale considered? With which plant characteristics are the parasitoid and the herbivore associated? Do parasitoid morphospecies vary in the magnitude of their positive indirect effect on plant reproduction? We evaluated three approximations of herbivore and parasitoid abundance (raw numbers, ratios, and attack rates) at four spatial scales: regional (three different regions which differ in terms of abiotic and biotic characteristics); population (i.e. four populations within each region); patch (four 1 m2 plots in each population); and plant level (using a number of plant characteristics). Finally, we determined whether parasitoids have a positive indirect effect on plant reproductive success (seed number). Herbivore and parasitoid numbers differed at three of the spatial scales considered. However, herbivore/fruit ratio and attack rates did not differ at the population level. Parasitoid/host ratio and attack rates did not differ at any scale, although there was a tendency of a higher attack in one region. At the plant level, herbivore and parasitoid abundances were related to different plant traits, varying the importance and the direction (positive or negative) of those traits. In addition, only one parasitoid species (Bracon sp.) had a positive effect on plant fitness saving up to 20% of the seeds in a fruit. These results underline the importance of knowing the scales that are relevant to organisms at different trophic levels and distinguish between the specific effects of species.

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

PubMed

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

2013-01-01

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

Static and dynamic properties of two-dimensional Coulomb clusters.

PubMed

Ash, Biswarup; Chakrabarti, J; Ghosal, Amit

2017-10-01

We study the temperature dependence of static and dynamic responses of Coulomb interacting particles in two-dimensional confinements across the crossover from solid- to liquid-like behaviors. While static correlations that investigate the translational and bond orientational order in the confinements show the footprints of hexatic-like phase at low temperatures, dynamics of the particles slow down considerably in this phase, reminiscent of a supercooled liquid. Using density correlations, we probe long-lived heterogeneities arising from the interplay of the irregularity in the confinement and long-range Coulomb interactions. The relaxation at multiple time scales show stretched-exponential decay of spatial correlations in irregular traps. Temperature dependence of characteristic time scales, depicting the structural relaxation of the system, show striking similarities with those observed for the glassy systems, indicating that some of the key signatures of supercooled liquids emerge in confinements with lower spatial symmetries.

Canopies to Continents: What spatial scales are needed to represent landcover distributions in earth system models?

NASA Astrophysics Data System (ADS)

Guenther, A. B.; Duhl, T.

2011-12-01

Increasing computational resources have enabled a steady improvement in the spatial resolution used for earth system models. Land surface models and landcover distributions have kept ahead by providing higher spatial resolution than typically used in these models. Satellite observations have played a major role in providing high resolution landcover distributions over large regions or the entire earth surface but ground observations are needed to calibrate these data and provide accurate inputs for models. As our ability to resolve individual landscape components improves, it is important to consider what scale is sufficient for providing inputs to earth system models. The required spatial scale is dependent on the processes being represented and the scientific questions being addressed. This presentation will describe the development a contiguous U.S. landcover database using high resolution imagery (1 to 1000 meters) and surface observations of species composition and other landcover characteristics. The database includes plant functional types and species composition and is suitable for driving land surface models (CLM and MEGAN) that predict land surface exchange of carbon, water, energy and biogenic reactive gases (e.g., isoprene, sesquiterpenes, and NO). We investigate the sensitivity of model results to landcover distributions with spatial scales ranging over six orders of magnitude (1 meter to 1000000 meters). The implications for predictions of regional climate and air quality will be discussed along with recommendations for regional and global earth system modeling.

Scale-Dependent Rates of Uranyl Surface Complexation Reaction in Sediments

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

Liu, Chongxuan; Shang, Jianying; Kerisit, Sebastien N.

Scale-dependency of uranyl[U(VI)] surface complexation rates was investigated in stirred flow-cell and column systems using a U(VI)-contaminated sediment from the US Department of Energy, Hanford site, WA. The experimental results were used to estimate the apparent rate of U(VI) surface complexation at the grain-scale and in porous media. Numerical simulations using molecular, pore-scale, and continuum models were performed to provide insights into and to estimate the rate constants of U(VI) surface complexation at the different scales. The results showed that the grain-scale rate constant of U(VI) surface complexation was over 3 to 10 orders of magnitude smaller, dependent on themore » temporal scale, than the rate constant calculated using the molecular simulations. The grain-scale rate was faster initially and slower with time, showing the temporal scale-dependency. The largest rate constant at the grain-scale decreased additional 2 orders of magnitude when the rate was scaled to the porous media in the column. The scaling effect from the grain-scale to the porous media became less important for the slower sorption sites. Pore-scale simulations revealed the importance of coupled mass transport and reactions in both intragranular and inter-granular domains, which caused both spatial and temporal dependence of U(VI) surface complexation rates in the sediment. Pore-scale simulations also revealed a new rate-limiting mechanism in the intragranular porous domains that the rate of coupled diffusion and surface complexation reaction was slower than either process alone. The results provided important implications for developing models to scale geochemical/biogeochemical reactions.« less

Seeing the forest for the homogeneous trees: stand-scale resource distributions emerge from tree-scale structure

Treesearch

Suzanne Boyden; Rebecca Montgomery; Peter B. Reich; Brian J. Palik

2012-01-01

Forest ecosystem processes depend on local interactions that are modified by the spatial pattern of trees and resources. Effects of resource supplies on processes such as regeneration are increasingly well understood, yet we have few tools to compare resource heterogeneity among forests that differ in structural complexity. We used a neighborhood approach to examine...

Influence of laser radiation polarisation on small-scale self-focusing in isotropic crystals

NASA Astrophysics Data System (ADS)

Ginzburg, V. N.; Kochetkov, A. A.; Kuz'mina, M. S.; Burdonov, K. F.; Shaykin, A. A.; Khazanov, E. A.

2017-04-01

The gain of spatial noise in the field of an intense linearly polarised wave, propagating in a BaF2 cubic crystal with orientation [001], is directly measured. The previously predicted strong dependence of the evolution of small-scale self-focusing on the angle between the radiation polarisation vector and the crystallographic axis of crystal is demonstrated.

Multiscale habitat relationships of stream amphibians in the Klamath-Siskiyou region of California and Oregon

Treesearch

Hartwell H. Welsh Jr; Amy J. Lind

2002-01-01

Regional amphibian distribution patterns can vary greatly depending on species and the spatial scale of inquiry (e.g., landscape to microenvironment). These differences appear to be related both to habitat selection among species as well as availability of suitable habitats across scales. We sampled amphibians in 39 second- and third-order streams in the conifer-...

Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example

USGS Publications Warehouse

Cross, Paul C.; Caillaud, Damien; Heisey, Dennis M.

2013-01-01

Many ecological and epidemiological studies occur in systems with mobile individuals and heterogeneous landscapes. Using a simulation model, we show that the accuracy of inferring an underlying biological process from observational data depends on movement and spatial scale of the analysis. As an example, we focused on estimating the relationship between host density and pathogen transmission. Observational data can result in highly biased inference about the underlying process when individuals move among sampling areas. Even without sampling error, the effect of host density on disease transmission is underestimated by approximately 50 % when one in ten hosts move among sampling areas per lifetime. Aggregating data across larger regions causes minimal bias when host movement is low, and results in less biased inference when movement rates are high. However, increasing data aggregation reduces the observed spatial variation, which would lead to the misperception that a spatially targeted control effort may not be very effective. In addition, averaging over the local heterogeneity will result in underestimating the importance of spatial covariates. Minimizing the bias due to movement is not just about choosing the best spatial scale for analysis, but also about reducing the error associated with using the sampling location as a proxy for an individual’s spatial history. This error associated with the exposure covariate can be reduced by choosing sampling regions with less movement, including longitudinal information of individuals’ movements, or reducing the window of exposure by using repeated sampling or younger individuals.

Spatial heterogeneity of leaf area index across scales from simulation and remote sensing

NASA Astrophysics Data System (ADS)

Reichenau, Tim G.; Korres, Wolfgang; Montzka, Carsten; Schneider, Karl

2016-04-01

Leaf area index (LAI, single sided leaf area per ground area) influences mass and energy exchange of vegetated surfaces. Therefore LAI is an input variable for many land surface schemes of coupled large scale models, which do not simulate LAI. Since these models typically run on rather coarse resolution grids, LAI is often inferred from coarse resolution remote sensing. However, especially in agriculturally used areas, a grid cell of these products often covers more than a single land-use. In that case, the given LAI does not apply to any single land-use. Therefore, the overall spatial heterogeneity in these datasets differs from that on resolutions high enough to distinguish areas with differing land-use. Detailed process-based plant growth models simulate LAI for separate plant functional types or specific species. However, limited availability of observations causes reduced spatial heterogeneity of model input data (soil, weather, land-use). Since LAI is strongly heterogeneous in space and time and since processes depend on LAI in a nonlinear way, a correct representation of LAI spatial heterogeneity is also desirable on coarse resolutions. The current study assesses this issue by comparing the spatial heterogeneity of LAI from remote sensing (RapidEye) and process-based simulations (DANUBIA simulation system) across scales. Spatial heterogeneity is assessed by analyzing LAI frequency distributions (spatial variability) and semivariograms (spatial structure). Test case is the arable land in the fertile loess plain of the Rur catchment near the Germany-Netherlands border.

Scale Dependence of Statistics of Spatially Averaged Rain Rate Seen in TOGA COARE Comparison with Predictions from a Stochastic Model

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Bell, T. L.; Lau, William K. M. (Technical Monitor)

2002-01-01

A characteristic feature of rainfall statistics is that they in general depend on the space and time scales over which rain data are averaged. As a part of an earlier effort to determine the sampling error of satellite rain averages, a space-time model of rainfall statistics was developed to describe the statistics of gridded rain observed in GATE. The model allows one to compute the second moment statistics of space- and time-averaged rain rate which can be fitted to satellite or rain gauge data to determine the four model parameters appearing in the precipitation spectrum - an overall strength parameter, a characteristic length separating the long and short wavelength regimes and a characteristic relaxation time for decay of the autocorrelation of the instantaneous local rain rate and a certain 'fractal' power law exponent. For area-averaged instantaneous rain rate, this exponent governs the power law dependence of these statistics on the averaging length scale $L$ predicted by the model in the limit of small $L$. In particular, the variance of rain rate averaged over an $L \\times L$ area exhibits a power law singularity as $L \\rightarrow 0$. In the present work the model is used to investigate how the statistics of area-averaged rain rate over the tropical Western Pacific measured with ship borne radar during TOGA COARE (Tropical Ocean Global Atmosphere Coupled Ocean Atmospheric Response Experiment) and gridded on a 2 km grid depends on the size of the spatial averaging scale. Good agreement is found between the data and predictions from the model over a wide range of averaging length scales.

Orientation and size-dependent mechanical modulation within individual secondary osteons in cortical bone tissue

PubMed Central

Carnelli, Davide; Vena, Pasquale; Dao, Ming; Ortiz, Christine; Contro, Roberto

2013-01-01

Anisotropy is one of the most peculiar aspects of cortical bone mechanics; however, its anisotropic mechanical behaviour should be treated only with strict relationship to the length scale of investigation. In this study, we focus on quantifying the orientation and size dependence of the spatial mechanical modulation in individual secondary osteons of bovine cortical bone using nanoindentation. Tests were performed on the same osteonal structure in the axial (along the long bone axis) and transverse (normal to the long bone axis) directions along arrays going radially out from the Haversian canal at four different maximum depths on three secondary osteons. Results clearly show a periodic pattern of stiffness with spatial distance across the osteon. The effect of length scale on lamellar bone anisotropy and the critical length at which homogenization of the mechanical properties occurs were determined. Further, a laminate-composite-based analytical model was applied to the stiffness trends obtained at the highest spatial resolution to evaluate the elastic constants for a sub-layer of mineralized collagen fibrils within an osteonal lamella on the basis of the spatial arrangement of the fibrils. The hierarchical arrangement of lamellar bone is found to be a major determinant for modulation of mechanical properties and anisotropic mechanical behaviour of the tissue. PMID:23389895

Multivariate Non-Symmetric Stochastic Models for Spatial Dependence Models

NASA Astrophysics Data System (ADS)

Haslauer, C. P.; Bárdossy, A.

2017-12-01

A copula based multivariate framework allows more flexibility to describe different kind of dependences than what is possible using models relying on the confining assumption of symmetric Gaussian models: different quantiles can be modelled with a different degree of dependence; it will be demonstrated how this can be expected given process understanding. maximum likelihood based multivariate quantitative parameter estimation yields stable and reliable results; not only improved results in cross-validation based measures of uncertainty are obtained but also a more realistic spatial structure of uncertainty compared to second order models of dependence; as much information as is available is included in the parameter estimation: incorporation of censored measurements (e.g., below detection limit, or ones that are above the sensitive range of the measurement device) yield to more realistic spatial models; the proportion of true zeros can be jointly estimated with and distinguished from censored measurements which allow estimates about the age of a contaminant in the system; secondary information (categorical and on the rational scale) has been used to improve the estimation of the primary variable; These copula based multivariate statistical techniques are demonstrated based on hydraulic conductivity observations at the Borden (Canada) site, the MADE site (USA), and a large regional groundwater quality data-set in south-west Germany. Fields of spatially distributed K were simulated with identical marginal simulation, identical second order spatial moments, yet substantially differing solute transport characteristics when numerical tracer tests were performed. A statistical methodology is shown that allows the delineation of a boundary layer separating homogenous parts of a spatial data-set. The effects of this boundary layer (macro structure) and the spatial dependence of K (micro structure) on solute transport behaviour is shown.

Spatial vs. non-spatial eco-evolutionary dynamics in a tumor growth model.

PubMed

You, Li; Brown, Joel S; Thuijsman, Frank; Cunningham, Jessica J; Gatenby, Robert A; Zhang, Jingsong; Staňková, Kateřina

2017-12-21

Metastatic prostate cancer is initially treated with androgen deprivation therapy (ADT). However, resistance typically develops in about 1 year - a clinical condition termed metastatic castrate-resistant prostate cancer (mCRPC). We develop and investigate a spatial game (agent based continuous space) of mCRPC that considers three distinct cancer cell types: (1) those dependent on exogenous testosterone (T + ), (2) those with increased CYP17A expression that produce testosterone and provide it to the environment as a public good (T P ), and (3) those independent of testosterone (T - ). The interactions within and between cancer cell types can be represented by a 3 × 3 matrix. Based on the known biology of this cancer there are 22 potential matrices that give roughly three major outcomes depending upon the absence (good prognosis), near absence or high frequency (poor prognosis) of T -  cells at the evolutionarily stable strategy (ESS). When just two cell types coexist the spatial game faithfully reproduces the ESS of the corresponding matrix game. With three cell types divergences occur, in some cases just two strategies coexist in the spatial game even as a non-spatial matrix game supports all three. Discrepancies between the spatial game and non-spatial ESS happen because different cell types become more or less clumped in the spatial game - leading to non-random assortative interactions between cell types. Three key spatial scales influence the distribution and abundance of cell types in the spatial game: i. Increasing the radius at which cells interact with each other can lead to higher clumping of each type, ii. Increasing the radius at which cells experience limits to population growth can cause densely packed tumor clusters in space, iii. Increasing the dispersal radius of daughter cells promotes increased mixing of cell types. To our knowledge the effects of these spatial scales on eco-evolutionary dynamics have not been explored in cancer models. The fact that cancer interactions are spatially explicit and that our spatial game of mCRPC provides in general different outcomes than the non-spatial game might suggest that non-spatial models are insufficient for capturing key elements of tumorigenesis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessment of Rip-Current Hazards Using Alongshore Topographic Anisotropy at Bondi Beach, Australia

NASA Astrophysics Data System (ADS)

Hartman, K.; Trimble, S. M.; Bishop, M. P.; Houser, C.

2016-12-01

Rip currents are a relatively high-velocity flow of water away from the beach common in coastal environments. As beach morphology adapts to sediment fluxes and wave climate, it is essential to be able to assess rip-current hazard conditions. Furthermore, it is essential to be able to characterize the scale-dependent bathymetric morphology that governs the extent and magnitude of a rip current. Consequently, our primary objective is to assess the alongshore distribution of topographic anisotropy, in order to identify rip-current hazard locations. Specifically, we utilized multi-band satellite imagery to generate a bathymetric digital elevation model (DEM) for Bondi Beach Australia, and collected field data to support our analysis. Scale-dependent spatial analysis of the DEM was conducted to assess the directional dependence of topographic relief, the magnitude of topographic anisotropy, and the degree of anisotropic symmetry. We displayed anisotropy parameters as images and false-color composites to visualize morphological conditions associated with rip channels. Our preliminary results indicate that rip channels generally have a higher anisotropy index and orthogonal orientation compared to dissipative or reflective beach anisotropy and orientation. Scale-dependent variations in anisotropy can be used to assess the spatial extent of rip currents. Furthermore, well-defined rip channels exhibit positive symmetry, while variations in the distribution of symmetry reflect sediment-flux variations alongshore. These results clearly reveal that a well-developed rip channel can be identified and assessed using topographic anisotropy, as scale-dependent anisotropy patterns are unique when compared to the surrounding bathymetry and terrain. In this way, it is possible to evaluate the alongshore distribution of rip currents. Alongshore topographic anisotropy data will be extremely important as input into hazard assessment studies and the development of hazard decision support systems.

Understanding Plasma Interactions with the Atmosphere: The Geospace Electrodynamic Connections (GEC) Mission

NASA Technical Reports Server (NTRS)

2001-01-01

The Geospace Electrodynamic Connections (GEC) mission is a multispacecraft Solar-Terrestrial Probe that has been specifically designed to advance the level of physical insight of our understanding of the coupling among the ionosphere, thermosphere, and magnetosphere. GEC is NASA's fifth Solar-Terrestrial Probe. Through multipoint measurements in the Earth's ionosphere-thermosphere (I-T) system, GEC will (i) discover the spatial and temporal scales on which magnetospheric energy input into the I-T region occurs, (ii) determine the spatial and temporal scales for the response of the I-T system to this input of energy, and (iii) quantify the altitude dependence of the response.

A comment on the position dependent diffusion coefficient representation of structural heterogeneity

NASA Astrophysics Data System (ADS)

Wolfson, Molly; Liepold, Christopher; Lin, Binhua; Rice, Stuart A.

2018-05-01

Experimental studies of the variation of the mean square displacement (MSD) of a particle in a confined colloid suspension that exhibits density variations on the scale length of the particle diameter are not in agreement with the prediction that the spatial variation in MSD should mimic the spatial variation in density. The predicted behavior is derived from the expectation that the MSD of a particle depends on the system density and the assumption that the force acting on a particle is a point function of position. The experimental data are obtained from studies of the MSDs of particles in narrow ribbon channels and between narrowly spaced parallel plates and from new data, reported herein, of the radial and azimuthal MSDs of a colloid particle in a dense colloid suspension confined to a small circular cavity. In each of these geometries, a dense colloid suspension exhibits pronounced density oscillations with spacing of a particle diameter. We remove the discrepancy between prediction and experiment using the Fisher-Methfessel interpretation of how local equilibrium in an inhomogeneous system is maintained to argue that the force acting on a particle is delocalized over a volume with radius equal to a particle diameter. Our interpretation has relevance to the relationship between the scale of inhomogeneity and the utility of translation of the particle MSD into a position dependent diffusion coefficient and to the use of a spatially dependent diffusion coefficient to describe mass transport in a heterogeneous system.

Microplume model of spatial-yield spectra. [applying to electron gas degradation in molecular nitrogen gas

NASA Technical Reports Server (NTRS)

Green, A. E. S.; Singhal, R. P.

1979-01-01

An analytic representation for the spatial (radial and longitudinal) yield spectra is developed in terms of a model containing three simple 'microplumes'. The model is applied to electron energy degradation in molecular nitrogen gas for 0.1 to 5 keV incident electrons. From the nature of the cross section input to this model it is expected that the scaled spatial yield spectra for other gases will be quite similar. The model indicates that each excitation, ionization, etc. plume should have its individual spatial and energy dependence. Extensions and aeronomical and radiological applications of the model are discussed.

The Berkeley Atmospheric CO2 Observation Network (BEACON): Measuring Greenhouse Gases and Criteria Pollutants within the Urban Dome

NASA Astrophysics Data System (ADS)

Teige, V. E.; Weichsel, K.; Hooker, A.; Wooldridge, P. J.; Cohen, R. C.

2012-12-01

Efforts to curb greenhouse gas emissions, while global in their impacts, often focus on local and regional scales for execution and are dependent on the actions of communities and individuals. Evaluating the effectiveness of local policies requires observations with much higher spatial resolution than are currently available---kilometer scale. The Berkeley Atmospheric CO2 Observation Network (BEACON):, launched at the end of 2011, aims to provide measurements of urban-scale concentrations of CO2, temperature, pressure, relative humidity, O3, CO, and NO2 with sufficient spatial and temporal resolution to characterize the sources of CO2 within cities. Our initial deployment in Oakland, California uses ~40 sensor packages at a roughly 2 km spacing throughout the city. We will present an initial analysis of the vertical gradients and other spatial patterns observed to date.

The Resilience of Coral Reefs Across a Hierarchy of Spatial and Temporal scales

NASA Astrophysics Data System (ADS)

Mumby, P. J.

2016-02-01

Resilience is a dynamical property of ecosystems that integrates processes of recovery, disturbance and internal dynamics, including reinforcing feedbacks. As such, resilience is a useful framework to consider how ecosystems respond to multiple drivers occurring over multiple scales. Many insights have emerged recently including the way in which stressors can combine synergistically to deplete resilience. However, while recent advances have mapped resilience across seascapes, most studies have not captured emergent spatial dependencies and dynamics across the seascape (e.g., independent box models are run across the seascape in isolation). Here, we explore the dynamics that emerge when the seascape is `wired up' using data on larval dispersal, thereby giving a fully spatially-realistic model. We then consider how dynamics change across even larger, biogeographic scales, posing the question, `are there robust and global "rules of thumb" for the resilience of a single ecosystem?'. Answers to this question will help managers tailor their interventions and research needs for their own jurisdiction.

Studies of x-ray localization and thickness dependence in atomic-scale elemental mapping by STEM energy-dispersive x-ray spectroscopy using single-frame scanning method

DOE PAGES

Lu, Ping; Moya, Jaime M.; Yuan, Renliang; ...

2018-03-01

The delocalization of x-ray signals limits the spatial resolution in atomic-scale elemental mapping by scanning transmission electron microscopy (STEM) using energy-dispersive x-ray spectroscopy (EDS). In this study, using a SrTiO 3 [001] single crystal, we show that the x-ray localization to atomic columns is strongly dependent on crystal thickness, and a thin crystal is critical for improving the spatial resolution in atomic-scale EDS mapping. A single-frame scanning technique is used in this study instead of the multiple-frame technique to avoid peak broadening due to tracking error. The strong thickness dependence is realized by measuring the full width at half maximamore » (FWHM) as well as the peak-to-valley (P/V) ratio of the EDS profiles for Ti K and Sr K+L, obtained at several crystal thicknesses. A FWHM of about 0.16 nm and a P/V ratio of greater than 7.0 are obtained for Ti K for a crystal thickness of less than 20 nm. In conclusion, with increasing crystal thickness, the FWHM and P/V ratio increases and decreases, respectively, indicating the advantage of using a thin crystal for high-resolution EDS mapping.« less

Studies of x-ray localization and thickness dependence in atomic-scale elemental mapping by STEM energy-dispersive x-ray spectroscopy using single-frame scanning method

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

Lu, Ping; Moya, Jaime M.; Yuan, Renliang

The delocalization of x-ray signals limits the spatial resolution in atomic-scale elemental mapping by scanning transmission electron microscopy (STEM) using energy-dispersive x-ray spectroscopy (EDS). In this study, using a SrTiO 3 [001] single crystal, we show that the x-ray localization to atomic columns is strongly dependent on crystal thickness, and a thin crystal is critical for improving the spatial resolution in atomic-scale EDS mapping. A single-frame scanning technique is used in this study instead of the multiple-frame technique to avoid peak broadening due to tracking error. The strong thickness dependence is realized by measuring the full width at half maximamore » (FWHM) as well as the peak-to-valley (P/V) ratio of the EDS profiles for Ti K and Sr K+L, obtained at several crystal thicknesses. A FWHM of about 0.16 nm and a P/V ratio of greater than 7.0 are obtained for Ti K for a crystal thickness of less than 20 nm. In conclusion, with increasing crystal thickness, the FWHM and P/V ratio increases and decreases, respectively, indicating the advantage of using a thin crystal for high-resolution EDS mapping.« less

Studies of x-ray localization and thickness dependence in atomic-scale elemental mapping by STEM energy-dispersive x-ray spectroscopy using single-frame scanning method.

PubMed

Lu, Ping; Moya, Jaime M; Yuan, Renliang; Zuo, Jian Min

2018-03-01

The delocalization of x-ray signals limits the spatial resolution in atomic-scale elemental mapping by scanning transmission electron microscopy (STEM) using energy-dispersive x-ray spectroscopy (EDS). In this study, using a SrTiO 3 [001] single crystal, we show that the x-ray localization to atomic columns is strongly dependent on crystal thickness, and a thin crystal is critical for improving the spatial resolution in atomic-scale EDS mapping. A single-frame scanning technique is used in this study instead of the multiple-frame technique to avoid peak broadening due to tracking error. The strong thickness dependence is realized by measuring the full width at half maxima (FWHM) as well as the peak-to-valley (P/V) ratio of the EDS profiles for Ti K and Sr K + L, obtained at several crystal thicknesses. A FWHM of about 0.16 nm and a P/V ratio of greater than 7.0 are obtained for Ti K for a crystal thickness of less than 20 nm. With increasing crystal thickness, the FWHM and P/V ratio increases and decreases, respectively, indicating the advantage of using a thin crystal for high-resolution EDS mapping. Published by Elsevier B.V.

Effects of hedgerows on bats and bush crickets at different spatial scales

NASA Astrophysics Data System (ADS)

Lacoeuilhe, Aurélie; Machon, Nathalie; Julien, Jean-François; Kerbiriou, Christian

2016-02-01

Biodiversity is threatened by the loss and fragmentation of habitats. The role of hedgerows in maintaining biodiversity is well established, but few studies have addressed the importance for biodiversity of the intrinsic characteristics of hedgerows and the quality of hedgerow networks along a spatial scale. We examined three quality indices providing information at different territorial levels: density in the landscape, structural diversity and wood production. We performed an acoustic survey in a grassland to estimate the species abundance and community composition of bats (9 taxa) and bush crickets (11 species). Using an approach based on species and traits, we assessed how hedgerow quality influenced the activity of these taxa at different spatial scales (from 50 to 1000 m) and focused on three types of traits: bush cricket mobility ability, bat foraging strategy and habitat specialization. In general, our results showed the importance of hedgerow quality for bats and bush crickets, but the strength of the association between taxa and hedgerows varied substantially among the species and the spatial scales. Although it depends on the taxa, the production, density and structural diversity of hedgerows each had an overall positive effect. Our results suggested that these effects were generally more important at large scales. The scale effect of the production index is the best predictor of activity for bat and bush cricket taxa and traits. Our results showed the importance of hedgerow quality for the ecology of bat and bush cricket communities and could be used to improve conservation management.

Sex Differences in Spatial Memory in Brown-Headed Cowbirds: Males Outperform Females on a Touchscreen Task

PubMed Central

Guigueno, Mélanie F.; MacDougall-Shackleton, Scott A.; Sherry, David F.

2015-01-01

Spatial cognition in females and males can differ in species in which there are sex-specific patterns in the use of space. Brown-headed cowbirds are brood parasites that show a reversal of sex-typical space use often seen in mammals. Female cowbirds, search for, revisit and parasitize hosts nests, have a larger hippocampus than males and have better memory than males for a rewarded location in an open spatial environment. In the current study, we tested female and male cowbirds in breeding and non-breeding conditions on a touchscreen delayed-match-to-sample task using both spatial and colour stimuli. Our goal was to determine whether sex differences in spatial memory in cowbirds generalizes to all spatial tasks or is task-dependant. Both sexes performed better on the spatial than on the colour touchscreen task. On the spatial task, breeding males outperformed breeding females. On the colour task, females and males did not differ, but females performed better in breeding condition than in non-breeding condition. Although female cowbirds were observed to outperform males on a previous larger-scale spatial task, males performed better than females on a task testing spatial memory in the cowbirds’ immediate visual field. Spatial abilities in cowbirds can favour males or females depending on the type of spatial task, as has been observed in mammals, including humans. PMID:26083573

Are fractal dimensions of the spatial distribution of mineral deposits meaningful?

USGS Publications Warehouse

Raines, G.L.

2008-01-01

It has been proposed that the spatial distribution of mineral deposits is bifractal. An implication of this property is that the number of deposits in a permissive area is a function of the shape of the area. This is because the fractal density functions of deposits are dependent on the distance from known deposits. A long thin permissive area with most of the deposits in one end, such as the Alaskan porphyry permissive area, has a major portion of the area far from known deposits and consequently a low density of deposits associated with most of the permissive area. On the other hand, a more equi-dimensioned permissive area, such as the Arizona porphyry permissive area, has a more uniform density of deposits. Another implication of the fractal distribution is that the Poisson assumption typically used for estimating deposit numbers is invalid. Based on datasets of mineral deposits classified by type as inputs, the distributions of many different deposit types are found to have characteristically two fractal dimensions over separate non-overlapping spatial scales in the range of 5-1000 km. In particular, one typically observes a local dimension at spatial scales less than 30-60 km, and a regional dimension at larger spatial scales. The deposit type, geologic setting, and sample size influence the fractal dimensions. The consequence of the geologic setting can be diminished by using deposits classified by type. The crossover point between the two fractal domains is proportional to the median size of the deposit type. A plot of the crossover points for porphyry copper deposits from different geologic domains against median deposit sizes defines linear relationships and identifies regions that are significantly underexplored. Plots of the fractal dimension can also be used to define density functions from which the number of undiscovered deposits can be estimated. This density function is only dependent on the distribution of deposits and is independent of the definition of the permissive area. Density functions for porphyry copper deposits appear to be significantly different for regions in the Andes, Mexico, United States, and western Canada. Consequently, depending on which regional density function is used, quite different estimates of numbers of undiscovered deposits can be obtained. These fractal properties suggest that geologic studies based on mapping at scales of 1:24,000 to 1:100,000 may not recognize processes that are important in the formation of mineral deposits at scales larger than the crossover points at 30-60 km. ?? 2008 International Association for Mathematical Geology.

Detection and extraction of orientation-and-scale-dependent information from two-dimensional GPR data with tuneable directional wavelet filters

NASA Astrophysics Data System (ADS)

Tzanis, Andreas

2013-02-01

The Ground Probing Radar (GPR) is a valuable tool for near surface geological, geotechnical, engineering, environmental, archaeological and other work. GPR images of the subsurface frequently contain geometric information (constant or variable-dip reflections) from various structures such as bedding, cracks, fractures, etc. Such features are frequently the target of the survey; however, they are usually not good reflectors and they are highly localized in time and in space. Their scale is therefore a factor significantly affecting their detectability. At the same time, the GPR method is very sensitive to broadband noise from buried small objects, electromagnetic anthropogenic activity and systemic factors, which frequently blurs the reflections from such targets. This paper introduces a method to de-noise GPR data and extract geometric information from scale-and-dip dependent structural features, based on one-dimensional B-Spline Wavelets, two-dimensional directional B-Spline Wavelet (BSW) Filters and two-dimensional Gabor Filters. A directional BSW Filter is built by sidewise arranging s identical one-dimensional wavelets of length L, tapering the s-parallel direction (span) with a suitable window function and rotating the resulting matrix to the desired orientation. The length L of the wavelet defines the temporal and spatial scale to be isolated and the span determines the length over which to smooth (spatial resolution). The Gabor Filter is generated by multiplying an elliptical Gaussian by a complex plane wave; at any orientation the temporal or spatial scale(s) to be isolated are determined by the wavelength. λ of the plane wave and the spatial resolution by the spatial aspect ratio γ, which specifies the ellipticity of the support of the Gabor function. At any orientation, both types of filter may be tuned at any frequency or spatial wavenumber by varying the length or the wavelength respectively. The filters can be applied directly to two-dimensional radargrams, in which case they abstract information about given scales at given orientations. Alternatively, they can be rotated to different orientations under adaptive control, so that they remain tuned at a given frequency or wavenumber and the resulting images can be stacked in the LS sense, so as to obtain a complete representation of the input data at a given temporal or spatial scale. In addition to isolating geometrical information for further scrutiny, the proposed filtering methods can be used to enhance the S/N ratio in a manner particularly suitable for GPR data, because the frequency response of the filters mimics the frequency characteristics of the source wavelet. Finally, signal attenuation and temporal localization are closely associated: low attenuation interfaces tend to produce reflections rich in high frequencies and fine-scale localization as a function of time. Conversely, high attenuation interfaces will produce reflections rich in low frequencies and broad localization. Accordingly, the temporal localization characteristics of the filters may be exploited to investigate the characteristics of signal propagation (hence material properties). The method is shown to be very effective in extracting fine to coarse scale information from noisy data and is demonstrated with applications to noisy GPR data from archaeometric and geotechnical surveys.

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data.

PubMed

Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

2016-01-01

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960-2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60-70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures.

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data

PubMed Central

Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

2016-01-01

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960–2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60–70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures. PMID:26901763

Drivers of protogynous sex change differ across spatial scales.

PubMed

Taylor, Brett M

2014-01-22

The influence of social demography on sex change schedules in protogynous reef fishes is well established, yet effects across spatial scales (in particular, the magnitude of natural variation relative to size-selective fishing effects) are poorly understood. Here, I examine variation in timing of sex change for exploited parrotfishes across a range of environmental, anthropogenic and geographical factors. Results were highly dependent on spatial scale. Fishing pressure was the most influential factor determining length at sex change at the within-island scale where a wide range of anthropogenic pressure existed. Sex transition occurred at smaller sizes where fishing pressure was high. Among islands, however, differences were overwhelmingly predicted by reefal-scale structural features, a pattern evident for all species examined. For the most abundant species, Chlorurus spilurus, length at sex change increased at higher overall densities and greater female-to-male sex ratios at all islands except where targeted by fishermen; here the trend was reversed. This implies differing selective pressures on adult individuals can significantly alter sex change dynamics, highlighting the importance of social structure, demography and the selective forces structuring populations. Considerable life-history responses to exploitation were observed, but results suggest potential fishing effects on demography may be obscured by natural variation at biogeographic scales.

Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models.

PubMed

Rogers, Lauren A; Storvik, Geir O; Knutsen, Halvor; Olsen, Esben M; Stenseth, Nils C

2017-07-01

Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub-structure and dynamics. The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence). Specifically, we developed dynamic, age-structured, state-space models to test different hypotheses regarding the spatial structure of a population complex of coastal Atlantic cod (Gadus morhua). Data were from a 93-year survey of juvenile (age 0 and 1) cod sampled along >200 km of the Norwegian Skagerrak coast. We compared two models: one which assumes all sampled cod belong to one larger population, and a second which assumes that each fjord contains a unique population with locally determined dynamics. Using the best supported model, we then reconstructed the historical spatial and temporal dynamics of Skagerrak coastal cod. Cross-validation showed that the spatially structured model with local dynamics had better predictive ability. Furthermore, posterior predictive checks showed that a model which assumes one homogeneous population failed to capture the spatial correlation pattern present in the survey data. The spatially structured model indicated that population trends differed markedly among fjords, as did estimates of population parameters including density-dependent survival. Recent biomass was estimated to be at a near-record low all along the coast, but the finer scale model indicated that the decline occurred at different times in different regions. Warm temperatures were associated with poor recruitment, but local changes in habitat and fishing pressure may have played a role in driving local dynamics. More generally, we demonstrated how state-space models can be used to test evidence for population spatial structure based on survey time-series data. Our study shows the importance of considering spatially structured dynamics, as the inferences from such an approach can lead to a different ecological understanding of the drivers of population declines, and fundamentally different management actions to restore populations. © 2017 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

The spectral signature of cloud spatial structure in shortwave irradiance

PubMed Central

Song, Shi; Schmidt, K. Sebastian; Pilewskie, Peter; King, Michael D.; Heidinger, Andrew K.; Walther, Andi; Iwabuchi, Hironobu; Wind, Gala; Coddington, Odele M.

2017-01-01

In this paper, we used cloud imagery from a NASA field experiment in conjunction with three-dimensional radiative transfer calculations to show that cloud spatial structure manifests itself as a spectral signature in shortwave irradiance fields – specifically in transmittance and net horizontal photon transport in the visible and near-ultraviolet wavelength range. We found a robust correlation between the magnitude of net horizontal photon transport (H) and its spectral dependence (slope), which is scale-invariant and holds for the entire pixel population of a domain. This was surprising at first given the large degree of spatial inhomogeneity. We prove that the underlying physical mechanism for this phenomenon is molecular scattering in conjunction with cloud spatial structure. On this basis, we developed a simple parameterization through a single parameter ε, which quantifies the characteristic spectral signature of spatial inhomogeneities. In the case we studied, neglecting net horizontal photon transport leads to a local transmittance bias of ±12–19 %, even at the relatively coarse spatial resolution of 20 km. Since three-dimensional effects depend on the spatial context of a given pixel in a nontrivial way, the spectral dimension of this problem may emerge as the starting point for future bias corrections. PMID:28824698

The spectral signature of cloud spatial structure in shortwave irradiance.

PubMed

Song, Shi; Schmidt, K Sebastian; Pilewskie, Peter; King, Michael D; Heidinger, Andrew K; Walther, Andi; Iwabuchi, Hironobu; Wind, Gala; Coddington, Odele M

2016-11-08

In this paper, we used cloud imagery from a NASA field experiment in conjunction with three-dimensional radiative transfer calculations to show that cloud spatial structure manifests itself as a spectral signature in shortwave irradiance fields - specifically in transmittance and net horizontal photon transport in the visible and near-ultraviolet wavelength range. We found a robust correlation between the magnitude of net horizontal photon transport ( H ) and its spectral dependence (slope), which is scale-invariant and holds for the entire pixel population of a domain. This was surprising at first given the large degree of spatial inhomogeneity. We prove that the underlying physical mechanism for this phenomenon is molecular scattering in conjunction with cloud spatial structure. On this basis, we developed a simple parameterization through a single parameter ε , which quantifies the characteristic spectral signature of spatial inhomogeneities. In the case we studied, neglecting net horizontal photon transport leads to a local transmittance bias of ±12-19 %, even at the relatively coarse spatial resolution of 20 km. Since three-dimensional effects depend on the spatial context of a given pixel in a nontrivial way, the spectral dimension of this problem may emerge as the starting point for future bias corrections.

Metacommunity theory as a multispecies, multiscale framework for studying the influence of river network structure on riverine communities and ecosystems

USGS Publications Warehouse

Brown, B.L.; Swan, C.M.; Auerbach, D.A.; Campbell, Grant E.H.; Hitt, N.P.; Maloney, K.O.; Patrick, C.

2011-01-01

Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.

Community assembly of the ferns of Florida.

PubMed

Sessa, Emily B; Chambers, Sally M; Li, Daijiang; Trotta, Lauren; Endara, Lorena; Burleigh, J Gordon; Baiser, Benjamin

2018-03-01

Many ecological and evolutionary processes shape the assembly of organisms into local communities from a regional pool of species. We analyzed phylogenetic and functional diversity to understand community assembly of the ferns of Florida at two spatial scales. We built a phylogeny for 125 of the 141 species of ferns in Florida using five chloroplast markers. We calculated mean pairwise dissimilarity (MPD) and mean nearest taxon distance (MNTD) from phylogenetic distances and functional trait data for both spatial scales and compared the results to null models to assess significance. Our results for over vs. underdispersion in functional and phylogenetic diversity differed depending on spatial scale and metric considered. At the county scale, MPD revealed evidence for phylogenetic overdispersion, while MNTD revealed phylogenetic and functional underdispersion, and at the conservation area scale, MPD revealed phylogenetic and functional underdispersion while MNTD revealed evidence only of functional underdispersion. Our results are consistent with environmental filtering playing a larger role at the smaller, conservation area scale. The smaller spatial units are likely composed of fewer local habitat types that are selecting for closely related species, with the larger-scale units more likely to be composed of multiple habitat types that bring together a larger pool of species from across the phylogeny. Several aspects of fern biology, including their unique physiology and water relations and the importance of the independent gametophyte stage of the life cycle, make ferns highly sensitive to local, microhabitat conditions. © 2018 The Authors. American Journal of Botany is published by Wiley Periodicals, Inc. on behalf of the Botanical Society of America.

Context-dependent spatially periodic activity in the human entorhinal cortex

PubMed Central

Nguyen, T. Peter; Török, Ágoston; Shen, Jason Y.; Briggs, Deborah E.; Modur, Pradeep N.; Buchanan, Robert J.

2017-01-01

The spatially periodic activity of grid cells in the entorhinal cortex (EC) of the rodent, primate, and human provides a coordinate system that, together with the hippocampus, informs an individual of its location relative to the environment and encodes the memory of that location. Among the most defining features of grid-cell activity are the 60° rotational symmetry of grids and preservation of grid scale across environments. Grid cells, however, do display a limited degree of adaptation to environments. It remains unclear if this level of environment invariance generalizes to human grid-cell analogs, where the relative contribution of visual input to the multimodal sensory input of the EC is significantly larger than in rodents. Patients diagnosed with nontractable epilepsy who were implanted with entorhinal cortical electrodes performing virtual navigation tasks to memorized locations enabled us to investigate associations between grid-like patterns and environment. Here, we report that the activity of human entorhinal cortical neurons exhibits adaptive scaling in grid period, grid orientation, and rotational symmetry in close association with changes in environment size, shape, and visual cues, suggesting scale invariance of the frequency, rather than the wavelength, of spatially periodic activity. Our results demonstrate that neurons in the human EC represent space with an enhanced flexibility relative to neurons in rodents because they are endowed with adaptive scalability and context dependency. PMID:28396399

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

PubMed

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

2013-02-01

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

Determinants of single family residential water use across scales in four western US cities.

PubMed

Chang, Heejun; Bonnette, Matthew Ryan; Stoker, Philip; Crow-Miller, Britt; Wentz, Elizabeth

2017-10-15

A growing body of literature examines urban water sustainability with increasing evidence that locally-based physical and social spatial interactions contribute to water use. These studies however are based on single-city analysis and often fail to consider whether these interactions occur more generally. We examine a multi-city comparison using a common set of spatially-explicit water, socioeconomic, and biophysical data. We investigate the relative importance of variables for explaining the variations of single family residential (SFR) water uses at Census Block Group (CBG) and Census Tract (CT) scales in four representative western US cities - Austin, Phoenix, Portland, and Salt Lake City, - which cover a wide range of climate and development density. We used both ordinary least squares regression and spatial error regression models to identify the influence of spatial dependence on water use patterns. Our results show that older downtown areas show lower water use than newer suburban areas in all four cities. Tax assessed value and building age are the main determinants of SFR water use across the four cities regardless of the scale. Impervious surface area becomes an important variable for summer water use in all cities, and it is important in all seasons for arid environments such as Phoenix. CT level analysis shows better model predictability than CBG analysis. In all cities, seasons, and spatial scales, spatial error regression models better explain the variations of SFR water use. Such a spatially-varying relationship of urban water consumption provides additional evidence for the need to integrate urban land use planning and municipal water planning. Copyright © 2017 Elsevier B.V. All rights reserved.

Scale effect challenges in urban hydrology highlighted with a distributed hydrological model

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire

2018-01-01

Hydrological models are extensively used in urban water management, development and evaluation of future scenarios and research activities. There is a growing interest in the development of fully distributed and grid-based models. However, some complex questions related to scale effects are not yet fully understood and still remain open issues in urban hydrology. In this paper we propose a two-step investigation framework to illustrate the extent of scale effects in urban hydrology. First, fractal tools are used to highlight the scale dependence observed within distributed data input into urban hydrological models. Then an intensive multi-scale modelling work is carried out to understand scale effects on hydrological model performance. Investigations are conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model is implemented at 17 spatial resolutions ranging from 100 to 5 m. Results clearly exhibit scale effect challenges in urban hydrology modelling. The applicability of fractal concepts highlights the scale dependence observed within distributed data. Patterns of geophysical data change when the size of the observation pixel changes. The multi-scale modelling investigation confirms scale effects on hydrological model performance. Results are analysed over three ranges of scales identified in the fractal analysis and confirmed through modelling. This work also discusses some remaining issues in urban hydrology modelling related to the availability of high-quality data at high resolutions, and model numerical instabilities as well as the computation time requirements. The main findings of this paper enable a replacement of traditional methods of model calibration by innovative methods of model resolution alteration based on the spatial data variability and scaling of flows in urban hydrology.

Slope-scale dynamic states of rockfalls

NASA Astrophysics Data System (ADS)

Agliardi, F.; Crosta, G. B.

2009-04-01

Rockfalls are common earth surface phenomena characterised by complex dynamics at the slope scale, depending on local block kinematics and slope geometry. We investigated the nature of this slope-scale dynamics by parametric 3D numerical modelling of rockfalls over synthetic slopes with different inclination, roughness and spatial resolution. Simulations were performed through an original code specifically designed for rockfall modeling, incorporating kinematic and hybrid algorithms with different damping functions available to model local energy loss by impact and pure rolling. Modelling results in terms of average velocity profiles suggest that three dynamic regimes (i.e. decelerating, steady-state and accelerating), previously recognized in the literature through laboratory experiments on granular flows, can set up at the slope scale depending on slope average inclination and roughness. Sharp changes in rock fall kinematics, including motion type and lateral dispersion of trajectories, are associated to the transition among different regimes. Associated threshold conditions, portrayed in "phase diagrams" as slope-roughness critical lines, were analysed depending on block size, impact/rebound angles, velocity and energy, and model spatial resolution. Motion in regime B (i.e. steady state) is governed by a slope-scale "viscous friction" with average velocity linearly related to the sine of slope inclination. This suggest an analogy between rockfall motion in regime B and newtonian flow, whereas in regime C (i.e. accelerating) an analogy with a dilatant flow was observed. Thus, although local behavior of single falling blocks is well described by rigid body dynamics, the slope scale dynamics of rockfalls seem to statistically approach that of granular media. Possible outcomes of these findings include a discussion of the transition from rockfall to granular flow, the evaluation of the reliability of predictive models, and the implementation of criteria for a preliminary evaluation of hazard assessment and countermeasure planning.

Scale-dependent geomorphic responses to active restoration and implications for cutthroat trout

NASA Astrophysics Data System (ADS)

Salant, N.; Miller, S. W.

2009-12-01

The predominant goal of instream habitat restoration is to increase the diversity, density and/or biomass of aquatic organisms through enhanced physical heterogeneity and increased food availability. In physically homogenized systems, habitat restoration is most commonly achieved at the reach-scale through the addition of structures or channel reconfiguration. Despite the completion of over 6,000 restoration projects in the United States, studies of fish responses to habitat restoration have largely produced equivocal results. Paradoxically, restoration monitoring overwhelmingly focuses on fish response without understanding how these responses link to the physical variables being altered and the scale at which geomorphic changes occur. Our study investigates whether instream habitat restoration affects geomorphic conditions at spatial scales relevant to the organism of interest (i.e. the spatial scale of the variables limiting to that organism). We measure the effects of active restoration on geomorphic metrics at three spatial scales (local, unit, and reach) using a before-after-control-impact design in a historically disturbed and heavily managed cutthroat trout stream. Observed trout habitat preferences (for spawning and juvenile/adult residence) are used to identify the limiting physical variables and are compared to the scale of spatially explicit geomorphic responses. Four reaches representing three different stages of restoration (before, one month and one year after) are surveyed for local-scale physical conditions, unit- and reach-scale morphology, resident fish use, and redd locations. Local-scale physical metrics include depth, nearbed and average velocity, overhead cover, particle size, and water quality metrics. Point measurements stratified by morphological unit are used to determine physical variability among unit types. Habitat complexity and availability are assessed at the reach-scale from topographic surveys and unit maps. Our multi-scale, process-based approach evaluates whether a commonly used restoration strategy creates geomorphic heterogeneity at scales relevant to fish diversity and microhabitat utilization, an understanding that will improve the efficiency and success of future restoration projects.

GIS based procedure of cumulative environmental impact assessment.

PubMed

Balakrishna Reddy, M; Blah, Baiantimon

2009-07-01

Scale and spatial limits of impact assessment study in a GIS platform are two very important factors that could have a bearing on the genuineness and quality of impact assessment. While effect of scale has been documented and well understood, no significant study has been carried out on spatial considerations in an impact assessment study employing GIS technique. A novel technique of impact assessment demonstrable through GIS approach termed hereby as 'spatial data integrated GIS impact assessment method (SGIAM)' is narrated in this paper. The technique makes a fundamental presumption that the importance of environmental impacts is dependent, among other things, on spatial distribution of the effects of the proposed action and of the affected receptors in a study area. For each environmental component considered (e.g., air quality), impact indices are calculated through aggregation of impact indicators which are measures of the severity of the impact. The presence and spread of environmental descriptors are suitably quantified through modeling techniques and depicted. The environmental impact index is calculated from data exported from ArcINFO, thus giving significant importance to spatial data in the impact assessment exercise.

Measuring Spatial Dependence for Infectious Disease Epidemiology

PubMed Central

Grabowski, M. Kate; Cummings, Derek A. T.

2016-01-01

Global spatial clustering is the tendency of points, here cases of infectious disease, to occur closer together than expected by chance. The extent of global clustering can provide a window into the spatial scale of disease transmission, thereby providing insights into the mechanism of spread, and informing optimal surveillance and control. Here the authors present an interpretable measure of spatial clustering, τ, which can be understood as a measure of relative risk. When biological or temporal information can be used to identify sets of potentially linked and likely unlinked cases, this measure can be estimated without knowledge of the underlying population distribution. The greater our ability to distinguish closely related (i.e., separated by few generations of transmission) from more distantly related cases, the more closely τ will track the true scale of transmission. The authors illustrate this approach using examples from the analyses of HIV, dengue and measles, and provide an R package implementing the methods described. The statistic presented, and measures of global clustering in general, can be powerful tools for analysis of spatially resolved data on infectious diseases. PMID:27196422

Consistency of Aquarius version-4 sea surface salinity with Argo products on various spatial and temporal scales

NASA Astrophysics Data System (ADS)

Lee, Tong

2017-04-01

Understanding the accuracies of satellite-derived sea surface salinity (SSS) measurements in depicting temporal changes and the dependence of the accuracies on spatiotemporal scales are important to capability assessment, future mission design, and applications to study oceanic phenomena of different spatiotemporal scales. This study quantifies the consistency between Aquarius Version-4 monthly gridded SSS (released in late 2015) with two widely used Argo monthly gridded near-surface salinity products. The analysis focused on their consistency in depicting temporal changes (including seasonal and non-seasonal) on various spatial scales: 1˚ x1˚ , 3˚ x3˚ , and 10˚ x10˚ . Globally averaged standard deviation (STD) values for Aquarius-Argo salinity differences on these three spatial scales are 0.16, 0.14, 0.09 psu, compared to those between the two Argo products of 0.10, 0.09, and 0.04 psu. Aquarius SSS compare better with Argo data on non-seasonal (e.g., interannual and intraseasonal) than for seasonal time scales. The seasonal Aquarius-Argo SSS differences are mostly concentrated at high latitudes. The Aquarius team is making active efforts to further reduce these high-latitude seasonal biases. The consistency between Aquarius and Argo salinity is similar to that between the two Argo products in the tropics and subtropics for non-seasonal signals, and in the tropics for seasonal signals. Therefore, the representativeness errors of the Argo products for various spatial scales (related to sampling and gridding) need to be taken into account when estimating the uncertainty of Aquarius SSS. The globally averaged uncertainty of large-scale (10˚ x10˚ ) non-seasonal Aquarius SSS is approximately 0.04 psu. These estimates reflect the significant improvements of Aquarius Version-4 SSS over the previous versions. The estimates can be used as baseline requirements for future ocean salinity missions from space. The spatial distribution of the uncertainty estimates is also useful for assimilation of Aquarius SSS.

Modeling and Compensating Temperature-Dependent Non-Uniformity Noise in IR Microbolometer Cameras

PubMed Central

Wolf, Alejandro; Pezoa, Jorge E.; Figueroa, Miguel

2016-01-01

Images rendered by uncooled microbolometer-based infrared (IR) cameras are severely degraded by the spatial non-uniformity (NU) noise. The NU noise imposes a fixed-pattern over the true images, and the intensity of the pattern changes with time due to the temperature instability of such cameras. In this paper, we present a novel model and a compensation algorithm for the spatial NU noise and its temperature-dependent variations. The model separates the NU noise into two components: a constant term, which corresponds to a set of NU parameters determining the spatial structure of the noise, and a dynamic term, which scales linearly with the fluctuations of the temperature surrounding the array of microbolometers. We use a black-body radiator and samples of the temperature surrounding the IR array to offline characterize both the constant and the temperature-dependent NU noise parameters. Next, the temperature-dependent variations are estimated online using both a spatially uniform Hammerstein-Wiener estimator and a pixelwise least mean squares (LMS) estimator. We compensate for the NU noise in IR images from two long-wave IR cameras. Results show an excellent NU correction performance and a root mean square error of less than 0.25 ∘C, when the array’s temperature varies by approximately 15 ∘C. PMID:27447637

Spatially and temporally resolved exciton dynamics and transport in single nanostructures and assemblies

NASA Astrophysics Data System (ADS)

Huang, Libai

2015-03-01

The frontier in solar energy conversion now lies in learning how to integrate functional entities across multiple length scales to create optimal devices. To address this new frontier, I will discuss our recent efforts on elucidating multi-scale energy transfer, migration, and dissipation processes with simultaneous femtosecond temporal resolution and nanometer spatial resolution. We have developed ultrafast microscopy that combines ultrafast spectroscopy with optical microscopy to map exciton dynamics and transport with simultaneous ultrafast time resolution and diffraction-limited spatial resolution. We have employed pump-probe transient absorption microscopy to elucidate morphology and structure dependent exciton dynamics and transport in single nanostructures and molecular assemblies. More specifically, (1) We have applied transient absorption microscopy (TAM) to probe environmental and structure dependent exciton relaxation pathways in sing-walled carbon nanotubes (SWNTs) by mapping dynamics in individual pristine SWNTs with known structures. (2) We have systematically measured and modeled the optical properties of the Frenkel excitons in self-assembled porphyrin tubular aggregates that represent an analog to natural photosynthetic antennae. Using a combination of ultrafast optical microscopy and stochastic exciton modeling, we address exciton transport and relaxation pathways, especially those related to disorder.

Grain-dependent responses of mammalian diversity to land use and the implications for conservation set-aside.

PubMed

Wearn, Oliver R; Carbone, Chris; Rowcliffe, J Marcus; Bernard, Henry; Ewers, Robert M

2016-07-01

Diversity responses to land-use change are poorly understood at local scales, hindering our ability to make forecasts and management recommendations at scales which are of practical relevance. A key barrier in this has been the underappreciation of grain-dependent diversity responses and the role that β-diversity (variation in community composition across space) plays in this. Decisions about the most effective spatial arrangement of conservation set-aside, for example high conservation value areas, have also neglected β-diversity, despite its role in determining the complementarity of sites. We examined local-scale mammalian species richness and β-diversity across old-growth forest, logged forest, and oil palm plantations in Borneo, using intensive camera- and live-trapping. For the first time, we were able to investigate diversity responses, as well as β-diversity, at multiple spatial grains, and across the whole terrestrial mammal community (large and small mammals); β-diversity was quantified by comparing observed β-diversity with that obtained under a null model, in order to control for sampling effects, and we refer to this as the β-diversity signal. Community responses to land use were grain dependent, with large mammals showing reduced richness in logged forest compared to old-growth forest at the grain of individual sampling points, but no change at the overall land-use level. Responses varied with species group, however, with small mammals increasing in richness at all grains in logged forest compared to old-growth forest. Both species groups were significantly depauperate in oil palm. Large mammal communities in old-growth forest became more heterogeneous at coarser spatial grains and small mammal communities became more homogeneous, while this pattern was reversed in logged forest. Both groups, however, showed a significant β-diversity signal at the finest grain in logged forest, likely due to logging-induced environmental heterogeneity. The β-diversity signal in oil palm was weak, but heterogeneity at the coarsest spatial grain was still evident, likely due to variation in landscape forest cover. Our findings suggest that the most effective spatial arrangement of set-aside will involve trade-offs between conserving large and small mammals. Greater consideration in the conservation and management of tropical landscapes needs to be given to β-diversity at a range of spatial grains. © 2016 by the Ecological Society of America.

Spatial dependence and correlation of rainfall in the Danube catchment and its role in flood risk assessment.

NASA Astrophysics Data System (ADS)

Martina, M. L. V.; Vitolo, R.; Todini, E.; Stephenson, D. B.; Cook, I. M.

2009-04-01

The possibility that multiple catastrophic events occur within a given timespan and affect the same portfolio of insured properties may induce enhanced risk. For this reason, in the insurance industry it is of interest to characterise not only the point probability of catastrophic events, but also their spatial structure. As far as floods are concerned it is important to determine the probability of having multiple simultaneous events in different parts of the same basin: in this case, indeed, the loss in a portfolio can be significantly different. Understanding the spatial structure of the precipitation field is a necessary step for the proper modelling of the spatial dependence and correlation of river discharge. Several stochastic models are available in the scientific literature for the multi-site generation of precipitation. Although most models achieve good performance in modelling mean values, temporal variability and inter-site dependence of extremes are still delicate issues. In this work we aim at identifying the main spatial characteristics of the precipitation structure and then at analysing them in a real case. We consider data from a large network of raingauges in the Danube catchment. This catchment is a good example of a large-scale catchment where the spatial correlation of flood events can radically change the effect in term of flood damage.

Spatial Scaling of Environmental Variables Improves Species-Habitat Models of Fishes in a Small, Sand-Bed Lowland River

PubMed Central

Radinger, Johannes; Wolter, Christian; Kail, Jochem

2015-01-01

Habitat suitability and the distinct mobility of species depict fundamental keys for explaining and understanding the distribution of river fishes. In recent years, comprehensive data on river hydromorphology has been mapped at spatial scales down to 100 m, potentially serving high resolution species-habitat models, e.g., for fish. However, the relative importance of specific hydromorphological and in-stream habitat variables and their spatial scales of influence is poorly understood. Applying boosted regression trees, we developed species-habitat models for 13 fish species in a sand-bed lowland river based on river morphological and in-stream habitat data. First, we calculated mean values for the predictor variables in five distance classes (from the sampling site up to 4000 m up- and downstream) to identify the spatial scale that best predicts the presence of fish species. Second, we compared the suitability of measured variables and assessment scores related to natural reference conditions. Third, we identified variables which best explained the presence of fish species. The mean model quality (AUC = 0.78, area under the receiver operating characteristic curve) significantly increased when information on the habitat conditions up- and downstream of a sampling site (maximum AUC at 2500 m distance class, +0.049) and topological variables (e.g., stream order) were included (AUC = +0.014). Both measured and assessed variables were similarly well suited to predict species’ presence. Stream order variables and measured cross section features (e.g., width, depth, velocity) were best-suited predictors. In addition, measured channel-bed characteristics (e.g., substrate types) and assessed longitudinal channel features (e.g., naturalness of river planform) were also good predictors. These findings demonstrate (i) the applicability of high resolution river morphological and instream-habitat data (measured and assessed variables) to predict fish presence, (ii) the importance of considering habitat at spatial scales larger than the sampling site, and (iii) that the importance of (river morphological) habitat characteristics differs depending on the spatial scale. PMID:26569119

Biotic homogenization can decrease landscape-scale forest multifunctionality.

PubMed

van der Plas, Fons; Manning, Pete; Soliveres, Santiago; Allan, Eric; Scherer-Lorenzen, Michael; Verheyen, Kris; Wirth, Christian; Zavala, Miguel A; Ampoorter, Evy; Baeten, Lander; Barbaro, Luc; Bauhus, Jürgen; Benavides, Raquel; Benneter, Adam; Bonal, Damien; Bouriaud, Olivier; Bruelheide, Helge; Bussotti, Filippo; Carnol, Monique; Castagneyrol, Bastien; Charbonnier, Yohan; Coomes, David Anthony; Coppi, Andrea; Bastias, Cristina C; Dawud, Seid Muhie; De Wandeler, Hans; Domisch, Timo; Finér, Leena; Gessler, Arthur; Granier, André; Grossiord, Charlotte; Guyot, Virginie; Hättenschwiler, Stephan; Jactel, Hervé; Jaroszewicz, Bogdan; Joly, François-Xavier; Jucker, Tommaso; Koricheva, Julia; Milligan, Harriet; Mueller, Sandra; Muys, Bart; Nguyen, Diem; Pollastrini, Martina; Ratcliffe, Sophia; Raulund-Rasmussen, Karsten; Selvi, Federico; Stenlid, Jan; Valladares, Fernando; Vesterdal, Lars; Zielínski, Dawid; Fischer, Markus

2016-03-29

Many experiments have shown that local biodiversity loss impairs the ability of ecosystems to maintain multiple ecosystem functions at high levels (multifunctionality). In contrast, the role of biodiversity in driving ecosystem multifunctionality at landscape scales remains unresolved. We used a comprehensive pan-European dataset, including 16 ecosystem functions measured in 209 forest plots across six European countries, and performed simulations to investigate how local plot-scale richness of tree species (α-diversity) and their turnover between plots (β-diversity) are related to landscape-scale multifunctionality. After accounting for variation in environmental conditions, we found that relationships between α-diversity and landscape-scale multifunctionality varied from positive to negative depending on the multifunctionality metric used. In contrast, when significant, relationships between β-diversity and landscape-scale multifunctionality were always positive, because a high spatial turnover in species composition was closely related to a high spatial turnover in functions that were supported at high levels. Our findings have major implications for forest management and indicate that biotic homogenization can have previously unrecognized and negative consequences for large-scale ecosystem multifunctionality.

Biotic homogenization can decrease landscape-scale forest multifunctionality

PubMed Central

van der Plas, Fons; Manning, Pete; Soliveres, Santiago; Allan, Eric; Scherer-Lorenzen, Michael; Verheyen, Kris; Wirth, Christian; Zavala, Miguel A.; Ampoorter, Evy; Baeten, Lander; Barbaro, Luc; Bauhus, Jürgen; Benavides, Raquel; Benneter, Adam; Bonal, Damien; Bouriaud, Olivier; Bruelheide, Helge; Bussotti, Filippo; Carnol, Monique; Castagneyrol, Bastien; Charbonnier, Yohan; Coppi, Andrea; Bastias, Cristina C.; Dawud, Seid Muhie; De Wandeler, Hans; Domisch, Timo; Finér, Leena; Granier, André; Grossiord, Charlotte; Guyot, Virginie; Hättenschwiler, Stephan; Jactel, Hervé; Jaroszewicz, Bogdan; Joly, François-xavier; Jucker, Tommaso; Koricheva, Julia; Milligan, Harriet; Mueller, Sandra; Muys, Bart; Nguyen, Diem; Pollastrini, Martina; Ratcliffe, Sophia; Raulund-Rasmussen, Karsten; Selvi, Federico; Stenlid, Jan; Valladares, Fernando; Vesterdal, Lars; Zielínski, Dawid; Fischer, Markus

2016-01-01

Many experiments have shown that local biodiversity loss impairs the ability of ecosystems to maintain multiple ecosystem functions at high levels (multifunctionality). In contrast, the role of biodiversity in driving ecosystem multifunctionality at landscape scales remains unresolved. We used a comprehensive pan-European dataset, including 16 ecosystem functions measured in 209 forest plots across six European countries, and performed simulations to investigate how local plot-scale richness of tree species (α-diversity) and their turnover between plots (β-diversity) are related to landscape-scale multifunctionality. After accounting for variation in environmental conditions, we found that relationships between α-diversity and landscape-scale multifunctionality varied from positive to negative depending on the multifunctionality metric used. In contrast, when significant, relationships between β-diversity and landscape-scale multifunctionality were always positive, because a high spatial turnover in species composition was closely related to a high spatial turnover in functions that were supported at high levels. Our findings have major implications for forest management and indicate that biotic homogenization can have previously unrecognized and negative consequences for large-scale ecosystem multifunctionality. PMID:26979952

Density-dependent productivity in a colonial vulture at two spatial scales.

PubMed

Fernández-Bellon, Darío; Cortés-Avizanda, Ainara; Arenas, Rafael; Donázar, José Antonio

2016-02-01

Understanding how density dependence modifies demographic parameters in long-lived vertebrates is a challenge for ecologists. Two alternative hypotheses have been used to explain the mechanisms behind density-dependent effects on breeding output: habitat heterogeneity and individual adjustment (also known as interference competition). A number of studies have highlighted the importance of habitat heterogeneity in density dependence in territorial species, but less information exists on demographic processes in colonial species. For these, we expect density-dependent mechanisms to operate at two spatial scales: colony and breeding unit. In this study, we used long-term data from a recovering population of Cinereous Vultures (Aegypius monachus) in southern Spain. We analyzed a long-term data set with information on 2162 breeding attempts at four colonies over a nine-year period (2002-2010) to evaluate environmental and population parameters influencing breeding output. Our results suggest that breeding productivity is subject to density-dependent processes at the colony and the nest site scale and is best explained by interference competition. Factors intrinsic to each colony, as well as environmental constraints linked to physiography and human presence, also play a role in regulatory processes. We detected the existence of a trade-off between the disadvantages of nesting too close to conspecifics and the benefits of coloniality. These could be mediated by the agonistic interactions between breeding pairs and the benefits derived from social sharing of information by breeding individuals. We propose that this trade-off may play a role in defining colony structure and may hold true for other colonial breeding bird species. Our findings also have important management implications for the conservation of this threatened species.

Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh

PubMed Central

Bi, Qifang; Azman, Andrew S.; Satter, Syed Moinuddin; Khan, Azharul Islam; Ahmed, Dilruba; Riaj, Altaf Ahmed; Gurley, Emily S.; Lessler, Justin

2016-01-01

Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets) near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs) to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98), type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00), and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00) exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a cholera endemic population suggests a possible role for highly targeted interventions. Studies with cluster designs in areas with strong spatial clustering of exposures should increase sample size to account for the correlation of these exposures. PMID:26866926

Spatial variation in the climatic predictors of species compositional turnover and endemism

PubMed Central

Di Virgilio, Giovanni; Laffan, Shawn W; Ebach, Malte C; Chapple, David G

2014-01-01

Previous research focusing on broad-scale or geographically invariant species-environment dependencies suggest that temperature-related variables explain more of the variation in reptile distributions than precipitation. However, species–environment relationships may exhibit considerable spatial variation contingent upon the geographic nuances that vary between locations. Broad-scale, geographically invariant analyses may mask this local variation and their findings may not generalize to different locations at local scales. We assess how reptile–climatic relationships change with varying spatial scale, location, and direction. Since the spatial distributions of diversity and endemism hotspots differ for other species groups, we also assess whether reptile species turnover and endemism hotspots are influenced differently by climatic predictors. Using New Zealand reptiles as an example, the variation in species turnover, endemism and turnover in climatic variables was measured using directional moving window analyses, rotated through 360°. Correlations between the species turnover, endemism and climatic turnover results generated by each rotation of the moving window were analysed using multivariate generalized linear models applied at national, regional, and local scales. At national-scale, temperature turnover consistently exhibited the greatest influence on species turnover and endemism, but model predictive capacity was low (typically r2 = 0.05, P < 0.001). At regional scales the relative influence of temperature and precipitation turnover varied between regions, although model predictive capacity was also generally low. Climatic turnover was considerably more predictive of species turnover and endemism at local scales (e.g., r2 = 0.65, P < 0.001). While temperature turnover had the greatest effect in one locale (the northern North Island), there was substantial variation in the relative influence of temperature and precipitation predictors in the remaining four locales. Species turnover and endemism hotspots often occurred in different locations. Climatic predictors had a smaller influence on endemism. Our results caution against assuming that variability in temperature will always be most predictive of reptile biodiversity across different spatial scales, locations and directions. The influence of climatic turnover on the species turnover and endemism of other taxa may exhibit similar patterns of spatial variation. Such intricate variation might be discerned more readily if studies at broad scales are complemented by geographically variant, local-scale analyses. PMID:25473479

Convergence and divergence in a long-term old-field succession: the importance of spatial scale and species abundance.

PubMed

Li, Shao-Peng; Cadotte, Marc W; Meiners, Scott J; Pu, Zhichao; Fukami, Tadashi; Jiang, Lin

2016-09-01

Whether plant communities in a given region converge towards a particular stable state during succession has long been debated, but rarely tested at a sufficiently long time scale. By analysing a 50-year continuous study of post-agricultural secondary succession in New Jersey, USA, we show that the extent of community convergence varies with the spatial scale and species abundance classes. At the larger field scale, abundance-based dissimilarities among communities decreased over time, indicating convergence of dominant species, whereas incidence-based dissimilarities showed little temporal tend, indicating no sign of convergence. In contrast, plots within each field diverged in both species composition and abundance. Abundance-based successional rates decreased over time, whereas rare species and herbaceous plants showed little change in temporal turnover rates. Initial abandonment conditions only influenced community structure early in succession. Overall, our findings provide strong evidence for scale and abundance dependence of stochastic and deterministic processes over old-field succession. © 2016 John Wiley & Sons Ltd/CNRS.

Dissipation of Turbulence in the Solar Wind as Measured by Cluster

NASA Technical Reports Server (NTRS)

Goldstein, Melvyn

2012-01-01

Turbulence in fluids and plasmas is a scale-dependent process that generates fluctuations towards ever-smaller scales until dissipation occurs. Recent Cluster observations in the solar wind demonstrate the existence of a cascade of magnetic energy from the scale of the proton Larmor radius, where kinetic properties of ions invalidate fluid approximations, down to the electron Larmor radius, where electrons become demagnetized. The cascade is quasi-two-dimensional and has been interpreted as consisting of highly oblique kinetic Alfvenic fluctuations that dissipate near at the electron gyroradius scale via proton and electron Landau damping. Here we investigate for the first time the spatial properties of the turbulence at these scales. We report the presence of thin current sheets and discontinuities with spatial sizes greater than or approximately equal to the proton Larmor radius. These isolated structures may be manifestations of intermittency, and such would localize sites of turbulent dissipation. Studying the relationship between turbulent dissipation, reconnection and intermittency is crucial for understanding the dynamics of laboratory and astrophysical plasmas.

The scaling of contact rates with population density for the infectious disease models.

PubMed

Hu, Hao; Nigmatulina, Karima; Eckhoff, Philip

2013-08-01

Contact rates and patterns among individuals in a geographic area drive transmission of directly-transmitted pathogens, making it essential to understand and estimate contacts for simulation of disease dynamics. Under the uniform mixing assumption, one of two mechanisms is typically used to describe the relation between contact rate and population density: density-dependent or frequency-dependent. Based on existing evidence of population threshold and human mobility patterns, we formulated a spatial contact model to describe the appropriate form of transmission with initial growth at low density and saturation at higher density. We show that the two mechanisms are extreme cases that do not capture real population movement across all scales. Empirical data of human and wildlife diseases indicate that a nonlinear function may work better when looking at the full spectrum of densities. This estimation can be applied to large areas with population mixing in general activities. For crowds with unusually large densities (e.g., transportation terminals, stadiums, or mass gatherings), the lack of organized social contact structure deviates the physical contacts towards a special case of the spatial contact model - the dynamics of kinetic gas molecule collision. In this case, an ideal gas model with van der Waals correction fits well; existing movement observation data and the contact rate between individuals is estimated using kinetic theory. A complete picture of contact rate scaling with population density may help clarify the definition of transmission rates in heterogeneous, large-scale spatial systems. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Movement reveals scale dependence in habitat selection of a large ungulate

USGS Publications Warehouse

Northrup, Joseph; Anderson, Charles R.; Hooten, Mevin B.; Wittemyer, George

2016-01-01

Ecological processes operate across temporal and spatial scales. Anthropogenic disturbances impact these processes, but examinations of scale dependence in impacts are infrequent. Such examinations can provide important insight to wildlife–human interactions and guide management efforts to reduce impacts. We assessed spatiotemporal scale dependence in habitat selection of mule deer (Odocoileus hemionus) in the Piceance Basin of Colorado, USA, an area of ongoing natural gas development. We employed a newly developed animal movement method to assess habitat selection across scales defined using animal-centric spatiotemporal definitions ranging from the local (defined from five hour movements) to the broad (defined from weekly movements). We extended our analysis to examine variation in scale dependence between night and day and assess functional responses in habitat selection patterns relative to the density of anthropogenic features. Mule deer displayed scale invariance in the direction of their response to energy development features, avoiding well pads and the areas closest to roads at all scales, though with increasing strength of avoidance at coarser scales. Deer displayed scale-dependent responses to most other habitat features, including land cover type and habitat edges. Selection differed between night and day at the finest scales, but homogenized as scale increased. Deer displayed functional responses to development, with deer inhabiting the least developed ranges more strongly avoiding development relative to those with more development in their ranges. Energy development was a primary driver of habitat selection patterns in mule deer, structuring their behaviors across all scales examined. Stronger avoidance at coarser scales suggests that deer behaviorally mediated their interaction with development, but only to a degree. At higher development densities than seen in this area, such mediation may not be possible and thus maintenance of sufficient habitat with lower development densities will be a critical best management practice as development expands globally.

Determining Scale-dependent Patterns in Spatial and Temporal Datasets

NASA Astrophysics Data System (ADS)

Roy, A.; Perfect, E.; Mukerji, T.; Sylvester, L.

2016-12-01

Spatial and temporal datasets of interest to Earth scientists often contain plots of one variable against another, e.g., rainfall magnitude vs. time or fracture aperture vs. spacing. Such data, comprised of distributions of events along a transect / timeline along with their magnitudes, can display persistent or antipersistent trends, as well as random behavior, that may contain signatures of underlying physical processes. Lacunarity is a technique that was originally developed for multiscale analysis of data. In a recent study we showed that lacunarity can be used for revealing changes in scale-dependent patterns in fracture spacing data. Here we present a further improvement in our technique, with lacunarity applied to various non-binary datasets comprised of event spacings and magnitudes. We test our technique on a set of four synthetic datasets, three of which are based on an autoregressive model and have magnitudes at every point along the "timeline" thus representing antipersistent, persistent, and random trends. The fourth dataset is made up of five clusters of events, each containing a set of random magnitudes. The concept of lacunarity ratio, LR, is introduced; this is the lacunarity of a given dataset normalized to the lacunarity of its random counterpart. It is demonstrated that LR can successfully delineate scale-dependent changes in terms of antipersistence and persistence in the synthetic datasets. This technique is then applied to three different types of data: a hundred-year rainfall record from Knoxville, TN, USA, a set of varved sediments from Marca Shale, and a set of fracture aperture and spacing data from NE Mexico. While the rainfall data and varved sediments both appear to be persistent at small scales, at larger scales they both become random. On the other hand, the fracture data shows antipersistence at small scale (within cluster) and random behavior at large scales. Such differences in behavior with respect to scale-dependent changes in antipersistence to random, persistence to random, or otherwise, maybe be related to differences in the physicochemical properties and processes contributing to multiscale datasets.

Chromosome territories reposition during DNA damage-repair response

PubMed Central

2013-01-01

Background Local higher-order chromatin structure, dynamics and composition of the DNA are known to determine double-strand break frequencies and the efficiency of repair. However, how DNA damage response affects the spatial organization of chromosome territories is still unexplored. Results Our report investigates the effect of DNA damage on the spatial organization of chromosome territories within interphase nuclei of human cells. We show that DNA damage induces a large-scale spatial repositioning of chromosome territories that are relatively gene dense. This response is dose dependent, and involves territories moving from the nuclear interior to the periphery and vice versa. Furthermore, we have found that chromosome territory repositioning is contingent upon double-strand break recognition and damage sensing. Importantly, our results suggest that this is a reversible process where, following repair, chromosome territories re-occupy positions similar to those in undamaged control cells. Conclusions Thus, our report for the first time highlights DNA damage-dependent spatial reorganization of whole chromosomes, which might be an integral aspect of cellular damage response. PMID:24330859

Measuring spatial patterns in floodplains: A step towards understanding the complexity of floodplain ecosystems: Chapter 6

USGS Publications Warehouse

Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.; Gilvear, David J.; Greenwood, Malcolm T.; Thoms, Martin C.; Wood, Paul J.

2016-01-01

Floodplains can be viewed as complex adaptive systems (Levin, 1998) because they are comprised of many different biophysical components, such as morphological features, soil groups and vegetation communities as well as being sites of key biogeochemical processing (Stanford et al., 2005). Interactions and feedbacks among the biophysical components often result in additional phenomena occuring over a range of scales, often in the absence of any controlling factors (sensu Hallet, 1990). This emergence of new biophysical features and rates of processing can lead to alternative stable states which feed back into floodplain adaptive cycles (cf. Hughes, 1997; Stanford et al., 2005). Interactions between different biophysical components, feedbacks, self emergence and scale are all key properties of complex adaptive systems (Levin, 1998; Phillips, 2003; Murray et al., 2014) and therefore will influence the manner in which we study and view spatial patterns. Measuring the spatial patterns of floodplain biophysical components is a prerequisite to examining and understanding these ecosystems as complex adaptive systems. Elucidating relationships between pattern and process, which are intrinsically linked within floodplains (Ward et al., 2002), is dependent upon an understanding of spatial pattern. This knowledge can help river scientists determine the major drivers, controllers and responses of floodplain structure and function, as well as the consequences of altering those drivers and controllers (Hughes and Cass, 1997; Whited et al., 2007). Interactions and feedbacks between physical, chemical and biological components of floodplain ecosystems create and maintain a structurally diverse and dynamic template (Stanford et al., 2005). This template influences subsequent interactions between components that consequently affect system trajectories within floodplains (sensu Bak et al., 1988). Constructing and evaluating models used to predict floodplain ecosystem responses to natural and anthropogenic disturbances therefore require quantification of spatial pattern (Asselman and Middelkoop, 1995; Walling and He, 1998). Quantifying these patterns also provides insights into the spatial and temporal domains of structuring processes as well as enabling the detection of self-emergent phenomena, environmental constraints or anthropogenic interference (Turner et al., 1990; Holling, 1992; De Jager and Rohweder, 2012). Thus, quantifying spatial pattern is an important building block on which to examine floodplains as complex adaptive systems (Levin, 1998). Approaches to measuring spatial pattern in floodplains must be cognisant of scale, self-emergent phenomena, spatial organisation, and location. Fundamental problems may arise when patterns observed at a site or transect scale are scaled-up to infer processes and patterns over entire floodplain surfaces (Wiens, 2002; Thorp et al., 2008). Likewise, patterns observed over the entire spatial extent of a landscape can mask important variation and detail at finer scales (Riitters et al., 2002). Indeed, different patterns often emerge at different scales (Turner et al., 1990) because of hierarchical structuring processes (O'Neill et al., 1991). Categorising data into discrete, homogeneous and predefined spatial units at a particular scale (e.g. polygons) creates issues and errors associated with scale and subjective classification (McGarigal et al., 2009; Cushman et al., 2010). These include, loss of information within classified ‘patches’, as well as the ability to detect the emergence of new features that do not fit the original classification scheme. Many of these issues arise because floodplains are highly heterogeneous and have complex spatial organizations (Carbonneau et al., 2012; Legleiter, 2013). As a result, the scale and location at which measurements are made can influence the observed spatial patterns; and patterns may not be scale independent or applicable in different geomorp

Spatial and velocity statistics of inertial particles in turbulent flows

NASA Astrophysics Data System (ADS)

Bec, J.; Biferale, L.; Cencini, M.; Lanotte, A. S.; Toschi, F.

2011-12-01

Spatial and velocity statistics of heavy point-like particles in incompressible, homogeneous, and isotropic three-dimensional turbulence is studied by means of direct numerical simulations at two values of the Taylor-scale Reynolds number Reλ ~ 200 and Reλ ~ 400, corresponding to resolutions of 5123 and 20483 grid points, respectively. Particles Stokes number values range from St ≈ 0.2 to 70. Stationary small-scale particle distribution is shown to display a singular -multifractal- measure, characterized by a set of generalized fractal dimensions with a strong sensitivity on the Stokes number and a possible, small Reynolds number dependency. Velocity increments between two inertial particles depend on the relative weight between smooth events - where particle velocity is approximately the same of the fluid velocity-, and caustic contributions - when two close particles have very different velocities. The latter events lead to a non-differentiable small-scale behaviour for the relative velocity. The relative weight of these two contributions changes at varying the importance of inertia. We show that moments of the velocity difference display a quasi bi-fractal-behavior and that the scaling properties of velocity increments for not too small Stokes number are in good agreement with a recent theoretical prediction made by K. Gustavsson and B. Mehlig arXiv: 1012.1789v1 [physics.flu-dyn], connecting the saturation of velocity scaling exponents with the fractal dimension of particle clustering.

Tigers on trails: occupancy modeling for cluster sampling.

PubMed

Hines, J E; Nichols, J D; Royle, J A; MacKenzie, D I; Gopalaswamy, A M; Kumar, N Samba; Karanth, K U

2010-07-01

Occupancy modeling focuses on inference about the distribution of organisms over space, using temporal or spatial replication to allow inference about the detection process. Inference based on spatial replication strictly requires that replicates be selected randomly and with replacement, but the importance of these design requirements is not well understood. This paper focuses on an increasingly popular sampling design based on spatial replicates that are not selected randomly and that are expected to exhibit Markovian dependence. We develop two new occupancy models for data collected under this sort of design, one based on an underlying Markov model for spatial dependence and the other based on a trap response model with Markovian detections. We then simulated data under the model for Markovian spatial dependence and fit the data to standard occupancy models and to the two new models. Bias of occupancy estimates was substantial for the standard models, smaller for the new trap response model, and negligible for the new spatial process model. We also fit these models to data from a large-scale tiger occupancy survey recently conducted in Karnataka State, southwestern India. In addition to providing evidence of a positive relationship between tiger occupancy and habitat, model selection statistics and estimates strongly supported the use of the model with Markovian spatial dependence. This new model provides another tool for the decomposition of the detection process, which is sometimes needed for proper estimation and which may also permit interesting biological inferences. In addition to designs employing spatial replication, we note the likely existence of temporal Markovian dependence in many designs using temporal replication. The models developed here will be useful either directly, or with minor extensions, for these designs as well. We believe that these new models represent important additions to the suite of modeling tools now available for occupancy estimation in conservation monitoring. More generally, this work represents a contribution to the topic of cluster sampling for situations in which there is a need for specific modeling (e.g., reflecting dependence) for the distribution of the variable(s) of interest among subunits.

LFNet: A Novel Bidirectional Recurrent Convolutional Neural Network for Light-Field Image Super-Resolution.

PubMed

Wang, Yunlong; Liu, Fei; Zhang, Kunbo; Hou, Guangqi; Sun, Zhenan; Tan, Tieniu

2018-09-01

The low spatial resolution of light-field image poses significant difficulties in exploiting its advantage. To mitigate the dependency of accurate depth or disparity information as priors for light-field image super-resolution, we propose an implicitly multi-scale fusion scheme to accumulate contextual information from multiple scales for super-resolution reconstruction. The implicitly multi-scale fusion scheme is then incorporated into bidirectional recurrent convolutional neural network, which aims to iteratively model spatial relations between horizontally or vertically adjacent sub-aperture images of light-field data. Within the network, the recurrent convolutions are modified to be more effective and flexible in modeling the spatial correlations between neighboring views. A horizontal sub-network and a vertical sub-network of the same network structure are ensembled for final outputs via stacked generalization. Experimental results on synthetic and real-world data sets demonstrate that the proposed method outperforms other state-of-the-art methods by a large margin in peak signal-to-noise ratio and gray-scale structural similarity indexes, which also achieves superior quality for human visual systems. Furthermore, the proposed method can enhance the performance of light field applications such as depth estimation.

Adapting populations in space: clonal interference and genetic diversity

NASA Astrophysics Data System (ADS)

Weissman, Daniel; Barton, Nick

Most species inhabit ranges much larger than the scales over which individuals interact. How does this spatial structure interact with adaptive evolution? We consider a simple model of a spatially-extended, adapting population and show that, while clonal interference severely limits the adaptation of purely asexual populations, even rare recombination is enough to allow adaptation at rates approaching those of well-mixed populations. We also find that the genetic hitchhiking produced by the adaptive alleles sweeping through the population has strange effects on the patterns of genetic diversity. In large spatial ranges, even low rates of adaptation cause all individuals in the population to rapidly trace their ancestry back to individuals living in a small region in the center of the range. The probability of fixation of an allele is thus strongly dependent on the allele's spatial location, with alleles from the center favored. Surprisingly, these effects are seen genome-wide (instead of being localized to the regions of the genome undergoing the sweeps). The spatial concentration of ancestry produces a power-law dependence of relatedness on distance, so that even individuals sampled far apart are likely to be fairly closely related, masking the underlying spatial structure.

The Time Dependent Propensity Function for Acceleration of Spatial Stochastic Simulation of Reaction-Diffusion Systems

PubMed Central

Wu, Sheng; Li, Hong; Petzold, Linda R.

2015-01-01

The inhomogeneous stochastic simulation algorithm (ISSA) is a fundamental method for spatial stochastic simulation. However, when diffusion events occur more frequently than reaction events, simulating the diffusion events by ISSA is quite costly. To reduce this cost, we propose to use the time dependent propensity function in each step. In this way we can avoid simulating individual diffusion events, and use the time interval between two adjacent reaction events as the simulation stepsize. We demonstrate that the new algorithm can achieve orders of magnitude efficiency gains over widely-used exact algorithms, scales well with increasing grid resolution, and maintains a high level of accuracy. PMID:26609185

Geometry and scaling laws of excursion and iso-sets of enstrophy and dissipation in isotropic turbulence

NASA Astrophysics Data System (ADS)

Elsas, José Hugo; Szalay, Alexander S.; Meneveau, Charles

2018-04-01

Motivated by interest in the geometry of high intensity events of turbulent flows, we examine the spatial correlation functions of sets where turbulent events are particularly intense. These sets are defined using indicator functions on excursion and iso-value sets. Their geometric scaling properties are analysed by examining possible power-law decay of their radial correlation function. We apply the analysis to enstrophy, dissipation and velocity gradient invariants Q and R and their joint spatial distributions, using data from a direct numerical simulation of isotropic turbulence at Reλ ≈ 430. While no fractal scaling is found in the inertial range using box-counting in the finite Reynolds number flow considered here, power-law scaling in the inertial range is found in the radial correlation functions. Thus, a geometric characterisation in terms of these sets' correlation dimension is possible. Strong dependence on the enstrophy and dissipation threshold is found, consistent with multifractal behaviour. Nevertheless, the lack of scaling of the box-counting analysis precludes direct quantitative comparisons with earlier work based on multifractal formalism. Surprising trends, such as a lower correlation dimension for strong dissipation events compared to strong enstrophy events, are observed and interpreted in terms of spatial coherence of vortices in the flow.

EMIC Wave Scale Size in the Inner Magnetosphere: Observations From the Dual Van Allen Probes

NASA Technical Reports Server (NTRS)

Blum, L. W.; Bonnell, J. W.; Agapitov, O.; Paulson, K.; Kletzing, C.

2017-01-01

Estimating the spatial scales of electromagnetic ion cyclotron (EMIC) waves is critical for quantifying their overall scattering efficiency and effects on thermal plasma, ring current, and radiation belt particles. Using measurements from the dual Van Allen Probes in 2013-2014, we characterize the spatial and temporal extents of regions of EMIC wave activity and how these depend on local time and radial distance within the inner magnetosphere. Observations are categorized into three types: waves observed by only one spacecraft, waves measured by both spacecraft simultaneously, and waves observed by both spacecraft with some time lag. Analysis reveals that dayside (and H+ band) EMIC waves more frequently span larger spatial areas, while nightside (and He+ band) waves are more often localized but can persist many hours. These investigations give insight into the nature of EMIC wave generation and support more accurate quantification of their effects on the ring current and outer radiation belt.

EMIC wave scale size in the inner magnetosphere: Observations from the dual Van Allen Probes

NASA Astrophysics Data System (ADS)

Blum, L. W.; Bonnell, J. W.; Agapitov, O.; Paulson, K.; Kletzing, C.

2017-02-01

Estimating the spatial scales of electromagnetic ion cyclotron (EMIC) waves is critical for quantifying their overall scattering efficiency and effects on thermal plasma, ring current, and radiation belt particles. Using measurements from the dual Van Allen Probes in 2013-2014, we characterize the spatial and temporal extents of regions of EMIC wave activity and how these depend on local time and radial distance within the inner magnetosphere. Observations are categorized into three types—waves observed by only one spacecraft, waves measured by both spacecraft simultaneously, and waves observed by both spacecraft with some time lag. Analysis reveals that dayside (and H+ band) EMIC waves more frequently span larger spatial areas, while nightside (and He+ band) waves are more often localized but can persist many hours. These investigations give insight into the nature of EMIC wave generation and support more accurate quantification of their effects on the ring current and outer radiation belt.

Range expansion through fragmented landscapes under a variable climate

PubMed Central

Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J

2013-01-01

Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124

Scale-dependent correlation of seabirds with schooling fish in a coastal ecosystem

USGS Publications Warehouse

Schneider, Davod C.; Piatt, John F.

1986-01-01

The distribution of piscivorous seabirds relative to schooling fish was investigated by repeated censusing of 2 intersecting transects in the Avalon Channel, which carries the Labrador Current southward along the east coast of Newfoundland. Murres (primarily common murres Uria aalge), Atlantic puffins Fratercula arctica, and schooling fish (primarily capelin Mallotus villosus) were highly aggregated at spatial scales ranging from 0.25 to 15 km. Patchiness of murres, puffins and schooling fish was scale-dependent, as indicated by significantly higher variance-to-mean ratios at large measurement distances than at the minimum distance, 0.25 km. Patch scale of puffins ranged from 2.5 to 15 km, of murres from 3 to 8.75 km, and of schooling fish from 1.25 to 15 km. Patch scale of birds and schooling fish was similar m 6 out of 9 comparisons. Correlation between seabirds and schooling birds was significant at the minimum measurement distance in 6 out of 12 comparisons. Correlation was scale-dependent, as indicated by significantly higher coefficients at large measurement distances than at the minimum distance. Tracking scale, as indicated by the maximum significant correlation between birds and schooling fish, ranged from 2 to 6 km. Our analysis showed that extended aggregations of seabirds are associated with extended aggregations of schooling fish and that correlation of these marine carnivores with their prey is scale-dependent.

Multi-scale Slip Inversion Based on Simultaneous Spatial and Temporal Domain Wavelet Transform

NASA Astrophysics Data System (ADS)

Liu, W.; Yao, H.; Yang, H. Y.

2017-12-01

Finite fault inversion is a widely used method to study earthquake rupture processes. Some previous studies have proposed different methods to implement finite fault inversion, including time-domain, frequency-domain, and wavelet-domain methods. Many previous studies have found that different frequency bands show different characteristics of the seismic rupture (e.g., Wang and Mori, 2011; Yao et al., 2011, 2013; Uchide et al., 2013; Yin et al., 2017). Generally, lower frequency waveforms correspond to larger-scale rupture characteristics while higher frequency data are representative of smaller-scale ones. Therefore, multi-scale analysis can help us understand the earthquake rupture process thoroughly from larger scale to smaller scale. By the use of wavelet transform, the wavelet-domain methods can analyze both the time and frequency information of signals in different scales. Traditional wavelet-domain methods (e.g., Ji et al., 2002) implement finite fault inversion with both lower and higher frequency signals together to recover larger-scale and smaller-scale characteristics of the rupture process simultaneously. Here we propose an alternative strategy with a two-step procedure, i.e., firstly constraining the larger-scale characteristics with lower frequency signals, and then resolving the smaller-scale ones with higher frequency signals. We have designed some synthetic tests to testify our strategy and compare it with the traditional one. We also have applied our strategy to study the 2015 Gorkha Nepal earthquake using tele-seismic waveforms. Both the traditional method and our two-step strategy only analyze the data in different temporal scales (i.e., different frequency bands), while the spatial distribution of model parameters also shows multi-scale characteristics. A more sophisticated strategy is to transfer the slip model into different spatial scales, and then analyze the smooth slip distribution (larger scales) with lower frequency data firstly and more detailed slip distribution (smaller scales) with higher frequency data subsequently. We are now implementing the slip inversion using both spatial and temporal domain wavelets. This multi-scale analysis can help us better understand frequency-dependent rupture characteristics of large earthquakes.

What FIREs Up Star Formation: the Emergence of the Kennicutt-Schmidt Law from Feedback

NASA Astrophysics Data System (ADS)

Orr, Matthew E.; Hayward, Christopher C.; Hopkins, Philip F.; Chan, T. K.; Faucher-Giguère, Claude-André; Feldmann, Robert; Kereš, Dušan; Murray, Norman; Quataert, Eliot

2018-05-01

We present an analysis of the global and spatially-resolved Kennicutt-Schmidt (KS) star formation relation in the FIRE (Feedback In Realistic Environments) suite of cosmological simulations, including halos with z = 0 masses ranging from 1010 - 1013 M⊙. We show that the KS relation emerges and is robustly maintained due to the effects of feedback on local scales regulating star-forming gas, independent of the particular small-scale star formation prescriptions employed. We demonstrate that the time-averaged KS relation is relatively independent of redshift and spatial averaging scale, and that the star formation rate surface density is weakly dependent on metallicity and inversely dependent on orbital dynamical time. At constant star formation rate surface density, the `Cold & Dense' gas surface density (gas with T < 300 K and n > 10 cm-3, used as a proxy for the molecular gas surface density) of the simulated galaxies is ˜0.5 dex less than observed at ˜kpc scales. This discrepancy may arise from underestimates of the local column density at the particle-scale for the purposes of shielding in the simulations. Finally, we show that on scales larger than individual giant molecular clouds, the primary condition that determines whether star formation occurs is whether a patch of the galactic disk is thermally Toomre-unstable (not whether it is self-shielding): once a patch can no longer be thermally stabilized against fragmentation, it collapses, becomes self-shielding, cools, and forms stars, regardless of epoch or environment.

Spatial evolutionary public goods game on complete graph and dense complex networks

NASA Astrophysics Data System (ADS)

Kim, Jinho; Chae, Huiseung; Yook, Soon-Hyung; Kim, Yup

2015-03-01

We study the spatial evolutionary public goods game (SEPGG) with voluntary or optional participation on a complete graph (CG) and on dense networks. Based on analyses of the SEPGG rate equation on finite CG, we find that SEPGG has two stable states depending on the value of multiplication factor r, illustrating how the ``tragedy of the commons'' and ``an anomalous state without any active participants'' occurs in real-life situations. When r is low (), the state with only loners is stable, and the state with only defectors is stable when r is high (). We also derive the exact scaling relation for r*. All of the results are confirmed by numerical simulation. Furthermore, we find that a cooperator-dominant state emerges when the number of participants or the mean degree, , decreases. We also investigate the scaling dependence of the emergence of cooperation on r and . These results show how ``tragedy of the commons'' disappears when cooperation between egoistic individuals without any additional socioeconomic punishment increases.

A test of Lee's quasi-linear theory of ion acceleration by interplanetary traveling shocks

NASA Technical Reports Server (NTRS)

Kennel, C. F.; Coroniti, F. V.; Scarf, F. L.; Livesey, W. A.; Russell, C. T.; Smith, E. J.

1986-01-01

Lee's (1983) quasi-linear theory of ion acceleration is tested using ISEE-3 measurements of the November 12, 1978 quasi-parallel interplanetary shock. His theory accounts with varying degrees of precision for the energetic proton spatial profiles; the dependence of the spectral index of the power law proton velocity distribution upon the shock compression ratio; the power law dependence of the upstream proton scalelength upon energy; the absolute magnitude of the upstream proton scale length; the behavior of the energetic proton anisotropy upstream and downstream of the shock; the behavior of the alpha-particle proton ratio upstream; the equality of the spatial scale lengths at the shock of the upstream waves and of the protons that resonate with them; and the dependence of the integrated wave energy density upon the proton energy density at the shock. However, the trace magnetic field frequency spectra disagree with his theory in two ways. The part of the spectrum that can resonate with the observed protons via first-order cyclotron resonance is flat, whereas Lee's theory predicts an f exp - 7/4 frequency dependence for the November 12 shock. Higher frequency waves, which could not resonate with the observed upstream protons, increased in amplitude as the shock approached, suggesting that they too were generated by the shock.

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

PubMed Central

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

2013-01-01

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

Wetland characteristics linked to broad-scale patterns in Culiseta melanura abundance and eastern equine encephalitis virus infection.

PubMed

Skaff, Nicholas K; Armstrong, Philip M; Andreadis, Theodore G; Cheruvelil, Kendra S

2017-10-18

Eastern equine encephalitis virus (EEEV) is an expanding mosquito-borne threat to humans and domestic animal populations in the northeastern United States. Outbreaks of EEEV are challenging to predict due to spatial and temporal uncertainty in the abundance and viral infection of Cs. melanura, the principal enzootic vector. EEEV activity may be closely linked to wetlands because they provide essential habitat for mosquito vectors and avian reservoir hosts. However, wetlands are not homogeneous and can vary by vegetation, connectivity, size, and inundation patterns. Wetlands may also have different effects on EEEV transmission depending on the assessed spatial scale. We investigated associations between wetland characteristics and Cs. melanura abundance and infection with EEEV at multiple spatial scales in Connecticut, USA. Our findings indicate that wetland vegetative characteristics have strong associations with Cs. melanura abundance. Deciduous and evergreen forested wetlands were associated with higher Cs. melanura abundance, likely because these wetlands provide suitable subterranean habitat for Cs. melanura development. In contrast, Cs. melanura abundance was negatively associated with emergent and scrub/shrub wetlands, and wetland connectivity to streams. These relationships were generally strongest at broad spatial scales. Additionally, the relationships between wetland characteristics and EEEV infection in Cs. melanura were generally weak. However, Cs. melanura abundance was strongly associated with EEEV infection, suggesting that wetland-associated changes in abundance may be indirectly linked to EEEV infection in Cs. melanura. Finally, we found that wet hydrological conditions during the transmission season and during the fall/winter preceding the transmission season were associated with higher Cs. melanura abundance and EEEV infection, indicating that wet conditions are favorable for EEEV transmission. These results expand the broad-scale understanding of the effects of wetlands on EEEV transmission and help to reduce the spatial and temporal uncertainty associated with EEEV outbreaks.

Spatial variability structure of soil CO2 emission and soil physical and chemical properties characterized by fractal dimension in sugarcane areas

NASA Astrophysics Data System (ADS)

Bicalho, E. S.; Teixeira, D. B.; Panosso, A. R.; Perillo, L. I.; Iamaguti, J. L.; Pereira, G. T.; La Scala, N., Jr.

2012-04-01

Soil CO2 emission (FCO2) is influenced by chemical, physical and biological factors that affect the production of CO2 in the soil and its transport to the atmosphere, varying in time and space depending on environmental conditions, including the management of agricultural area. The aim of this study was to investigate the structure of spatial variability of FCO2 and soil properties by using fractal dimension (DF), derived from isotropic variograms at different scales, and construction of fractograms. The experimental area consisted of a regular grid of 60 × 60 m on sugarcane area under green management, containing 141 points spaced at minimum distances ranging from 0.5 to 10 m. Soil CO2 emission, soil temperature and soil moisture were evaluated over a period of 7 days, and soil chemical and physical properties were determined by sampling at a depth of 0.0 to 0.1 m. FCO2 showed an overall average of 1.51 µmol m-2 s-1, correlated significantly (p < 0.05) with soil physical factors such as soil bulk density, air-filled pore space, macroporosity and microporosity. Significant DF values were obtained in the characterization of FCO2 in medium and large scales (from 20 m). Variations in DF with the scale, which is the fractogram, indicate that the structure of FCO2 variability is similar to that observed for the soil temperature and total pore volume, and reverse for the other soil properties, except for macroporosity, sand content, soil organic matter, carbon stock, C/N ratio and CEC, which fractograms were not significantly correlated to the FCO2 fractogram. Thus, the structure of spatial variability for most soil properties, characterized by fractogram, presents a significant relationship with the structure of spatial variability of FCO2, generally with similar or dissimilar behavior, indicating the possibility of using the fractogram as tool to better observe the behavior of the spatial dependence of the variables along the scale.

Relativity of Scales: Application to AN Endo-Perspective of Temporal Structures

NASA Astrophysics Data System (ADS)

Nottale, Laurent; Timar, Pierre

The theory of scale relativity is an extension of the principle of relativity to scale transformations of the reference system, in a fractal geometry framework where coordinates become explicitly dependent on resolutions. Applied to an observer perspective, it means that the scales of length and of time, usually attributed to the observed object as being intrinsic to it, have actually no existence by themselves, since only the ratio between an external scale and an internal scale, which serves as unit, is meaningful. Oliver Sacks' observations on patients suffering from temporal and spatial distortions in Parkinson's and encephalitis lethargica disease offer a particularly relevant field of application for such a scale-relativistic view.

Time Dependent Tomography of the Solar Corona in Three Spatial Dimensions

NASA Astrophysics Data System (ADS)

Butala, M. D.; Frazin, R. A.; Kamalabadi, F.

2006-12-01

The combination of the soon to be launched STEREO mission with SOHO will provide scientists with three simultaneous space-borne views of the Sun. The increase in available measurements will reduce the data acquisition time necessary to obtain 3D coronal electron density (N_e) estimates from coronagraph images using a technique called solar rotational tomography (SRT). However, the data acquisition period will still be long enough for the corona to dynamically evolve, requiring time dependent solar tomography. The Kalman filter (KF) would seem to be an ideal computational method for time dependent SRT. Unfortunately, the KF scales poorly with problem size and is, as a result, inapplicable. A Monte Carlo approximation to the KF called the localized ensemble Kalman filter was developed for massive applications and has the promise of making the time dependent estimation of the 3D coronal N_e possible. We present simulations showing that this method will make time dependent tomography in three spatial dimensions computationally feasible.

Scale-dependent approaches to modeling spatial epidemiology of chronic wasting disease.

USGS Publications Warehouse

Conner, Mary M.; Gross, John E.; Cross, Paul C.; Ebinger, Michael R.; Gillies, Robert; Samuel, Michael D.; Miller, Michael W.

2007-01-01

For each scale, we presented a focal approach that would be useful for understanding the spatial pattern and epidemiology of CWD, as well as being a useful tool for CWD management. The focal approaches include risk analysis and micromaps for the regional scale, cluster analysis for the landscape scale, and individual based modeling for the fine scale of within population. For each of these methods, we used simulated data and walked through the method step by step to fully illustrate the “how to”, with specifics about what is input and output, as well as what questions the method addresses. We also provided a summary table to, at a glance, describe the scale, questions that can be addressed, and general data required for each method described in this e-book. We hope that this review will be helpful to biologists and managers by increasing the utility of their surveillance data, and ultimately be useful for increasing our understanding of CWD and allowing wildlife biologists and managers to move beyond retroactive fire-fighting to proactive preventative action.

Identifying spatial priorities for protecting ecosystem services

PubMed Central

Luck, Gary W

2012-01-01

Priorities for protecting ecosystem services must be identified to ensure future human well-being. Approaches to broad-scale spatial prioritization of ecosystem services are becoming increasingly popular and are a vital precursor to identifying locations where further detailed analyses of the management of ecosystem services is required (e.g., examining trade-offs among management actions). Prioritization approaches often examine the spatial congruence between priorities for protecting ecosystem services and priorities for protecting biodiversity; therefore, the spatial prioritization method used is crucial because it will influence the alignment of service protection and conservation goals. While spatial prioritization of ecosystem services and prioritization for conservation share similarities, such as the need to document threats and costs, the former differs substantially from the latter owing to the requirement to measure the following components: supply of services; availability of human-derived alternatives to service provision; capacity to meet beneficiary demand; and site dependency in and scale of service delivery. We review studies that identify broad-scale spatial priorities for managing ecosystem services and demonstrate that researchers have used different approaches and included various measures for identifying priorities, and most studies do not consider all of the components listed above. We describe a conceptual framework for integrating each of these components into spatial prioritization of ecosystem services and illustrate our approach using a worked example for water provision. A fuller characterization of the biophysical and social context for ecosystem services that we call for should improve future prioritization and the identification of locations where ecosystem-service management is especially important or cost effective. PMID:24555017

Scaling Law for Cross-stream Diffusion in Microchannels under Combined Electroosmotic and Pressure Driven Flow.

PubMed

Song, Hongjun; Wang, Yi; Pant, Kapil

2013-01-01

This paper presents an analytical study of the cross-stream diffusion of an analyte in a rectangular microchannel under combined electroosmotic flow (EOF) and pressure driven flow to investigate the heterogeneous transport behavior and spatially-dependent diffusion scaling law. An analytical model capable of accurately describing 3D steady-state convection-diffusion in microchannels with arbitrary aspect ratios is developed based on the assumption of the thin Electric Double Layer (EDL). The model is verified against high-fidelity numerical simulation in terms of flow velocity and analyte concentration profiles with excellent agreement (<0.5% relative error). An extensive parametric analysis is then undertaken to interrogate the effect of the combined flow velocity field on the transport behavior in both the positive pressure gradient (PPG) and negative pressure gradient (NPG) cases. For the first time, the evolution from the spindle-shaped concentration profile in the PPG case, via the stripe-shaped profile (pure EOF), and finally to the butterfly-shaped profile in the PPG case is obtained using the analytical model along with a quantitative depiction of the spatially-dependent diffusion layer thickness and scaling law across a wide range of the parameter space.

Scaling Law for Cross-stream Diffusion in Microchannels under Combined Electroosmotic and Pressure Driven Flow

PubMed Central

Song, Hongjun; Wang, Yi; Pant, Kapil

2012-01-01

This paper presents an analytical study of the cross-stream diffusion of an analyte in a rectangular microchannel under combined electroosmotic flow (EOF) and pressure driven flow to investigate the heterogeneous transport behavior and spatially-dependent diffusion scaling law. An analytical model capable of accurately describing 3D steady-state convection-diffusion in microchannels with arbitrary aspect ratios is developed based on the assumption of the thin Electric Double Layer (EDL). The model is verified against high-fidelity numerical simulation in terms of flow velocity and analyte concentration profiles with excellent agreement (<0.5% relative error). An extensive parametric analysis is then undertaken to interrogate the effect of the combined flow velocity field on the transport behavior in both the positive pressure gradient (PPG) and negative pressure gradient (NPG) cases. For the first time, the evolution from the spindle-shaped concentration profile in the PPG case, via the stripe-shaped profile (pure EOF), and finally to the butterfly-shaped profile in the PPG case is obtained using the analytical model along with a quantitative depiction of the spatially-dependent diffusion layer thickness and scaling law across a wide range of the parameter space. PMID:23554584

Spatial dimensions of the electron diffusion region in anti-parallel magnetic reconnection

NASA Astrophysics Data System (ADS)

Nakamura, Takuma; Nakamura, Rumi; Haseagwa, Hiroshi

2016-03-01

Spatial dimensions of the detailed structures of the electron diffusion region in anti-parallel magnetic reconnection were analyzed based on two-dimensional fully kinetic particle-in-cell simulations. The electron diffusion region in this study is defined as the region where the positive reconnection electric field is sustained by the electron inertial and non-gyrotropic pressure components. Past kinetic studies demonstrated that the dimensions of the whole electron diffusion region and the inner non-gyrotropic region are scaled by the electron inertial length de and the width of the electron meandering motion, respectively. In this study, we successfully obtained more precise scalings of the dimensions of these two regions than the previous studies by performing simulations with sufficiently small grid spacing (1/16-1/8 de) and a sufficient number of particles (800 particles cell-1 on average) under different conditions changing the ion-to-electron mass ratio, the background density and the electron βe (temperature). The obtained scalings are adequately supported by some theories considering spatial variations of field and plasma parameters within the diffusion region. In the reconnection inflow direction, the dimensions of both regions are proportional to de based on the background density. Both dimensions also depend on βe based on the background values, but the dependence in the inner region ( ˜ 0.375th power) is larger than the whole region (0.125th power) reflecting the orbits of meandering and accelerated electrons within the inner region. In the outflow direction, almost only the non-gyrotropic component sustains the positive reconnection electric field. The dimension of this single-scale diffusion region is proportional to the ion-electron hybrid inertial length (dide)1/2 based on the background density and weakly depends on the background βe with the 0.25th power. These firm scalings allow us to predict observable dimensions in real space which are indeed in reasonable agreement with past in situ spacecraft observations in the Earth's magnetotail and have important implications for future observations with higher resolutions such as the NASA Magnetospheric Multiscale (MMS) mission.

A Global and Spatially Explicit Assessment of Climate Change Impacts on Crop Production and Consumptive Water Use

PubMed Central

Liu, Junguo; Folberth, Christian; Yang, Hong; Röckström, Johan; Abbaspour, Karim; Zehnder, Alexander J. B.

2013-01-01

Food security and water scarcity have become two major concerns for future human's sustainable development, particularly in the context of climate change. Here we present a comprehensive assessment of climate change impacts on the production and water use of major cereal crops on a global scale with a spatial resolution of 30 arc-minutes for the 2030s (short term) and the 2090s (long term), respectively. Our findings show that impact uncertainties are higher on larger spatial scales (e.g., global and continental) but lower on smaller spatial scales (e.g., national and grid cell). Such patterns allow decision makers and investors to take adaptive measures without being puzzled by a highly uncertain future at the global level. Short-term gains in crop production from climate change are projected for many regions, particularly in African countries, but the gains will mostly vanish and turn to losses in the long run. Irrigation dependence in crop production is projected to increase in general. However, several water poor regions will rely less heavily on irrigation, conducive to alleviating regional water scarcity. The heterogeneity of spatial patterns and the non-linearity of temporal changes of the impacts call for site-specific adaptive measures with perspectives of reducing short- and long-term risks of future food and water security. PMID:23460901

Mitotic Cortical Waves Predict Future Division Sites by Encoding Positional and Size Information.

PubMed

Xiao, Shengping; Tong, Cheesan; Yang, Yang; Wu, Min

2017-11-20

Dynamic spatial patterns such as traveling waves could theoretically encode spatial information, but little is known about whether or how they are employed by biological systems, especially higher eukaryotes. Here, we show that concentric target or spiral waves of active Cdc42 and the F-BAR protein FBP17 are invoked in adherent cells at the onset of mitosis. These waves predict the future sites of cell divisions and represent the earliest known spatial cues for furrow assembly. Unlike interphase waves, the frequencies and wavelengths of the mitotic waves display size-dependent scaling properties. While the positioning role of the metaphase waves requires microtubule dynamics, spindle and microtubule-independent inhibitory signals are propagated by the mitotic waves to ensure the singularity of furrow formation. Taken together, we propose that metaphase cortical waves integrate positional and cell size information for division-plane specification in adhesion-dependent cytokinesis. Copyright © 2017 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2003-05-01

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

Spectroscopic measurement of spin-dependent resonant tunneling through a 3D disorder: the case of MnAs/GaAs/MnAs junctions.

PubMed

Garcia, V; Jaffrès, H; George, J-M; Marangolo, M; Eddrief, M; Etgens, V H

2006-12-15

We propose an analytical model of spin-dependent resonant tunneling through a 3D assembly of localized states (spread out in energy and in space) in a barrier. An inhomogeneous distribution of localized states leads to resonant tunneling magnetoresistance inversion and asymmetric bias dependence as evidenced with a set of experiments with MnAs/GaAs(7-10 nm)/MnAs tunnel junctions. One of the key parameters of our theory is a dimensionless critical exponent beta scaling the typical extension of the localized states over the characteristic length scale of the spatial distribution function. Furthermore, we demonstrate, through experiments with localized states introduced preferentially in the middle of the barrier, the influence of an homogeneous distribution on the spin-dependent transport properties.

Explaining variation in tropical plant community composition: influence of environmental and spatial data quality.

PubMed

Jones, Mirkka M; Tuomisto, Hanna; Borcard, Daniel; Legendre, Pierre; Clark, David B; Olivas, Paulo C

2008-03-01

The degree to which variation in plant community composition (beta-diversity) is predictable from environmental variation, relative to other spatial processes, is of considerable current interest. We addressed this question in Costa Rican rain forest pteridophytes (1,045 plots, 127 species). We also tested the effect of data quality on the results, which has largely been overlooked in earlier studies. To do so, we compared two alternative spatial models [polynomial vs. principal coordinates of neighbour matrices (PCNM)] and ten alternative environmental models (all available environmental variables vs. four subsets, and including their polynomials vs. not). Of the environmental data types, soil chemistry contributed most to explaining pteridophyte community variation, followed in decreasing order of contribution by topography, soil type and forest structure. Environmentally explained variation increased moderately when polynomials of the environmental variables were included. Spatially explained variation increased substantially when the multi-scale PCNM spatial model was used instead of the traditional, broad-scale polynomial spatial model. The best model combination (PCNM spatial model and full environmental model including polynomials) explained 32% of pteridophyte community variation, after correcting for the number of sampling sites and explanatory variables. Overall evidence for environmental control of beta-diversity was strong, and the main floristic gradients detected were correlated with environmental variation at all scales encompassed by the study (c. 100-2,000 m). Depending on model choice, however, total explained variation differed more than fourfold, and the apparent relative importance of space and environment could be reversed. Therefore, we advocate a broader recognition of the impacts that data quality has on analysis results. A general understanding of the relative contributions of spatial and environmental processes to species distributions and beta-diversity requires that methodological artefacts are separated from real ecological differences.

Scale dependence of felid predation risk: Identifying predictors of livestock kills by tiger and leopard in Bhutan

Treesearch

Susana Rostro-Garcia; Lhendup Tharchen; Leandro Abade; Christos Astaras; Samuel A. Cushman; David W. Macdonald

2016-01-01

Livestock predation by tiger and leopard in Bhutan is a major threat to the conservation of these felids. Conflict mitigation planning would benefit from an improved understanding of the spatial pattern of livestock kills by the two predators.

Soil Systems for Upscaling Saturated Hydraulic Conductivity (Ksat) for Hydrological Modeling in the Critical Zone

USDA-ARS?s Scientific Manuscript database

Successful hydrological model predictions depend on appropriate framing of scale and the spatial-temporal accuracy of input parameters describing soil hydraulic properties. Saturated soil hydraulic conductivity (Ksat) is one of the most important properties influencing water movement through soil un...

Density-dependent home-range size revealed by spatially explicit capture–recapture

USGS Publications Warehouse

Efford, M.G.; Dawson, Deanna K.; Jhala, Y.V.; Qureshi, Q.

2016-01-01

The size of animal home ranges often varies inversely with population density among populations of a species. This fact has implications for population monitoring using spatially explicit capture–recapture (SECR) models, in which both the scale of home-range movements σ and population density D usually appear as parameters, and both may vary among populations. It will often be appropriate to model a structural relationship between population-specific values of these parameters, rather than to assume independence. We suggest re-parameterizing the SECR model using kp = σp √Dp, where kp relates to the degree of overlap between home ranges and the subscript p distinguishes populations. We observe that kp is often nearly constant for populations spanning a range of densities. This justifies fitting a model in which the separate kp are replaced by the single parameter k and σp is a density-dependent derived parameter. Continuous density-dependent spatial variation in σ may also be modelled, using a scaled non-Euclidean distance between detectors and the locations of animals. We illustrate these methods with data from automatic photography of tigers (Panthera tigris) across India, in which the variation is among populations, from mist-netting of ovenbirds (Seiurus aurocapilla) in Maryland, USA, in which the variation is within a single population over time, and from live-trapping of brushtail possums (Trichosurus vulpecula) in New Zealand, modelling spatial variation within one population. Possible applications and limitations of the methods are discussed. A model in which kp is constant, while density varies, provides a parsimonious null model for SECR. The parameter k of the null model is a concise summary of the empirical relationship between home-range size and density that is useful in comparative studies. We expect deviations from this model, particularly the dependence of kp on covariates, to be biologically interesting.

Temporal and spatial scaling impacts on extreme precipitation

NASA Astrophysics Data System (ADS)

Eggert, B.; Berg, P.; Haerter, J. O.; Jacob, D.; Moseley, C.

2015-01-01

Both in the current climate and in the light of climate change, understanding of the causes and risk of precipitation extremes is essential for protection of human life and adequate design of infrastructure. Precipitation extreme events depend qualitatively on the temporal and spatial scales at which they are measured, in part due to the distinct types of rain formation processes that dominate extremes at different scales. To capture these differences, we first filter large datasets of high-resolution radar measurements over Germany (5 min temporally and 1 km spatially) using synoptic cloud observations, to distinguish convective and stratiform rain events. In a second step, for each precipitation type, the observed data are aggregated over a sequence of time intervals and spatial areas. The resulting matrix allows a detailed investigation of the resolutions at which convective or stratiform events are expected to contribute most to the extremes. We analyze where the statistics of the two types differ and discuss at which resolutions transitions occur between dominance of either of the two precipitation types. We characterize the scales at which the convective or stratiform events will dominate the statistics. For both types, we further develop a mapping between pairs of spatially and temporally aggregated statistics. The resulting curve is relevant when deciding on data resolutions where statistical information in space and time is balanced. Our study may hence also serve as a practical guide for modelers, and for planning the space-time layout of measurement campaigns. We also describe a mapping between different pairs of resolutions, possibly relevant when working with mismatched model and observational resolutions, such as in statistical bias correction.

Modeling the influence of preferential flow on the spatial variability and time-dependence of mineral weathering rates

DOE PAGES

Pandey, Sachin; Rajaram, Harihar

2016-12-05

Inferences of weathering rates from laboratory and field observations suggest significant scale and time-dependence. Preferential flow induced by heterogeneity (manifest as permeability variations or discrete fractures) has been suggested as one potential mechanism causing scale/time-dependence. In this paper, we present a quantitative evaluation of the influence of preferential flow on weathering rates using reactive transport modeling. Simulations were performed in discrete fracture networks (DFNs) and correlated random permeability fields (CRPFs), and compared to simulations in homogeneous permeability fields. The simulations reveal spatial variability in the weathering rate, multidimensional distribution of reactions zones, and the formation of rough weathering interfaces andmore » corestones due to preferential flow. In the homogeneous fields and CRPFs, the domain-averaged weathering rate is initially constant as long as the weathering front is contained within the domain, reflecting equilibrium-controlled behavior. The behavior in the CRPFs was influenced by macrodispersion, with more spread-out weathering profiles, an earlier departure from the initial constant rate and longer persistence of weathering. DFN simulations exhibited a sustained time-dependence resulting from the formation of diffusion-controlled weathering fronts in matrix blocks, which is consistent with the shrinking core mechanism. A significant decrease in the domain-averaged weathering rate is evident despite high remaining mineral volume fractions, but the decline does not follow a math formula dependence, characteristic of diffusion, due to network scale effects and advection-controlled behavior near the inflow boundary. Finally, the DFN simulations also reveal relatively constant horizontally averaged weathering rates over a significant depth range, challenging the very notion of a weathering front.« less

Modeling the influence of preferential flow on the spatial variability and time-dependence of mineral weathering rates

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

Pandey, Sachin; Rajaram, Harihar

Inferences of weathering rates from laboratory and field observations suggest significant scale and time-dependence. Preferential flow induced by heterogeneity (manifest as permeability variations or discrete fractures) has been suggested as one potential mechanism causing scale/time-dependence. In this paper, we present a quantitative evaluation of the influence of preferential flow on weathering rates using reactive transport modeling. Simulations were performed in discrete fracture networks (DFNs) and correlated random permeability fields (CRPFs), and compared to simulations in homogeneous permeability fields. The simulations reveal spatial variability in the weathering rate, multidimensional distribution of reactions zones, and the formation of rough weathering interfaces andmore » corestones due to preferential flow. In the homogeneous fields and CRPFs, the domain-averaged weathering rate is initially constant as long as the weathering front is contained within the domain, reflecting equilibrium-controlled behavior. The behavior in the CRPFs was influenced by macrodispersion, with more spread-out weathering profiles, an earlier departure from the initial constant rate and longer persistence of weathering. DFN simulations exhibited a sustained time-dependence resulting from the formation of diffusion-controlled weathering fronts in matrix blocks, which is consistent with the shrinking core mechanism. A significant decrease in the domain-averaged weathering rate is evident despite high remaining mineral volume fractions, but the decline does not follow a math formula dependence, characteristic of diffusion, due to network scale effects and advection-controlled behavior near the inflow boundary. Finally, the DFN simulations also reveal relatively constant horizontally averaged weathering rates over a significant depth range, challenging the very notion of a weathering front.« less

Implications of the change in confinement status of a heterogeneous aquifer for scale-dependent dispersion and mass-transfer processes

NASA Astrophysics Data System (ADS)

Pedretti, D.; Molinari, A.; Fallico, C.; Guzzi, S.

2016-10-01

A series of experimental tracer tests were performed to explore the implications of the change in the pressure status of a heterogeneous bimodal aquifer for scale-dependent dispersion and mass-transfer processes. The sandbox was filled with sands and gravel channels and patches to form an alluvial-like bimodal aquifer. We performed multiple injections of a conservative tracer from 26 different locations of the sandbox and interpreted the resulting depth-integrated breakthrough curves (BTCs) at the central pumping well to obtain a scale-dependent distribution of local and field-integrated apparent longitudinal dispersivity (respectively, αLloc and αLapp). We repeated the experiments under confined (CS) and unconfined (UNS) pressure status, keeping the same heterogeneous configuration. Results showed that αLloc(associated with transport through gravel zones) was poorly influenced by the change in aquifer pressure and the presence of channels. Instead, αLapp(i.e. macrodispersion) strongly increased when changing from CS to UNS. In specific, we found αLapp ≈ 0.03 r for the CS and αLapp ≈ 0.15 r for the UNS (being r the distance from the well). Second-to-fourth-order temporal moments showed strong spatial dependence in the UNS and no spatial dependence in the CS. These results seem consistent with a ;vadose-zone-driven; kinetic mass-transfer process occurring in the UNS but not in the CS. The vadose zone enhances vertical flow due to the presence of free surface and large contrasts in hydraulic conductivity triggered by the desaturation of gravel channels nearby the pumping well. The vadose zone enhances vertical mixing between gravel and sands and generates BTC tailing. In the CS vertical mixing is negligible and anomalous transport is not observed.

A Stochastic Model of Space-Time Variability of Mesoscale Rainfall: Statistics of Spatial Averages

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Bell, Thomas L.

2003-01-01

A characteristic feature of rainfall statistics is that they depend on the space and time scales over which rain data are averaged. A previously developed spectral model of rain statistics that is designed to capture this property, predicts power law scaling behavior for the second moment statistics of area-averaged rain rate on the averaging length scale L as L right arrow 0. In the present work a more efficient method of estimating the model parameters is presented, and used to fit the model to the statistics of area-averaged rain rate derived from gridded radar precipitation data from TOGA COARE. Statistical properties of the data and the model predictions are compared over a wide range of averaging scales. An extension of the spectral model scaling relations to describe the dependence of the average fraction of grid boxes within an area containing nonzero rain (the "rainy area fraction") on the grid scale L is also explored.

The interaction of spatial scale and predator-prey functional response

USGS Publications Warehouse

Blaine, T.W.; DeAngelis, D.L.

1997-01-01

Predator-prey models with a prey-dependent functional response have the property that the prey equilibrium value is determined only by predator characteristics. However, in observed natural systems (for instance, snail-periphyton interactions in streams) the equilibrium periphyton biomass has been shown experimentally to be influenced by both snail numbers and levels of available limiting nutrient in the water. Hypothesizing that the observed patchiness in periphyton in streams may be part of the explanation for the departure of behavior of the equilibrium biomasses from predictions of the prey-dependent response of the snail-periphyton system, we developed and analyzed a spatially-explicit model of periphyton in which snails were modeled as individuals in their movement and feeding, and periphyton was modeled as patches or spatial cells. Three different assumptions on snail movement were used: (1) random movement between spatial cells, (2) tracking by snails of local abundances of periphyton, and (3) delayed departure of snails from cells to reduce costs associated with movement. Of these assumptions, only the third strategy, based on an herbivore strategy of staying in one patch until local periphyton biomass concentration falls below a certain threshold amount, produced results in which both periphyton and snail biomass increased with nutrient input. Thus, if data are averaged spatially over the whole system, we expect that a ratio-dependent functional response may be observed if the herbivore behaves according to the third assumption. Both random movement and delayed cell departure had the result that spatial heterogeneity of periphyton increased with nutrient input.

Quantifying drivers of wild pig movement across multiple spatial and temporal scales.

PubMed

Kay, Shannon L; Fischer, Justin W; Monaghan, Andrew J; Beasley, James C; Boughton, Raoul; Campbell, Tyler A; Cooper, Susan M; Ditchkoff, Stephen S; Hartley, Steve B; Kilgo, John C; Wisely, Samantha M; Wyckoff, A Christy; VerCauteren, Kurt C; Pepin, Kim M

2017-01-01

The movement behavior of an animal is determined by extrinsic and intrinsic factors that operate at multiple spatio-temporal scales, yet much of our knowledge of animal movement comes from studies that examine only one or two scales concurrently. Understanding the drivers of animal movement across multiple scales is crucial for understanding the fundamentals of movement ecology, predicting changes in distribution, describing disease dynamics, and identifying efficient methods of wildlife conservation and management. We obtained over 400,000 GPS locations of wild pigs from 13 different studies spanning six states in southern U.S.A., and quantified movement rates and home range size within a single analytical framework. We used a generalized additive mixed model framework to quantify the effects of five broad predictor categories on movement: individual-level attributes, geographic factors, landscape attributes, meteorological conditions, and temporal variables. We examined effects of predictors across three temporal scales: daily, monthly, and using all data during the study period. We considered both local environmental factors such as daily weather data and distance to various resources on the landscape, as well as factors acting at a broader spatial scale such as ecoregion and season. We found meteorological variables (temperature and pressure), landscape features (distance to water sources), a broad-scale geographic factor (ecoregion), and individual-level characteristics (sex-age class), drove wild pig movement across all scales, but both the magnitude and shape of covariate relationships to movement differed across temporal scales. The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc ) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

Scale invariance in natural and artificial collective systems: a review

PubMed Central

Huepe, Cristián

2017-01-01

Self-organized collective coordinated behaviour is an impressive phenomenon, observed in a variety of natural and artificial systems, in which coherent global structures or dynamics emerge from local interactions between individual parts. If the degree of collective integration of a system does not depend on size, its level of robustness and adaptivity is typically increased and we refer to it as scale-invariant. In this review, we first identify three main types of self-organized scale-invariant systems: scale-invariant spatial structures, scale-invariant topologies and scale-invariant dynamics. We then provide examples of scale invariance from different domains in science, describe their origins and main features and discuss potential challenges and approaches for designing and engineering artificial systems with scale-invariant properties. PMID:29093130

Chain conformations dictate multiscale charge transport phenomena in disordered semiconducting polymers

PubMed Central

Noriega, Rodrigo; Salleo, Alberto; Spakowitz, Andrew J.

2013-01-01

Existing models for the electronic properties of conjugated polymers do not capture the spatial arrangement of the disordered macromolecular chains over which charge transport occurs. Here, we present an analytical and computational description in which the morphology of individual polymer chains is dictated by well-known statistical models and the electronic coupling between units is determined using Marcus theory. The multiscale transport of charges in these materials (high mobility at short length scales, low mobility at long length scales) is naturally described with our framework. Additionally, the dependence of mobility with electric field and temperature is explained in terms of conformational variability and spatial correlation. Our model offers a predictive approach to connecting processing conditions with transport behavior. PMID:24062459

Chain conformations dictate multiscale charge transport phenomena in disordered semiconducting polymers.

PubMed

Noriega, Rodrigo; Salleo, Alberto; Spakowitz, Andrew J

2013-10-08

Existing models for the electronic properties of conjugated polymers do not capture the spatial arrangement of the disordered macromolecular chains over which charge transport occurs. Here, we present an analytical and computational description in which the morphology of individual polymer chains is dictated by well-known statistical models and the electronic coupling between units is determined using Marcus theory. The multiscale transport of charges in these materials (high mobility at short length scales, low mobility at long length scales) is naturally described with our framework. Additionally, the dependence of mobility with electric field and temperature is explained in terms of conformational variability and spatial correlation. Our model offers a predictive approach to connecting processing conditions with transport behavior.

Soil moisture observations using L-, C-, and X-band microwave radiometers

NASA Astrophysics Data System (ADS)

Bolten, John Dennis

The purpose of this thesis is to further the current understanding of soil moisture remote sensing under varying conditions using L-, C-, and X-band. Aircraft and satellite instruments are used to investigate the effects of frequency and spatial resolution on soil moisture sensitivity. The specific objectives of the research are to examine multi-scale observed and modeled microwave radiobrightness, evaluate new EOS Aqua Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperature and soil moisture retrievals, and examine future satellite-based technologies for soil moisture sensing. The cycling of Earth's water, energy and carbon is vital to understanding global climate. Over land, these processes are largely dependent on the amount of moisture within the top few centimeters of the soil. However, there are currently no methods available that can accurately characterize Earth's soil moisture layer at the spatial scales or temporal resolutions appropriate for climate modeling. The current work uses ground truth, satellite and aircraft remote sensing data from three large-scale field experiments having different land surface, topographic and climate conditions. A physically-based radiative transfer model is used to simulate the observed aircraft and satellite measurements using spatially and temporally co-located surface parameters. A robust analysis of surface heterogeneity and scaling is possible due to the combination of multiple datasets from a range of microwave frequencies and field conditions. Accurate characterization of spatial and temporal variability of soil moisture during the three field experiments is achieved through sensor calibration and algorithm validation. Comparisons of satellite observations and resampled aircraft observations are made using soil moisture from a Numerical Weather Prediction (NWP) model in order to further demonstrate a soil moisture correlation where point data was unavailable. The influence of vegetation, spatial scaling, and surface heterogeneity on multi-scale soil moisture prediction is presented. This work demonstrates that derived soil moisture using remote sensing provides a better coverage of soil moisture spatial variability than traditional in-situ sensors. Effects of spatial scale were shown to be less significant than frequency on soil moisture sensitivity. Retrievals of soil moisture using the current methods proved inadequate under some conditions; however, this study demonstrates the need for concurrent spaceborne frequencies including L-, C, and X-band.

Spatial occupancy models applied to atlas data show Southern Ground Hornbills strongly depend on protected areas.

PubMed

Broms, Kristin M; Johnson, Devin S; Altwegg, Res; Conquest, Loveday L

2014-03-01

Determining the range of a species and exploring species--habitat associations are central questions in ecology and can be answered by analyzing presence--absence data. Often, both the sampling of sites and the desired area of inference involve neighboring sites; thus, positive spatial autocorrelation between these sites is expected. Using survey data for the Southern Ground Hornbill (Bucorvus leadbeateri) from the Southern African Bird Atlas Project, we compared advantages and disadvantages of three increasingly complex models for species occupancy: an occupancy model that accounted for nondetection but assumed all sites were independent, and two spatial occupancy models that accounted for both nondetection and spatial autocorrelation. We modeled the spatial autocorrelation with an intrinsic conditional autoregressive (ICAR) model and with a restricted spatial regression (RSR) model. Both spatial models can readily be applied to any other gridded, presence--absence data set using a newly introduced R package. The RSR model provided the best inference and was able to capture small-scale variation that the other models did not. It showed that ground hornbills are strongly dependent on protected areas in the north of their South African range, but less so further south. The ICAR models did not capture any spatial autocorrelation in the data, and they took an order, of magnitude longer than the RSR models to run. Thus, the RSR occupancy model appears to be an attractive choice for modeling occurrences at large spatial domains, while accounting for imperfect detection and spatial autocorrelation.

Spatial embedding of structural similarity in the cerebral cortex

PubMed Central

Song, H. Francis; Kennedy, Henry; Wang, Xiao-Jing

2014-01-01

Recent anatomical tracing studies have yielded substantial amounts of data on the areal connectivity underlying distributed processing in cortex, yet the fundamental principles that govern the large-scale organization of cortex remain unknown. Here we show that functional similarity between areas as defined by the pattern of shared inputs or outputs is a key to understanding the areal network of cortex. In particular, we report a systematic relation in the monkey, human, and mouse cortex between the occurrence of connections from one area to another and their similarity distance. This characteristic relation is rooted in the wiring distance dependence of connections in the brain. We introduce a weighted, spatially embedded random network model that robustly gives rise to this structure, as well as many other spatial and topological properties observed in cortex. These include features that were not accounted for in any previous model, such as the wide range of interareal connection weights. Connections in the model emerge from an underlying distribution of spatially embedded axons, thereby integrating the two scales of cortical connectivity—individual axons and interareal pathways—into a common geometric framework. These results provide insights into the origin of large-scale connectivity in cortex and have important implications for theories of cortical organization. PMID:25368200

Atomic-Scale Nuclear Spin Imaging Using Quantum-Assisted Sensors in Diamond

NASA Astrophysics Data System (ADS)

Ajoy, A.; Bissbort, U.; Lukin, M. D.; Walsworth, R. L.; Cappellaro, P.

2015-01-01

Nuclear spin imaging at the atomic level is essential for the understanding of fundamental biological phenomena and for applications such as drug discovery. The advent of novel nanoscale sensors promises to achieve the long-standing goal of single-protein, high spatial-resolution structure determination under ambient conditions. In particular, quantum sensors based on the spin-dependent photoluminescence of nitrogen-vacancy (NV) centers in diamond have recently been used to detect nanoscale ensembles of external nuclear spins. While NV sensitivity is approaching single-spin levels, extracting relevant information from a very complex structure is a further challenge since it requires not only the ability to sense the magnetic field of an isolated nuclear spin but also to achieve atomic-scale spatial resolution. Here, we propose a method that, by exploiting the coupling of the NV center to an intrinsic quantum memory associated with the nitrogen nuclear spin, can reach a tenfold improvement in spatial resolution, down to atomic scales. The spatial resolution enhancement is achieved through coherent control of the sensor spin, which creates a dynamic frequency filter selecting only a few nuclear spins at a time. We propose and analyze a protocol that would allow not only sensing individual spins in a complex biomolecule, but also unraveling couplings among them, thus elucidating local characteristics of the molecule structure.

Scaling identity connects human mobility and social interactions.

PubMed

Deville, Pierre; Song, Chaoming; Eagle, Nathan; Blondel, Vincent D; Barabási, Albert-László; Wang, Dashun

2016-06-28

Massive datasets that capture human movements and social interactions have catalyzed rapid advances in our quantitative understanding of human behavior during the past years. One important aspect affecting both areas is the critical role space plays. Indeed, growing evidence suggests both our movements and communication patterns are associated with spatial costs that follow reproducible scaling laws, each characterized by its specific critical exponents. Although human mobility and social networks develop concomitantly as two prolific yet largely separated fields, we lack any known relationships between the critical exponents explored by them, despite the fact that they often study the same datasets. Here, by exploiting three different mobile phone datasets that capture simultaneously these two aspects, we discovered a new scaling relationship, mediated by a universal flux distribution, which links the critical exponents characterizing the spatial dependencies in human mobility and social networks. Therefore, the widely studied scaling laws uncovered in these two areas are not independent but connected through a deeper underlying reality.

Scale-dependent spatial variability in peatland lead pollution in the southern Pennines, UK.

PubMed

Rothwell, James J; Evans, Martin G; Lindsay, John B; Allott, Timothy E H

2007-01-01

Increasingly, within-site and regional comparisons of peatland lead pollution have been undertaken using the inventory approach. The peatlands of the Peak District, southern Pennines, UK, have received significant atmospheric inputs of lead over the last few hundred years. A multi-core study at three peatland sites in the Peak District demonstrates significant within-site spatial variability in industrial lead pollution. Stochastic simulations reveal that 15 peat cores are required to calculate reliable lead inventories at the within-site and within-region scale for this highly polluted area of the southern Pennines. Within-site variability in lead pollution is dominant at the within-region scale. The study demonstrates that significant errors may be associated with peatland lead inventories at sites where only a single peat core has been used to calculate an inventory. Meaningful comparisons of lead inventories at the regional or global scale can only be made if the within-site variability of lead pollution has been quantified reliably.

Scaling identity connects human mobility and social interactions

PubMed Central

Deville, Pierre; Song, Chaoming; Eagle, Nathan; Blondel, Vincent D.; Barabási, Albert-László; Wang, Dashun

2016-01-01

Massive datasets that capture human movements and social interactions have catalyzed rapid advances in our quantitative understanding of human behavior during the past years. One important aspect affecting both areas is the critical role space plays. Indeed, growing evidence suggests both our movements and communication patterns are associated with spatial costs that follow reproducible scaling laws, each characterized by its specific critical exponents. Although human mobility and social networks develop concomitantly as two prolific yet largely separated fields, we lack any known relationships between the critical exponents explored by them, despite the fact that they often study the same datasets. Here, by exploiting three different mobile phone datasets that capture simultaneously these two aspects, we discovered a new scaling relationship, mediated by a universal flux distribution, which links the critical exponents characterizing the spatial dependencies in human mobility and social networks. Therefore, the widely studied scaling laws uncovered in these two areas are not independent but connected through a deeper underlying reality. PMID:27274050

Spatial correlation analysis of urban traffic state under a perspective of community detection

NASA Astrophysics Data System (ADS)

Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan

2018-05-01

Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.

Quasar Astrophysics with the Space Interferometry Mission

NASA Technical Reports Server (NTRS)

Unwin, Stephen; Wehrle, Ann; Meier, David; Jones, Dayton; Piner, Glenn

2007-01-01

Optical astrometry of quasars and active galaxies can provide key information on the spatial distribution and variability of emission in compact nuclei. The Space Interferometry Mission (SIM PlanetQuest) will have the sensitivity to measure a significant number of quasar positions at the microarcsecond level. SIM will be very sensitive to astrometric shifts for objects as faint as V = 19. A variety of AGN phenomena are expected to be visible to SIM on these scales, including time and spectral dependence in position offsets between accretion disk and jet emission. These represent unique data on the spatial distribution and time dependence of quasar emission. It will also probe the use of quasar nuclei as fundamental astrometric references. Comparisons between the time-dependent optical photocenter position and VLBI radio images will provide further insight into the jet emission mechanism. Observations will be tailored to each specific target and science question. SIM will be able to distinguish spatially between jet and accretion disk emission; and it can observe the cores of galaxies potentially harboring binary supermassive black holes resulting from mergers.

Scale criticality in estimating ecosystem carbon dynamics

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang

2014-01-01

Scaling is central to ecology and Earth system sciences. However, the importance of scale (i.e. resolution and extent) for understanding carbon dynamics across scales is poorly understood and quantified. We simulated carbon dynamics under a wide range of combinations of resolution (nine spatial resolutions of 250 m, 500 m, 1 km, 2 km, 5 km, 10 km, 20 km, 50 km, and 100 km) and extent (57 geospatial extents ranging from 108 to 1 247 034 km2) in the southeastern United States to explore the existence of scale dependence of the simulated regional carbon balance. Results clearly show the existence of a critical threshold resolution for estimating carbon sequestration within a given extent and an error limit. Furthermore, an invariant power law scaling relationship was found between the critical resolution and the spatial extent as the critical resolution is proportional to An (n is a constant, and A is the extent). Scale criticality and the power law relationship might be driven by the power law probability distributions of land surface and ecological quantities including disturbances at landscape to regional scales. The current overwhelming practices without considering scale criticality might have largely contributed to difficulties in balancing carbon budgets at regional and global scales.

A map overlay error model based on boundary geometry

USGS Publications Warehouse

Gaeuman, D.; Symanzik, J.; Schmidt, J.C.

2005-01-01

An error model for quantifying the magnitudes and variability of errors generated in the areas of polygons during spatial overlay of vector geographic information system layers is presented. Numerical simulation of polygon boundary displacements was used to propagate coordinate errors to spatial overlays. The model departs from most previous error models in that it incorporates spatial dependence of coordinate errors at the scale of the boundary segment. It can be readily adapted to match the scale of error-boundary interactions responsible for error generation on a given overlay. The area of error generated by overlay depends on the sinuosity of polygon boundaries, as well as the magnitude of the coordinate errors on the input layers. Asymmetry in boundary shape has relatively little effect on error generation. Overlay errors are affected by real differences in boundary positions on the input layers, as well as errors in the boundary positions. Real differences between input layers tend to compensate for much of the error generated by coordinate errors. Thus, the area of change measured on an overlay layer produced by the XOR overlay operation will be more accurate if the area of real change depicted on the overlay is large. The model presented here considers these interactions, making it especially useful for estimating errors studies of landscape change over time. ?? 2005 The Ohio State University.

Spatial patterns and broad-scale weather cues of beech mast seeding in Europe.

PubMed

Vacchiano, Giorgio; Hacket-Pain, Andrew; Turco, Marco; Motta, Renzo; Maringer, Janet; Conedera, Marco; Drobyshev, Igor; Ascoli, Davide

2017-07-01

Mast seeding is a crucial population process in many tree species, but its spatio-temporal patterns and drivers at the continental scale remain unknown . Using a large dataset (8000 masting observations across Europe for years 1950-2014) we analysed the spatial pattern of masting across the entire geographical range of European beech, how it is influenced by precipitation, temperature and drought, and the temporal and spatial stability of masting-weather correlations. Beech masting exhibited a general distance-dependent synchronicity and a pattern structured in three broad geographical groups consistent with continental climate regimes. Spearman's correlations and logistic regression revealed a general pattern of beech masting correlating negatively with temperature in the summer 2 yr before masting, and positively with summer temperature 1 yr before masting (i.e. 2T model). The temperature difference between the two previous summers (DeltaT model) was also a good predictor. Moving correlation analysis applied to the longest eight chronologies (74-114 yr) revealed stable correlations between temperature and masting, confirming consistency in weather cues across space and time. These results confirm widespread dependency of masting on temperature and lend robustness to the attempts to reconstruct and predict mast years using temperature data. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Characterizing local biological hotspots in the Gulf of Maine using remote sensing data

NASA Astrophysics Data System (ADS)

Ribera, Marta M.

Researchers increasingly advocate the use of ecosystem-based management (EBM) for managing complex marine ecosystems. This approach requires managers to focus on processes and cross-scale interactions, rather than individual components. However, they often lack appropriate tools and data sources to pursue this change in management approach. One method that has been proposed to understand the ecological complexity inherent in marine ecosystems is the study of biological hotspots. Biological hotspots are locations where organisms from different trophic levels aggregate to feed on abundant supplies, and they are considered a first step toward understanding the processes driving spatial and temporal heterogeneity in marine systems. Biological hotspots are supported by phytoplankton aggregations, which are characterized by high spatial and temporal variability. As a result, methods developed to locate biological hotspots in relatively stable terrestrial systems are not well suited for more dynamic marine ecosystems. The main objective of this thesis is thus to identify and characterize local-scale biological hotspots in the western side of the Gulf of Maine. The first chapter describes a new methodological framework with the steps needed to locate these types of hotspots in marine ecosystems using remote sensing datasets. Then, in the second chapter these hotspots are characterized using a novel metric that uses time series information and spatial statistics to account for both the temporal variability and spatial structure of these marine aggregations. This metric redefines biological hotspots as areas with a high probability of exhibiting positive anomalies of productivity compared to the expected regional seasonal pattern. Finally, the third chapter compares the resulting biological hotspots to fishery-dependent abundance indices of surface and benthic predators to determine the effect of the location and magnitude of phytoplankton aggregations on the rest of the ecosystem. Analyses indicate that the spatial scale and magnitude of biological hotspots in the Gulf of Maine depend on the location and time of the year. Results also show that these hotspots change over time in response to both short-term oceanographic processes and long-term climatic cycles. Finally, the new metric presented here facilitates the spatial comparison between different trophic levels, thus allowing interdisciplinary ecosystem-wide studies.

Statistical characterization of Earth’s heterogeneities from seismic scattering

NASA Astrophysics Data System (ADS)

Zheng, Y.; Wu, R.

2009-12-01

The distortion of a teleseismic wavefront carries information about the heterogeneities through which the wave propagates and it is manifestited as logarithmic amplitude (logA) and phase fluctuations of the direct P wave recorded by a seismic network. By cross correlating the fluctuations (e.g., logA-logA or phase-phase), we obtain coherence functions, which depend on spatial lags between stations and incident angles between the incident waves. We have mathematically related the depth-dependent heterogeneity spectrum to the observable coherence functions using seismic scattering theory. We will show that our method has sharp depth resolution. Using the HiNet seismic network data in Japan, we have inverted power spectra for two depth ranges, ~0-120km and below ~120km depth. The coherence functions formed by different groups of stations or by different groups of earthquakes at different back azimuths are similar. This demonstrates that the method is statistically stable and the inhomogeneities are statistically stationary. In both depth intervals, the trend of the spectral amplitude decays from large scale to small scale in a power-law fashion with exceptions at ~50km for the logA data. Due to the spatial spacing of the seismometers, only information from length scale 15km to 200km is inverted. However our scattering method provides new information on small to intermediate scales that are comparable to scales of the recycled materials and thus is complimentary to the global seismic tomography which reveals mainly large-scale heterogeneities on the order of ~1000km. The small-scale heterogeneities revealed here are not likely of pure thermal origin. Therefore, the length scale and strength of heterogeneities as a function of depth may provide important constraints in mechanical mixing of various components in the mantle convection.

Spatial patterns of hydro-social metrics in the Northeastern United States from the Colonial Era through the Industrial Revolution (1600-1920)

NASA Astrophysics Data System (ADS)

Witherell, B. B.; Bain, D. J.; Salant, N.; Aloysius, N. R.

2009-12-01

Humans impact the hydrologic cycle at local, regional and global scales. Understanding how spatial patterns of human water use and hydrologic impact have changed over time is important to future water management in an era of increasing water constraints and globalization of high water-use resources. This study investigates spatial dependence and spatial patterns of hydro-social metrics for the Northeastern United States from 1600 to 1920 through the use of spatial statistical techniques. Several relevant hydro-social metrics, including water residence time, surface water storage (natural and human engineered) and per capita water availability, are analyzed. This study covers a region and period of time that saw significant population growth, landscape change, and industrial growth. These changes had important impacts on water availability. Although some changes such as the elimination of beavers, and the resulting loss of beaver ponds on low-order streams, are felt at a regional scale, preliminary analysis indicates that humans responded to water constraints by acting locally (e.g., mill ponds for water power and water supply reservoirs for public health). This 320-year historical analysis of spatial patterns of hydro-social metrics provides unique insight into long-term changes in coupled human-water systems.

Cities, traffic, and CO2: A multidecadal assessment of trends, drivers, and scaling relationships

PubMed Central

Gately, Conor K.; Hutyra, Lucy R.; Sue Wing, Ian

2015-01-01

Emissions of CO2 from road vehicles were 1.57 billion metric tons in 2012, accounting for 28% of US fossil fuel CO2 emissions, but the spatial distributions of these emissions are highly uncertain. We develop a new emissions inventory, the Database of Road Transportation Emissions (DARTE), which estimates CO2 emitted by US road transport at a resolution of 1 km annually for 1980–2012. DARTE reveals that urban areas are responsible for 80% of on-road emissions growth since 1980 and for 63% of total 2012 emissions. We observe nonlinearities between CO2 emissions and population density at broad spatial/temporal scales, with total on-road CO2 increasing nonlinearly with population density, rapidly up to 1,650 persons per square kilometer and slowly thereafter. Per capita emissions decline as density rises, but at markedly varying rates depending on existing densities. We make use of DARTE’s bottom-up construction to highlight the biases associated with the common practice of using population as a linear proxy for disaggregating national- or state-scale emissions. Comparing DARTE with existing downscaled inventories, we find biases of 100% or more in the spatial distribution of urban and rural emissions, largely driven by mismatches between inventory downscaling proxies and the actual spatial patterns of vehicle activity at urban scales. Given cities’ dual importance as sources of CO2 and an emerging nexus of climate mitigation initiatives, high-resolution estimates such as DARTE are critical both for accurately quantifying surface carbon fluxes and for verifying the effectiveness of emissions mitigation efforts at urban scales. PMID:25847992

Spatial dynamics of the 1918 influenza pandemic in England, Wales and the United States.

PubMed

Eggo, Rosalind M; Cauchemez, Simon; Ferguson, Neil M

2011-02-06

There is still limited understanding of key determinants of spatial spread of influenza. The 1918 pandemic provides an opportunity to elucidate spatial determinants of spread on a large scale. To better characterize the spread of the 1918 major wave, we fitted a range of city-to-city transmission models to mortality data collected for 246 population centres in England and Wales and 47 cities in the US. Using a gravity model for city-to-city contacts, we explored the effect of population size and distance on the spread of disease and tested assumptions regarding density dependence in connectivity between cities. We employed Bayesian Markov Chain Monte Carlo methods to estimate parameters of the model for population, infectivity, distance and density dependence. We inferred the most likely transmission trees for both countries. For England and Wales, a model that estimated the degree of density dependence in connectivity between cities was preferable by deviance information criterion comparison. Early in the major wave, long distance infective interactions predominated, with local infection events more likely as the epidemic became widespread. For the US, with fewer more widely dispersed cities, statistical power was lacking to estimate population size dependence or the degree of density dependence, with the preferred model depending on distance only. We find that parameters estimated from the England and Wales dataset can be applied to the US data with no likelihood penalty.

Spatial dynamics of the 1918 influenza pandemic in England, Wales and the United States

PubMed Central

Eggo, Rosalind M.; Cauchemez, Simon; Ferguson, Neil M.

2011-01-01

There is still limited understanding of key determinants of spatial spread of influenza. The 1918 pandemic provides an opportunity to elucidate spatial determinants of spread on a large scale. To better characterize the spread of the 1918 major wave, we fitted a range of city-to-city transmission models to mortality data collected for 246 population centres in England and Wales and 47 cities in the US. Using a gravity model for city-to-city contacts, we explored the effect of population size and distance on the spread of disease and tested assumptions regarding density dependence in connectivity between cities. We employed Bayesian Markov Chain Monte Carlo methods to estimate parameters of the model for population, infectivity, distance and density dependence. We inferred the most likely transmission trees for both countries. For England and Wales, a model that estimated the degree of density dependence in connectivity between cities was preferable by deviance information criterion comparison. Early in the major wave, long distance infective interactions predominated, with local infection events more likely as the epidemic became widespread. For the US, with fewer more widely dispersed cities, statistical power was lacking to estimate population size dependence or the degree of density dependence, with the preferred model depending on distance only. We find that parameters estimated from the England and Wales dataset can be applied to the US data with no likelihood penalty. PMID:20573630

Spatial variation in disease resistance: from molecules to metapopulations

PubMed Central

Laine, Anna-Liisa; Burdon, Jeremy J.; Dodds, Peter N.; Thrall, Peter H.

2010-01-01

Summary Variation in disease resistance is a widespread phenomenon in wild plant-pathogen associations. Here, we review current literature on natural plant-pathogen associations to determine how diversity in disease resistance is distributed at different hierarchical levels – within host individuals, within host populations, among host populations at the metapopulation scale and at larger regional scales. We find diversity in resistance across all spatial scales examined. Furthermore, variability seems to be the best counter-defence of plants against their rapidly evolving pathogens. We find that higher diversity of resistance phenotypes also results in higher levels of resistance at the population level. Overall, we find that wild plant populations are more likely to be susceptible than resistant to their pathogens. However, the degree of resistance differs strikingly depending on the origin of the pathogen strains used in experimental inoculation studies. Plant populations are on average 16% more resistant to allopatric pathogen strains than they are to strains that occur within the same population (48 % vs. 32 % respectively). Pathogen dispersal mode affects levels of resistance in natural plant populations with lowest levels detected for hosts of airborne pathogens and highest for waterborne pathogens. Detailed analysis of two model systems, Linum marginale infected by Melampsora lini, and Plantago lanceolata infected by Podosphaera plantaginis, show that the amount of variation in disease resistance declines towards higher spatial scales as we move from individual hosts to metapopulations, but evaluation of multiple spatial scales is needed to fully capture the structure of disease resistance. Synthesis: Variation in disease resistance is ubiquitous in wild plant-pathogen associations. While the debate over whether the resistance structure of plant populations is determined by pathogen-imposed selection versus non-adaptive processes remains unresolved, we do report examples of pathogen-imposed selection on host resistance. Here we highlight the importance of measuring resistance across multiple spatial scales, and of using sympatric strains when looking for signs of coevolution in wild plant-pathogen interactions. PMID:21243068

Imaging high-speed friction at the nanometer scale

PubMed Central

Thorén, Per-Anders; de Wijn, Astrid S.; Borgani, Riccardo; Forchheimer, Daniel; Haviland, David B.

2016-01-01

Friction is a complicated phenomenon involving nonlinear dynamics at different length and time scales. Understanding its microscopic origin requires methods for measuring force on nanometer-scale asperities sliding at velocities reaching centimetres per second. Despite enormous advances in experimental technique, this combination of small length scale and high velocity remain elusive. We present a technique for rapidly measuring the frictional forces on a single asperity over a velocity range from zero to several centimetres per second. At each image pixel we obtain the velocity dependence of both conservative and dissipative forces, revealing the transition from stick-slip to smooth sliding friction. We explain measurements on graphite using a modified Prandtl–Tomlinson model, including the damped elastic deformation of the asperity. With its improved force sensitivity and small sliding amplitude, our method enables rapid and detailed surface mapping of the velocity dependence of frictional forces with less than 10 nm spatial resolution. PMID:27958267

Spatial-temporal variations of seismic noise and their relation to wind, rivers, and basins in central Alaska

NASA Astrophysics Data System (ADS)

Smith, K.; Tape, C.; Bruton, C. P.; West, M. E.

2016-12-01

Continuous seismic recordings-or ambient noise-provide means for time-dependent monitoring of site conditions. Frequency-domain amplitude spectra of seismic recordings can be used to characterize time-dependent variations as a function of period (or frequency). Spatial variations can be characterized by using a set of stations across a large region. We analyze time-dependent ambient noise spectra from stations across central Alaska with three purposes. First, we are interested in monitoring the station performance and quality of a new array (FLATS) of 13 posthole seismometers near the Tanana River in Minto Flats. Second, we want to understand time-dependent threshold levels for earthquake detection: when noise is high, earthquake detections are low. Third, we are interested in identifying the effects of nature and Earth structure on seismic stations at different spatial-temporal scales. Our results show that seismic stations are sensitive to variations in wind speed and river flow. Correlations between wind speed and long-period (>10 seconds) seismic noise variations are probably due to tilt effects that have been previously documented. We identify a seismic signal at 10 Hz that is present only on stations close (<100 m) to the main channel of the Tanana river. The 10-Hz signal is strongly correlated with river gage height during summer and weakly correlated during the winter, when the river surface is covered in 1 m of ice. Spatial correlations among stations reveal large variations at shorter time scales (days); these could be due to weather anomalies. The amplitude of seismic noise at periods 2-10 s is strongly influenced by the thickness of sediment, which ranges from 0 m at bedrock sites to 6000 m at sites in the deepest part of Nenana basin. Our analysis allows us to better monitor the performance of temporary and permanent seismic stations, and to understand the physical causes of time-dependent noise variations in Alaska. Our findings show that seismic stations near rivers can potentially be used to monitor the flow of the river during summer and during ice-covered winter, raising the possibility for monitoring river ice break-up during April.

Coarsening of stripe patterns: variations with quench depth and scaling.

PubMed

Tripathi, Ashwani K; Kumar, Deepak

2015-02-01

The coarsening of stripe patterns when the system is evolved from random initial states is studied by varying the quench depth ε, which is a measure of distance from the transition point of the stripe phase. The dynamics of the growth of stripe order, which is characterized by two length scales, depends on the quench depth. The growth exponents of the two length scales vary continuously with ε. The decay exponents for free energy, stripe curvature, and densities of defects like grain boundaries and dislocations also show similar variation. This implies a breakdown of the standard picture of nonequilibrium dynamical scaling. In order to understand the variations with ε we propose an additional scaling with a length scale dependent on ε. The main contribution to this length scale comes from the "pinning potential," which is unique to systems where the order parameter is spatially periodic. The periodic order parameter gives rise to an ε-dependent potential, which can pin defects like grain boundaries, dislocations, etc. This additional scaling provides a compact description of variations of growth exponents with quench depth in terms of just one exponent for each of the length scales. The relaxation of free energy, stripe curvature, and the defect densities have also been related to these length scales. The study is done at zero temperature using Swift-Hohenberg equation in two dimensions.

Temporal consistency of spatial pattern in growth of the mussel, Mytilus edulis: Implications for predictive modelling

NASA Astrophysics Data System (ADS)

Bergström, Per; Lindegarth, Susanne; Lindegarth, Mats

2013-10-01

Human pressures on coastal seas are increasing and methods for sustainable management, including spatial planning and mitigative actions, are therefore needed. In coastal areas worldwide, the development of mussel farming as an economically and ecologically sustainable industry requires geographic information on the growth and potential production capacity. In practice this means that coherent maps of temporally stable spatial patterns of growth need to be available in the planning process and that maps need to be based on mechanistic or empirical models. Therefore, as a first step towards development of models of growth, we assessed empirically the fundamental requirement that there are temporally consistent spatial patterns of growth in the blue mussel, Mytilus edulis. Using a pilot study we designed and dimensioned a transplant experiment, where the spatial consistency in the growth of mussels was evaluated at two resolutions. We found strong temporal and scale-dependent spatial variability in growth but patterns suggested that spatial patterns were uncoupled between growth of shell and that of soft tissue. Spatial patterns of shell growth were complex and largely inconsistent among years. Importantly, however, the growth of soft tissue was qualitatively consistent among years at the scale of km. The results suggest that processes affecting the whole coastal area cause substantial differences in growth of soft tissue among years but that factors varying at the scale of km create strong and persistent spatial patterns of growth, with a potential doubling of productivity by identifying the most suitable locations. We conclude that the observed spatial consistency provides a basis for further development of predictive modelling and mapping of soft tissue growth in these coastal areas. Potential causes of observed patterns, consequences for mussel-farming as a tool for mitigating eutrophication, aspects of precision of modelling and sampling of mussel growth as well as ecological functions in general are discussed.

Validation of spatial variability in downscaling results from the VALUE perfect predictor experiment

NASA Astrophysics Data System (ADS)

Widmann, Martin; Bedia, Joaquin; Gutiérrez, Jose Manuel; Maraun, Douglas; Huth, Radan; Fischer, Andreas; Keller, Denise; Hertig, Elke; Vrac, Mathieu; Wibig, Joanna; Pagé, Christian; Cardoso, Rita M.; Soares, Pedro MM; Bosshard, Thomas; Casado, Maria Jesus; Ramos, Petra

2016-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. Within VALUE a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods has been developed. In the first validation experiment the downscaling methods are validated in a setup with perfect predictors taken from the ERA-interim reanalysis for the period 1997 - 2008. This allows to investigate the isolated skill of downscaling methods without further error contributions from the large-scale predictors. One aspect of the validation is the representation of spatial variability. As part of the VALUE validation we have compared various properties of the spatial variability of downscaled daily temperature and precipitation with the corresponding properties in observations. We have used two test validation datasets, one European-wide set of 86 stations, and one higher-density network of 50 stations in Germany. Here we present results based on three approaches, namely the analysis of i.) correlation matrices, ii.) pairwise joint threshold exceedances, and iii.) regions of similar variability. We summarise the information contained in correlation matrices by calculating the dependence of the correlations on distance and deriving decorrelation lengths, as well as by determining the independent degrees of freedom. Probabilities for joint threshold exceedances and (where appropriate) non-exceedances are calculated for various user-relevant thresholds related for instance to extreme precipitation or frost and heat days. The dependence of these probabilities on distance is again characterised by calculating typical length scales that separate dependent from independent exceedances. Regionalisation is based on rotated Principal Component Analysis. The results indicate which downscaling methods are preferable if the dependency of variability at different locations is relevant for the user.

Soil maps as data input for soil erosion models: errors related to map scales

NASA Astrophysics Data System (ADS)

van Dijk, Paul; Sauter, Joëlle; Hofstetter, Elodie

2010-05-01

Soil erosion rates depend in many ways on soil and soil surface characteristics which vary in space and in time. To account for spatial variations of soil features, most distributed soil erosion models require data input derived from soil maps. Ideally, the level of spatial detail contained in the applied soil map should correspond to the objective of the modelling study. However, often the model user has only one soil map available which is then applied without questioning its suitability. The present study seeks to determine in how far soil map scale can be a source of error in erosion model output. The study was conducted on two different spatial scales, with for each of them a convenient soil erosion model: a) the catchment scale using the physically-based Limbourg Soil Erosion Model (LISEM), and b) the regional scale using the decision-tree expert model MESALES. The suitability of the applied soil map was evaluated with respect to an imaginary though realistic study objective for both models: the definition of erosion control measures at strategic locations at the catchment scale; the identification of target areas for the definition of control measures strategies at the regional scale. Two catchments were selected to test the sensitivity of LISEM to the spatial detail contained in soil maps: one catchment with relatively little contrast in soil texture, dominated by loess-derived soil (south of the Alsace), and one catchment with strongly contrasted soils at the limit between the Alsatian piedmont and the loess-covered hills of the Kochersberg. LISEM was run for both catchments using different soil maps ranging in scale from 1/25 000 to 1/100 000 to derive soil related input parameters. The comparison of the output differences was used to quantify the map scale impact on the quality of the model output. The sensitivity of MESALES was tested on the Haut-Rhin county for which two soil maps are available for comparison: 1/50 000 and 1/100 000. The order of resulting target areas (communes) was compared to evaluate the error induced by using the coarser soil data at 1/100 000. Results shows that both models are sensitive to the soil map scale used for model data input. A low sensitivity was found for the catchment with relatively homogeneous soil textures and the use of 1/100 000 soil maps seems allowed. The results for the catchment with strong soil texture variations showed significant differences depending on soil map scale on 75% of the catchment area. Here, the use of 1/100 000 soil map will indeed lead to wrong erosion diagnostics and will hamper the definition of a sound erosion control strategy. The regional scale model MESALES proved to be very sensitive to soil information. The two soil related model parameters (crusting sensitivity, and soil erodibility) reacted very often in the same direction therewith amplifying the change in the final erosion hazard class. The 1/100 000 soil map yielded different results on 40% of the sloping area compared to the 1/50 000 map. Significant differences in the order of target areas were found as well. The present study shows that the degree of sensitivity of the model output to soil map scale is rather variable and depends partly on the spatial variability of soil texture within the study area. Soil (textural) diversity needs to be accounted for to assure a fruitful use of soil erosion models. In some situations this might imply that additional soil data need to be collected in the field to refine the available soil map.

A new spatially scanning 2.7 µm laser hygrometer and new small-scale wind tunnel for direct analysis of the H2O boundary layer structure at single plant leaves

NASA Astrophysics Data System (ADS)

Wunderle, K.; Rascher, U.; Pieruschka, R.; Schurr, U.; Ebert, V.

2015-01-01

A new spatially scanning TDLAS in situ hygrometer based on a 2.7-µm DFB diode laser was constructed and used to analyse the water vapour concentration boundary layer structure at the surface of a single plant leaf. Using an absorption length of only 5.4 cm, the TDLAS hygrometer permits a H2O vapour concentration resolution of 31 ppmv. This corresponds to a normalized precision of 1.7 ppm m. In order to preserve and control the H2O boundary layer on an individual leaf and to study the boundary layer dependence on the wind speed to which the leaf might be exposed in nature, we also constructed a new, application specific, small-scale, wind tunnel for individual plant leaves. The rectangular, closed-loop tunnel has overall dimensions of 1.2 × 0.6 m and a measurement chamber dimension of 40 × 54 mm (H × W). It allows to generate a laminar flow with a precisely controlled wind speed at the plant leaf surface. Combining honeycombs and a miniaturized compression orifice, we could generate and control stable wind speeds from 0.1 to 0.9 m/s, and a highly laminar and homogeneous flow with an excellent relative spatial homogeneity of 0.969 ± 0.03. Combining the spectrometer and the wind tunnel, we analysed (for the first time) non-invasively the wind speed-dependent vertical structure of the H2O vapour distribution within the boundary layer of a single plant leaf. Using our time-lag-free data acquisition procedure for phase locked signal averaging, we achieved a temporal resolution of 0.2 s for an individual spatial point, while a complete vertical spatial scan at a spatial resolution of 0.18 mm took 77 s. The boundary layer thickness was found to decrease from 6.7 to 3.6 mm at increasing wind speeds of 0.1-0.9 m/s. According to our knowledge, this is the first experimental quantification of wind speed-dependent H2O vapour boundary layer concentration profiles of single plant leaves.

What if the Hubbard Brook weirs had been built somewhere else? Spatial uncertainty in the application of catchment budgets

NASA Astrophysics Data System (ADS)

Bailey, S. W.

2016-12-01

Nine catchments are gaged at Hubbard Brook Experimental Forest, Woodstock, NH, USA, with weirs installed on adjacent first-order streams. These catchments have been used as unit ecosystems for analysis of chemical budgets, including evaluation of long term trends and response to disturbance. This study examines uncertainty in the representativeness of these budgets to other nearby catchments, or as representatives of the broader northern hardwood ecosystem, depending on choice of location of the stream gaging station. Within forested northern hardwood catchments across the Hubbard Brook region, there is relatively little spatial variation in amount or chemistry of precipitation inputs or in amount of streamwater outputs. For example, runoff per unit catchment area varies by less than 10% at gaging stations on first to sixth order streams. In contrast, concentrations of major solutes vary by an order of magnitude or more across stream sampling sites, with a similar range in concentrations seen within individual first order catchments as seen across the third order Hubbard Brook valley or across the White Mountain region. These spatial variations in stream chemistry are temporally persistent across a range of flow conditions. Thus first order catchment budgets vary greatly depending on very local variations in stream chemistry driven by choice of the site to develop a stream gage. For example, carbon output in dissolved organic matter varies by a factor of five depending on where the catchment output is defined at Watershed 3. I hypothesize that catchment outputs from first order streams are driven by spatially variable chemistry of shallow groundwater, reflecting local variations in the distribution of soils and vegetation. In contrast, spatial variability in stream chemistry decreases with stream order, hypothesized to reflect deeper groundwater inputs on larger streams, which are more regionally uniform. Thus, choice of a gaging site and definition of an ecosystem as a unit of analysis at a larger scale, such as the Hubbard Brook valley, would have less impact on calculated budgets than at the headwater scale. Monitoring of a larger catchment is more likely to be representative of other similar sized catchments. However, particular research questions may be better studied at the smaller headwater scale.

A random spatial network model based on elementary postulates

USGS Publications Warehouse

Karlinger, Michael R.; Troutman, Brent M.

1989-01-01

A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.

Holographic grating relaxation technique for soft matter science

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

Lesnichii, Vasilii, E-mail: vasilii.lesnichii@physchem.uni-freiburg.de; ITMO University, Kronverksky prospekt 49, Saint-Petersburg 197101; Kiessling, Andy

2016-06-17

The holographic grating relaxation technique also known as forced Rayleigh scattering consists basically in writing a holographic grating in the specimen of interest and monitoring its diffraction efficiency as a function of time, from which valuable information on mass or heat transfer and photoinduced transformations can be extracted. In a more detailed view, the shape of the relaxation curve and the relaxation rate as a function of the grating period were found to be affected by the architecture of diffusing species (molecular probes) that constitute the grating, as well as that of the environment they diffuse in, thus making itmore » possible to access and study spatial heterogeneity of materials and different modes of e.g., polymer motion. Minimum displacements and spatial domains approachable by the technique are in nanometer range, well below spatial periods of holographic gratings. In the present paper, several cases of holographic relaxation in heterogeneous media and complex motions are exemplified. Nano- to micro-structures or inhomogeneities comparable in spatial scale with holographic gratings manifest themselves in relaxation experiments via non-exponential decay (stepwise or stretched), spatial-period-dependent apparent diffusion coefficient, or unusual dependence of diffusion coefficient on molecular volume of diffusing probes.« less

Detecting changes resulting from human pressure in a naturally quick-changing and heterogeneous environment: Spatial and temporal scales of variability in coastal lagoons

NASA Astrophysics Data System (ADS)

Pérez-Ruzafa, A.; Marcos, C.; Pérez-Ruzafa, I. M.; Barcala, E.; Hegazi, M. I.; Quispe, J.

2007-10-01

To detect changes in ecosystems due to human impact, experimental designs must include replicates at the appropriate scale to avoid pseudoreplication. Although coastal lagoons, with their highly variable environmental factors and biological assemblages, are relatively well-studied systems, very little is known about their natural scales of variation. In this study, we investigate the spatio-temporal scales of variability in the Mar Menor coastal lagoon (SE Spain) using structured hierarchical sampling designs, mixed and permutational multi-variate analyses of variance, and ordination multi-variate analyses applied to hydrographical parameters, nutrients, chlorophyll a and ichthyoplankton in the water column, and to macrophyte and fish benthic assemblages. Lagoon processes in the Mar Menor show heterogeneous patterns at different temporal and spatial scales. The water column characteristics (including nutrient concentration) showed small-scale spatio-temporal variability, from 10 0 to 10 1 km and from fortnightly to seasonally. Biological features (chlorophyll a concentration and ichthyoplankton assemblage descriptors) showed monthly changes and spatial patterns at the scale of 10 0 (chlorophyll a) - 10 1 km (ichthyoplankton). Benthic assemblages (macrophytes and fishes) showed significant differences between types of substrates in the same locality and between localities, according to horizontal gradients related with confinement in the lagoon, at the scale of 10 0-10 1 km. The vertical zonation of macrophyte assemblages (at scales of 10 1-10 2 cm) overlaps changes in substrata and horizontal gradients. Seasonal patterns in vegetation biomass were not significant, but the significant interaction between Locality and Season indicated that the seasons of maximum and minimum biomass depend on local environmental conditions. Benthic fish assemblages showed no significant patterns at the monthly scale but did show seasonal patterns.

Spatial and Temporal Scaling of Thermal Infrared Remote Sensing Data

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Goel, Narendra S.

1995-01-01

Although remote sensing has a central role to play in the acquisition of synoptic data obtained at multiple spatial and temporal scales to facilitate our understanding of local and regional processes as they influence the global climate, the use of thermal infrared (TIR) remote sensing data in this capacity has received only minimal attention. This results from some fundamental challenges that are associated with employing TIR data collected at different space and time scales, either with the same or different sensing systems, and also from other problems that arise in applying a multiple scaled approach to the measurement of surface temperatures. In this paper, we describe some of the more important problems associated with using TIR remote sensing data obtained at different spatial and temporal scales, examine why these problems appear as impediments to using multiple scaled TIR data, and provide some suggestions for future research activities that may address these problems. We elucidate the fundamental concept of scale as it relates to remote sensing and explore how space and time relationships affect TIR data from a problem-dependency perspective. We also describe how linearity and non-linearity observation versus parameter relationships affect the quantitative analysis of TIR data. Some insight is given on how the atmosphere between target and sensor influences the accurate measurement of surface temperatures and how these effects will be compounded in analyzing multiple scaled TIR data. Last, we describe some of the challenges in modeling TIR data obtained at different space and time scales and discuss how multiple scaled TIR data can be used to provide new and important information for measuring and modeling land-atmosphere energy balance processes.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe.

PubMed

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe

PubMed Central

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes. PMID:27074044

Disease spread across multiple scales in a spatial hierarchy: effect of host spatial structure and of inoculum quantity and distribution.

PubMed

Gosme, Marie; Lucas, Philippe

2009-07-01

Spatial patterns of both the host and the disease influence disease spread and crop losses. Therefore, the manipulation of these patterns might help improve control strategies. Considering disease spread across multiple scales in a spatial hierarchy allows one to capture important features of epidemics developing in space without using explicitly spatialized variables. Thus, if the system under study is composed of roots, plants, and planting hills, the effect of host spatial pattern can be studied by varying the number of plants per planting hill. A simulation model based on hierarchy theory was used to simulate the effects of large versus small planting hills, low versus high level of initial infections, and aggregated versus uniform distribution of initial infections. The results showed that aggregating the initially infected plants always resulted in slower epidemics than spreading out the initial infections uniformly. Simulation results also showed that, in most cases, disease epidemics were slower in the case of large host aggregates (100 plants/hill) than with smaller aggregates (25 plants/hill), except when the initially infected plants were both numerous and spread out uniformly. The optimal strategy for disease control depends on several factors, including initial conditions. More importantly, the model offers a framework to account for the interplay between the spatial characteristics of the system, rates of infection, and aggregation of the disease.

Multi-Decadal Pathfinder Data Sets of Global Land Biophysical Variables from AVHRR and MODIS and their Use in GCM Studies of Biogeophysics and Biogeochemistry

NASA Technical Reports Server (NTRS)

Myneni, Ranga

2003-01-01

The problem of how the scale, or spatial resolution, of reflectance data impacts retrievals of vegetation leaf area index (LAI) and fraction absorbed photosynthetically active radiation (PAR) has been investigated. We define the goal of scaling as the process by which it is established that LAI and FPAR values derived from coarse resolution sensor data equal the arithmetic average of values derived independently from fine resolution sensor data. The increasing probability of land cover mixtures with decreasing resolution is defined as heterogeneity, which is a key concept in scaling studies. The effect of pixel heterogeneity on spectral reflectances and LAI/FPAR retrievals is investigated with 1 km Advanced Very High Resolution Radiometer (AVHRR) data aggregated to different coarse spatial resolutions. It is shown that LAI retrieval errors at coarse resolution are inversely related to the proportion of the dominant land cover in such pixel. Further, large errors in LAI retrievals are incurred when forests are minority biomes in non-forest pixels compared to when forest biomes are mixed with one another, and vice-versa. A physically based technique for scaling with explicit spatial resolution dependent radiative transfer formulation is developed. The successful application of this theory to scaling LAI retrievals from AVHRR data of different resolutions is demonstrated

Spatially resolved penetration depth measurements and vortex manipulation in the ferromagnetic superconductor ErNi 2 B 2 C

DOE PAGES

Wulferding, Dirk; Yang, Ilkyu; Yang, Jinho; ...

2015-07-31

We present a local probe study of the magnetic superconductor ErNi 2B 2C, using magnetic force microscopy at sub-Kelvin temperatures. ErNi 2B 2C is an ideal system to explore the effects of concomitant superconductivity and ferromagnetism. At 500 mK, far below the transition to a weakly ferromagnetic state, we directly observe a structured magnetic background on the micrometer scale. We determine spatially resolved absolute values of the magnetic penetration depth λ and study its temperature dependence as the system undergoes magnetic phase transitions from paramagnetic to antiferromagnetic, and to weak ferromagnetic, all within the superconducting regime. We estimate the absolutemore » pinning force of Abrikosov vortices, which shows a position dependence and temperature dependence as well, and discuss the possibility of the purported spontaneous vortex formation.« less

Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

PubMed Central

Dechesne, Arnaud; Badawi, Nora; Aamand, Jens; Smets, Barth F.

2014-01-01

Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found significant diversity in the approaches used to describe and quantify spatial heterogeneity, which complicates inter-studies comparisons. However, it is clear that the presence and activity of pesticide degraders is often highly spatially variable with coefficients of variation often exceeding 50% and frequently displays non-random spatial patterns. A few controlling factors have tentatively been identified across pesticide classes: they include some soil characteristics (pH) and some agricultural management practices (pesticide application, tillage), while other potential controlling factors have more conflicting effects depending on the site or the pesticide. Evidence demonstrating the importance of spatial heterogeneity on the fate of pesticides in soil has been difficult to obtain but modeling and experimental systems that do not include soil's full complexity reveal that this heterogeneity must be considered to improve prediction of pesticide biodegradation rates or of leaching risks. Overall, studying the spatial heterogeneity of pesticide biodegradation is a relatively new field at the interface of agronomy, microbial ecology, and geosciences and a wealth of novel data is being collected from these different disciplinary perspectives. We make suggestions on possible avenues to take full advantage of these investigations for a better understanding and prediction of the fate of pesticides in soil. PMID:25538691

Reduced fine-scale spatial genetic structure in grazed populations of Dianthus carthusianorum

PubMed Central

Rico, Y; Wagner, H H

2016-01-01

Strong spatial genetic structure in plant populations can increase homozygosity, reducing genetic diversity and adaptive potential. The strength of spatial genetic structure largely depends on rates of seed dispersal and pollen flow. Seeds without dispersal adaptations are likely to be dispersed over short distances within the vicinity of the mother plant, resulting in spatial clustering of related genotypes (fine-scale spatial genetic structure, hereafter spatial genetic structure (SGS)). However, primary seed dispersal by zoochory can promote effective dispersal, increasing the mixing of seeds and influencing SGS within plant populations. In this study, we investigated the effects of seed dispersal by rotational sheep grazing on the strength of SGS and genetic diversity using 11 nuclear microsatellites for 49 populations of the calcareous grassland forb Dianthus carthusianorum. Populations connected by rotational sheep grazing showed significantly weaker SGS and higher genetic diversity than populations in ungrazed grasslands. Independent of grazing treatment, small populations showed significantly stronger SGS and lower genetic diversity than larger populations, likely due to genetic drift. A lack of significant differences in the strength of SGS and genetic diversity between populations that were recently colonized and pre-existing populations suggested that populations colonized after the reintroduction of rotational sheep grazing were likely founded by colonists from diverse source populations. We conclude that dispersal by rotational sheep grazing has the potential to considerably reduce SGS within D. carthusianorum populations. Our study highlights the effectiveness of landscape management by rotational sheep grazing to importantly reduce genetic structure at local scales within restored plant populations. PMID:27381322

Reduced fine-scale spatial genetic structure in grazed populations of Dianthus carthusianorum.

PubMed

Rico, Y; Wagner, H H

2016-11-01

Strong spatial genetic structure in plant populations can increase homozygosity, reducing genetic diversity and adaptive potential. The strength of spatial genetic structure largely depends on rates of seed dispersal and pollen flow. Seeds without dispersal adaptations are likely to be dispersed over short distances within the vicinity of the mother plant, resulting in spatial clustering of related genotypes (fine-scale spatial genetic structure, hereafter spatial genetic structure (SGS)). However, primary seed dispersal by zoochory can promote effective dispersal, increasing the mixing of seeds and influencing SGS within plant populations. In this study, we investigated the effects of seed dispersal by rotational sheep grazing on the strength of SGS and genetic diversity using 11 nuclear microsatellites for 49 populations of the calcareous grassland forb Dianthus carthusianorum. Populations connected by rotational sheep grazing showed significantly weaker SGS and higher genetic diversity than populations in ungrazed grasslands. Independent of grazing treatment, small populations showed significantly stronger SGS and lower genetic diversity than larger populations, likely due to genetic drift. A lack of significant differences in the strength of SGS and genetic diversity between populations that were recently colonized and pre-existing populations suggested that populations colonized after the reintroduction of rotational sheep grazing were likely founded by colonists from diverse source populations. We conclude that dispersal by rotational sheep grazing has the potential to considerably reduce SGS within D. carthusianorum populations. Our study highlights the effectiveness of landscape management by rotational sheep grazing to importantly reduce genetic structure at local scales within restored plant populations.

Scale dependent behavioral responses to human development by a large predator, the puma.

PubMed

Wilmers, Christopher C; Wang, Yiwei; Nickel, Barry; Houghtaling, Paul; Shakeri, Yasaman; Allen, Maximilian L; Kermish-Wells, Joe; Yovovich, Veronica; Williams, Terrie

2013-01-01

The spatial scale at which organisms respond to human activity can affect both ecological function and conservation planning. Yet little is known regarding the spatial scale at which distinct behaviors related to reproduction and survival are impacted by human interference. Here we provide a novel approach to estimating the spatial scale at which a top predator, the puma (Puma concolor), responds to human development when it is moving, feeding, communicating, and denning. We find that reproductive behaviors (communication and denning) require at least a 4× larger buffer from human development than non-reproductive behaviors (movement and feeding). In addition, pumas give a wider berth to types of human development that provide a more consistent source of human interference (neighborhoods) than they do to those in which human presence is more intermittent (arterial roads with speeds >35 mph). Neighborhoods were a deterrent to pumas regardless of behavior, while arterial roads only deterred pumas when they were communicating and denning. Female pumas were less deterred by human development than males, but they showed larger variation in their responses overall. Our behaviorally explicit approach to modeling animal response to human activity can be used as a novel tool to assess habitat quality, identify wildlife corridors, and mitigate human-wildlife conflict.

Addressing Spatial Dependence Bias in Climate Model Simulations—An Independent Component Analysis Approach

NASA Astrophysics Data System (ADS)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2018-02-01

Conventional bias correction is usually applied on a grid-by-grid basis, meaning that the resulting corrections cannot address biases in the spatial distribution of climate variables. To solve this problem, a two-step bias correction method is proposed here to correct time series at multiple locations conjointly. The first step transforms the data to a set of statistically independent univariate time series, using a technique known as independent component analysis (ICA). The mutually independent signals can then be bias corrected as univariate time series and back-transformed to improve the representation of spatial dependence in the data. The spatially corrected data are then bias corrected at the grid scale in the second step. The method has been applied to two CMIP5 General Circulation Model simulations for six different climate regions of Australia for two climate variables—temperature and precipitation. The results demonstrate that the ICA-based technique leads to considerable improvements in temperature simulations with more modest improvements in precipitation. Overall, the method results in current climate simulations that have greater equivalency in space and time with observational data.

Spatial heterogeneity and risk factors for stunting among children under age five in Ethiopia: A Bayesian geo-statistical model.

PubMed

Hagos, Seifu; Hailemariam, Damen; WoldeHanna, Tasew; Lindtjørn, Bernt

2017-01-01

Understanding the spatial distribution of stunting and underlying factors operating at meso-scale is of paramount importance for intervention designing and implementations. Yet, little is known about the spatial distribution of stunting and some discrepancies are documented on the relative importance of reported risk factors. Therefore, the present study aims at exploring the spatial distribution of stunting at meso- (district) scale, and evaluates the effect of spatial dependency on the identification of risk factors and their relative contribution to the occurrence of stunting and severe stunting in a rural area of Ethiopia. A community based cross sectional study was conducted to measure the occurrence of stunting and severe stunting among children aged 0-59 months. Additionally, we collected relevant information on anthropometric measures, dietary habits, parent and child-related demographic and socio-economic status. Latitude and longitude of surveyed households were also recorded. Local Anselin Moran's I was calculated to investigate the spatial variation of stunting prevalence and identify potential local pockets (hotspots) of high prevalence. Finally, we employed a Bayesian geo-statistical model, which accounted for spatial dependency structure in the data, to identify potential risk factors for stunting in the study area. Overall, the prevalence of stunting and severe stunting in the district was 43.7% [95%CI: 40.9, 46.4] and 21.3% [95%CI: 19.5, 23.3] respectively. We identified statistically significant clusters of high prevalence of stunting (hotspots) in the eastern part of the district and clusters of low prevalence (cold spots) in the western. We found out that the inclusion of spatial structure of the data into the Bayesian model has shown to improve the fit for stunting model. The Bayesian geo-statistical model indicated that the risk of stunting increased as the child's age increased (OR 4.74; 95% Bayesian credible interval [BCI]:3.35-6.58) and among boys (OR 1.28; 95%BCI; 1.12-1.45). However, maternal education and household food security were found to be protective against stunting and severe stunting. Stunting prevalence may vary across space at different scale. For this, it's important that nutrition studies and, more importantly, control interventions take into account this spatial heterogeneity in the distribution of nutritional deficits and their underlying associated factors. The findings of this study also indicated that interventions integrating household food insecurity in nutrition programs in the district might help to avert the burden of stunting.

Movement reveals scale dependence in habitat selection of a large ungulate.

PubMed

Northrup, Joseph M; Anderson, Charles R; Hooten, Mevin B; Wittemyer, George

2016-12-01

Ecological processes operate across temporal and spatial scales. Anthropogenic disturbances impact these processes, but examinations of scale dependence in impacts are infrequent. Such examinations can provide important insight to wildlife-human interactions and guide management efforts to reduce impacts. We assessed spatiotemporal scale dependence in habitat selection of mule deer (Odocoileus hemionus) in the Piceance Basin of Colorado, USA, an area of ongoing natural gas development. We employed a newly developed animal movement method to assess habitat selection across scales defined using animal-centric spatiotemporal definitions ranging from the local (defined from five hour movements) to the broad (defined from weekly movements). We extended our analysis to examine variation in scale dependence between night and day and assess functional responses in habitat selection patterns relative to the density of anthropogenic features. Mule deer displayed scale invariance in the direction of their response to energy development features, avoiding well pads and the areas closest to roads at all scales, though with increasing strength of avoidance at coarser scales. Deer displayed scale-dependent responses to most other habitat features, including land cover type and habitat edges. Selection differed between night and day at the finest scales, but homogenized as scale increased. Deer displayed functional responses to development, with deer inhabiting the least developed ranges more strongly avoiding development relative to those with more development in their ranges. Energy development was a primary driver of habitat selection patterns in mule deer, structuring their behaviors across all scales examined. Stronger avoidance at coarser scales suggests that deer behaviorally mediated their interaction with development, but only to a degree. At higher development densities than seen in this area, such mediation may not be possible and thus maintenance of sufficient habitat with lower development densities will be a critical best management practice as development expands globally. © 2016 by the Ecological Society of America.

A Kennicutt-Schmidt relation at molecular cloud scales and beyond

NASA Astrophysics Data System (ADS)

Khoperskov, Sergey A.; Vasiliev, Evgenii O.

2017-06-01

Using N-body/gasdynamic simulations of a Milky Way-like galaxy, we analyse a Kennicutt-Schmidt (KS) relation, Σ _SFR ∝ Σ _gas^N, at different spatial scales. We simulate synthetic observations in CO lines and ultraviolet (UV) band. We adopt the star formation rate (SFR) defined in two ways: based on free fall collapse of a molecular cloud - ΣSFR, cl, and calculated by using a UV flux calibration - ΣSFR,UV. We study a KS relation for spatially smoothed maps with effective spatial resolution from molecular cloud scales to several hundred parsecs. We find that for spatially and kinematically resolved molecular clouds the Σ _{SFR, cl} ∝ σ _{gas}^N relation follows the power law with index N ≈ 1.4. Using UV flux as SFR calibrator, we confirm a systematic offset between the ΣSFR,UV and Σgas distributions on scales compared to molecular cloud sizes. Degrading resolution of our simulated maps for surface densities of gas and SFRs, we establish that there is no relation ΣSFR,UV -Σgas below the resolution ˜50 pc. We find a transition range around scales ˜50-120 pc, where the power-law index N increases from 0 to 1-1.8 and saturates for scales larger ˜120 pc. A value of the index saturated depends on a surface gas density threshold and it becomes steeper for higher Σgas threshold. Averaging over scales with size of ≳ 150 pc the power-law index N equals 1.3-1.4 for surface gas density threshold ˜5 M⊙ pc-2. At scales ≳ 120 pc surface SFR densities determined by using CO data and UV flux, ΣSFR,UV/SFR, cl, demonstrate a discrepancy about a factor of 3. We argue that this may be originated from overestimating (constant) values of conversion factor, star formation efficiency or UV calibration used in our analysis.

The statistical power to detect cross-scale interactions at macroscales

USGS Publications Warehouse

Wagner, Tyler; Fergus, C. Emi; Stow, Craig A.; Cheruvelil, Kendra S.; Soranno, Patricia A.

2016-01-01

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

Uncertainty Quantification in Scale-Dependent Models of Flow in Porous Media: SCALE-DEPENDENT UQ

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

Tartakovsky, A. M.; Panzeri, M.; Tartakovsky, G. D.

Equations governing flow and transport in heterogeneous porous media are scale-dependent. We demonstrate that it is possible to identify a support scalemore » $$\\eta^*$$, such that the typically employed approximate formulations of Moment Equations (ME) yield accurate (statistical) moments of a target environmental state variable. Under these circumstances, the ME approach can be used as an alternative to the Monte Carlo (MC) method for Uncertainty Quantification in diverse fields of Earth and environmental sciences. MEs are directly satisfied by the leading moments of the quantities of interest and are defined on the same support scale as the governing stochastic partial differential equations (PDEs). Computable approximations of the otherwise exact MEs can be obtained through perturbation expansion of moments of the state variables in orders of the standard deviation of the random model parameters. As such, their convergence is guaranteed only for the standard deviation smaller than one. We demonstrate our approach in the context of steady-state groundwater flow in a porous medium with a spatially random hydraulic conductivity.« less

SPM investigation of local aging effects in glassy polymers

NASA Astrophysics Data System (ADS)

Crider, Philip

2005-03-01

We investigate the cooperative and heterogeneous nature of glassy dynamics by nanometer-scale probing in a glassy polymer, Polyvinyl-Actetate (PVAc), with a Scanning Force Microscope (SFM). Using ultra-high-vacuum (UHV) Scanning Capacitive Force Microscopy techniques, nanometer-scale capacitive responses are probed. Dielectric relaxation near the glass transition is investigated, and scanning capabilities are utilized to analyze spatial response on a nanometer scale. The results of these studies may yield insight into the understanding of temperature-dependent cooperative length scales, local aging properties, and energy landscape properties of evolving dipole clusters on a mesoscopic scale. Results are used to test the validity and relevance of current models of glassy dynamics.

Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes

PubMed Central

Ghosh, Subimal; Vittal, H.; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K. S.; Dhanesh, Y.; Sudheer, K. P.; Gunthe, S. S.

2016-01-01

India’s agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins. PMID:27463092

Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes.

PubMed

Ghosh, Subimal; Vittal, H; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K S; Dhanesh, Y; Sudheer, K P; Gunthe, S S

2016-01-01

India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins.

Spatial scale, means and gradients of hydrographic variables define pelagic seascapes of bluefin and bullet tuna spawning distribution.

PubMed

Alvarez-Berastegui, Diego; Ciannelli, Lorenzo; Aparicio-Gonzalez, Alberto; Reglero, Patricia; Hidalgo, Manuel; López-Jurado, Jose Luis; Tintoré, Joaquín; Alemany, Francisco

2014-01-01

Seascape ecology is an emerging discipline focused on understanding how features of the marine habitat influence the spatial distribution of marine species. However, there is still a gap in the development of concepts and techniques for its application in the marine pelagic realm, where there are no clear boundaries delimitating habitats. Here we demonstrate that pelagic seascape metrics defined as a combination of hydrographic variables and their spatial gradients calculated at an appropriate spatial scale, improve our ability to model pelagic fish distribution. We apply the analysis to study the spawning locations of two tuna species: Atlantic bluefin and bullet tuna. These two species represent a gradient in life history strategies. Bluefin tuna has a large body size and is a long-distant migrant, while bullet tuna has a small body size and lives year-round in coastal waters within the Mediterranean Sea. The results show that the models performance incorporating the proposed seascape metrics increases significantly when compared with models that do not consider these metrics. This improvement is more important for Atlantic bluefin, whose spawning ecology is dependent on the local oceanographic scenario, than it is for bullet tuna, which is less influenced by the hydrographic conditions. Our study advances our understanding of how species perceive their habitat and confirms that the spatial scale at which the seascape metrics provide information is related to the spawning ecology and life history strategy of each species.

General scale-dependent anisotropic turbulence and its impact on free space optical communication system performance.

PubMed

Toselli, Italo; Korotkova, Olga

2015-06-01

We generalize a recently introduced model for nonclassic turbulent spatial power spectrum involving anisotropy along two mutually orthogonal axes transverse to the direction of beam propagation by including two scale-dependent weighting factors for these directions. Such a turbulent model may be pertinent to atmospheric fluctuations in the refractive index in stratified regions well above the boundary layer and employed for air-air communication channels. When restricting ourselves to an unpolarized, coherent Gaussian beam and a weak turbulence regime, we examine the effects of such a turbulence type on the OOK FSO link performance by including the results on scintillation flux, probability of fade, SNR, and BERs.

Galaxy clustering and the origin of large-scale flows

NASA Technical Reports Server (NTRS)

Juszkiewicz, R.; Yahil, A.

1989-01-01

Peebles's 'cosmic virial theorem' is extended from its original range of validity at small separations, where hydrostatic equilibrium holds, to large separations, in which linear gravitational stability theory applies. The rms pairwise velocity difference at separation r is shown to depend on the spatial galaxy correlation function xi(x) only for x less than r. Gravitational instability theory can therefore be tested by comparing the two up to the maximum separation for which both can reliably be determined, and there is no dependence on the poorly known large-scale density and velocity fields. With the expected improvement in the data over the next few years, however, this method should yield a reliable determination of omega.

Exploring the effect of drought extent and interval on the Florida snail kite: Interplay between spatial and temporal scales

USGS Publications Warehouse

Mooij, Wolf M.; Bennetts, Robert E.; Kitchens, Wiley M.; DeAngelis, Donald L.

2002-01-01

The paper aims at exploring the viability of the Florida snail kite population under various drought regimes in its wetland habitat. The population dynamics of snail kites are strongly linked with the hydrology of the system due to the dependence of this bird species on one exclusive prey species, the apple snail, which is negatively affected by a drying out of habitat. Based on empirical evidence, it has been hypothesised that the viability of the snail kite population critically depends not only on the time interval between droughts, but also on the spatial extent of these droughts. A system wide drought is likely to result in reduced reproduction and increased mortality, whereas the birds can respond to local droughts by moving to sites where conditions are still favourable. This paper explores the implications of this hypothesis by means of a spatially-explicit individual-based model. The specific aim of the model is to study in a factorial design the dynamics of the kite population in relation to two scale parameters, the temporal interval between droughts and the spatial correlation between droughts. In the model high drought frequencies led to reduced numbers of kites. Also, habitat degradation due to prolonged periods of inundation led to lower predicted numbers of kites. Another main result was that when the spatial correlation between droughts was low, the model showed little variability in the predicted numbers of kites. But when droughts occurred mostly on a system wide level, environmental stochasticity strongly increased the stochasticity in kite numbers and in the worst case the viability of the kite population was seriously threatened.

Nonextensive Entropy Approach to Space Plasma Fluctuations and Turbulence

NASA Astrophysics Data System (ADS)

Leubner, M. P.; Vörös, Z.; Baumjohann, W.

Spatial intermittency in fully developed turbulence is an established feature of astrophysical plasma fluctuations and in particular apparent in the interplanetary medium by in situ observations. In this situation, the classical Boltzmann— Gibbs extensive thermo-statistics, applicable when microscopic interactions and memory are short ranged and the environment is a continuous and differentiable manifold, fails. Upon generalization of the entropy function to nonextensivity, accounting for long-range interactions and thus for correlations in the system, it is demonstrated that the corresponding probability distribution functions (PDFs) are members of a family of specific power-law distributions. In particular, the resulting theoretical bi-κ functional reproduces accurately the observed global leptokurtic, non-Gaussian shape of the increment PDFs of characteristic solar wind variables on all scales, where nonlocality in turbulence is controlled via a multiscale coupling parameter. Gradual decoupling is obtained by enhancing the spatial separation scale corresponding to increasing κ-values in case of slow solar wind conditions where a Gaussian is approached in the limit of large scales. Contrary, the scaling properties in the high speed solar wind are predominantly governed by the mean energy or variance of the distribution, appearing as second parameter in the theory. The PDFs of solar wind scalar field differences are computed from WIND and ACE data for different time-lags and bulk speeds and analyzed within the nonextensive theory, where also a particular nonlinear dependence of the coupling parameter and variance with scale arises for best fitting theoretical PDFs. Consequently, nonlocality in fluctuations, related to both, turbulence and its large scale driving, should be related to long-range interactions in the context of nonextensive entropy generalization, providing fundamentally the physical background of the observed scale dependence of fluctuations in intermittent space plasmas.

Effects of Spatial Patch Arrangement and Scale of Covarying Resources on Growth and Intraspecific Competition of a Clonal Plant

PubMed Central

Wang, Yong-Jian; Shi, Xue-Ping; Meng, Xue-Feng; Wu, Xiao-Jing; Luo, Fang-Li; Yu, Fei-Hai

2016-01-01

Spatial heterogeneity in two co-variable resources such as light and water availability is common and can affect the growth of clonal plants. Several studies have tested effects of spatial heterogeneity in the supply of a single resource on competitive interactions of plants, but none has examined those of heterogeneous distribution of two co-variable resources. In a greenhouse experiment, we grew one (without intraspecific competition) or nine isolated ramets (with competition) of a rhizomatous herb Iris japonica under a homogeneous environment and four heterogeneous environments differing in patch arrangement (reciprocal and parallel patchiness of light and soil water) and patch scale (large and small patches of light and water). Intraspecific competition significantly decreased the growth of I. japonica, but at the whole container level there were no significant interaction effects of competition by spatial heterogeneity or significant effect of heterogeneity on competitive intensity. Irrespective of competition, the growth of I. japonica in the high and the low water patches did not differ significantly in the homogeneous treatments, but it was significantly larger in the high than in the low water patches in the heterogeneous treatments with large patches. For the heterogeneous treatments with small patches, the growth of I. japonica was significantly larger in the high than in the low water patches in the presence of competition, but such an effect was not significant in the absence of competition. Furthermore, patch arrangement and patch scale significantly affected competitive intensity at the patch level. Therefore, spatial heterogeneity in light and water supply can alter intraspecific competition at the patch level and such effects depend on patch arrangement and patch scale. PMID:27375630

Effects of Spatial Patch Arrangement and Scale of Covarying Resources on Growth and Intraspecific Competition of a Clonal Plant.

PubMed

Wang, Yong-Jian; Shi, Xue-Ping; Meng, Xue-Feng; Wu, Xiao-Jing; Luo, Fang-Li; Yu, Fei-Hai

2016-01-01

Spatial heterogeneity in two co-variable resources such as light and water availability is common and can affect the growth of clonal plants. Several studies have tested effects of spatial heterogeneity in the supply of a single resource on competitive interactions of plants, but none has examined those of heterogeneous distribution of two co-variable resources. In a greenhouse experiment, we grew one (without intraspecific competition) or nine isolated ramets (with competition) of a rhizomatous herb Iris japonica under a homogeneous environment and four heterogeneous environments differing in patch arrangement (reciprocal and parallel patchiness of light and soil water) and patch scale (large and small patches of light and water). Intraspecific competition significantly decreased the growth of I. japonica, but at the whole container level there were no significant interaction effects of competition by spatial heterogeneity or significant effect of heterogeneity on competitive intensity. Irrespective of competition, the growth of I. japonica in the high and the low water patches did not differ significantly in the homogeneous treatments, but it was significantly larger in the high than in the low water patches in the heterogeneous treatments with large patches. For the heterogeneous treatments with small patches, the growth of I. japonica was significantly larger in the high than in the low water patches in the presence of competition, but such an effect was not significant in the absence of competition. Furthermore, patch arrangement and patch scale significantly affected competitive intensity at the patch level. Therefore, spatial heterogeneity in light and water supply can alter intraspecific competition at the patch level and such effects depend on patch arrangement and patch scale.

Multiscale Bayesian neural networks for soil water content estimation

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.; Springer, Everett P.

2008-08-01

Artificial neural networks (ANN) have been used for some time now to estimate soil hydraulic parameters from other available or more easily measurable soil properties. However, most such uses of ANNs as pedotransfer functions (PTFs) have been at matching spatial scales (1:1) of inputs and outputs. This approach assumes that the outputs are only required at the same scale as the input data. Unfortunately, this is rarely true. Different hydrologic, hydroclimatic, and contaminant transport models require soil hydraulic parameter data at different spatial scales, depending upon their grid sizes. While conventional (deterministic) ANNs have been traditionally used in these studies, the use of Bayesian training of ANNs is a more recent development. In this paper, we develop a Bayesian framework to derive soil water retention function including its uncertainty at the point or local scale using PTFs trained with coarser-scale Soil Survey Geographic (SSURGO)-based soil data. The approach includes an ANN trained with Bayesian techniques as a PTF tool with training and validation data collected across spatial extents (scales) in two different regions in the United States. The two study areas include the Las Cruces Trench site in the Rio Grande basin of New Mexico, and the Southern Great Plains 1997 (SGP97) hydrology experimental region in Oklahoma. Each region-specific Bayesian ANN is trained using soil texture and bulk density data from the SSURGO database (scale 1:24,000), and predictions of the soil water contents at different pressure heads with point scale data (1:1) inputs are made. The resulting outputs are corrected for bias using both linear and nonlinear correction techniques. The results show good agreement between the soil water content values measured at the point scale and those predicted by the Bayesian ANN-based PTFs for both the study sites. Overall, Bayesian ANNs coupled with nonlinear bias correction are found to be very suitable tools for deriving soil hydraulic parameters at the local/fine scale from soil physical properties at coarser-scale and across different spatial extents. This approach could potentially be used for soil hydraulic properties estimation and downscaling.

(In) Sensitivity to spatial distortion in natural scenes

PubMed Central

Bex, Peter J.

2010-01-01

The perception of object structure in the natural environment is remarkably stable under large variation in image size and projection, especially given our insensitivity to spatial position outside the fovea. Sensitivity to periodic spatial distortions that were introduced into one quadrant of gray-scale natural images was measured in a 4AFC task. Observers were able to detect the presence of distortions in unfamiliar images even though they did not significantly affect the amplitude spectrum. Sensitivity depended on the spatial period of the distortion and on the image structure at the location of the distortion. The results suggest that the detection of distortion involves decisions made in the late stages of image perception and is based on an expectation of the typical structure of natural scenes. PMID:20462324

Investigating disparities in spatial accessibility to and characteristics of sport facilities: direction, strength, and spatial scale of associations with area income.

PubMed

Billaudeau, Nathalie; Oppert, Jean-Michel; Simon, Chantal; Charreire, Hélène; Casey, Romain; Salze, Paul; Badariotti, Dominique; Banos, Arnaud; Weber, Christiane; Chaix, Basile

2011-01-01

We conducted an environmental justice study of the spatial distribution of sport facilities, a major resource for physical activity, in the Paris Region in France. Comprehensive data of the French Census of Sport Facilities allowed us to investigate disparities not only in the spatial accessibility to facilities, but also in the characteristics of these facilities. We found that the associations between area income and the presence of facilities or favorable characteristics of these facilities varied from positive to negative depending on the facilities and on the characteristics examined. Sensitivity analyses defining area income in circular areas of different radii permitted a refined identification of areas underserved in sport facilities. Copyright © 2010 Elsevier Ltd. All rights reserved.

Upscaling of dilution and mixing using a trajectory based Spatial Markov random walk model in a periodic flow domain

NASA Astrophysics Data System (ADS)

Sund, Nicole L.; Porta, Giovanni M.; Bolster, Diogo

2017-05-01

The Spatial Markov Model (SMM) is an upscaled model that has been used successfully to predict effective mean transport across a broad range of hydrologic settings. Here we propose a novel variant of the SMM, applicable to spatially periodic systems. This SMM is built using particle trajectories, rather than travel times. By applying the proposed SMM to a simple benchmark problem we demonstrate that it can predict mean effective transport, when compared to data from fully resolved direct numerical simulations. Next we propose a methodology for using this SMM framework to predict measures of mixing and dilution, that do not just depend on mean concentrations, but are strongly impacted by pore-scale concentration fluctuations. We use information from trajectories of particles to downscale and reconstruct pore-scale approximate concentration fields from which mixing and dilution measures are then calculated. The comparison between measurements from fully resolved simulations and predictions with the SMM agree very favorably.

Multidomain spectral solution of shock-turbulence interactions

NASA Technical Reports Server (NTRS)

Kopriva, David A.; Hussaini, M. Yousuff

1989-01-01

The use of a fitted-shock multidomain spectral method for solving the time-dependent Euler equations of gasdynamics is described. The multidomain method allows short spatial scale features near the shock to be resolved throughout the calculation. Examples presented are of a shock-plane wave, shock-hot spot and shock-vortex street interaction.

Exploring the relevance of spatial scale to life cycle inventory results using environmentally-extended input-output models of the United States

EPA Science Inventory

The accuracy of direct and indirect resource use and emissions of products as quantified in life cycle models depends in part upon the geographical and technological representativeness of the production models. Production conditions vary not just between nations, but also within ...

Effects of Spatial Variability of Soil Properties on the Triggering of Rainfall-Induced Shallow Landslides

NASA Astrophysics Data System (ADS)

Fan, Linfeng; Lehmann, Peter; Or, Dani

2015-04-01

Naturally-occurring spatial variations in soil properties (e.g., soil depth, moisture, and texture) affect key hydrological processes and potentially the mechanical response of soil to hydromechanical loading (relative to the commonly-assumed uniform soil mantle). We quantified the effects of soil spatial variability on the triggering of rainfall-induced shallow landslides at the hillslope- and catchment-scales, using a physically-based landslide triggering model that considers interacting soil columns with mechanical strength thresholds (represented by the Fiber Bundle Model). The spatial variations in soil properties are represented as Gaussian random distributions and the level of variation is characterized by the coefficient of variation and correlation lengths of soil properties (i.e., soil depth, soil texture and initial water content in this study). The impacts of these spatial variations on landslide triggering characteristics were measured by comparing the times to triggering and landslide volumes for heterogeneous soil properties and homogeneous cases. Results at hillslope scale indicate that for spatial variations of an individual property (without cross correlation), the increasing of coefficient of variation introduces weak spots where mechanical damage is accelerated and leads to earlier onset of landslide triggering and smaller volumes. Increasing spatial correlation length of soil texture and initial water content also induces early landslide triggering and small released volumes due to the transition of failure mode from brittle to ductile failure. In contrast, increasing spatial correlation length of soil depth "reduces" local steepness and postpones landslide triggering. Cross-correlated soil properties generally promote landslide initiation, but depending on the internal structure of spatial distribution of each soil property, landslide triggering may be reduced. The effects of cross-correlation between initial water content and soil texture were investigated in detail at the catchment scale by incorporating correlations of both variables with topography. Results indicate that the internal structure of the spatial distribution of each soil property together with their interplays determine the overall performance of the coupled spatial variability. This study emphasizes the importance of both the randomness and spatial structure of soil properties on landslide triggering and characteristics.

Toward an operational tool to simulate green roof hydrological impact at the basin scale: a new version of the distributed rainfall-runoff model Multi-Hydro.

PubMed

Versini, Pierre-Antoine; Gires, Auguste; Tchinguirinskaia, Ioulia; Schertzer, Daniel

2016-10-01

Currently widespread in new urban projects, green roofs have shown a positive impact on urban runoff at the building scale: decrease and slow-down of the peak discharge, and decrease of runoff volume. The present work aims to study their possible impact at the catchment scale, more compatible with stormwater management issues. For this purpose, a specific module dedicated to simulating the hydrological behaviour of a green roof has been developed in the distributed rainfall-runoff model (Multi-Hydro). It has been applied on a French urban catchment where most of the building roofs are flat and assumed to accept the implementation of a green roof. Catchment responses to several rainfall events covering a wide range of meteorological situations have been simulated. The simulation results show green roofs can significantly reduce runoff volume and the magnitude of peak discharge (up to 80%) depending on the rainfall event and initial saturation of the substrate. Additional tests have been made to assess the susceptibility of this response regarding both spatial distributions of green roofs and precipitation. It appears that the total area of greened roofs is more important than their locations. On the other hand, peak discharge reduction seems to be clearly dependent on spatial distribution of precipitation.

Spatial spread of the Hantavirus infection

NASA Astrophysics Data System (ADS)

Reinoso, José A.; de la Rubia, F. Javier

2015-03-01

The spatial propagation of Hantavirus-infected mice is considered a serious threat for public health. We analyze the spatial spread of the infected mice by including diffusion in the stage-dependent model for Hantavirus infection recently proposed by Reinoso and de la Rubia [Phys. Rev. E 87, 042706 (2013), 10.1103/PhysRevE.87.042706]. We consider a general scenario in which mice propagate in fronts from their refugia to the surroundings and find an expression for the speed of the front of infected mice. We also introduce a depletion time that measures the time scale for an appreciable impoverishment of the environment conditions and show how this new situation may change the spreading of the infection significantly.

Landscape-scale consequences of differential tree mortality from catastrophic wind disturbance in the Amazon.

PubMed

Rifai, Sami W; Urquiza Muñoz, José D; Negrón-Juárez, Robinson I; Ramírez Arévalo, Fredy R; Tello-Espinoza, Rodil; Vanderwel, Mark C; Lichstein, Jeremy W; Chambers, Jeffrey Q; Bohlman, Stephanie A

2016-10-01

Wind disturbance can create large forest blowdowns, which greatly reduces live biomass and adds uncertainty to the strength of the Amazon carbon sink. Observational studies from within the central Amazon have quantified blowdown size and estimated total mortality but have not determined which trees are most likely to die from a catastrophic wind disturbance. Also, the impact of spatial dependence upon tree mortality from wind disturbance has seldom been quantified, which is important because wind disturbance often kills clusters of trees due to large treefalls killing surrounding neighbors. We examine (1) the causes of differential mortality between adult trees from a 300-ha blowdown event in the Peruvian region of the northwestern Amazon, (2) how accounting for spatial dependence affects mortality predictions, and (3) how incorporating both differential mortality and spatial dependence affect the landscape level estimation of necromass produced from the blowdown. Standard regression and spatial regression models were used to estimate how stem diameter, wood density, elevation, and a satellite-derived disturbance metric influenced the probability of tree death from the blowdown event. The model parameters regarding tree characteristics, topography, and spatial autocorrelation of the field data were then used to determine the consequences of non-random mortality for landscape production of necromass through a simulation model. Tree mortality was highly non-random within the blowdown, where tree mortality rates were highest for trees that were large, had low wood density, and were located at high elevation. Of the differential mortality models, the non-spatial models overpredicted necromass, whereas the spatial model slightly underpredicted necromass. When parameterized from the same field data, the spatial regression model with differential mortality estimated only 7.5% more dead trees across the entire blowdown than the random mortality model, yet it estimated 51% greater necromass. We suggest that predictions of forest carbon loss from wind disturbance are sensitive to not only the underlying spatial dependence of observations, but also the biological differences between individuals that promote differential levels of mortality. © 2016 by the Ecological Society of America.

Negative density-dependent dispersal in the American black bear (Ursus americanus) revealed by noninvasive sampling and genotyping

PubMed Central

Roy, Justin; Yannic, Glenn; Côté, Steeve D; Bernatchez, Louis

2012-01-01

Although the dispersal of animals is influenced by a variety of factors, few studies have used a condition-dependent approach to assess it. The mechanisms underlying dispersal are thus poorly known in many species, especially in large mammals. We used 10 microsatellite loci to examine population density effects on sex-specific dispersal behavior in the American black bear, Ursus americanus. We tested whether dispersal increases with population density in both sexes. Fine-scale genetic structure was investigated in each of four sampling areas using Mantel tests and spatial autocorrelation analyses. Our results revealed male-biased dispersal pattern in low-density areas. As population density increased, females appeared to exhibit philopatry at smaller scales. Fine-scale genetic structure for males at higher densities may indicate reduced dispersal distances and delayed dispersal by subadults. PMID:22822432

Spatial variability assessment of soil nutrients in an intense agricultural area, a case study of Rugao County in Yangtze River Delta Region, China

NASA Astrophysics Data System (ADS)

Zhao, Yongcun; Xu, Xianghua; Darilek, Jeremy Landon; Huang, Biao; Sun, Weixia; Shi, Xuezheng

2009-05-01

Topsoil samples (0-20 cm) ( n = 237) were collected from Rugao County, China. Geostatistical variogram analysis, sequential Gaussian simulation (SGS), and principal component (PC) analysis were applied to assess spatial variability of soil nutrients, identify the possible areas of nutrient deficiency, and explore spatial scale of variability of soil nutrients in the county. High variability of soil nutrient such as soil organic matter (SOM), total nitrogen (TN), available P, K, Fe, Mn, Cu, Zn, and B concentrations were observed. Soil nutrient properties displayed significant differences in their spatial structures, with available Cu having strong spatial dependence, SOM and available P having weak spatial dependence, and other nutrient properties having moderate spatial dependence. The soil nutrient deficiency, defined here as measured nutrient concentrations which do not meet the advisory threshold values specific to the county for dominant crops, namely rice, wheat, and rape seeds, was observed in available K and Zn, and the deficient areas covered 38 and 11%, respectively. The first three PCs of the nine soil nutrient properties explained 62.40% of the total variance. TN and SOM with higher loadings on PC1 are closely related to soil texture derived from different parent materials. The PC2 combined intermediate response variables such as available Zn and P that are likely to be controlled by land use and soil pH. Available B has the highest loading on PC3 and its variability of concentrations may be primarily ascribed to localized anthropogenic influence. The amelioration of soil physical properties (i.e. soil texture) and soil pH may improve the availability of soil nutrients and the sustainability of the agricultural system of Rugao County.

Landscape structure control on soil CO2 efflux variability in complex terrain: Scaling from point observations to watershed scale fluxes

Treesearch

Diego A. Riveros-Iregui; Brian L. McGlynn

2009-01-01

We investigated the spatial and temporal variability of soil CO2 efflux across 62 sites of a 393-ha complex watershed of the northern Rocky Mountains. Growing season (83 day) cumulative soil CO2 efflux varied from ~300 to ~2000 g CO2 m-2, depending upon landscape position, with a median of 879.8 g CO2 m-2. Our findings revealed that highest soil CO2 efflux rates were...

Spatially nonrandom tree mortality and ingrowth maintain equilibrium pattern in an old-growth Pseudotsuga-Tsuga forest.

PubMed

Lutz, James A; Larson, Andrew J; Furniss, Tucker J; Donato, Daniel C; Freund, James A; Swanson, Mark E; Bible, Kenneth J; Chen, Jiquan; Franklin, Jerry F

2014-08-01

Mortality processes in old-growth forests are generally assumed to be driven by gap-scale disturbance, with only a limited role ascribed to density-dependent mortality, but these assumptions are rarely tested with data sets incorporating repeated measurements. Using a 12-ha spatially explicit plot censused 13 years apart in an approximately 500-year-old Pseudotsuga-Tsuga forest, we demonstrate significant density-dependent mortality and spatially aggregated tree recruitment. However, the combined effect of these strongly nonrandom demographic processes was to maintain tree patterns in a state of dynamic equilibrium. Density-dependent mortality was most pronounced for the dominant late-successional species, Tsuga heterophylla. The long-lived, early-seral Pseudotsuga menziesii experienced an annual stem mortality rate of 0.84% and no new recruitment. Late-seral species Tsuga and Abies amabilis had nearly balanced demographic rates of ingrowth and mortality. The 2.34% mortality rate for Taxus brevifolia was higher than expected, notably less than ingrowth, and strongly affected by proximity to Tsuga. Large-diameter Tsuga structured both the regenerating conspecific and heterospecific cohorts with recruitment of Tsuga and Abies unlikely in neighborhoods crowded with large-diameter competitors (P < 0.001). Density-dependent competitive interactions strongly shape forest communities even five centuries after stand initiation, underscoring the dynamic nature of even equilibrial old-growth forests.

Spatial and Temporal Trends of Global Pollination Benefit

PubMed Central

Lautenbach, Sven; Seppelt, Ralf; Liebscher, Juliane; Dormann, Carsten F.

2012-01-01

Pollination is a well-studied and at the same time a threatened ecosystem service. A significant part of global crop production depends on or profits from pollination by animals. Using detailed information on global crop yields of 60 pollination dependent or profiting crops, we provide a map of global pollination benefits on a 5′ by 5′ latitude-longitude grid. The current spatial pattern of pollination benefits is only partly correlated with climate variables and the distribution of cropland. The resulting map of pollination benefits identifies hot spots of pollination benefits at sufficient detail to guide political decisions on where to protect pollination services by investing in structural diversity of land use. Additionally, we investigated the vulnerability of the national economies with respect to potential decline of pollination services as the portion of the (agricultural) economy depending on pollination benefits. While the general dependency of the agricultural economy on pollination seems to be stable from 1993 until 2009, we see increases in producer prices for pollination dependent crops, which we interpret as an early warning signal for a conflict between pollination service and other land uses at the global scale. Our spatially explicit analysis of global pollination benefit points to hot spots for the generation of pollination benefits and can serve as a base for further planning of land use, protection sites and agricultural policies for maintaining pollination services. PMID:22563427

Mustiscaling Analysis applied to field Water Content through Distributed Fiber Optic Temperature sensing measurements

NASA Astrophysics Data System (ADS)

Benitez Buelga, Javier; Rodriguez-Sinobas, Leonor; Sanchez, Raul; Gil, Maria; Tarquis, Ana M.

2014-05-01

Soils can be seen as the result of spatial variation operating over several scales. This observation points to 'variability' as a key soil attribute that should be studied. Soil variability has often been considered to be composed of 'functional' (explained) variations plus random fluctuations or noise. However, the distinction between these two components is scale dependent because increasing the scale of observation almost always reveals structure in the noise. Geostatistical methods and, more recently, multifractal/wavelet techniques have been used to characterize scaling and heterogeneity of soil properties among others coming from complexity science. Multifractal formalism, first proposed by Mandelbrot (1982), is suitable for variables with self-similar distribution on a spatial domain (Kravchenko et al., 2002). Multifractal analysis can provide insight into spatial variability of crop or soil parameters (Vereecken et al., 2007). This technique has been used to characterize the scaling property of a variable measured along a transect as a mass distribution of a statistical measure on a spatial domain of the studied field (Zeleke and Si, 2004). To do this, it divides the transect into a number of self-similar segments. It identifies the differences among the subsets by using a wide range of statistical moments. Wavelets were developed in the 1980s for signal processing, and later introduced to soil science by Lark and Webster (1999). The wavelet transform decomposes a series; whether this be a time series (Whitcher, 1998; Percival and Walden, 2000), or as in our case a series of measurements made along a transect; into components (wavelet coefficients) which describe local variation in the series at different scale (or frequency) intervals, giving up only some resolution in space (Lark et al., 2003, 2004). Wavelet coefficients can be used to estimate scale specific components of variation and correlation. This allows us to see which scales contribute most to signal variation, or to see at which scales signals are most correlated. This can give us an insight into the dominant processes An alternative to both of the above methods has been described recently. Relative entropy and increments in relative entropy has been applied in soil images (Bird et al., 2006) and in soil transect data (Tarquis et al., 2008) to study scale effects localized in scale and provide the information that is complementary to the information about scale dependencies found across a range of scales. We will use them in this work to describe the spatial scaling properties of a set of field water content data measured in an extension of a corn field, in a plot of 500 m2 and an spatial resolution of 25 cm. These measurements are based on an optics cable (BruggSteal) buried on a ziz-zag deployment at 30cm depth. References Bird, N., M.C. Díaz, A. Saa, and A.M. Tarquis. 2006. A review of fractal and multifractal analysis of soil pore-scale images. J. Hydrol. 322:211-219. Kravchenko, A.N., R. Omonode, G.A. Bollero, and D.G. Bullock. 2002. Quantitative mapping of soil drainage classes using topographical data and soil electrical conductivity. Soil Sci. Soc. Am. J. 66:235-243. Lark, R.M., A.E. Milne, T.M. Addiscott, K.W.T. Goulding, C.P. Webster, and S. O'Flaherty. 2004. Scale- and location-dependent correlation of nitrous oxide emissions with soil properties: An analysis using wavelets. Eur. J. Soil Sci. 55:611-627. Lark, R.M., S.R. Kaffka, and D.L. Corwin. 2003. Multiresolution analysis of data on electrical conductivity of soil using wavelets. J. Hydrol. 272:276-290. Lark, R. M. and Webster, R. 1999. Analysis and elucidation of soil variation using wavelets. European J. of Soil Science, 50(2): 185-206. Mandelbrot, B.B. 1982. The fractal geometry of nature. W.H. Freeman, New York. Percival, D.B., and A.T. Walden. 2000. Wavelet methods for time series analysis. Cambridge Univ. Press, Cambridge, UK. Tarquis, A.M., N.R. Bird, A.P. Whitmore, M.C. Cartagena, and Y. Pachepsky. 2008. Multiscale analysis of soil transect data. Vadose Zone J. 7: 563-569. Vereecken, H., R. Kasteel, J. Vanderborght, and T. Harter. 2007. Upscaling hydraulic properties and soil water flow processes in heterogeneous soils: A review. Vadose Zone J. 6:1-28. Whitcher, B.J. 1998. Assessing nonstationary time series using wavelets. Ph.D. diss. Univ. of Washington, Seattle (Diss. Abstr. 9907961). Zeleke, T.B., and B.C. Si. 2004. Scaling properties of topographic indices and crop yield: Multifractal and joint multifractal approaches. Agron J., 96:1082-1090.

High nymphal host density and mortality negatively impact parasitoid complex during an insect herbivore outbreak.

PubMed

Hall, Aidan A G; Johnson, Scott N; Cook, James M; Riegler, Markus

2017-08-26

Insect herbivore outbreaks frequently occur and this may be due to factors that restrict top-down control by parasitoids, for example, host-parasitoid asynchrony, hyperparasitization, resource limitation and climate. Few studies have examined host-parasitoid density relationships during an insect herbivore outbreak in a natural ecosystem with diverse parasitoids. We studied parasitization patterns of Cardiaspina psyllids during an outbreak in a Eucalyptus woodland. First, we established the trophic roles of the parasitoids through a species-specific multiplex PCR approach on mummies from which parasitoids emerged. Then, we assessed host-parasitoid density relationships across three spatial scales (leaf, tree and site) over one year. We detected four endoparasitoid species of the family Encyrtidae (Hymenoptera); two primary parasitoid and one heteronomous hyperparasitoid Psyllaephagus species (the latter with female development as a primary parasitoid and male development as a hyperparasitoid), and the hyperparasitoid Coccidoctonus psyllae. Parasitoid development was host-synchronized, although synchrony between sites appeared constrained during winter (due to temperature differences). Parasitization was predominantly driven by one primary parasitoid species and was mostly inversely host-density dependent across the spatial scales. Hyperparasitization by C. psyllae was psyllid-density dependent at the site scale, however, this only impacted the rarer primary parasitoid. High larval parasitoid mortality due to density-dependent nymphal psyllid mortality (a consequence of resource limitation) compounded by a summer heat wave was incorporated in the assessment and resulted in density independence of host-parasitoid relationships. As such, high larval parasitoid mortality during insect herbivore outbreaks may contribute to the absence of host density-dependent parasitization during outbreak events. © 2017 Institute of Zoology, Chinese Academy of Sciences.

The influence of spatially and temporally varying oceanographic conditions on meroplanktonic metapopulations

NASA Astrophysics Data System (ADS)

Botsford, L. W.; Moloney, C. L.; Hastings, A.; Largier, J. L.; Powell, T. M.; Higgins, K.; Quinn, J. F.

We synthesize the results of several modelling studies that address the influence of variability in larval transport and survival on the dynamics of marine metapopulations distributed along a coast. Two important benthic invertebrates in the California Current System (CCS), the Dungeness crab and the red sea urchin, are used as examples of the way in which physical oceanographic conditions can influence stability, synchrony and persistence of meroplanktonic metapopulations. We first explore population dynamics of subpopulations and metapopulations. Even without environmental forcing, isolated local subpopulations with density-dependence can vary on time scales roughly twice the generation time at high adult survival, shifting to annual time scales at low survivals. The high frequency behavior is not seen in models of the Dungeness crab, because of their high adult survival rates. Metapopulations with density-dependent recruitment and deterministic larval dispersal fluctuate in an asynchronous fashion. Along the coast, abundance varies on spatial scales which increase with dispersal distance. Coastwide, synchronous, random environmental variability tends to synchronize these metapopulations. Climate change could cause a long-term increase or decrease in mean larval survival, which in this model leads to greater synchrony or extinction respectively. Spatially managed metapopulations of red sea urchins go extinct when distances between harvest refugia become greater than the scale of larval dispersal. All assessments of population dynamics indicate that metapopulation behavior in general dependes critically on the temporal and spatial nature of larval dispersal, which is largely determined by physical oceanographic conditions. We therfore explore physical influences on larval dispersal patterns. Observed trends in temperature and salinity applied to laboratory-determined responses indicate that natural variability in temperature and salinity can lead to variability in larval development period on interannual (50%), intra-annual (20%) and latitudinal (200%) scales. Variability in development period significantly influences larval survival and, thus, net transport. Larval drifters that undertake diel vertical migration in a primitive equation model of coastal circulation (SPEM) demonstrate the importance of vertical migration in determining horizontal transport. Empirically derived estimates of the effects of wind forcing on larval transport of vertically migrating larvae (wind drift when near the surface and Ekman transport below the surface) match cross-shelf distributions in 4 years of existing larval data. We use a one-dimensional advection-diffusion model, which includes intra-annual timing of cross-shelf flows in the CCS, to explore the combined effects on settlement: (1) temperature- and salinity-dependent development and survival rates and (2) possible horizontal transport due to vertical migration of crab larvae. Natural variability in temperature, wind forcing, and the timing of the spring transition can cause the observed variability in recruitment. We conclude that understanding the dynamics of coastally distributed metapopulations in response to physically-induced variability in larval dispersal will be a critical step in assessing the effects of climate change on marine populations.

Modeling trends from North American Breeding Bird Survey data: a spatially explicit approach

USGS Publications Warehouse

Bled, Florent; Sauer, John R.; Pardieck, Keith L.; Doherty, Paul; Royle, J. Andy

2013-01-01

Population trends, defined as interval-specific proportional changes in population size, are often used to help identify species of conservation interest. Efficient modeling of such trends depends on the consideration of the correlation of population changes with key spatial and environmental covariates. This can provide insights into causal mechanisms and allow spatially explicit summaries at scales that are of interest to management agencies. We expand the hierarchical modeling framework used in the North American Breeding Bird Survey (BBS) by developing a spatially explicit model of temporal trend using a conditional autoregressive (CAR) model. By adopting a formal spatial model for abundance, we produce spatially explicit abundance and trend estimates. Analyses based on large-scale geographic strata such as Bird Conservation Regions (BCR) can suffer from basic imbalances in spatial sampling. Our approach addresses this issue by providing an explicit weighting based on the fundamental sample allocation unit of the BBS. We applied the spatial model to three species from the BBS. Species have been chosen based upon their well-known population change patterns, which allows us to evaluate the quality of our model and the biological meaning of our estimates. We also compare our results with the ones obtained for BCRs using a nonspatial hierarchical model (Sauer and Link 2011). Globally, estimates for mean trends are consistent between the two approaches but spatial estimates provide much more precise trend estimates in regions on the edges of species ranges that were poorly estimated in non-spatial analyses. Incorporating a spatial component in the analysis not only allows us to obtain relevant and biologically meaningful estimates for population trends, but also enables us to provide a flexible framework in order to obtain trend estimates for any area.

Determination of Spatio-Temporal Characteristics of D-region Electron Density during Annular Solar Eclipse from VLF Network Observations

NASA Astrophysics Data System (ADS)

Basak, T.; Hobara, Y.

2015-12-01

A major part of the path of the annular solar eclipse of May 20, 2012 (magnitude 0.9439) was over southern Japan. The D-region ionospheric changes associated with that eclipse, led to several degree of observable perturbations of sub-ionospheric very low frequency (VLF) radio signal. The University of Electro-Communications (UEC) operates VLF observation network over Japan. The solar eclipse associated signal changes were recorded in several receiving stations (Rx) simultaneously for the VLF signals coming from NWC/19.8kHz, JJI/22.2kHz, JJY/40.0kHz, NLK/24.8kHz and other VLF transmitters (Tx). These temporal dependences of VLF signal perturbation have been analyzed and the spatio-temporal characteristics of respective sub-ionospheric perturbations has already been studied by earlier workers using 2D-Finite Difference Time Domain method of simulation. In this work, we determine the spatial scale, depth and temporal dependence of lower ionospheric perturbation in consistence with umbral and penumbral motion. We considered the 2-parameter D-region ionospheric model with exponential electron density profile. To model the solar obscuration effect over it, we assumed a generalized space-time dependent 2-dimensional elliptical Gaussian distribution for ionospheric parameters, such as, effective reflection height (h') and sharpness factor (β). The depth (△hmax, △βmax), center of shadow (lato(t), lono(t)) and spatial scale (σlat,lon) of that Gaussian distribution are used as model parameters. In the vicinity of the eclipse zone, we compute the VLF signal perturbations using Long Wave Propagation Capability (LWPC) code for several signal propagation paths. The propagation path characteristics, such as, ground and water conductivity and geomagnetic effect on ionosphere are considered from standard LWPC prescriptions. The model parameters are tuned to set an optimum agreement between our computation and observed positive and negative type of VLF perturbations. Thus, appropriate set of parameters lead us to the possible determination of spatial scale, depth and temporal dependence of eclipse associated D-region electron density perturbation solely from the VLF-network observations coupled with theoretical modeling.

The biogeodynamics of microbial landscapes

NASA Astrophysics Data System (ADS)

Battin, T. J.; Hödl, I.; Bertuzzo, E.; Mari, L.; Suweis, S. S.; Rinaldo, A.

2011-12-01

Spatial configuration is fundamental in defining the structural and functional properties of biological systems. Biofilms, surface-attached and matrix-enclosed microorganisms, are a striking example of spatial organisation. Coupled biotic and abiotic processes shape the spatial organisation across scales of the landscapes formed by these benthic biofilms in streams and rivers. Experimenting with such biofilms in streams, we found that, depending on the streambed topography and the related hydrodynamic microenvironment, biofilm landscapes form increasingly diverging spatial patterns as they grow. Strikingly, however, cluster size distributions tend to converge even in contrasting hydrodynamic microenvironments. To reproduce the observed cluster size distributions we used a continuous, size-structured population model. The model accounts for the formation, growth, erosion and merging of biofilm clusters. Our results suggest not only that hydrodynamic forcing induce the diverging patterning of the microbial landscape, but also that microorganisms have developed strategies to equally exploit spatial resources independently of the physical structure of the microenvironment where they live.

Parametric spatiotemporal oscillation in reaction-diffusion systems.

PubMed

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Parametric spatiotemporal oscillation in reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Computing aerodynamic sound using advanced statistical turbulence theories

NASA Technical Reports Server (NTRS)

Hecht, A. M.; Teske, M. E.; Bilanin, A. J.

1981-01-01

It is noted that the calculation of turbulence-generated aerodynamic sound requires knowledge of the spatial and temporal variation of Q sub ij (xi sub k, tau), the two-point, two-time turbulent velocity correlations. A technique is presented to obtain an approximate form of these correlations based on closure of the Reynolds stress equations by modeling of higher order terms. The governing equations for Q sub ij are first developed for a general flow. The case of homogeneous, stationary turbulence in a unidirectional constant shear mean flow is then assumed. The required closure form for Q sub ij is selected which is capable of qualitatively reproducing experimentally observed behavior. This form contains separation time dependent scale factors as parameters and depends explicitly on spatial separation. The approximate forms of Q sub ij are used in the differential equations and integral moments are taken over the spatial domain. The velocity correlations are used in the Lighthill theory of aerodynamic sound by assuming normal joint probability.

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

NASA Astrophysics Data System (ADS)

Mann, B. F.; Small, C.

2014-12-01

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

Cities, traffic, and CO 2: A multidecadal assessment of trends, drivers, and scaling relationships

DOE PAGES

Gately, Conor K.; Hutyra, Lucy R.; Sue Wing, Ian

2015-04-06

Emissions of CO 2 from road vehicles were 1.57 billion metric tons in 2012, accounting for 28% of US fossil fuel CO 2 emissions, but the spatial distributions of these emissions are highly uncertain. We develop a new emissions inventory, the Database of Road Transportation Emissions (DARTE), which estimates CO 2 emitted by US road transport at a resolution of 1 km annually for 1980-2012. DARTE reveals that urban areas are responsible for 80% of on-road emissions growth since 1980 and for 63% of total 2012 emissions. We observe nonlinearities between CO 2 emissions and population density at broad spatial/temporalmore » scales, with total on-road CO 2 increasing nonlinearly with population density, rapidly up to 1,650 persons per square kilometer and slowly thereafter. Per capita emissions decline as density rises, but at markedly varying rates depending on existing densities. Here, we make use of DARTE's bottom-up construction to highlight the biases associated with the common practice of using population as a linear proxy for disaggregating national- or state-scale emissions. Comparing DARTE with existing downscaled inventories, we find biases of 100% or more in the spatial distribution of urban and rural emissions, largely driven by mismatches between inventory downscaling proxies and the actual spatial patterns of vehicle activity at urban scales. Here, given cities' dual importance as sources of CO 2 and an emerging nexus of climate mitigation initiatives, high-resolution estimates such as DARTE are critical both for accurately quantifying surface carbon fluxes and for verifying the effectiveness of emissions mitigation efforts at urban scales.« less

Consistency of Aquarius version-4 sea surface salinity with Argo products on various spatial and temporal scales

NASA Astrophysics Data System (ADS)

Lee, T.

2016-12-01

Understanding the accuracies of satellite-derived sea surface salinity (SSS) measurements in depicting temporal changes and the dependence of the accuracies on spatio-temporal scales are important to applications, capability assessment, and future mission design. This study quantifies the consistency between Aquarius Version-4 monthly gridded SSS (released in October 2015) with two widely used Argo monthly gridded near-surface salinity products. The analysis focused on their consistency in depicting temporal changes (including seasonal and non-seasonal) on various spatial scales: 1°x1°, 3°x3°, and 10°x10°. Globally averaged standard deviation (STD) values for Aquarius-Argo salinity differences on these three spatial scales are 0.16, 0.14, 0.09 psu, compared to those between the two Argo products of 0.10, 0.09, and 0.04 psu. Aquarius SSS compare better with Argo data on non-seasonal (e.g., interannual and intraseasonal) than for seasonal time scales. The seasonal Aquarius-Argo SSS differences are mostly concentrated at high latitudes. The Aquarius team is making active efforts to further reduce these high-latitude seasonal biases. The consistency between Aquarius and Argo salinity is similar to that between the two Argo products in the tropics and subtropics for non-seasonal signals, and in the tropics for seasonal signals. Therefore, the representativeness errors of the Argo products for various spatial scales (related to sampling and gridding) need to be taken into account when estimating the uncertainty of Aquarius SSS. The globally averaged uncertainty of large-scale (10°x10°) non-seasonal Aquarius SSS is approximately 0.04 psu. These estimates reflect the significant improvements of Aquarius Version-4 SSS over the previous versions. The estimates can be used as baseline requirements for future ocean salinity missions from space.

Mammalian phylogenetic diversity-area relationships at a continental scale

PubMed Central

Mazel, Florent; Renaud, Julien; Guilhaumon, François; Mouillot, David; Gravel, Dominique; Thuiller, Wilfried

2015-01-01

In analogy to the species-area relationship (SAR), one of the few laws in Ecology, the phylogenetic diversity-area relationship (PDAR) describes the tendency of phylogenetic diversity (PD) to increase with area. Although investigating PDAR has the potential to unravel the underlying processes shaping assemblages across spatial scales and to predict PD loss through habitat reduction, it has been little investigated so far. Focusing on PD has noticeable advantages compared to species richness (SR) since PD also gives insights on processes such as speciation/extinction, assembly rules and ecosystem functioning. Here we investigate the universality and pervasiveness of the PDAR at continental scale using terrestrial mammals as study case. We define the relative robustness of PD (compared to SR) to habitat loss as the area between the standardized PDAR and standardized SAR (i.e. standardized by the diversity of the largest spatial window) divided by the area under the standardized SAR only. This metric quantifies the relative increase of PD robustness compared to SR robustness. We show that PD robustness is higher than SR robustness but that it varies among continents. We further use a null model approach to disentangle the relative effect of phylogenetic tree shape and non random spatial distribution of evolutionary history on the PDAR. We find that for most spatial scales and for all continents except Eurasia, PDARs are not different from expected by a model using only the observed SAR and the shape of the phylogenetic tree at continental scale. Interestingly, we detect a strong phylogenetic structure of the Eurasian PDAR that can be predicted by a model that specifically account for a finer biogeographical delineation of this continent. In conclusion, the relative robustness of PD to habitat loss compared to species richness is determined by the phylogenetic tree shape but also depends on the spatial structure of PD. PMID:26649401

Spatial relationships among cereal yields and selected soil physical and chemical properties.

PubMed

Lipiec, Jerzy; Usowicz, Bogusław

2018-08-15

Sandy soils occupy large area in Poland (about 50%) and in the world. This study aimed at determining spatial relationships of cereal yields and the selected soil physical and chemical properties in three study years (2001-2003) on low productive sandy Podzol soil (Podlasie, Poland). The yields and soil properties in plough and subsoil layers were determined at 72-150 points. The test crops were: wheat, wheat and barley mixture and oats. To explore the spatial relationship between cereal yields and each soil property spatial statistics was used. The best fitting models were adjusted to empirical semivariance and cross-semivariance, which were used to draw maps using kriging. Majority of the soil properties and crop yields exhibited low and medium variability (coefficient of variation 5-70%). The effective ranges of the spatial dependence (the distance at which data are autocorrelated) for yields and all soil properties were 24.3-58.5m and 10.5-373m, respectively. Nugget to sill ratios showed that crop yields and soil properties were strongly spatially dependent except bulk density. Majority of the pairs in cross-semivariograms exhibited strong spatial interdependence. The ranges of the spatial dependence varied in plough layer between 54.6m for yield×pH up to 2433m for yield×silt content. Corresponding ranges in subsoil were 24.8m for crop yield×clay content in 2003 and 1404m for yield×bulk density. Kriging maps allowed separating sub-field area with the lowest yield and soil cation exchange capacity, organic carbon content and pH. This area had lighter color on the aerial photograph due to high content of the sand and low content of soil organic carbon. The results will help farmers at identifying sub-field areas for applying localized management practices to improve these soil properties and further spatial studies in larger scale. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

The spatially resolved star formation history of CALIFA galaxies. Cosmic time scales

NASA Astrophysics Data System (ADS)

García-Benito, R.; González Delgado, R. M.; Pérez, E.; Cid Fernandes, R.; Cortijo-Ferrero, C.; López Fernández, R.; de Amorim, A. L.; Lacerda, E. A. D.; Vale Asari, N.; Sánchez, S. F.

2017-12-01

This paper presents the mass assembly time scales of nearby galaxies observed by CALIFA at the 3.5 m telescope in Calar Alto. We apply the fossil record method of the stellar populations to the complete sample of the 3rd CALIFA data release, with a total of 661 galaxies, covering stellar masses from 108.4 to 1012M⊙ and a wide range of Hubble types. We apply spectral synthesis techniques to the datacubes and process the results to produce the mass growth time scales and mass weighted ages, from which we obtain temporal and spatially resolved information in seven bins of galaxy morphology (E, S0, Sa, Sb, Sc, and Sd) and six bins of stellar mass and stellar mass surface density. We use three different tracers of the spatially resolved star formation history (mass assembly curves, ratio of half mass to half light radii, and mass-weighted age gradients) to test if galaxies grow inside-out, and its dependence with galaxy stellar mass, stellar mass surface density, and morphology. Our main results are as follows: (a) the innermost regions of galaxies assemble their mass at an earlier time than regions located in the outer parts; this happens at any given stellar mass (M⋆), stellar mass surface density (Σ⋆), or Hubble type, including the lowest mass systems in our sample. (b) Galaxies present a significant diversity in their characteristic formation epochs for lower-mass systems. This diversity shows a strong dependence of the mass assembly time scales on Σ⋆ and Hubble type in the lower-mass range (108.4 to 1010.4), but a very mild dependence in higher-mass bins. (c) The lowest half mass radius (HMR) to half light radius (HLR) ratio is found for galaxies between 1010.4 and 1011.1M⊙, where galaxies are 25% smaller in mass than in light. Low-mass galaxies show the largest ratio with HMR/HLR 0.89. Sb and Sbc galaxies present the lowest HMR/HLR ratio (0.74). The ratio HMR/HLR is always, on average, below 1, indicating that galaxies grow faster in mass than in light. (d) All galaxies show negative ⟨log age⟩ M gradients in the inner 1 HLR. The profile flattens (slope less negative) with increasing values of Σ⋆. There is no significant dependence on M⋆ within a particular Σ⋆ bin, except for the lowest bin, where the gradients becomes steeper. (e) Downsizing is spatially preserved as a function of M⋆ and Σ⋆, but it is broken for E and SO where the outer parts are assembled in later epochs than Sa galaxies. These results suggest that independently of their stellar mass, stellar mass surface density, and morphology, galaxies form inside-out on average.

The Backscattering Phase Function for a Sphere with a Two-Scale Relief of Rough Surface

NASA Astrophysics Data System (ADS)

Klass, E. V.

2017-12-01

The backscattering of light from spherical surfaces characterized by one and two-scale roughness reliefs has been investigated. The analysis is performed using the three-dimensional Monte-Carlo program POKS-RG (geometrical-optics approximation), which makes it possible to take into account the roughness of objects under study by introducing local geometries of different levels. The geometric module of the program is aimed at describing objects by equations of second-order surfaces. One-scale roughness is set as an ensemble of geometric figures (convex or concave halves of ellipsoids or cones). The two-scale roughness is modeled by convex halves of ellipsoids, with surface containing ellipsoidal pores. It is shown that a spherical surface with one-scale convex inhomogeneities has a flatter backscattering phase function than a surface with concave inhomogeneities (pores). For a sphere with two-scale roughness, the dependence of the backscattering intensity is found to be determined mostly by the lower-level inhomogeneities. The influence of roughness on the dependence of the backscattering from different spatial regions of spherical surface is analyzed.

A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

NASA Astrophysics Data System (ADS)

Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

2017-04-01

The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of land-use/land-cover changes and river regulation on network-scale connectivity.

Global and local indicators of spatial association between points and polygons: A study of land use change

NASA Astrophysics Data System (ADS)

Guo, Luo; Du, Shihong; Haining, Robert; Zhang, Lianjun

2013-04-01

The existing indicators related to spatial association, especially the K function, can measure only the same dimension of vector data, such as points, lines and polygons, respectively. We develop four new indicators that can analyze and model spatial association for the mixture of different dimensions of vector data, such as lines and points, points and polygons, lines and polygons. The four indicators can measure the spatial association between points and polygons from both global and local perspectives. We also apply the presented methods to investigate the association of temples and villages on land-use change at multiple distance scales in the Guoluo Tibetan Autonomous Prefecture in Qinghai Province, PR China. Global indicators show that temples are positively associated with land-use change at large spatial distances (e.g., >6000 m), while the association between villages and land-use change is insignificant at all distance scales. Thus temples, as religious and cultural centers, have a stronger association with land-use change than the places where people live. However, local indicators show that these associations vary significantly in different sub-areas of the study region. Furthermore, the association of temples with land-use change is also dependent on the specific type of land-use change. The case study demonstrates that the presented indicators are powerful tools for analyzing the spatial association between points and polygons.

[Response of fine roots to soil nutrient spatial heterogeneity].

PubMed

Wang, Qingcheng; Cheng, Yunhuan

2004-06-01

The spatial heterogeneity is the complexity and variation of systems or their attributes, and the heterogeneity of soil nutrients is ubiquitous in all natural ecosystems. The scale of spatial heterogeneity varies considerably among different ecosystems, from tens of centimeters to hundred meters. Some of the scales can be detected by individual plant. Because the growth of individual plants can be strongly influenced by soil heterogeneity, it follows that the inter-specific competition should also be affected. During the long process of evolution, plants developed various plastic responses with their root system, including morphological, physiological and mycorrhizal plasticity, to maximize the nutrient acquisition from heterogeneous soil resources. Morphological plasticity, an adjustment in root system spatial allocation and architecture in response to spatial heterogeneous distribution of available soil resources, has been most intensively studied, and root proliferation in nutrient rich patches has been certified for many species. The species that do respond may have an increased rate of nutrient uptake, leading to a competitive advantage. Scale and precision are two important features employed in describing the size and foraging behavior of root system. It was hypothesized that scale and precision is negatively related, i. e., the species with high scale of root system tend to be a less precise forager. The outcomes of different research work have been diverse, far from reaching a consensus. Species with high scale are not necessarily less precise in fine root allocation, and vice versa. The proliferation of fine root in enriched micro-sites is species dependent, and also affected by other factors, such as patch attributes (size and nutrients concentration), nutrients, and overall soil fertility. Beside root proliferation in nutrient enriched patches, plants can also adapt themselves to the heterogeneous soil environment by altering other root characteristics such as fine root diameter, branch angle, length, and spatial architecture of root system. Physiological and mycorrhizal plasticity can add some influence on the morphological plasticity to some extent, but they are less studied. Roots located in different patches can quickly regulate their nutrient uptake kinetics within different nutrient patches, and increase overall nutrient uptake. Physiological response may, to certain extent, reduce morphological response, and is meaningful for plant growth on soils with frequently changing spatial and temporal heterogeneity. Mycorrhizal plasticity has been least studied so far. Some researches revealed that mycorrhiza, rather than fine root, proliferated in enriched patches. But, it is not the case with other studies. The proliferation of mycorrhiza within enriched patches is more profitable in term of carbon invest. The effect of fine root proliferation on nutrient uptake is complex, depending on ion mobility and whether or not neighboring plant exists. The influence of root plasticity on the growth of plants is species specific. Some species (sensitive species) gain growth benefit, while others don't. The ability of an individual plant to response to heterogeneous resources has significant effect on its competitive ability and its fate within the community, and eventually shapes the composition and structure of the community.

Dynamics of Phenanthrenequinone on Carbon Nano-Onion Surfaces Probed by Quasielastic Neutron Scattering

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

Anjos, Daniela M; Mamontov, Eugene; Brown, Gilbert M

We used quasielastic neutron scattering (QENS) to study the dynamics of phenanthrenequinone (PQ) on the surface of onion-like carbon (OLC), or so called carbon onions, as a function of surface coverage and temperature. For both the high- and low-coverage samples, we observed two diffusion processes; a faster process and nearly an order of magnitude slower process. On the high-coverage surface, the slow diffusion process is of long-range translational character, whereas the fast diffusion process is spatially localized on the length scale of ~ 4.7 . On the low-coverage surface, both diffusion processes are spatially localized; on the same length scalemore » of ~ 4.7 for the fast diffusion and a somewhat larger length scale for the slow diffusion. Arrhenius temperature dependence is observed except for the long-range diffusion on the high-coverage surface. We attribute the fast diffusion process to the generic localized in-cage dynamics of PQ molecules, and the slow diffusion process to the long-range translational dynamics of PQ molecules, which, depending on the coverage, may be either spatially restricted, or long-range. On the low-coverage surface, uniform surface coverage is not attained, and the PQ molecules experience the effect of spatial constraints on their long-range translational dynamics. Unexpectedly, the dynamics of PQ molecules on OLC as a function of temperature and surface coverage bears qualitative resemblance to the dynamics of water molecules on oxide surfaces, including practically temperature-independent residence times for the low-coverage surface. The dynamics features that we observed may be universal across different classes of surface adsorbates.« less

Functional Connectivity of Resting Hemodynamic Signals in Submillimeter Orientation Columns of the Visual Cortex.

PubMed

Vasireddi, Anil K; Vazquez, Alberto L; Whitney, David E; Fukuda, Mitsuhiro; Kim, Seong-Gi

2016-09-07

Resting-state functional magnetic resonance imaging has been increasingly used for examining connectivity across brain regions. The spatial scale by which hemodynamic imaging can resolve functional connections at rest remains unknown. To examine this issue, deoxyhemoglobin-weighted intrinsic optical imaging data were acquired from the visual cortex of lightly anesthetized ferrets. The neural activity of orientation domains, which span a distance of 0.7-0.8 mm, has been shown to be correlated during evoked activity and at rest. We performed separate analyses to assess the degree to which the spatial and temporal characteristics of spontaneous hemodynamic signals depend on the known functional organization of orientation columns. As a control, artificial orientation column maps were generated. Spatially, resting hemodynamic patterns showed a higher spatial resemblance to iso-orientation maps than artificially generated maps. Temporally, a correlation analysis was used to establish whether iso-orientation domains are more correlated than orthogonal orientation domains. After accounting for a significant decrease in correlation as a function of distance, a small but significant temporal correlation between iso-orientation domains was found, which decreased with increasing difference in orientation preference. This dependence was abolished when using artificially synthetized orientation maps. Finally, the temporal correlation coefficient as a function of orientation difference at rest showed a correspondence with that calculated during visual stimulation suggesting that the strength of resting connectivity is related to the strength of the visual stimulation response. Our results suggest that temporal coherence of hemodynamic signals measured by optical imaging of intrinsic signals exists at a submillimeter columnar scale in resting state.

Predictors, spatial distribution, and occurrence of woody invasive plants in subtropical urban ecosystems.

PubMed

Staudhammer, Christina L; Escobedo, Francisco J; Holt, Nathan; Young, Linda J; Brandeis, Thomas J; Zipperer, Wayne

2015-05-15

We examined the spatial distribution, occurrence, and socioecological predictors of woody invasive plants (WIP) in two subtropical, coastal urban ecosystems: San Juan, Puerto Rico and Miami-Dade, United States. These two cities have similar climates and ecosystems typical of subtropical regions but differ in socioeconomics, topography, and urbanization processes. Using permanent plot data, available forest inventory protocols and statistical analyses of geographic and socioeconomic spatial predictors, we found that landscape level distribution and occurrence of WIPs was not clustered. We also characterized WIP composition and occurrence using logistic models, and found they were strongly related to the proportional area of residential land uses. However, the magnitude and trend of increase depended on median household income and grass cover. In San Juan, WIP occurrence was higher in areas of high residential cover when incomes were low or grass cover was low, whereas the opposite was true in Miami-Dade. Although Miami-Dade had greater invasive shrub cover and numbers of WIP species, San Juan had far greater invasive tree density, basal area and crown cover. This study provides an approach for incorporating field and available census data in geospatial distribution models of WIPs in cities throughout the globe. Findings indicate that identifying spatial predictors of WIPs depends on site-specific factors and the ecological scale of the predictor. Thus, mapping protocols and policies to eradicate urban WIPs should target indicators of a relevant scale specific to the area of interest for their improved and proactive management. Copyright © 2015 Elsevier Ltd. All rights reserved.

Detecting fractal power-law long-range dependence in pre-sliced cooked pork ham surface intensity patterns using Detrended Fluctuation Analysis.

PubMed

Valous, Nektarios A; Drakakis, Konstantinos; Sun, Da-Wen

2010-10-01

The visual texture of pork ham slices reveals information about the different qualities and perceived image heterogeneity, which is encapsulated as spatial variations in geometry and spectral characteristics. Detrended Fluctuation Analysis (DFA) detects long-range correlations in nonstationary spatial sequences, by a self-similarity scaling exponent alpha. In the current work, the aim is to investigate the usefulness of alpha, using different colour channels (R, G, B, L*, a*, b*, H, S, V, and Grey), as a quantitative descriptor of visual texture in sliced ham surface patterns for the detection of long-range correlations in unidimensional spatial series of greyscale intensity pixel values at 0 degrees , 30 degrees , 45 degrees , 60 degrees , and 90 degrees rotations. Images were acquired from three qualities of pre-sliced pork ham, typically consumed in Ireland (200 slices per quality). Results indicated that the DFA approach can be used to characterize and quantify the textural appearance of the three ham qualities, for different image orientations, with a global scaling exponent. The spatial series extracted from the ham images display long-range dependence, indicating an average behaviour around 1/f-noise. Results indicate that alpha has a universal character in quantifying the visual texture of ham surface intensity patterns, with no considerable crossovers that alter the behaviour of the fluctuations. Fractal correlation properties can thus be a useful metric for capturing information embedded in the visual texture of hams. Copyright (c) 2010 The American Meat Science Association. Published by Elsevier Ltd. All rights reserved.

Asymptotics of nonparametric L-1 regression models with dependent data

PubMed Central

ZHAO, ZHIBIAO; WEI, YING; LIN, DENNIS K.J.

2013-01-01

We investigate asymptotic properties of least-absolute-deviation or median quantile estimates of the location and scale functions in nonparametric regression models with dependent data from multiple subjects. Under a general dependence structure that allows for longitudinal data and some spatially correlated data, we establish uniform Bahadur representations for the proposed median quantile estimates. The obtained Bahadur representations provide deep insights into the asymptotic behavior of the estimates. Our main theoretical development is based on studying the modulus of continuity of kernel weighted empirical process through a coupling argument. Progesterone data is used for an illustration. PMID:24955016

Detecting and modelling structures on the micro and the macro scales: Assessing their effects on solute transport behaviour

NASA Astrophysics Data System (ADS)

Haslauer, C. P.; Bárdossy, A.; Sudicky, E. A.

2017-09-01

This paper demonstrates quantitative reasoning to separate the dataset of spatially distributed variables into different entities and subsequently characterize their geostatistical properties, properly. The main contribution of the paper is a statistical based algorithm that matches the manual distinction results. This algorithm is based on measured data and is generally applicable. In this paper, it is successfully applied at two datasets of saturated hydraulic conductivity (K) measured at the Borden (Canada) and the Lauswiesen (Germany) aquifers. The boundary layer was successfully delineated at Borden despite its only mild heterogeneity and only small statistical differences between the divided units. The methods are verified with the more heterogeneous Lauswiesen aquifer K data-set, where a boundary layer has previously been delineated. The effects of the macro- and the microstructure on solute transport behaviour are evaluated using numerical solute tracer experiments. Within the microscale structure, both Gaussian and non-Gaussian models of spatial dependence of K are evaluated. The effects of heterogeneity both on the macro- and the microscale are analysed using numerical tracer experiments based on four scenarios: including or not including the macroscale structures and optimally fitting a Gaussian or a non-Gaussian model for the spatial dependence in the micro-structure. The paper shows that both micro- and macro-scale structures are important, as in each of the four possible geostatistical scenarios solute transport behaviour differs meaningfully.

Forest climate change Vulnerability and Adaptation Assessment in Himalayas

NASA Astrophysics Data System (ADS)

Chitale, V. S.; Shrestha, H. L.; Agarwal, N. K.; Choudhurya, D.; Gilani, H.; Dhonju, H. K.; Murthy, M. S. R.

2014-11-01

Forests offer an important basis for creating and safeguarding more climate-resilient communities over Hindu Kush Himalayan region. The forest ecosystem vulnerability assessment to climate change and developing knowledge base to identify and support relevant adaptation strategies is realized as an urgent need. The multi scale adaptation strategies portray increasing complexity with the increasing levels in terms of data requirements, vulnerability understanding and decision making to choose a particular adaptation strategy. We present here how such complexities could be addressed and adaptation decisions could be either directly supported by open source remote sensing based forestry products or geospatial analysis and modelled products. The forest vulnerability assessment under climate change scenario coupled with increasing forest social dependence was studied using IPCC Landscape scale Vulnerability framework in Chitwan-Annapurna Landscape (CHAL) situated in Nepal. Around twenty layers of geospatial information on climate, forest biophysical and forest social dependence data was used to assess forest vulnerability and associated adaptation needs using self-learning decision tree based approaches. The increase in forest fires, evapotranspiration and reduction in productivity over changing climate scenario was observed. The adaptation measures on enhancing productivity, improving resilience, reducing or avoiding pressure with spatial specificity are identified to support suitable decision making. The study provides spatial analytical framework to evaluate multitude of parameters to understand vulnerabilities and assess scope for alternative adaptation strategies with spatial explicitness.

Relevance of anisotropy and spatial variability of gas diffusivity for soil-gas transport

NASA Astrophysics Data System (ADS)

Schack-Kirchner, Helmer; Kühne, Anke; Lang, Friederike

2017-04-01

Models of soil gas transport generally do not consider neither direction dependence of gas diffusivity, nor its small-scale variability. However, in a recent study, we could provide evidence for anisotropy favouring vertical gas diffusion in natural soils. We hypothesize that gas transport models based on gas diffusion data measured with soil rings are strongly influenced by both, anisotropy and spatial variability and the use of averaged diffusivities could be misleading. To test this we used a 2-dimensional model of soil gas transport to under compacted wheel tracks to model the soil-air oxygen distribution in the soil. The model was parametrized with data obtained from soil-ring measurements with its central tendency and variability. The model includes vertical parameter variability as well as variation perpendicular to the elongated wheel track. Different parametrization types have been tested: [i)]Averaged values for wheel track and undisturbed. em [ii)]Random distribution of soil cells with normally distributed variability within the strata. em [iii)]Random distributed soil cells with uniformly distributed variability within the strata. All three types of small-scale variability has been tested for [j)] isotropic gas diffusivity and em [jj)]reduced horizontal gas diffusivity (constant factor), yielding in total six models. As expected the different parametrizations had an important influence to the aeration state under wheel tracks with the strongest oxygen depletion in case of uniformly distributed variability and anisotropy towards higher vertical diffusivity. The simple simulation approach clearly showed the relevance of anisotropy and spatial variability in case of identical central tendency measures of gas diffusivity. However, until now it did not consider spatial dependency of variability, that could even aggravate effects. To consider anisotropy and spatial variability in gas transport models we recommend a) to measure soil-gas transport parameters spatially explicit including different directions and b) to use random-field stochastic models to assess the possible effects for gas-exchange models.

Scale-dependent associations of Band-tailed Pigeon counts at mineral sites

USGS Publications Warehouse

Overton, Cory T.; Casazza, Michael L.; Coates, Peter S.

2010-01-01

The abundance of Band-tailed Pigeons (Patagioenas fasciata monilis) has declined substantially from historic numbers along the Pacific Coast. Identification of patterns and causative factors of this decline are hampered because habitat use data are limited, and temporal and spatial variability patterns associated with population indices are not known. Furthermore, counts are influenced not only by pigeon abundance but also by rate of visitation to mineral sites, which may not be consistent. To address these issues, we conducted mineral site counts during 2001 and 2002 at 20 locations from 4 regions in the Pacific Northwest, including central Oregon and western Washington, USA, and British Columbia, Canada. We developed inference models that consisted of environmental factors and spatial characteristics at multiple spatial scales. Based on information theory, we compared models within a final set that included variables measured at 3 spatial scales (0.03 ha, 3.14 ha, and 7850 ha). Pigeon counts increased from central Oregon through northern Oregon and decreased into British Columbia. After accounting for this spatial pattern, we found that pigeon counts increased 12% ± 2.7 with a 10% increase in the amount of deciduous forested area within 100 m from a mineral site. Also, distance from the mineral site of interest to the nearest known mineral site was positively related to pigeon counts. These findings provide direction for future research focusing on understanding the relationships between indices of relative abundance and complete counts (censuses) of pigeon populations by identifying habitat characteristics that might influence visitation rates. Furthermore, our results suggest that spatial arrangement of mineral sites influences Band-tailed Pigeon counts and the populations which those counts represent.

Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

NASA Astrophysics Data System (ADS)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.

15x optical zoom and extreme optical image stabilisation: diffraction limited integral field spectroscopy with the Oxford SWIFT spectrograph

NASA Astrophysics Data System (ADS)

Tecza, Matthias; Thatte, Niranjan; Clarke, Fraser; Lynn, James; Freeman, David; Roberts, Jennifer; Dekany, Richard

2012-09-01

When commissioned in November 2008 at the Palomar 200 inch Hale Telescope, the Oxford SWIFT I and z band integral field spectrograph, fed by the adaptive optics system PALAO, provided a wide (3×) range of spatial resolutions: three plate scales of 235 mas, 160 mas, and 80 mas per spaxel over a contiguous field-of-view of 89×44 pixels. Depending on observing conditions and guide star brightness we can choose a seeing limited scale of 235 mas per spaxel, or 160 mas and 80 mas per spaxel for very bright guide star AO with substantial increase of enclosed energy. Over the last two years PALAO was upgraded to PALM-3000: an extreme, high-order adaptive optics system with two deformable mirrors with more than 3000 actuators, promising diffraction limited performance in SWIFT's wavelength range. In order to take advantage of this increased spatial resolution we upgraded SWIFT with new pre-optics allowing us to spatially Nyquist sample the diffraction limited PALM-3000 point spread function with 16 mas resolution, reducing the spaxel scale by another factor of 5×. We designed, manufactured, integrated and tested the new pre-optics in the first half of 2011 and commissioned it in December 2011. Here we present the opto-mechanical design and assembly of the new scale changing optics, as well as laboratory and on-sky commissioning results. In optimal observing conditions we achieve substantial Strehl ratios, delivering the near diffraction limited spatial resolution in the I and z bands.

Understanding the origins of uncertainty in landscape-scale variations of emissions of nitrous oxide

NASA Astrophysics Data System (ADS)

Milne, Alice; Haskard, Kathy; Webster, Colin; Truan, Imogen; Goulding, Keith

2014-05-01

Nitrous oxide is a potent greenhouse gas which is over 300 times more radiatively effective than carbon dioxide. In the UK, the agricultural sector is estimated to be responsible for over 80% of nitrous oxide emissions, with these emissions resulting from livestock and farmers adding nitrogen fertilizer to soils. For the purposes of reporting emissions to the IPCC, the estimates are calculated using simple models whereby readily-available national or international statistics are combined with IPCC default emission factors. The IPCC emission factor for direct emissions of nitrous oxide from soils has a very large uncertainty. This is primarily because the variability of nitrous oxide emissions in space is large and this results in uncertainty that may be regarded as sample noise. To both reduce uncertainty through improved modelling, and to communicate an understanding of this uncertainty, we must understand the origins of the variation. We analysed data on nitrous oxide emission rate and some other soil properties collected from a 7.5-km transect across contrasting land uses and parent materials in eastern England. We investigated the scale-dependence and spatial uniformity of the correlations between soil properties and emission rates from farm to landscape scale using wavelet analysis. The analysis revealed a complex pattern of scale-dependence. Emission rates were strongly correlated with a process-specific function of the water-filled pore space at the coarsest scale and nitrate at intermediate and coarsest scales. We also found significant correlations between pH and emission rates at the intermediate scales. The wavelet analysis showed that these correlations were not spatially uniform and that at certain scales changes in parent material coincided with significant changes in correlation. Our results indicate that, at the landscape scale, nitrate content and water-filled pore space are key soil properties for predicting nitrous oxide emissions and should therefore be incorporated into process models and emission factors for inventory calculations.

Testing scale-dependent effects of seminatural habitats on farmland biodiversity.

PubMed

Dainese, Matteo; Luna, Diego Inclán; Sitzia, Tommaso; Marini, Lorenzo

2015-09-01

The effectiveness of conservation interventions for maximizing biodiversity benefits from agri-environment schemes (AESs) is expected to depend on the quantity of seminatural habitats in the surrounding landscape. To verify this hypothesis, we developed a hierarchical sampling design to assess the effects of field boundary type and cover of seminatural habitats in the landscape at two nested spatial scales. We sampled three types of field boundaries with increasing structural complexity (grass margin, simple hedgerow, complex hedgerow) in paired landscapes with the presence or absence of seminatural habitats (radius 0.5 km), that in turn, were nested within 15 areas with different proportions of seminatural habitats at a larger spatial scale (10 X 10 km). Overall, 90 field boundaries were sampled across a Mediterranean'region (northeastern Italy). We considered species richness response across three different taxonomic groups: vascular plants, butterflies, and tachinid flies. No interactions between type of field boundary and surrounding landscape were found at either 0.5 and 10 km, indicating that the quality of field boundary had the same effect irrespective of the cover of seminatural habitats. At the local scale, extended-width grass margins yielded higher plant species richness, while hedgerows yielded higher species richness of butterflies and tachinids. At the 0.5-km landscape scale, the effect of the proportion of seminatural habitats was neutral for plants and tachinids, while butterflies were positively related to the proportion of forest. At the 10-km landscape scale, only butterflies responded positively to the proportion of seminatural habitats. Our study confirmed the importance of testing multiple scales when considering species from different taxa and with different mobility. We showed that the quality of field boundaries at the local scale was an important factor in enhancing farmland biodiversity. For butterflies, AESs should focus particular attention on preservation'of forest patches in agricultural landscapes within 0.5 kin, as well as the conservation of seminatural habitats at a wider landscape scale.

Scaling up functional traits for ecosystem services with remote sensing: concepts and methods.

PubMed

Abelleira Martínez, Oscar J; Fremier, Alexander K; Günter, Sven; Ramos Bendaña, Zayra; Vierling, Lee; Galbraith, Sara M; Bosque-Pérez, Nilsa A; Ordoñez, Jenny C

2016-07-01

Ecosystem service-based management requires an accurate understanding of how human modification influences ecosystem processes and these relationships are most accurate when based on functional traits. Although trait variation is typically sampled at local scales, remote sensing methods can facilitate scaling up trait variation to regional scales needed for ecosystem service management. We review concepts and methods for scaling up plant and animal functional traits from local to regional spatial scales with the goal of assessing impacts of human modification on ecosystem processes and services. We focus our objectives on considerations and approaches for (1) conducting local plot-level sampling of trait variation and (2) scaling up trait variation to regional spatial scales using remotely sensed data. We show that sampling methods for scaling up traits need to account for the modification of trait variation due to land cover change and species introductions. Sampling intraspecific variation, stratification by land cover type or landscape context, or inference of traits from published sources may be necessary depending on the traits of interest. Passive and active remote sensing are useful for mapping plant phenological, chemical, and structural traits. Combining these methods can significantly improve their capacity for mapping plant trait variation. These methods can also be used to map landscape and vegetation structure in order to infer animal trait variation. Due to high context dependency, relationships between trait variation and remotely sensed data are not directly transferable across regions. We end our review with a brief synthesis of issues to consider and outlook for the development of these approaches. Research that relates typical functional trait metrics, such as the community-weighted mean, with remote sensing data and that relates variation in traits that cannot be remotely sensed to other proxies is needed. Our review narrows the gap between functional trait and remote sensing methods for ecosystem service management.

Heating-insensitive scale increase caused by convective precipitation

NASA Astrophysics Data System (ADS)

Haerter, Jan; Moseley, Christopher; Berg, Peter

2017-04-01

The origin of intense convective extremes and their unusual temperature dependence has recently challenged traditional thermodynamic arguments, based on the Clausius-Clapeyron relation. In a sequence of studies (Lenderink and v. Mejgaard, Nat Geosc, 2008; Berg, Haerter, Moseley, Nat Geosc, 2013; and Moseley, Hohenegger, Berg, Haerter, Nat Geosc, 2016) the argument of convective-type precipitation overcoming the 7%/K increase in extremes by dynamical, rather than thermodynamic, processes has been promoted. How can the role of dynamical processes be approached for precipitating convective cloud? One-phase, non-precipitating Rayleigh-Bénard convection is a classical problem in complex systems science. When a fluid between two horizontal plates is sufficiently heated from below, convective rolls spontaneously form. In shallow, non-precipitating atmospheric convection, rolls are also known to form under specific conditions, with horizontal scales roughly proportional to the boundary layer height. Here we explore within idealized large-eddy simulations, how the scale of convection is modified, when precipitation sets in and intensifies in the course of diurnal solar heating. Before onset of precipitation, Bénard cells with relatively constant diameter form, roughly on the scale of the atmospheric boundary layer. We find that the onset of precipitation then signals an approximately linear (in time) increase in horizontal scale. This scale increase progresses at a speed which is rather insensitive to changes in surface temperature or changes in the rate at which boundary conditions change, hinting at spatial characteristics, rather than temperature, as a possible control on spatial scales of convection. When exploring the depth of spatial correlations, we find that precipitation onset causes a sudden disruption of order and a subsequent complete disintegration of organization —until precipitation eventually ceases. Returning to the initial question of convective extremes, we conclude that the formation of extreme events is a highly nonlinear process. However, our results suggest that crucial features of convective organization throughout the day may be independent of temperature - with possible implications for large-scale model parameterizations. Yet, the timing of the onset of initial precipitation depends strongly on the temperature boundary conditions, where higher temperatures, or earlier, moderate heating, lead to earlier initiation of convection and hence allow for more time for development and the production of extremes.

Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon

USGS Publications Warehouse

Waibel, Michael S.; Gannett, Marshall W.; Chang, Heejun; Hulbe, Christina L.

2013-01-01

We examine the spatial variability of the response of aquifer systems to climate change in and adjacent to the Cascade Range volcanic arc in the Deschutes Basin, Oregon using downscaled global climate model projections to drive surface hydrologic process and groundwater flow models. Projected warming over the 21st century is anticipated to shift the phase of precipitation toward more rain and less snow in mountainous areas in the Pacific Northwest, resulting in smaller winter snowpack and in a shift in the timing of runoff to earlier in the year. This will be accompanied by spatially variable changes in the timing of groundwater recharge. Analysis of historic climate and hydrologic data and modeling studies show that groundwater plays a key role in determining the response of stream systems to climate change. The spatial variability in the response of groundwater systems to climate change, particularly with regard to flow-system scale, however, has generally not been addressed in the literature. Here we simulate the hydrologic response to projected future climate to show that the response of groundwater systems can vary depending on the location and spatial scale of the flow systems and their aquifer characteristics. Mean annual recharge averaged over the basin does not change significantly between the 1980s and 2080s climate periods given the ensemble of global climate models and emission scenarios evaluated. There are, however, changes in the seasonality of groundwater recharge within the basin. Simulation results show that short-flow-path groundwater systems, such as those providing baseflow to many headwater streams, will likely have substantial changes in the timing of discharge in response changes in seasonality of recharge. Regional-scale aquifer systems with flow paths on the order of many tens of kilometers, in contrast, are much less affected by changes in seasonality of recharge. Flow systems at all spatial scales, however, are likely to reflect interannual changes in total recharge. These results provide insights into the possible impacts of climate change to other regional aquifer systems, and the streams they support, where discharge points represent a range of flow system scales.

Calculating Soil Wetness, Evapotranspiration and Carbon Cycle Processes Over Large Grid Areas Using a New Scaling Technique

NASA Technical Reports Server (NTRS)

Sellers, Piers

2012-01-01

Soil wetness typically shows great spatial variability over the length scales of general circulation model (GCM) grid areas (approx 100 km ), and the functions relating evapotranspiration and photosynthetic rate to local-scale (approx 1 m) soil wetness are highly non-linear. Soil respiration is also highly dependent on very small-scale variations in soil wetness. We therefore expect significant inaccuracies whenever we insert a single grid area-average soil wetness value into a function to calculate any of these rates for the grid area. For the particular case of evapotranspiration., this method - use of a grid-averaged soil wetness value - can also provoke severe oscillations in the evapotranspiration rate and soil wetness under some conditions. A method is presented whereby the probability distribution timction(pdf) for soil wetness within a grid area is represented by binning. and numerical integration of the binned pdf is performed to provide a spatially-integrated wetness stress term for the whole grid area, which then permits calculation of grid area fluxes in a single operation. The method is very accurate when 10 or more bins are used, can deal realistically with spatially variable precipitation, conserves moisture exactly and allows for precise modification of the soil wetness pdf after every time step. The method could also be applied to other ecological problems where small-scale processes must be area-integrated, or upscaled, to estimate fluxes over large areas, for example in treatments of the terrestrial carbon budget or trace gas generation.

Spatial heterogeneity and scale-dependent habitat selection for two sympatric raptors in mixed-grass prairie.

PubMed

Atuo, Fidelis Akunke; O'Connell, Timothy John

2017-08-01

Sympatric predators are predicted to partition resources, especially under conditions of food limitation. Spatial heterogeneity that influences prey availability might play an important role in the scales at which potential competitors select habitat. We assessed potential mechanisms for coexistence by examining the role of heterogeneity in resource partitioning between sympatric raptors overwintering in the southern Great Plains. We conducted surveys for wintering Red-tailed hawk ( Buteo jamaicensis ) and Northern Harrier ( Circus cyanea ) at two state wildlife management areas in Oklahoma, USA. We used information from repeated distance sampling to project use locations in a GIS. We applied resource selection functions to model habitat selection at three scales and analyzed for niche partitioning using the outlying mean index. Habitat selection of the two predators was mediated by spatial heterogeneity. The two predators demonstrated significant fine-scale discrimination in habitat selection in homogeneous landscapes, but were more sympatric in heterogeneous landscapes. Red-tailed hawk used a variety of cover types in heterogeneous landscapes but specialized on riparian forest in homogeneous landscapes. Northern Harrier specialized on upland grasslands in homogeneous landscapes but selected more cover types in heterogeneous landscapes. Our study supports the growing body of evidence that landscapes can affect animal behaviors. In the system we studied, larger patches of primary land cover types were associated with greater allopatry in habitat selection between two potentially competing predators. Heterogeneity within the scale of raptor home ranges was associated with greater sympatry in use and less specialization in land cover types selected.

Coincident Occurrences of Tropical Individual Cirrus Clouds and Deep Convective Systems Derived from TRMM Observations

NASA Technical Reports Server (NTRS)

Lin, Bing; Xu, Kuan-Man; Minnis, Patrick; Wielicki, Bruce A.; Hu, Yongxiang; Chambers, Lin; Fan, Alice; Sun, Wenbo

2007-01-01

Measurements of cloud properties and atmospheric radiation taken between January and August 1998 by the Tropical Rainfall Measuring Mission (TRMM) satellite were used to investigate the effect of spatial and temporal scales on the coincident occurrences of tropical individual cirrus clouds (ICCs) and deep convective systems (DCSs). It is found that there is little or even negative correlation between instantaneous occurrences of ICC and DCS in small areas, in which both types of clouds cannot grow and expand simultaneously. When spatial and temporal domains are increased, ICCs become more dependent on DCSs due to the origination of many ICCs from DCSs and moisture supply from the DCS in the upper troposphere for the ICCs to grow, resulting in significant positive correlation between the two types of tropical high clouds in large spatial and long temporal scales. This result may suggest that the decrease of tropical high clouds with SST from model simulations is likely caused by restricted spatial domains and limited temporal periods. Finally, the radiative feedback due to the change in tropical high cloud area coverage with sea surface temperature appears small and about -0.14 W/sq m per degree Kelvin.

Macroecology of unicellular organisms - patterns and processes.

PubMed

Soininen, Janne

2012-02-01

Macroecology examines the relationship between organisms and their environment at large spatial (and temporal) scales. Typically, macroecologists explain the large-scale patterns of abundance, distribution and diversity. Despite the difficulties in sampling and characterizing microbial diversity, macroecologists have recently also been interested in unicellular organisms. Here, I review the current advances made in microbial macroecology, as well as discuss related ecosystem functions. Overall, it seems that microorganisms suit surprisingly well to known species abundance distributions and show positive relationship between distribution and adundance. Microbial species-area and distance-decay relationships tend to be weaker than for macroorganisms, but nonetheless significant. Few findings on altitudinal gradients in unicellular taxa seem to differ greatly from corresponding findings for larger taxa, whereas latitudinal gradients among microorganisms have either been clearly evident or absent depending on the context. Literature also strongly emphasizes the role of spatial scale for the patterns of diversity and suggests that patterns are affected by species traits as well as ecosystem characteristics. Finally, I discuss the large role of local biotic and abiotic variables driving the community assembly in unicellular taxa and eventually dictating how multiple ecosystem processes are performed. Present review highlights the fact that most microorganisms may not differ fundamentally from larger taxa in their large-scale distribution patterns. Yet, review also shows that many aspects of microbial macroecology are still relatively poorly understood and specific patterns depend on focal taxa and ecosystem concerned. © 2011 Society for Applied Microbiology and Blackwell Publishing Ltd.

An automated approach for extracting Barrier Island morphology from digital elevation models

NASA Astrophysics Data System (ADS)

Wernette, Phillipe; Houser, Chris; Bishop, Michael P.

2016-06-01

The response and recovery of a barrier island to extreme storms depends on the elevation of the dune base and crest, both of which can vary considerably alongshore and through time. Quantifying the response to and recovery from storms requires that we can first identify and differentiate the dune(s) from the beach and back-barrier, which in turn depends on accurate identification and delineation of the dune toe, crest and heel. The purpose of this paper is to introduce a multi-scale automated approach for extracting beach, dune (dune toe, dune crest and dune heel), and barrier island morphology. The automated approach introduced here extracts the shoreline and back-barrier shoreline based on elevation thresholds, and extracts the dune toe, dune crest and dune heel based on the average relative relief (RR) across multiple spatial scales of analysis. The multi-scale automated RR approach to extracting dune toe, dune crest, and dune heel based upon relative relief is more objective than traditional approaches because every pixel is analyzed across multiple computational scales and the identification of features is based on the calculated RR values. The RR approach out-performed contemporary approaches and represents a fast objective means to define important beach and dune features for predicting barrier island response to storms. The RR method also does not require that the dune toe, crest, or heel are spatially continuous, which is important because dune morphology is likely naturally variable alongshore.

Scale effect challenges in urban hydrology highlighted with a Fully Distributed Model and High-resolution rainfall data

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire

2017-04-01

Nowadays, there is a growing interest on small-scale rainfall information, provided by weather radars, to be used in urban water management and decision-making. Therefore, an increasing interest is in parallel devoted to the development of fully distributed and grid-based models following the increase of computation capabilities, the availability of high-resolution GIS information needed for such models implementation. However, the choice of an appropriate implementation scale to integrate the catchment heterogeneity and the whole measured rainfall variability provided by High-resolution radar technologies still issues. This work proposes a two steps investigation of scale effects in urban hydrology and its effects on modeling works. In the first step fractal tools are used to highlight the scale dependency observed within distributed data used to describe the catchment heterogeneity, both the structure of the sewer network and the distribution of impervious areas are analyzed. Then an intensive multi-scale modeling work is carried out to understand scaling effects on hydrological model performance. Investigations were conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model was implemented at 17 spatial resolutions ranging from 100 m to 5 m and modeling investigations were performed using both rain gauge rainfall information as well as high resolution X band radar data in order to assess the sensitivity of the model to small scale rainfall variability. Results coming out from this work demonstrate scale effect challenges in urban hydrology modeling. In fact, fractal concept highlights the scale dependency observed within distributed data used to implement hydrological models. Patterns of geophysical data change when we change the observation pixel size. The multi-scale modeling investigation performed with Multi-Hydro model at 17 spatial resolutions confirms scaling effect on hydrological model performance. Results were analyzed at three ranges of scales identified in the fractal analysis and confirmed in the modeling work. The sensitivity of the model to small-scale rainfall variability was discussed as well.

Process, pattern and scale: hydrogeomorphology and plant diversity in forested wetlands across multiple spatial scales

NASA Astrophysics Data System (ADS)

Alexander, L.; Hupp, C. R.; Forman, R. T.

2002-12-01

Many geodisturbances occur across large spatial scales, spanning entire landscapes and creating ecological phenomena in their wake. Ecological study at large scales poses special problems: (1) large-scale studies require large-scale resources, and (2) sampling is not always feasible at the appropriate scale, and researchers rely on data collected at smaller scales to interpret patterns across broad regions. A criticism of landscape ecology is that findings at small spatial scales are "scaled up" and applied indiscriminately across larger spatial scales. In this research, landscape scaling is addressed through process-pattern relationships between hydrogeomorphic processes and patterns of plant diversity in forested wetlands. The research addresses: (1) whether patterns and relationships between hydrogeomorphic, vegetation, and spatial variables can transcend scale; and (2) whether data collected at small spatial scales can be used to describe patterns and relationships across larger spatial scales. Field measurements of hydrologic, geomorphic, spatial, and vegetation data were collected or calculated for 15- 1-ha sites on forested floodplains of six (6) Chesapeake Bay Coastal Plain streams over a total area of about 20,000 km2. Hydroperiod (day/yr), floodplain surface elevation range (m), discharge (m3/s), stream power (kg-m/s2), sediment deposition (mm/yr), relative position downstream and other variables were used in multivariate analyses to explain differences in species richness, tree diversity (Shannon-Wiener Diversity Index H'), and plant community composition at four spatial scales. Data collected at the plot (400-m2) and site- (c. 1-ha) scales are applied to and tested at the river watershed and regional spatial scales. Results indicate that plant species richness and tree diversity (Shannon-Wiener diversity index H') can be described by hydrogeomorphic conditions at all scales, but are best described at the site scale. Data collected at plot and site scales are tested for spatial heterogeneity across the Chesapeake Bay Coastal Plain using a geostatistical variogram, and multiple regression analysis is used to relate plant diversity, spatial, and hydrogeomorphic variables across Coastal Plain regions and hydrologic regimes. Results indicate that relationships between hydrogeomorphic processes and patterns of plant diversity at finer scales can proxy relationships at coarser scales in some, not all, cases. Findings also suggest that data collected at small scales can be used to describe trends across broader scales under limited conditions.

Phase separation driven by density-dependent movement: A novel mechanism for ecological patterns.

PubMed

Liu, Quan-Xing; Rietkerk, Max; Herman, Peter M J; Piersma, Theunis; Fryxell, John M; van de Koppel, Johan

2016-12-01

Many ecosystems develop strikingly regular spatial patterns because of small-scale interactions between organisms, a process generally referred to as spatial self-organization. Self-organized spatial patterns are important determinants of the functioning of ecosystems, promoting the growth and survival of the involved organisms, and affecting the capacity of the organisms to cope with changing environmental conditions. The predominant explanation for self-organized pattern formation is spatial heterogeneity in establishment, growth and mortality, resulting from the self-organization processes. A number of recent studies, however, have revealed that movement of organisms can be an important driving process creating extensive spatial patterning in many ecosystems. Here, we review studies that detail movement-based pattern formation in contrasting ecological settings. Our review highlights that a common principle, where movement of organisms is density-dependent, explains observed spatial regular patterns in all of these studies. This principle, well known to physics as the Cahn-Hilliard principle of phase separation, has so-far remained unrecognized as a general mechanism for self-organized complexity in ecology. Using the examples presented in this paper, we explain how this movement principle can be discerned in ecological settings, and clarify how to test this mechanism experimentally. Our study highlights that animal movement, both in isolation and in unison with other processes, is an important mechanism for regular pattern formation in ecosystems. Copyright © 2016 Elsevier B.V. All rights reserved.

Recollection-Dependent Memory for Event Duration in Large-Scale Spatial Navigation

ERIC Educational Resources Information Center

Brunec, Iva K.; Ozubko, Jason D.; Barense, Morgan D.; Moscovitch, Morris

2017-01-01

Time and space represent two key aspects of episodic memories, forming the spatiotemporal context of events in a sequence. Little is known, however, about how temporal information, such as the duration and the order of particular events, are encoded into memory, and if it matters whether the memory representation is based on recollection or…

Changing spatial patterns of stand-replacing fire in California conifer forests

Treesearch

Jens T. Stevens; Brandon M. Collins; Jay D. Miller; Malcolm P. North; Scott L. Stephens

2017-01-01

Stand-replacing fire has profound ecological impacts in conifer forests, yet there is continued uncertainty over how best to describe the scale of stand-replacing effects within individual fires, and how these effects are changing over time. In forests where regeneration following stand-replacing fire depends on seed dispersal from surviving trees, the size and shape...

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

Treesearch

Kendra E. Kaiser; Ryan E. Emanuel

2013-01-01

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

Cell Migration Analysis: A Low-Cost Laboratory Experiment for Cell and Developmental Biology Courses Using Keratocytes from Fish Scales

ERIC Educational Resources Information Center

Prieto, Daniel; Aparicio, Gonzalo; Sotelo-Silveira, Jose R.

2017-01-01

Cell and developmental processes are complex, and profoundly dependent on spatial relationships that change over time. Innovative educational or teaching strategies are always needed to foster deep comprehension of these processes and their dynamic features. However, laboratory exercises in cell and developmental biology at the undergraduate level…

Scaling relations for watersheds

NASA Astrophysics Data System (ADS)

Fehr, E.; Kadau, D.; Araújo, N. A. M.; Andrade, J. S., Jr.; Herrmann, H. J.

2011-09-01

We study the morphology of watersheds in two and three dimensional systems subjected to different degrees of spatial correlations. The response of these objects to small, local perturbations is also investigated with extensive numerical simulations. We find the fractal dimension of the watersheds to generally decrease with the Hurst exponent, which quantifies the degree of spatial correlations. Moreover, in two dimensions, our results match the range of fractal dimensions 1.10≤df≤1.15 observed for natural landscapes. We report that the watershed is strongly affected by local perturbations. For perturbed two and three dimensional systems, we observe a power-law scaling behavior for the distribution of areas (volumes) enclosed by the original and the displaced watershed and for the distribution of distances between outlets. Finite-size effects are analyzed and the resulting scaling exponents are shown to depend significantly on the Hurst exponent. The intrinsic relation between watershed and invasion percolation, as well as relations between exponents conjectured in previous studies with two dimensional systems, are now confirmed by our results in three dimensions.

Characterization of Thermal Refugia and Biogeochemical Hotspots at Sleepers River Watershed, VT

NASA Astrophysics Data System (ADS)

Hwang, K.; Chandler, D. G.; Kelleher, C.; Shanley, J. B.; Shaw, S. B.

2017-12-01

During low flow, changes in the extent of the channel network in headwater catchments depend on groundwater-surface water interactions, and dictate thermal and biogeochemical heterogeneities. Channel reaches with low temperature may act as refugia for valued species such as brook trout, and warmer reaches with high dissolved organic matter may act as biogeochemical hotspots. Prior studies have found uniform scaling of hydrologic and biogeochemical processes above certain spatial thresholds but sizable heterogeneities in these processes below the threshold. We utilize high resolution measurements of water quality parameters including stream temperature, conductivity and fluorescent dissolved organic matter (fDOM) at tributaries in two catchments of Sleepers River Watershed, Vermont to investigate seasonal and spatial variation of water quality and scaling of stream chemistry within the intensive study area and the larger Sleepers River Watershed. This study leverages findings from various small scale regional studies to identify differences in headwater channel reach behavior in a similar climate across some dissimilar geomorphic units, to inform the identification of thermal refugia and biogeochemical hotspots.

Trophic interactions induce spatial self-organization of microbial consortia on rough surfaces.

PubMed

Wang, Gang; Or, Dani

2014-10-24

The spatial context of microbial interactions common in natural systems is largely absent in traditional pure culture-based microbiology. The understanding of how interdependent microbial communities assemble and coexist in limited spatial domains remains sketchy. A mechanistic model of cell-level interactions among multispecies microbial populations grown on hydrated rough surfaces facilitated systematic evaluation of how trophic dependencies shape spatial self-organization of microbial consortia in complex diffusion fields. The emerging patterns were persistent irrespective of initial conditions and resilient to spatial and temporal perturbations. Surprisingly, the hydration conditions conducive for self-assembly are extremely narrow and last only while microbial cells remain motile within thin aqueous films. The resulting self-organized microbial consortia patterns could represent optimal ecological templates for the architecture that underlie sessile microbial colonies on natural surfaces. Understanding microbial spatial self-organization offers new insights into mechanisms that sustain small-scale soil microbial diversity; and may guide the engineering of functional artificial microbial consortia.

Studies and Application of Remote Sensing Retrieval Method of Soil Moisture Content in Land Parcel Units in Irrigation Area

NASA Astrophysics Data System (ADS)

Zhu, H.; Zhao, H. L.; Jiang, Y. Z.; Zang, W. B.

2018-05-01

Soil moisture is one of the important hydrological elements. Obtaining soil moisture accurately and effectively is of great significance for water resource management in irrigation area. During the process of soil moisture content retrieval with multiremote sensing data, multi- remote sensing data always brings multi-spatial scale problems which results in inconformity of soil moisture content retrieved by remote sensing in different spatial scale. In addition, agricultural water use management has suitable spatial scale of soil moisture information so as to satisfy the demands of dynamic management of water use and water demand in certain unit. We have proposed to use land parcel unit as the minimum unit to do soil moisture content research in agricultural water using area, according to soil characteristics, vegetation coverage characteristics in underlying layer, and hydrological characteristic into the basis of study unit division. We have proposed division method of land parcel units. Based on multi thermal infrared and near infrared remote sensing data, we calculate the ndvi and tvdi index and make a statistical model between the tvdi index and soil moisture of ground monitoring station. Then we move forward to study soil moisture remote sensing retrieval method on land parcel unit scale. And the method has been applied in Hetao irrigation area. Results show that compared with pixel scale the soil moisture content in land parcel unit scale has displayed stronger correlation with true value. Hence, remote sensing retrieval method of soil moisture content in land parcel unit scale has shown good applicability in Hetao irrigation area. We converted the research unit into the scale of land parcel unit. Using the land parcel units with unified crops and soil attributes as the research units more complies with the characteristics of agricultural water areas, avoids the problems such as decomposition of mixed pixels and excessive dependence on high-resolution data caused by the research units of pixels, and doesn't involve compromises in the spatial scale and simulating precision like the grid simulation. When the application needs are met, the production efficiency of products can also be improved at a certain degree.

Dynamics and Steady States in Excitable Mobile Agent Systems

NASA Astrophysics Data System (ADS)

Peruani, Fernando; Sibona, Gustavo J.

2008-04-01

We study the spreading of excitations in 2D systems of mobile agents where the excitation is transmitted when a quiescent agent keeps contact with an excited one during a nonvanishing time. We show that the steady states strongly depend on the spatial agent dynamics. Moreover, the coupling between exposition time (ω) and agent-agent contact rate (CR) becomes crucial to understand the excitation dynamics, which exhibits three regimes with CR: no excitation for low CR, an excited regime in which the number of quiescent agents (S) is inversely proportional to CR, and, for high CR, a novel third regime, model dependent, where S scales with an exponent ξ-1, with ξ being the scaling exponent of ω with CR.

Scale-dependent habitat use by a large free-ranging predator, the Mediterranean fin whale

NASA Astrophysics Data System (ADS)

Cotté, Cédric; Guinet, Christophe; Taupier-Letage, Isabelle; Mate, Bruce; Petiau, Estelle

2009-05-01

Since the heterogeneity of oceanographic conditions drives abundance, distribution, and availability of prey, it is essential to understand how foraging predators interact with their dynamic environment at various spatial and temporal scales. We examined the spatio-temporal relationships between oceanographic features and abundance of fin whales ( Balaenoptera physalus), the largest free-ranging predator in the Western Mediterranean Sea (WM), through two independent approaches. First, spatial modeling was used to estimate whale density, using waiting distance (the distance between detections) for fin whales along ferry routes across the WM, in relation to remotely sensed oceanographic parameters. At a large scale (basin and year), fin whales exhibited fidelity to the northern WM with a summer-aggregated and winter-dispersed pattern. At mesoscale (20-100 km), whales were found in colder, saltier (from an on-board system) and dynamic areas defined by steep altimetric and temperature gradients. Second, using an independent fin whale satellite tracking dataset, we showed that tracked whales were effectively preferentially located in favorable habitats, i.e. in areas of high predicted densities as identified by our previous model using oceanographic data contemporaneous to the tracking period. We suggest that the large-scale fidelity corresponds to temporally and spatially predictable habitat of whale favorite prey, the northern krill ( Meganyctiphanes norvegica), while mesoscale relationships are likely to identify areas of high prey concentration and availability.

Satellite-based Monitoring of global Precipitation using the PERSIANN system: from Weather- to Climate-scales with some application examples

NASA Astrophysics Data System (ADS)

Switzer, A.; Yap, W.; Lauro, F.; Gouramanis, C.; Dominey-Howes, D.; Labbate, M.

2016-12-01

This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.

Satellite-based Monitoring of global Precipitation using the PERSIANN system: from Weather- to Climate-scales with some application examples

NASA Astrophysics Data System (ADS)

Sorooshian, S.; Nguyen, P.; Hsu, K. L.

2017-12-01

This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.

Spatial Distribution of Fate and Transport Parameters Using Cxtfit in a Karstified Limestone Model

NASA Astrophysics Data System (ADS)

Toro, J.; Padilla, I. Y.

2017-12-01

Karst environments have a high capacity to transport and store large amounts of water. This makes karst aquifers a productive resource for human consumption and ecological integrity, but also makes them vulnerable to potential contamination of hazardous chemical substances. High heterogeneity and anisotropy of karst aquifer properties make them very difficult to characterize for accurate prediction of contaminant mobility and persistence in groundwater. Current technologies to characterize and quantify flow and transport processes at field-scale is limited by low resolution of spatiotemporal data. To enhance this resolution and provide the essential knowledge of karst groundwater systems, studies at laboratory scale can be conducted. This work uses an intermediate karstified lab-scale physical model (IKLPM) to study fate and transport processes and assess viable tools to characterize heterogeneities in karst systems. Transport experiments are conducted in the IKLPM using step injections of calcium chloride, uranine, and rhodamine wt tracers. Temporal concentration distributions (TCDs) obtained from the experiments are analyzed using the method of moments and CXTFIT to quantify fate and transport parameters in the system at various flow rates. The spatial distribution of the estimated fate and transport parameters for the tracers revealed high variability related to preferential flow heterogeneities and scale dependence. Results are integrated to define spatially-variable transport regions within the system and assess their fate and transport characteristics.

Energy transfer, pressure tensor, and heating of kinetic plasma

NASA Astrophysics Data System (ADS)

Yang, Yan; Matthaeus, William H.; Parashar, Tulasi N.; Haggerty, Colby C.; Roytershteyn, Vadim; Daughton, William; Wan, Minping; Shi, Yipeng; Chen, Shiyi

2017-07-01

Kinetic plasma turbulence cascade spans multiple scales ranging from macroscopic fluid flow to sub-electron scales. Mechanisms that dissipate large scale energy, terminate the inertial range cascade, and convert kinetic energy into heat are hotly debated. Here, we revisit these puzzles using fully kinetic simulation. By performing scale-dependent spatial filtering on the Vlasov equation, we extract information at prescribed scales and introduce several energy transfer functions. This approach allows highly inhomogeneous energy cascade to be quantified as it proceeds down to kinetic scales. The pressure work, - ( P . ∇ ) . u , can trigger a channel of the energy conversion between fluid flow and random motions, which contains a collision-free generalization of the viscous dissipation in collisional fluid. Both the energy transfer and the pressure work are strongly correlated with velocity gradients.

Short-term spatial and temporal variability in greenhouse gas fluxes in riparian zones.

PubMed

Vidon, P; Marchese, S; Welsh, M; McMillan, S

2015-08-01

Recent research indicates that riparian zones have the potential to contribute significant amounts of greenhouse gases (GHG: N2O, CO2, CH4) to the atmosphere. Yet, the short-term spatial and temporal variability in GHG emission in these systems is poorly understood. Using two transects of three static chambers at two North Carolina agricultural riparian zones (one restored, one unrestored), we show that estimates of the average GHG flux at the site scale can vary by one order of magnitude depending on whether the mean or the median is used as a measure of central tendency. Because the median tends to mute the effect of outlier points (hot spots and hot moments), we propose that both must be reported or that other more advanced spatial averaging techniques (e.g., kriging, area-weighted average) should be used to estimate GHG fluxes at the site scale. Results also indicate that short-term temporal variability in GHG fluxes (a few days) under seemingly constant temperature and hydrological conditions can be as large as spatial variability at the site scale, suggesting that the scientific community should rethink sampling protocols for GHG at the soil-atmosphere interface to include repeated measures over short periods of time at select chambers to estimate GHG emissions in the field. Although recent advances in technology provide tools to address these challenges, their cost is often too high for widespread implementation. Until technology improves, sampling design strategies will need to be carefully considered to balance cost, time, and spatial and temporal representativeness of measurements.

Functional overestimation due to spatial smoothing of fMRI data.

PubMed

Liu, Peng; Calhoun, Vince; Chen, Zikuan

2017-11-01

Pearson correlation (simply correlation) is a basic technique for neuroimage function analysis. It has been observed that the spatial smoothing may cause functional overestimation, which however remains a lack of complete understanding. Herein, we present a theoretical explanation from the perspective of correlation scale invariance. For a task-evoked spatiotemporal functional dataset, we can extract the functional spatial map by calculating the temporal correlations (tcorr) of voxel timecourses against the task timecourse. From the relationship between image noise level (changed through spatial smoothing) and the tcorr map calculation, we show that the spatial smoothing causes a noise reduction, which in turn smooths the tcorr map and leads to a spatial expansion on neuroactivity blob estimation. Through numerical simulations and subject experiments, we show that the spatial smoothing of fMRI data may overestimate activation spots in the correlation functional map. Our results suggest a small spatial smoothing (with a smoothing kernel with a full width at half maximum (FWHM) of no more than two voxels) on fMRI data processing for correlation-based functional mapping COMPARISON WITH EXISTING METHODS: In extreme noiselessness, the correlation of scale-invariance property defines a meaningless binary tcorr map. In reality, a functional activity blob in a tcorr map is shaped due to the spoilage of image noise on correlative responses. We may reduce data noise level by smoothing processing, which poses a smoothing effect on correlation. This logic allows us to understand the noise dependence and the smoothing effect of correlation-based fMRI data analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Bacterial communities in full-scale wastewater treatment systems.

PubMed

Cydzik-Kwiatkowska, Agnieszka; Zielińska, Magdalena

2016-04-01

Bacterial metabolism determines the effectiveness of biological treatment of wastewater. Therefore, it is important to define the relations between the species structure and the performance of full-scale installations. Although there is much laboratory data on microbial consortia, our understanding of dependencies between the microbial structure and operational parameters of full-scale wastewater treatment plants (WWTP) is limited. This mini-review presents the types of microbial consortia in WWTP. Information is given on extracellular polymeric substances production as factor that is key for formation of spatial structures of microorganisms. Additionally, we discuss data on microbial groups including nitrifiers, denitrifiers, Anammox bacteria, and phosphate- and glycogen-accumulating bacteria in full-scale aerobic systems that was obtained with the use of molecular techniques, including high-throughput sequencing, to shed light on dependencies between the microbial ecology of biomass and the overall efficiency and functional stability of wastewater treatment systems. Sludge bulking in WWTPs is addressed, as well as the microbial composition of consortia involved in antibiotic and micropollutant removal.

Conditional sampling technique to test the applicability of the Taylor hypothesis for the large-scale coherent structures

NASA Technical Reports Server (NTRS)

Hussain, A. K. M. F.

1980-01-01

Comparisons of the distributions of large scale structures in turbulent flow with distributions based on time dependent signals from stationary probes and the Taylor hypothesis are presented. The study investigated an area in the near field of a 7.62 cm circular air jet at a Re of 32,000, specifically having coherent structures through small-amplitude controlled excitation and stable vortex pairing in the jet column mode. Hot-wire and X-wire anemometry were employed to establish phase averaged spatial distributions of longitudinal and lateral velocities, coherent Reynolds stress and vorticity, background turbulent intensities, streamlines and pseudo-stream functions. The Taylor hypothesis was used to calculate spatial distributions of the phase-averaged properties, with results indicating that the usage of the local time-average velocity or streamwise velocity produces large distortions.

Complex mountain terrain and disturbance history drive variation in forest aboveground live carbon density in the western Oregon Cascades, USA

PubMed Central

Zald, Harold S.J.; Spies, Thomas A.; Seidl, Rupert; Pabst, Robert J.; Olsen, Keith A.; Steel, E. Ashley

2016-01-01

Forest carbon (C) density varies tremendously across space due to the inherent heterogeneity of forest ecosystems. Variation of forest C density is especially pronounced in mountainous terrain, where environmental gradients are compressed and vary at multiple spatial scales. Additionally, the influence of environmental gradients may vary with forest age and developmental stage, an important consideration as forest landscapes often have a diversity of stand ages from past management and other disturbance agents. Quantifying forest C density and its underlying environmental determinants in mountain terrain has remained challenging because many available data sources lack the spatial grain and ecological resolution needed at both stand and landscape scales. The objective of this study was to determine if environmental factors influencing aboveground live carbon (ALC) density differed between young versus old forests. We integrated aerial light detection and ranging (lidar) data with 702 field plots to map forest ALC density at a grain of 25 m across the H.J. Andrews Experimental Forest, a 6369 ha watershed in the Cascade Mountains of Oregon, USA. We used linear regressions, random forest ensemble learning (RF) and sequential autoregressive modeling (SAR) to reveal how mapped forest ALC density was related to climate, topography, soils, and past disturbance history (timber harvesting and wildfires). ALC increased with stand age in young managed forests, with much greater variation of ALC in relation to years since wildfire in old unmanaged forests. Timber harvesting was the most important driver of ALC across the entire watershed, despite occurring on only 23% of the landscape. More variation in forest ALC density was explained in models of young managed forests than in models of old unmanaged forests. Besides stand age, ALC density in young managed forests was driven by factors influencing site productivity, whereas variation in ALC density in old unmanaged forests was also affected by finer scale topographic conditions associated with sheltered sites. Past wildfires only had a small influence on current ALC density, which may be a result of long times since fire and/or prevalence of non-stand replacing fire. Our results indicate that forest ALC density depends on a suite of multi-scale environmental drivers mediated by complex mountain topography, and that these relationships are dependent on stand age. The high and context-dependent spatial variability of forest ALC density has implications for quantifying forest carbon stores, establishing upper bounds of potential carbon sequestration, and scaling field data to landscape and regional scales. PMID:27041818

Sampling scales define occupancy and underlying occupancy-abundance relationships in animals.

PubMed

Steenweg, Robin; Hebblewhite, Mark; Whittington, Jesse; Lukacs, Paul; McKelvey, Kevin

2018-01-01

Occupancy-abundance (OA) relationships are a foundational ecological phenomenon and field of study, and occupancy models are increasingly used to track population trends and understand ecological interactions. However, these two fields of ecological inquiry remain largely isolated, despite growing appreciation of the importance of integration. For example, using occupancy models to infer trends in abundance is predicated on positive OA relationships. Many occupancy studies collect data that violate geographical closure assumptions due to the choice of sampling scales and application to mobile organisms, which may change how occupancy and abundance are related. Little research, however, has explored how different occupancy sampling designs affect OA relationships. We develop a conceptual framework for understanding how sampling scales affect the definition of occupancy for mobile organisms, which drives OA relationships. We explore how spatial and temporal sampling scales, and the choice of sampling unit (areal vs. point sampling), affect OA relationships. We develop predictions using simulations, and test them using empirical occupancy data from remote cameras on 11 medium-large mammals. Surprisingly, our simulations demonstrate that when using point sampling, OA relationships are unaffected by spatial sampling grain (i.e., cell size). In contrast, when using areal sampling (e.g., species atlas data), OA relationships are affected by spatial grain. Furthermore, OA relationships are also affected by temporal sampling scales, where the curvature of the OA relationship increases with temporal sampling duration. Our empirical results support these predictions, showing that at any given abundance, the spatial grain of point sampling does not affect occupancy estimates, but longer surveys do increase occupancy estimates. For rare species (low occupancy), estimates of occupancy will quickly increase with longer surveys, even while abundance remains constant. Our results also clearly demonstrate that occupancy for mobile species without geographical closure is not true occupancy. The independence of occupancy estimates from spatial sampling grain depends on the sampling unit. Point-sampling surveys can, however, provide unbiased estimates of occupancy for multiple species simultaneously, irrespective of home-range size. The use of occupancy for trend monitoring needs to explicitly articulate how the chosen sampling scales define occupancy and affect the occupancy-abundance relationship. © 2017 by the Ecological Society of America.

Improved Cloud and Snow Screening in MAIAC Aerosol Retrievals Using Spectral and Spatial Analysis

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Laszlo, I.; Kokrkin, S.

2012-01-01

An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.

Instantaneous variance scaling of AIRS thermodynamic profiles using a circular area Monte Carlo approach

NASA Astrophysics Data System (ADS)

Dorrestijn, Jesse; Kahn, Brian H.; Teixeira, João; Irion, Fredrick W.

2018-05-01

Satellite observations are used to obtain vertical profiles of variance scaling of temperature (T) and specific humidity (q) in the atmosphere. A higher spatial resolution nadir retrieval at 13.5 km complements previous Atmospheric Infrared Sounder (AIRS) investigations with 45 km resolution retrievals and enables the derivation of power law scaling exponents to length scales as small as 55 km. We introduce a variable-sized circular-area Monte Carlo methodology to compute exponents instantaneously within the swath of AIRS that yields additional insight into scaling behavior. While this method is approximate and some biases are likely to exist within non-Gaussian portions of the satellite observational swaths of T and q, this method enables the estimation of scale-dependent behavior within instantaneous swaths for individual tropical and extratropical systems of interest. Scaling exponents are shown to fluctuate between β = -1 and -3 at scales ≥ 500 km, while at scales ≤ 500 km they are typically near β ≈ -2, with q slightly lower than T at the smallest scales observed. In the extratropics, the large-scale β is near -3. Within the tropics, however, the large-scale β for T is closer to -1 as small-scale moist convective processes dominate. In the tropics, q exhibits large-scale β between -2 and -3. The values of β are generally consistent with previous works of either time-averaged spatial variance estimates, or aircraft observations that require averaging over numerous flight observational segments. The instantaneous variance scaling methodology is relevant for cloud parameterization development and the assessment of time variability of scaling exponents.

Baseflow physical characteristics differ at multiple spatial scales in stream networks across diverse biomes

Treesearch

Janine Ruegg; Walter K. Dodds; Melinda D. Daniels; Ken R. Sheehan; Christina L. Baker; William B. Bowden; Kaitlin J. Farrell; Michael B. Flinn; Tamara K. Harms; Jeremy B. Jones; Lauren E. Koenig; John S. Kominoski; William H. McDowell; Samuel P. Parker; Amy D. Rosemond; Matt T. Trentman; Matt Whiles; Wilfred M. Wollheim

2016-01-01

ContextSpatial scaling of ecological processes is facilitated by quantifying underlying habitat attributes. Physical and ecological patterns are often measured at disparate spatial scales limiting our ability to quantify ecological processes at broader spatial scales using physical attributes.

On the Design of Wide-Field X-ray Telescopes

NASA Technical Reports Server (NTRS)

Elsner, Ronald F.; O'Dell, Stephen L.; Ramsey, Brian D.; Weiskopf, Martin C.

2009-01-01

X-ray telescopes having a relatively wide field-of-view and spatial resolution vs. polar off-axis angle curves much flatter than the parabolic dependence characteristic of Wolter I designs are of great interest for surveys of the X-ray sky and potentially for study of the Sun s X-ray emission. We discuss the various considerations affecting the design of such telescopes, including the possible use of polynomial mirror surface prescriptions, a method of optimizing the polynomial coefficients, scaling laws for mirror segment length vs. intersection radius, the loss of on-axis spatial resolution, and the positioning of focal plane detectors.

An open source platform for multi-scale spatially distributed simulations of microbial ecosystems

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

Segre, Daniel

2014-08-14

The goal of this project was to develop a tool for facilitating simulation, validation and discovery of multiscale dynamical processes in microbial ecosystems. This led to the development of an open-source software platform for Computation Of Microbial Ecosystems in Time and Space (COMETS). COMETS performs spatially distributed time-dependent flux balance based simulations of microbial metabolism. Our plan involved building the software platform itself, calibrating and testing it through comparison with experimental data, and integrating simulations and experiments to address important open questions on the evolution and dynamics of cross-feeding interactions between microbial species.

Pine invasions in treeless environments: dispersal overruns microsite heterogeneity.

PubMed

Pauchard, Aníbal; Escudero, Adrián; García, Rafael A; de la Cruz, Marcelino; Langdon, Bárbara; Cavieres, Lohengrin A; Esquivel, Jocelyn

2016-01-01

Understanding biological invasions patterns and mechanisms is highly needed for forecasting and managing these processes and their negative impacts. At small scales, ecological processes driving plant invasions are expected to produce a spatially explicit pattern driven by propagule pressure and local ground heterogeneity. Our aim was to determine the interplay between the intensity of seed rain, using distance to a mature plantation as a proxy, and microsite heterogeneity in the spreading of Pinus contorta in the treeless Patagonian steppe. Three one-hectare plots were located under different degrees of P. contorta invasion (Coyhaique Alto, 45° 30'S and 71° 42'W). We fitted three types of inhomogeneous Poisson models to each pine plot in an attempt for describing the observed pattern as accurately as possible: the "dispersal" models, "local ground heterogeneity" models, and "combined" models, using both types of covariates. To include the temporal axis in the invasion process, we analyzed both the pattern of young and old recruits and also of all recruits together. As hypothesized, the spatial patterns of recruited pines showed coarse scale heterogeneity. Early pine invasion spatial patterns in our Patagonian steppe site is not different from expectations of inhomogeneous Poisson processes taking into consideration a linear and negative dependency of pine recruit intensity on the distance to afforestations. Models including ground-cover predictors were able to describe the point pattern process only in a couple of cases but never better than dispersal models. This finding concurs with the idea that early invasions depend more on seed pressure than on the biotic and abiotic relationships seed and seedlings establish at the microsite scale. Our results show that without a timely and active management, P. contorta will invade the Patagonian steppe independently of the local ground-cover conditions.

Pickup Ion Velocity Distributions at Titan: Effects of Spatial Gradients

NASA Technical Reports Server (NTRS)

Hartle, R. E.; Sittler, E. C.

2004-01-01

The principle source of pickup ions at Titan is its neutral exosphere, extending well above the ionopause into the magnetosphere of Saturn or the solar wind, depending on the moon's orbital position. Thermal and nonthermal processes in the thermosphere generate the distribution of neutral atoms and molecules in the exosphere. The combination of these processes and the range of mass numbers, 1 to over 28, contribute to an exospheric source structure that produces pickup ions with gyroradii that are much larger or smaller than the corresponding scale heights of their neutral sources. The resulting phase space distributions are dependent on the spatial structure of the exosphere as well as that of the magnetic field and background plasma. When the pickup ion gyroradius is less than the source gas scale height, the pickup ion velocity distribution is characterized by a sharp cutoff near the maximum speed, which is twice that of the ambient plasma times the sine of the angle between the magnetic field and the flow velocity. This was the case for pickup H(sup +) ions identified during the Voyager 1 flyby. In contrast, as the gyroradius becomes much larger than the scale height, the peak of the velocity distribution in the source region recedes from the maximum speed. Iri addition, the amplitude of the distribution near the maximum speed decreases. These more beam like distributions of heavy ions were not observed from Voyager 1 , but should be observable by more sensitive instruments on future spacecraft, including Cassini. The finite gyroradius effects in the pickup ion velocity distributions are studied by including in the analysis the possible range of spatial structures in the neutral exosphere and background plasma.

In Defense of an Accelerating Universe: Model Insensitivity of the Hubble Diagram

NASA Astrophysics Data System (ADS)

Ringermacher, Harry I.; Mead, Lawrence R.

2018-01-01

A recently published paper by Nielsen, Guffanti & Sarkar (. Sci. Rep. 6, 35596, Oct. 2016) argues that the evidence for cosmic acceleration is marginal and that a coasting universe - the “Milne Universe” - fits the same supernovae data in a Hubble diagram nearly as well. Other papers have since jumped on the bandwagon. The Milne Universe has negative spatial curvature, but is Riemann-flat. Nevertheless, we confirm that the Milne model fits the data just as well as LCDM. We show that this unexpected result points to a weakness in the Hubble diagram rather than to a failure in LCDM. It seems the Hubble diagram is insensitive to spatial curvature. To be specific, the spatial curvature dependences of the comoving radius in the luminosity distance nearly exactly cancel the energy density differences. That is, r(LCDM) = sinh[r(Milne)]. By transforming the distance modulus vs. redshift data to scale factor vs. cosmological time data, for each curvature, k = {+1, 0, -1}, the curvature dependence of the data is effectively separated thus permitting a more precise fit of the Omega parameters to the scale factor data to decide the correct model. Here we present the data and both models in a scale factor vs. cosmological time plot. The difference of the means of the k = 0 and k =-1 data separate at a 2-sigma confidence level. The LCDM fit to the k = 0 data are consistent with an accelerating universe to 99% confidence. The Milne universe fits the k =-1 data to no better than about 70% confidence. This is consistent with independent CMB and BAO observations supporting a flat universe.

Spatial Variability of Streambed Hydraulic Conductivity of a Lowland River

NASA Astrophysics Data System (ADS)

Schneidewind, Uwe; Thornton, Steven; Van De Vijver, Ellen; Joris, Ingeborg; Seuntjens, Piet

2015-04-01

Streambed hydraulic conductivity K is a key physical parameter, which describes flow processes in the hyporheic zone (HZ), i.e. the dynamic interface between aquifers and streams or rivers. Knowledge of the spatial variability of K is also important for the interpretation of contaminant transport processes in the HZ. Streambed K can vary over several magnitudes at small spatial scales. It depends mostly on streambed sediment characteristics (e.g. effective porosity, grain size, packing), streambed processes (e.g. sedimentation, colmation and erosion) and the development of stream channel geometry and streambed morphology (e.g. dunes, anti-dunes, pool-riffle sequences, etc.). Although heterogeneous in natural streambeds, streambed K is often considered to be a constant parameter due to a lack of information on its spatial distribution. Here we show the spatial variability of streambed K for a small section of the River Tern, a lowland river in the UK. Streambed K was determined for more than 120 vertically and horizontally distributed locations from grain size analyses using four empirical approaches (Hazen, Beyer, Kozeny and the USBR model). Additionally, streambed K was estimated from falling head tests in 36 piezometers installed into the streambed on a 4 m by 16 m grid, by applying the Springer-Gelhar Model. For both methods streambed K followed a log-normal distribution. Variogram analysis was used to deduce the spatial variability of the streambed K values within several streambed profiles parallel and perpendicular to the main flow direction in the stream. Hydraulic conductivity Kg estimated from grain size analyses varied between 1 m/d and 155 m/d with standard deviations of 79% to 99% depending on the empirical approach used. Kh estimated from falling head tests varied between 1 m/d and 22 m/d with a standard deviation of about 50%, depending on the degree of anisotropy assumed. After rescaling the data to obtain a common sample support, Pearson correlation coefficients r were calculated between Kg and Kh. Overall, a relatively weak correlation (r < 0.3) was found between both parameters. This is most probably a result from soil coring that destroys the original sediment structure and any anisotropy within it. Analysis of streambed K improved our understanding of the flow behavior in the HZ on a local scale. This will be of importance for the subsequent assessment of nitrate transport and attenuation in the river section.

Coarse Scale In Situ Albedo Observations over Heterogeneous Land Surfaces and Validation Strategy

NASA Astrophysics Data System (ADS)

Xiao, Q.; Wu, X.; Wen, J.; BAI, J., Sr.

2017-12-01

To evaluate and improve the quality of coarse-pixel land surface albedo products, validation with ground measurements of albedo is crucial over the spatially and temporally heterogeneous land surface. The performance of albedo validation depends on the quality of ground-based albedo measurements at a corresponding coarse-pixel scale, which can be conceptualized as the "truth" value of albedo at coarse-pixel scale. The wireless sensor network (WSN) technology provides access to continuously observe on the large pixel scale. Taking the albedo products as an example, this paper was dedicated to the validation of coarse-scale albedo products over heterogeneous surfaces based on the WSN observed data, which is aiming at narrowing down the uncertainty of results caused by the spatial scaling mismatch between satellite and ground measurements over heterogeneous surfaces. The reference value of albedo at coarse-pixel scale can be obtained through an upscaling transform function based on all of the observations for that pixel. We will devote to further improve and develop new method that that are better able to account for the spatio-temporal characteristic of surface albedo in the future. Additionally, how to use the widely distributed single site measurements over the heterogeneous surfaces is also a question to be answered. Keywords: Remote sensing; Albedo; Validation; Wireless sensor network (WSN); Upscaling; Heterogeneous land surface; Albedo truth at coarse-pixel scale

Habitat and Scale Shape the Demographic Fate of the Keystone Sea Urchin Paracentrotus lividus in Mediterranean Macrophyte Communities

PubMed Central

Prado, Patricia; Tomas, Fiona; Pinna, Stefania; Farina, Simone; Roca, Guillem; Ceccherelli, Giulia; Romero, Javier; Alcoverro, Teresa

2012-01-01

Demographic processes exert different degrees of control as individuals grow, and in species that span several habitats and spatial scales, this can influence our ability to predict their population at a particular life-history stage given the previous life stage. In particular, when keystone species are involved, this relative coupling between demographic stages can have significant implications for the functioning of ecosystems. We examined benthic and pelagic abundances of the sea urchin Paracentrotus lividus in order to: 1) understand the main life-history bottlenecks by observing the degree of coupling between demographic stages; and 2) explore the processes driving these linkages. P. lividus is the dominant invertebrate herbivore in the Mediterranean Sea, and has been repeatedly observed to overgraze shallow beds of the seagrass Posidonia oceanica and rocky macroalgal communities. We used a hierarchical sampling design at different spatial scales (100 s, 10 s and <1 km) and habitats (seagrass and rocky macroalgae) to describe the spatial patterns in the abundance of different demographic stages (larvae, settlers, recruits and adults). Our results indicate that large-scale factors (potentially currents, nutrients, temperature, etc.) determine larval availability and settlement in the pelagic stages of urchin life history. In rocky macroalgal habitats, benthic processes (like predation) acting at large or medium scales drive adult abundances. In contrast, adult numbers in seagrass meadows are most likely influenced by factors like local migration (from adjoining rocky habitats) functioning at much smaller scales. The complexity of spatial and habitat-dependent processes shaping urchin populations demands a multiplicity of approaches when addressing habitat conservation actions, yet such actions are currently mostly aimed at managing predation processes and fish numbers. We argue that a more holistic ecosystem management also needs to incorporate the landscape and habitat-quality level processes (eutrophication, fragmentation, etc.) that together regulate the populations of this keystone herbivore. PMID:22536355

Pelagic larval duration and settlement size of a reef fish are spatially consistent, but post-settlement growth varies at the reef scale

NASA Astrophysics Data System (ADS)

Leahy, Susannah M.; Russ, Garry R.; Abesamis, Rene A.

2015-12-01

Recent research has demonstrated that, despite a pelagic larval stage, many coral reef fishes disperse over relatively small distances, leading to well-connected populations on scales of 0-30 km. Although variation in key biological characteristics has been explored on the scale of 100-1000 s of km, it has rarely been explored at the scale relevant to actual larval dispersal and population connectivity on ecological timescales. In this study, we surveyed the habitat and collected specimens ( n = 447) of juvenile butterflyfish, Chaetodon vagabundus, at nine sites along an 80-km stretch of coastline in the central Philippines to identify variation in key life history parameters at a spatial scale relevant to population connectivity. Mean pelagic larval duration (PLD) was 24.03 d (SE = 0.16 d), and settlement size was estimated to be 20.54 mm total length (TL; SE = 0.61 mm). Both traits were spatially consistent, although this PLD is considerably shorter than that reported elsewhere. In contrast, post-settlement daily growth rates, calculated from otolith increment widths from 1 to 50 d post-settlement, varied strongly across the study region. Elevated growth rates were associated with rocky habitats that this species is known to recruit to, but were strongly negatively correlated with macroalgal cover and exhibited negative density dependence with conspecific juveniles. Larger animals had lower early (first 50 d post-settlement) growth rates than smaller animals, even after accounting for seasonal variation in growth rates. Both VBGF and Gompertz models provided good fits to post-settlement size-at-age data ( n = 447 fish), but the VBGF's estimate of asymptotic length ( L ∞ = 168 mm) was more consistent with field observations of maximum fish length. Our findings indicate that larval characteristics are consistent at the spatial scale at which populations are likely well connected, but that site-level biological differences develop post-settlement, most likely as a result of key differences in quality of recruitment habitat.

Groundwater level responses to precipitation variability in Mediterranean insular aquifers

NASA Astrophysics Data System (ADS)

Lorenzo-Lacruz, Jorge; Garcia, Celso; Morán-Tejeda, Enrique

2017-09-01

Groundwater is one of the largest and most important sources of fresh water on many regions under Mediterranean climate conditions, which are exposed to large precipitation variability that includes frequent meteorological drought episodes, and present high evapotranspiration rates and water demand during the dry season. The dependence on groundwater increases in those areas with predominant permeable lithologies, contributing to aquifer recharge and the abundance of ephemeral streams. The increasing pressure of tourism on water resources in many Mediterranean coastal areas, and uncertainty related to future precipitation and water availability, make it urgent to understand the spatio-temporal response of groundwater bodies to precipitation variability, if sustainable use of the resource is to be achieved. We present an assessment of the response of aquifers to precipitation variability based on correlations between the Standardized Precipitation Index (SPI) at various time scales and the Standardized Groundwater Index (SGI) across a Mediterranean island. We detected three main responses of aquifers to accumulated precipitation anomalies: (i) at short time scales of the SPI (<6 months); (ii) at medium time scales (6-24 months); and at long time scales (>24 months). The differing responses were mainly explained by differences in lithology and the percentage of highly permeable rock strata in the aquifer recharge areas. We also identified differences in the months and seasons when aquifer storages are more dependent on precipitation; these were related to climate seasonality and the degree of aquifer exploitation or underground water extraction. The recharge of some aquifers, especially in mountainous areas, is related to precipitation variability within a limited spatial extent, whereas for aquifers located in the plains, precipitation variability influence much larger areas; the topography and geological structure of the island explain these differences. Results indicate large spatial variability in the response of aquifers to precipitation in a very small area, highlighting the importance of having high spatial resolution hydro-climatic databases available to enable full understanding of the effects of climate variability on scarce water resources.

An online mineral dust model within the global/regional NMMB: current progress and plans

NASA Astrophysics Data System (ADS)

Perez, C.; Haustein, K.; Janjic, Z.; Jorba, O.; Baldasano, J. M.; Black, T.; Nickovic, S.

2008-12-01

While mineral dust distribution and effects are important on global scales, they strongly depend on dust emissions that are occurring on small spatial and temporal scales. Indeed, the accuracy of surface wind speed used in dust models is crucial. Due to the high-order power dependency on wind friction velocity and the threshold behaviour of dust emissions, small errors in surface wind speed lead to large dust emission errors. Most global dust models use prescribed wind fields provided by major meteorological centres (e.g., NCEP and ECMWF) and their spatial resolution is currently about 1 degree x 1 degree . Such wind speeds tend to be strongly underestimated over arid and semi-arid areas and do not account for mesoscale systems responsible for a significant fraction of dust emissions regionally and globally. Other significant uncertainties in dust emissions resulting from such approaches are related to the misrepresentation of high subgrid-scale spatial heterogeneity in soil and vegetation boundary conditions, mainly in semi-arid areas. In order to significantly reduce these uncertainties, the Barcelona Supercomputing Center is currently implementing a mineral dust model coupled on-line with the new global/regional NMMB atmospheric model using the ESMF framework under development in NOAA/NCEP/EMC. The NMMB is an evolution of the operational WRF-NMME extending from meso to global scales, and including non-hydrostatic option and improved tracer advection. This model is planned to become the next-generation NCEP mesoscale model for operational weather forecasting in North America. Current implementation is based on the well established regional dust model and forecast system Eta/DREAM (http://www.bsc.es/projects/earthscience/DREAM/). First successful global simulations show the potentials of such an approach and compare well with DREAM regionally. Ongoing developments include improvements in dust size distribution representation, sedimentation, dry deposition, wet scavenging and dust-radiation feedback, as well as the efficient implementation of the model on High Performance Supercomputers for global simulations and forecasts at high resolution.

Identifying Impacts of Hydropower Regulation on Salmonid Habitats to Guide River Restoration for Existing Schemes and Mitigate Adverse Effects of Future Developments

NASA Astrophysics Data System (ADS)

Buddendorf, B.; Geris, J.; Malcolm, I.; Wilkinson, M.; Soulsby, C.

2015-12-01

A decrease in longitudinal connectivity in riverine ecosystems resulting from the construction of transverse barriers has been identified as a major threat to biodiversity. For example, Atlantic Salmon (Salmo salar) have a seasonal variety of hydraulic habitat requirements for their different life stages. However, hydropower impoundments impact the spatial and temporal connectivity of natural habitat along many salmon rivers in ways that are not fully understood. Yet, these changes may affect the sustainability of habitat at local and regional scales and so ultimately the conservation of the species. Research is therefore needed both to aid the restoration and management of rivers impacted by previous hydropower development and guide new schemes to mitigate potentially adverse effects. To this end we assessed the effects of hydropower development on the flow related habitat conditions for different salmon life stages in Scottish rivers at different spatial scales. We used GIS techniques to map the changes in structural connectivity at regional scales, applying a weighting for habitat quality. Next, we used hydrological models to simulate past and present hydrologic conditions that in turn drive reach-scale hydraulic models to assess the impacts of regulation on habitat suitability in both space and time. Preliminary results indicate that: 1) impacts on connectivity depend on the location of the barrier within the river network; 2) multiple smaller barriers may have a potentially lower impact than a single larger barrier; 3) there is a relationship between habitat and connectivity where losing less but more suitable habitat potentially has a disproportionally large impact; 4) the impact of flow regulation can lead to a deterioration of habitat quality, though the effects are spatially variable and the extent of the impact depends on salmon life stage. This work can form a basis for using natural processes to perform targeted and cost-effective restoration of rivers.

Merging fine and coarse resolution remotely sensed data with household-level survey data to evaluate small-scale vulnerability to climate change in West Africa

NASA Astrophysics Data System (ADS)

Grace, K.; Husak, G. J.

2016-12-01

Climate change, in the form of increasingly variable temperatures and rainfall, is anticipated to have potentially dramatic impacts on subsistence agricultural communities throughout the world. Poor people who depend on rainfall to produce food or to produce products to sell to buy food are expected to be particularly vulnerable to the negative impacts associated with climate change. Poor people have extremely limited resources that can be used to cope with weather events and these resources are even more strained when the individuals live in poor countries. While poor and rural producers are most likely to face high levels of vulnerability to food insecurity due to their dependence on rainfall for their agricultural production, annual agricultural censuses are virtually non-existent. Surveying all of the producers in a country each year is extremely costly owing to difficulties in accessing farmers and the costs associated with extensive surveys. The result, however, is very limited information on the spatial and temporal variation in production and the resulting impacts on micro-scale food insecurity and livelihood stability. In this project we use a combination of fine and coarse resolution remotely sensed data ( 1m data, 250m NDVI data and 10km rainfall data, and others) and recently collected survey data from the World Bank to estimate agricultural and land use characteristics at a fine spatial scale in Burkina Faso, Mali and Niger. The analysis will produce estimates of cultivated area that incorporate spatially dynamic climate and vegetation data but that also account for the variation in agricultural practices associated with the different ethnic and religious groups within each country. The survey data will help to calibrate the models and will also serve as a way to validate the statistical models used to estimate on the ground agricultural practices. The models will then be used to evaluate fine-scale agricultural response to climate change in the form of drying and warming.

Field Comparisons of Three Biomarker Detection Methods in Icelandic Mars Analogue Environments

NASA Astrophysics Data System (ADS)

Gentry, D.; Amador, E. S.; Cable, M. L.; Chaudry, N.; Cullen, T.; Jacobsen, M.; Murusekan, G.; Schwieterman, E.; Stevens, A.; Stockton, A.; Yin, C.; Cullen, D.; Geppert, W.

2014-12-01

The ability to estimate the spatial and temporal distributions of biomarkers has been identified as a key need for planning life detection strategies. In a typical planetary exploration scenario, sampling site selection will be informed only by remote sensing data; however, if a difference of a few tens of meters, or centimeters, makes a significant difference in the results, science objectives may not be met. We conducted an analogue planetary expedition to test the correlation of three common biomarker detection methods -- cell counts through fluorescence microscopy, ATP quantification, and quantitative PCR with universal primer sets (bacteria, archaea, and fungi) -- and their spatial scale representativeness. Sampling sites in recent Icelandic lava fields (Fimmvörđuháls and Eldfell) spanned four nested spatial scales: 1 m, 10 m, 100 m, and > 1 km. Each site was homogeneous at typical 'remote sampling' resolution (overall temperature, apparent moisture content, and regolith grain size). No correlation between cell counts and either ATP or qPCR data was significant at any distance scale; ATP quantification and the archaeal and fungal qPCR data showed a marginal negative correlation at the 1 m level. Visible cell count data was statistically site-dependent for sites 10 m and 100 m apart, but not for sites > 1 km apart, whereas ATP results and qPCR data showed site dependence at all four scales. Distance had no significant effect on variability in cell counts and qPCR data, but was positively correlated with ATP variability. These results highlight the difficulty of choosing a 'good' biomarker: not only may different methods yield conflicting results, but they may also be differentially representative of the overall area. We intend to expand on this work with a follow-up campaign using comprehensive assays of physicochemical site properties to better distinguish between effects of environmental variability and intrinsic biomarker variability.

Historical foundations and future directions in macrosystems ecology.

PubMed

Rose, Kevin C; Graves, Rose A; Hansen, Winslow D; Harvey, Brian J; Qiu, Jiangxiao; Wood, Stephen A; Ziter, Carly; Turner, Monica G

2017-02-01

Macrosystems ecology is an effort to understand ecological processes and interactions at the broadest spatial scales and has potential to help solve globally important social and ecological challenges. It is important to understand the intellectual legacies underpinning macrosystems ecology: How the subdiscipline fits within, builds upon, differs from and extends previous theories. We trace the rise of macrosystems ecology with respect to preceding theories and present a new hypothesis that integrates the multiple components of macrosystems theory. The spatio-temporal anthropogenic rescaling (STAR) hypothesis suggests that human activities are altering the scales of ecological processes, resulting in interactions at novel space-time scale combinations that are diverse and predictable. We articulate four predictions about how human actions are "expanding", "shrinking", "speeding up" and "slowing down" ecological processes and interactions, and thereby generating new scaling relationships for ecological patterns and processes. We provide examples of these rescaling processes and describe ecological consequences across terrestrial, freshwater and marine ecosystems. Rescaling depends in part on characteristics including connectivity, stability and heterogeneity. Our STAR hypothesis challenges traditional assumptions about how the spatial and temporal scales of processes and interactions operate in different types of ecosystems and provides a lens through which to understand macrosystem-scale environmental change. © 2016 John Wiley & Sons Ltd/CNRS.

Fine-Scale Habitat Segregation between Two Ecologically Similar Top Predators.

PubMed

Palomares, Francisco; Fernández, Néstor; Roques, Severine; Chávez, Cuauhtemoc; Silveira, Leandro; Keller, Claudia; Adrados, Begoña

2016-01-01

Similar, coexisting species often segregate along the spatial ecological axis. Here, we examine if two top predators (jaguars and pumas) present different fine-scale habitat use in areas of coexistence, and discuss if the observed pattern can be explained by the risk of interference competition between them. Interference competition theory predicts that pumas should avoid habitats or areas used by jaguars (the dominant species), and as a consequence should present more variability of niche parameters across study areas. We used non-invasive genetic sampling of faeces in 12 different areas and sensor satellite fine-scale habitat indices to answer these questions. Meta-analysis confirmed differences in fine-scale habitat use between jaguars and pumas. Furthermore, average marginality of the realized niches of pumas was more variable than those of jaguars, and tolerance (a measure of niche breadth) was on average 2.2 times higher in pumas than in jaguars, as expected under the interference competition risk hypothesis. The use of sensor satellite fine-scale habitat indices allowed the detection of subtle differences in the environmental characteristics of the habitats used by these two similar top predators, which, as a rule, until now were recorded using the same general habitat types. The detection of fine spatial segregation between these two top predators was scale-dependent.

Spatial-Sequential Working Memory in Younger and Older Adults: Age Predicts Backward Recall Performance within Both Age Groups

PubMed Central

Brown, Louise A.

2016-01-01

Working memory is vulnerable to age-related decline, but there is debate regarding the age-sensitivity of different forms of spatial-sequential working memory task, depending on their passive or active nature. The functional architecture of spatial working memory was therefore explored in younger (18–40 years) and older (64–85 years) adults, using passive and active recall tasks. Spatial working memory was assessed using a modified version of the Spatial Span subtest of the Wechsler Memory Scale – Third Edition (WMS-III; Wechsler, 1998). Across both age groups, the effects of interference (control, visual, or spatial), and recall type (forward and backward), were investigated. There was a clear effect of age group, with younger adults demonstrating a larger spatial working memory capacity than the older adults overall. There was also a specific effect of interference, with the spatial interference task (spatial tapping) reliably reducing performance relative to both the control and visual interference (dynamic visual noise) conditions in both age groups and both recall types. This suggests that younger and older adults have similar dependence upon active spatial rehearsal, and that both forward and backward recall require this processing capacity. Linear regression analyses were then carried out within each age group, to assess the predictors of performance in each recall format (forward and backward). Specifically the backward recall task was significantly predicted by age, within both the younger and older adult groups. This finding supports previous literature showing lifespan linear declines in spatial-sequential working memory, and in working memory tasks from other domains, but contrasts with previous evidence that backward spatial span is no more sensitive to aging than forward span. The study suggests that backward spatial span is indeed more processing-intensive than forward span, even when both tasks include a retention period, and that age predicts backward spatial span performance across the adult lifespan, within both younger and older adulthood. PMID:27757096

Spatial-Sequential Working Memory in Younger and Older Adults: Age Predicts Backward Recall Performance within Both Age Groups.

PubMed

Brown, Louise A

2016-01-01

Working memory is vulnerable to age-related decline, but there is debate regarding the age-sensitivity of different forms of spatial-sequential working memory task, depending on their passive or active nature. The functional architecture of spatial working memory was therefore explored in younger (18-40 years) and older (64-85 years) adults, using passive and active recall tasks. Spatial working memory was assessed using a modified version of the Spatial Span subtest of the Wechsler Memory Scale - Third Edition (WMS-III; Wechsler, 1998). Across both age groups, the effects of interference (control, visual, or spatial), and recall type (forward and backward), were investigated. There was a clear effect of age group, with younger adults demonstrating a larger spatial working memory capacity than the older adults overall. There was also a specific effect of interference, with the spatial interference task (spatial tapping) reliably reducing performance relative to both the control and visual interference (dynamic visual noise) conditions in both age groups and both recall types. This suggests that younger and older adults have similar dependence upon active spatial rehearsal, and that both forward and backward recall require this processing capacity. Linear regression analyses were then carried out within each age group, to assess the predictors of performance in each recall format (forward and backward). Specifically the backward recall task was significantly predicted by age, within both the younger and older adult groups. This finding supports previous literature showing lifespan linear declines in spatial-sequential working memory, and in working memory tasks from other domains, but contrasts with previous evidence that backward spatial span is no more sensitive to aging than forward span. The study suggests that backward spatial span is indeed more processing-intensive than forward span, even when both tasks include a retention period, and that age predicts backward spatial span performance across the adult lifespan, within both younger and older adulthood.

Grid scale drives the scale and long-term stability of place maps

PubMed Central

Mallory, Caitlin S; Hardcastle, Kiah; Bant, Jason S; Giocomo, Lisa M

2018-01-01

Medial entorhinal cortex (MEC) grid cells fire at regular spatial intervals and project to the hippocampus, where place cells are active in spatially restricted locations. One feature of the grid population is the increase in grid spatial scale along the dorsal-ventral MEC axis. However, the difficulty in perturbing grid scale without impacting the properties of other functionally-defined MEC cell types has obscured how grid scale influences hippocampal coding and spatial memory. Here, we use a targeted viral approach to knock out HCN1 channels selectively in MEC, causing grid scale to expand while leaving other MEC spatial and velocity signals intact. Grid scale expansion resulted in place scale expansion in fields located far from environmental boundaries, reduced long-term place field stability and impaired spatial learning. These observations, combined with simulations of a grid-to-place cell model and position decoding of place cells, illuminate how grid scale impacts place coding and spatial memory. PMID:29335607

Stochastic Generation of Spatiotemporal Rainfall Events for Flood Risk Assessment

NASA Astrophysics Data System (ADS)

Diederen, D.; Liu, Y.; Gouldby, B.; Diermanse, F.

2017-12-01

Current flood risk analyses that only consider peaks of hydrometeorological forcing variables have limitations regarding their representation of reality. Simplistic assumptions regarding antecedent conditions are required, often different sources of flooding are considered in isolation, and the complex temporal and spatial evolution of the events is not considered. Mid-latitude storms, governed by large scale climatic conditions, often exhibit a high degree of temporal dependency, for example. For sustainable flood risk management, that accounts appropriately for climate change, it is desirable for flood risk analyses to reflect reality more appropriately. Analysis of risk mitigation measures and comparison of their relative performance is therefore likely to be more robust and lead to improved solutions. We provide a new framework for the provision of boundary conditions to flood risk analyses that more appropriately reflects reality. The boundary conditions capture the temporal dependencies of complex storms whilst preserving the extreme values and associated spatial dependencies. We demonstrate the application of this framework to generate a synthetic rainfall events time series boundary condition set from reanalysis rainfall data (CFSR) on the continental scale. We define spatiotemporal clusters of rainfall as events, extract hydrological parameters for each event, generate synthetic parameter sets with a multivariate distribution with a focus on the joint tail probability [Heffernan and Tawn, 2004], and finally create synthetic events from the generated synthetic parameters. We highlight the stochastic integration of (a) spatiotemporal features, e.g. event occurrence intensity over space-time, or time to previous event, which we use for the spatial placement and sequencing of the synthetic events, and (b) value-specific parameters, e.g. peak intensity and event extent. We contrast this to more traditional approaches to highlight the significant improvements in terms of representing the reality of extreme flood events.

Relevance of multiple spatial scales in habitat models: A case study with amphibians and grasshoppers

NASA Astrophysics Data System (ADS)

Altmoos, Michael; Henle, Klaus

2010-11-01

Habitat models for animal species are important tools in conservation planning. We assessed the need to consider several scales in a case study for three amphibian and two grasshopper species in the post-mining landscapes near Leipzig (Germany). The two species groups were selected because habitat analyses for grasshoppers are usually conducted on one scale only whereas amphibians are thought to depend on more than one spatial scale. First, we analysed how the preference to single habitat variables changed across nested scales. Most environmental variables were only significant for a habitat model on one or two scales, with the smallest scale being particularly important. On larger scales, other variables became significant, which cannot be recognized on lower scales. Similar preferences across scales occurred in only 13 out of 79 cases and in 3 out of 79 cases the preference and avoidance for the same variable were even reversed among scales. Second, we developed habitat models by using a logistic regression on every scale and for all combinations of scales and analysed how the quality of habitat models changed with the scales considered. To achieve a sufficient accuracy of the habitat models with a minimum number of variables, at least two scales were required for all species except for Bufo viridis, for which a single scale, the microscale, was sufficient. Only for the European tree frog ( Hyla arborea), at least three scales were required. The results indicate that the quality of habitat models increases with the number of surveyed variables and with the number of scales, but costs increase too. Searching for simplifications in multi-scaled habitat models, we suggest that 2 or 3 scales should be a suitable trade-off, when attempting to define a suitable microscale.

A model of partial differential equations for HIV propagation in lymph nodes

NASA Astrophysics Data System (ADS)

Marinho, E. B. S.; Bacelar, F. S.; Andrade, R. F. S.

2012-01-01

A system of partial differential equations is used to model the dissemination of the Human Immunodeficiency Virus (HIV) in CD4+T cells within lymph nodes. Besides diffusion terms, the model also includes a time-delay dependence to describe the time lag required by the immunologic system to provide defenses to new virus strains. The resulting dynamics strongly depends on the properties of the invariant sets of the model, consisting of three fixed points related to the time independent and spatial homogeneous tissue configurations in healthy and infected states. A region in the parameter space is considered, for which the time dependence of the space averaged model variables follows the clinical pattern reported for infected patients: a short scale primary infection, followed by a long latency period of almost complete recovery and third phase characterized by damped oscillations around a value with large HIV counting. Depending on the value of the diffusion coefficient, the latency time increases with respect to that one obtained for the space homogeneous version of the model. It is found that same initial conditions lead to quite different spatial patterns, which depend strongly on the latency interval.

[Spatial variability of soil nutrients based on geostatistics combined with GIS--a case study in Zunghua City of Hebei Province].

PubMed

Guo, X; Fu, B; Ma, K; Chen, L

2000-08-01

Geostatistics combined with GIS was applied to analyze the spatial variability of soil nutrients in topsoil (0-20 cm) in Zunghua City of Hebei Province. GIS can integrate attribute data with geographical data of system variables, which makes the application of geostatistics technique for large spatial scale more convenient. Soil nutrient data in this study included available N (alkaline hydrolyzing nitrogen), total N, available K, available P and organic matter. The results showed that the semivariograms of soil nutrients were best described by spherical model, except for that of available K, which was best fitted by complex structure of exponential model and linear with sill model. The spatial variability of available K was mainly produced by structural factor, while that of available N, total N, available P and organic matter was primarily caused by random factor. However, their spatial heterogeneity degree was different: the degree of total N and organic matter was higher, and that of available P and available N was lower. The results also indicated that the spatial correlation of the five tested soil nutrients at this large scale was moderately dependent. The ranges of available N and available P were almost same, which were 5 km and 5.5 km, respectively. The range of total N was up to 18 km, and that of organic matter was 8.5 km. For available K, the spatial variability scale primarily expressed exponential model between 0-3.5 km, but linear with sill model between 3.5-25.5 km. In addition, five soil nutrients exhibited different isotropic ranges. Available N and available P were isotropic through the whole research range (0-28 km). The isotropic range of available K was 0-8 km, and that of total N and organic matter was 0-10 km.

Adaptation of a pattern-scaling approach for assessment of local (village/valley) scale water resources and related vulnerabilities in the Upper Indus Basin

NASA Astrophysics Data System (ADS)

Forsythe, Nathan; Kilsby, Chris G.; Fowler, Hayley J.; Archer, David R.

2010-05-01

The water resources of the Upper Indus Basin (UIB) are of the utmost importance to the economic wellbeing of Pakistan. The irrigated agriculture made possible by Indus river runoff underpins the food security for Pakistan's nearly 200 million people. Contributions from hydropower account for more than one fifth of peak installed electrical generating capacity in a country where widespread, prolonged load-shedding handicaps business activity and industrial development. Pakistan's further socio-economic development thus depends largely on optimisation of its precious water resources. Confident, accurate seasonal predictions of water resource availability coupled with sound understanding of interannual variability are urgent insights needed by development planners and infrastructure managers at all levels. This study focuses on the challenge of providing meaningful quantitative information at the village/valley scale in the upper reaches of the UIB. Proceeding by progressive reductions in scale, the typology of the observed UIB hydrological regimes -- glacial, nival and pluvial -- are examined with special emphasis on interannual variability for individual seasons. Variations in discharge (runoff) are compared to observations of climate parameters (temperature, precipitation) and available spatial data (elevation, snow cover and snow-water-equivalent). The first scale presented is composed of the large-scale, long-record gauged UIB tributary basins. The Pakistan Water and Power Development Authority (WAPDA) has maintained these stations for several decades in order to monitor seasonal flows and accumulate data for design of further infrastructure. Data from basins defined by five gauging stations on the Indus, Hunza, Gilgit and Astore rivers are examined. The second scale presented is a set of smaller gauged headwater catchments with short records. These gauges were installed by WAPDA and its partners amongst the international development agencies to assess potential sites for medium-scale infrastructure projects. These catchments are placed in their context within the hydrological regime classification using the spatial data and (remote sensing) observations as well as river gauging measurements. The study assesses the degree of similarity with the larger basins of the same hydrological regime. This assessment focuses on the measured response to observed climate variable anomalies. The smallest scale considered is comprised of a number of case studies at the ungauged village/valley scale. These examples are based on the delineation of areas to which specific communities (villages) have customary (riparian) water rights. These examples were suggested by non-governmental organisations working on grassroots economic development initiatives and small-scale infrastructure projects in the region. The direct observations available for these subcatchments are limited to spatial data (elevation, snow parameters). The challenge at this level is to accurately extrapolate areal values (precipitation, temperature, runoff) from point observations at the basin scale. The study assesses both the degree of similarity in the distribution of spatial parameters to the larger gauged basins and the interannual variability (spatial heterogeneity) of remotely-sensed snow cover and snow-water-equivalent at this subcatchment scale. Based upon the characterisation of spatial and interannual variability at these three spatial scales, the challenges facing local water resource managers and infrastructure operators are enumerated. Local vulnerabilities include, but are not limited to, varying thresholds in irrigation water requirements based on crop-type, minimum base flows for micro-hydropower generation during winter (high load) months and relatively small but growing demand for domestic water usage. In conclusion the study posits potential strategies for managing interannual variability and potential emerging trends. Suggested strategies are guided by the principles of low-risk adaptation, participative decision making and local capacity building.

Estimation of the Relationship Between Remotely Sensed Anthropogenic Heat Discharge and Building Energy Use

NASA Technical Reports Server (NTRS)

Zhou, Yuyu; Weng, Qihao; Gurney, Kevin R.; Shuai, Yanmin; Hu, Xuefei

2012-01-01

This paper examined the relationship between remotely sensed anthropogenic heat discharge and energy use from residential and commercial buildings across multiple scales in the city of Indianapolis, Indiana, USA. The anthropogenic heat discharge was estimated with a remote sensing-based surface energy balance model, which was parameterized using land cover, land surface temperature, albedo, and meteorological data. The building energy use was estimated using a GIS-based building energy simulation model in conjunction with Department of Energy/Energy Information Administration survey data, the Assessor's parcel data, GIS floor areas data, and remote sensing-derived building height data. The spatial patterns of anthropogenic heat discharge and energy use from residential and commercial buildings were analyzed and compared. Quantitative relationships were evaluated across multiple scales from pixel aggregation to census block. The results indicate that anthropogenic heat discharge is consistent with building energy use in terms of the spatial pattern, and that building energy use accounts for a significant fraction of anthropogenic heat discharge. The research also implies that the relationship between anthropogenic heat discharge and building energy use is scale-dependent. The simultaneous estimation of anthropogenic heat discharge and building energy use via two independent methods improves the understanding of the surface energy balance in an urban landscape. The anthropogenic heat discharge derived from remote sensing and meteorological data may be able to serve as a spatial distribution proxy for spatially-resolved building energy use, and even for fossil-fuel CO2 emissions if additional factors are considered.

A wildland fire emission inventory for the western United States - uncertainty across spatial and temporal scales

Treesearch

Shawn Urbanski; WeiMin Hao

2010-01-01

Emissions of trace gases and aerosols by biomass burning (BB) have a significant influence on the chemical composition of the atmosphere, air quality, and climate. BB emissions depend on a range of variables including burned area, fuels, meteorology, combustion completeness, and emission factors (EF). Emission algorithms provide BB emission inventories (EI) which serve...

A Fuzzy Cognitive Model of aeolian instability across the South Texas Sandsheet

NASA Astrophysics Data System (ADS)

Houser, C.; Bishop, M. P.; Barrineau, C. P.

2014-12-01

Characterization of aeolian systems is complicated by rapidly changing surface-process regimes, spatio-temporal scale dependencies, and subjective interpretation of imagery and spatial data. This paper describes the development and application of analytical reasoning to quantify instability of an aeolian environment using scale-dependent information coupled with conceptual knowledge of process and feedback mechanisms. Specifically, a simple Fuzzy Cognitive Model (FCM) for aeolian landscape instability was developed that represents conceptual knowledge of key biophysical processes and feedbacks. Model inputs include satellite-derived surface biophysical and geomorphometric parameters. FCMs are a knowledge-based Artificial Intelligence (AI) technique that merges fuzzy logic and neural computing in which knowledge or concepts are structured as a web of relationships that is similar to both human reasoning and the human decision-making process. Given simple process-form relationships, the analytical reasoning model is able to map the influence of land management practices and the geomorphology of the inherited surface on aeolian instability within the South Texas Sandsheet. Results suggest that FCMs can be used to formalize process-form relationships and information integration analogous to human cognition with future iterations accounting for the spatial interactions and temporal lags across the sand sheets.

Spatial autocorrelation of radiation measured by the Earth Radiation Budget Experiment: Scene inhomogeneity and reciprocity violation

NASA Technical Reports Server (NTRS)

Davies, Roger

1994-01-01

The spatial autocorrelation functions of broad-band longwave and shortwave radiances measured by the Earth Radiation Budget Experiment (ERBE) are analyzed as a function of view angle in an investigation of the general effects of scene inhomogeneity on radiation. For nadir views, the correlation distance of the autocorrelation function is about 900 km for longwave radiance and about 500 km for shortwave radiance, consistent with higher degrees of freedom in shortwave reflection. Both functions rise monotonically with view angle, but there is a substantial difference in the relative angular dependence of the shortwave and longwave functions, especially for view angles less than 50 deg. In this range, the increase with angle of the longwave functions is found to depend only on the expansion of pixel area with angle, whereas the shortwave functions show an additional dependence on angle that is attributed to the occlusion of inhomogeneities by cloud height variations. Beyond a view angle of about 50 deg, both longwave and shortwave functions appear to be affected by cloud sides. The shortwave autocorrelation functions do not satisfy the principle of directional reciprocity, thereby proving that the average scene is horizontally inhomogeneous over the scale of an ERBE pixel (1500 sq km). Coarse stratification of the measurements by cloud amount, however, indicates that the average cloud-free scene does satisfy directional reciprocity on this scale.

The methane distribution on Titan: high resolution spectroscopy in the near-IR with Keck NIRSPEC/AO

NASA Astrophysics Data System (ADS)

Adamkovics, Mate; Mitchell, Jonathan L.

2014-11-01

The distribution of methane on Titan is a diagnostic of regional scale meteorology and large scale atmospheric circulation. The observed formation of clouds and the transport of heat through the atmosphere both depend on spatial and temporal variations in methane humidity. We have performed observations to measure the the distribution on methane Titan using high spectral resolution near-IR (H-band) observations made with NIRSPEC, with adaptive optics, at Keck Observatory in July 2014. This work builds on previous attempts at this measurement with improvement in the observing protocol and data reduction, together with increased integration times. Radiative transfer models using line-by-line calculation of methane opacities from the HITRAN2012 database are used to retrieve methane abundances. We will describe analysis of the reduced observations, which show latitudinal spatial variation in the region the spectrum that is thought to be sensitive to methane abundance. Quantifying the methane abundance variation requires models that include the spatial variation in surface albedo and meridional haze gradient; we will describe (currently preliminary) analysis of the the methane distribution and uncertainties in the retrieval.

Spatial rule-based assessment of habitat potential to predict impact of land use changes on biodiversity at municipal scale.

PubMed

Scolozzi, Rocco; Geneletti, Davide

2011-03-01

In human dominated landscapes, ecosystems are under increasing pressures caused by urbanization and infrastructure development. In Alpine valleys remnant natural areas are increasingly affected by habitat fragmentation and loss. In these contexts, there is a growing risk of local extinction for wildlife populations; hence assessing the consequences on biodiversity of proposed land use changes is extremely important. The article presents a methodology to assess the impacts of land use changes on target species at a local scale. The approach relies on the application of ecological profiles of target species for habitat potential (HP) assessment, using high resolution GIS-data within a multiple level framework. The HP, in this framework, is based on a species-specific assessment of the suitability of a site, as well of surrounding areas. This assessment is performed through spatial rules, structured as sets of queries on landscape objects. We show that by considering spatial dependencies in habitat assessment it is possible to perform better quantification of impacts of local-level land use changes on habitats.

Time-dependent shock acceleration of particles. Effect of the time-dependent injection, with application to supernova remnants

NASA Astrophysics Data System (ADS)

Petruk, O.; Kopytko, B.

2016-11-01

Three approaches are considered to solve the equation which describes the time-dependent diffusive shock acceleration of test particles at the non-relativistic shocks. At first, the solution of Drury for the particle distribution function at the shock is generalized to any relation between the acceleration time-scales upstream and downstream and for the time-dependent injection efficiency. Three alternative solutions for the spatial dependence of the distribution function are derived. Then, the two other approaches to solve the time-dependent equation are presented, one of which does not require the Laplace transform. At the end, our more general solution is discussed, with a particular attention to the time-dependent injection in supernova remnants. It is shown that, comparing to the case with the dominant upstream acceleration time-scale, the maximum momentum of accelerated particles shifts towards the smaller momenta with increase of the downstream acceleration time-scale. The time-dependent injection affects the shape of the particle spectrum. In particular, (I) the power-law index is not solely determined by the shock compression, in contrast to the stationary solution; (II) the larger the injection efficiency during the first decades after the supernova explosion, the harder the particle spectrum around the high-energy cutoff at the later times. This is important, in particular, for interpretation of the radio and gamma-ray observations of supernova remnants, as demonstrated on a number of examples.

The importance of spatial fishing behavior for coral reef resilience

NASA Astrophysics Data System (ADS)

Rassweiler, A.; Lauer, M.; Holbrook, S. J.

2016-02-01

Coral reefs are dynamic systems in which disturbances periodically reduce coral cover but are normally followed by recovery of the coral community. However, human activity may have reduced this resilience to disturbance in many coral reef systems, as an increasing number of reefs have undergone persistent transitions from coral-dominated to macroalgal-dominated community states. Fishing on herbivores may be one cause of reduced reef resilience, as lower herbivory can make it easier for macroalgae to become established after a disturbance. Despite the acknowledged importance of fishing, relatively little attention has been paid to the potential for feedbacks between ecosystem state and fisher behavior. Here we couple methods from environmental anthropology and ecology to explore these feedbacks between small-scale fisheries and coral reefs in Moorea, French Polynesia. We document how aspects of ecological state such as the abundance of macroalgae affect people's preference for fishing in particular lagoon habitats. We then incorporate biases towards fishing in certain ecological states into a spatially explicit bio-economic model of ecological dynamics and fishing in Moorea's lagoons. We find that feedbacks between spatial fishing behavior and ecological state can have critical effects on coral reefs. Presence of these spatial behaviors consistently leads to more coherence across the reef-scape. However, whether this coherence manifests as increased resilience or increased fragility depends on the spatial scales of fisher movement and the magnitudes of disturbance. These results emphasize the potential importance of spatially-explicit fishing behavior for reef resilience, but also the complexity of the feedbacks involved.

Plant trait detection with multi-scale spectrometry

NASA Astrophysics Data System (ADS)

Gamon, J. A.; Wang, R.

2017-12-01

Proximal and remote sensing using imaging spectrometry offers new opportunities for detecting plant traits, with benefits for phenotyping, productivity estimation, stress detection, and biodiversity studies. Using proximal and airborne spectrometry, we evaluated variation in plant optical properties at various spatial and spectral scales with the goal of identifying optimal scales for distinguishing plant traits related to photosynthetic function. Using directed approaches based on physiological vegetation indices, and statistical approaches based on spectral information content, we explored alternate ways of distinguishing plant traits with imaging spectrometry. With both leaf traits and canopy structure contributing to the signals, results exhibit a strong scale dependence. Our results demonstrate the benefits of multi-scale experimental approaches within a clear conceptual framework when applying remote sensing methods to plant trait detection for phenotyping, productivity, and biodiversity studies.

Fire-induced changes in boreal forest canopy volume and soil organic matter from multi-temporal airborne lidar

NASA Astrophysics Data System (ADS)

Alonzo, M.; Cook, B.; Andersen, H. E.; Babcock, C. R.; Morton, D. C.

2016-12-01

Fire in boreal forests initiates a cascade of biogeochemical and biophysical processes. Over typical fire return intervals, net radiative forcing from boreal forest fires depends on the offsetting impacts of greenhouse gas emissions and post-fire changes in land surface albedo. Whether boreal forest fires warm or cool the climate over these multi-decadal intervals depends on the magnitude of fire emissions and the time scales of decomposition, albedo changes, and forest regrowth. Our understanding of vegetation and surface organic matter (SOM) changes from boreal forest fires is shaped by field measurements and moderate resolution remote sensing data. Intensive field plot measurements offer detailed data on overstory, understory, and SOM changes from fire, but sparse plot data can be difficult to extend across the heterogeneous boreal forest landscape. Conversely, satellite measurements of burn severity are spatially extensive but only provide proxy measures of fire effects. In this research, we seek to bridge the scale gap between existing intensive and extensive methods using a combination of airborne lidar data and time series of Landsat data to evaluate pre- and post-fire conditions across Alaska's Kenai Peninsula. Lidar-based estimates of pre-fire stand structure and composition were essential to characterize the loss of canopy volume from fires between 2001 and 2014, quantify transitions from live to dead standing carbon pools, and isolate vegetation recovery following fire over 1 to 13 year time scales. Results from this study demonstrate the utility of lidar for estimating pre-fire structure and species composition at the scale of individual tree crowns. Multi-temporal airborne lidar data also provide essential insights regarding the heterogeneity of canopy and SOM losses at a sub-Landsat pixel scale. Fire effects are forest-structure and species dependent with variable temporal lags in carbon release due to delayed mortality (>5 years post fire) and standing dead trees. Establishing the spatial and temporal scales of canopy structural change will aid in constraining estimates of net radiative forcing from both carbon release and albedo in the years following fire.

Effective grid-dependent dispersion coefficient for conservative and reactive transport simulations in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Cortinez, J. M.; Valocchi, A. J.; Herrera, P. A.

2013-12-01

Because of the finite size of numerical grids, it is very difficult to correctly account for processes that occur at different spatial scales to accurately simulate the migration of conservative and reactive compounds dissolved in groundwater. In one hand, transport processes in heterogeneous porous media are controlled by local-scale dispersion associated to transport processes at the pore-scale. On the other hand, variations of velocity at the continuum- or Darcy-scale produce spreading of the contaminant plume, which is referred to as macro-dispersion. Furthermore, under some conditions both effects interact, so that spreading may enhance the action of local-scale dispersion resulting in higher mixing, dilution and reaction rates. Traditionally, transport processes at different spatial scales have been included in numerical simulations by using a single dispersion coefficient. This approach implicitly assumes that the separate effects of local-dispersion and macro-dispersion can be added and represented by a unique effective dispersion coefficient. Moreover, the selection of the effective dispersion coefficient for numerical simulations usually do not consider the filtering effect of the grid size over the small-scale flow features. We have developed a multi-scale Lagragian numerical method that allows using two different dispersion coefficients to represent local- and macro-scale dispersion. This technique considers fluid particles that carry solute mass and whose locations evolve according to a deterministic component given by the grid-scale velocity and a stochastic component that corresponds to a block-effective macro-dispersion coefficient. Mass transfer between particles due to local-scale dispersion is approximated by a meshless method. We use our model to test under which transport conditions the combined effect of local- and macro-dispersion are additive and can be represented by a single effective dispersion coefficient. We also demonstrate that for the situations where both processes are additive, an effective grid-dependent dispersion coefficient can be derived based on the concept of block-effective dispersion. We show that the proposed effective dispersion coefficient is able to reproduce dilution, mixing and reaction rates for a wide range of transport conditions similar to the ones found in many practical applications.

Seasonal change of topology and resilience of ecological networks in wetlandscapes

NASA Astrophysics Data System (ADS)

Bin, Kim; Park, Jeryang

2017-04-01

Wetlands distributed in a landscape provide various ecosystem services including habitat for flora and fauna, hydrologic controls, and biogeochemical processes. Hydrologic regime of each wetland at a given landscape varies by hydro-climatic and geological conditions as well as the bathymetry, forming a certain pattern in the wetland area distribution and spatial organization. However, its large-scale pattern also changes over time as this wetland complex is subject to stochastic hydro-climatic forcing in various temporal scales. Consequently, temporal variation in the spatial structure of wetlands inevitably affects the dispersal ability of species depending on those wetlands as habitat. Here, we numerically show (1) the spatiotemporal variation of wetlandscapes by forcing seasonally changing stochastic rainfall and (2) the corresponding ecological networks which either deterministically or stochastically forming the dispersal ranges. We selected four vernal pool regions with distinct climate conditions in California. The results indicate that the spatial structure of wetlands in a landscape by measuring the wetland area frequency distribution changes by seasonal hydro-climatic condition but eventually recovers to the initial state. However, the corresponding ecological networks, which the structure and function change by the change of distances between wetlands, and measured by degree distribution and network efficiency, may not recover to the initial state especially in the regions with high seasonal dryness index. Moreover, we observed that the changes in both the spatial structure of wetlands in a landscape and the corresponding ecological networks exhibit hysteresis over seasons. Our analysis indicates that the hydrologic and ecological resilience of a wetlandcape may be low in a dry region with seasonal hydro-climatic forcing. Implications of these results for modelling ecological networks depending on hydrologic systems especially for conservation purposes are discussed.

Species dispersal rates alter diversity and ecosystem stability in pond metacommunities.

PubMed

Howeth, Jennifer G; Leibold, Mathew A

2010-09-01

Metacommunity theory suggests that relationships between diversity and ecosystem stability can be determined by the rate of species dispersal among local communities. The predicted relationships, however, may depend upon the relative strength of local environmental processes and disturbance. Here we evaluate the role of dispersal frequency and local predation perturbations in affecting patterns of diversity and stability in pond plankton metacommunities. Pond metacommunities were composed of three mesocosm communities: one of the three communities maintained constant "press" predation from a selective predator, bluegill sunfish (Lepomis macrochirus); the second community maintained "press" conditions without predation; and the third community experienced recurrent "pulsed" predation from bluegill sunfish. The triads of pond communities were connected at either no, low (0.7%/d), or high (20%/d) planktonic dispersal. Richness and composition of zooplankton and stability of plankton biomass and ecosystem productivity were measured at local and regional spatial scales. Dispersal significantly affected diversity such that local and regional biotas at the low dispersal rate maintained the greatest number of species. The unimodal local dispersal-diversity relationship was predator-dependent, however, as selective press predation excluded species regardless of dispersal. Further, there was no effect of dispersal on beta diversity because predation generated local conditions that selected for distinct community assemblages. Spatial and temporal ecosystem stability responded to dispersal frequency but not predation. Low dispersal destabilized the spatial stability of producer biomass but stabilized temporal ecosystem productivity. The results indicate that selective predation can prevent species augmentation from mass effects but has no apparent influence on stability. Dispersal rates, in contrast, can have significant effects on both species diversity and ecosystem stability at multiple spatial scales in metacommunities.

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

Xiao, Kai; Ma, Ying -Zhong; Simpson, Mary Jane

Charge carrier trapping degrades the performance of organometallic halide perovskite solar cells. To characterize the locations of electronic trap states in a heterogeneous photoactive layer, a spatially resolved approach is essential. Here, we report a comparative study on methylammonium lead tri-iodide perovskite thin films subject to different thermal annealing times using a combined photoluminescence (PL) and femtosecond transient absorption microscopy (TAM) approach to spatially map trap states. This approach coregisters the initially populated electronic excited states with the regions that recombine radiatively. Although the TAM images are relatively homogeneous for both samples, the corresponding PL images are highly structured. Themore » remarkable variation in the PL intensities as compared to transient absorption signal amplitude suggests spatially dependent PL quantum efficiency, indicative of trapping events. Furthermore, detailed analysis enables identification of two trapping regimes: a densely packed trapping region and a sparse trapping area that appear as unique spatial features in scaled PL maps.« less