Interactions between landscape structure and animal behavior: the roles of heterogeneously distributed resources and food deprivation on movement patterns

To examine how resource distributions affect the movement behaviors of fed and food-deprived Eleodes extricata Say darkling beetles (Coleoptera: Tenebrionidae), we experimentally manipulated the dispersion of food to create clumped, random, and uniform distributions in an otherwise homogeneous 25-m² experimental field landscape. Quantitative measures of the tortuosity, net linear displacement, overall path length, and velocity of beetle movement pathways showed that food-deprived beetles generally moved more slowly and over shorter distances than did fed beetles. This effect was mediated by the spatial distribution of food, however; food distributed randomly over the landscape evoked more tortuous paths over larger overall distances. The foraging movements of food-deprived beetles were most different from those of fed individuals in treatments with randomly distributed food resources. These results show that the influence of spatial structure on individuals depends not only on the arrangement of pattern but also on the function that the structure plays. Thus, 'spatial structure' is defined not only by physical characteristics of the landscape but also by how that structure is used by animals.     

Resource depletion versus landscape complementation: habitat selection by a multiple central place forager

Context

The spatial distribution of non-substitutable resources implies diverging predictions for animal movement patterns. At broad scales, animals should respond to landscape complementation by selecting areas where resource patches are close-by to minimize movement costs. Yet at fine scales, central place effects lead to the depletion of patches that are close to one another and that should ultimately be avoided by consumers.

Objectives

We developed a multi-scale resource selection framework to test whether animal movement is driven by landscape complementation or resource depletion and identify at which spatial scale these processes are relevant from an animal’s perspective.

Methods

During the dry season, surface water and forage are non-substitutable resources for African elephants. Eight family herds were tracked using GPS loggers in Hwange National Park, Zimbabwe. We explained habitat selection during foraging trips by mapping surface water at two scales with gaussian kernels of varying widths placed over each waterhole.

Results

Unexpectedly, elephants select areas with low waterhole density at both fine scales (< 1 km) and broad scales (5–7 km). Selection is stronger when elephants forage far away from water, even more so as the dry season progresses.

Conclusions

Elephant selection of low waterhole density areas suggests that resource depletion around multiple central places is the main driver of their habitat selection. By identifying the scale at which animals respond to waterhole distribution we provide a template for water management in arid and semi-arid landscapes that can be tailored to match the requirements and mobility of free ranging wild or domestic species.

     

People and pines 1555<Emphasis Type="Bold">–</Emphasis>1910: integrating ecology,history and archaeology to assess long-term resource use in northern Fennoscandia

Context

Past human land use has received increasing attention as an important driver of ecosystem change also in seemingly natural landscapes. Quantification of historical land use is therefore critical for assessing the degree of human impact and requires integration of ecology, history and archaeology.

Objective

This study aims to assess and compare levels of resource use by different actors during 355 years across a large landscape of northern Sweden.

Method

Data on resource use derived from case studies were extrapolated using demographic data to estimate harvested resources at the landscape scale. Here, we examined the use of the key-specie Scots pine by native Sami peoples and farmers and through commercial logging, and reconstructed historical forest conditions in order to interpret harvest levels and sustainability.

Results

We show that (1) the pre-industrial use of Scots pine resources in Pite Lappmark was sustainable from a landscape perspective, and (2) that the early commercial logging, in contrast, was not sustainable. Large and old Scots pine trees were logged at a very high rate, reaching up to 300 % of the annual ingrowth.

Conclusion

We suggest that historical landscape studies should incorporate analysis at different spatial scales, as such an approach can mirror the overall use of resources. Only then can land use data be applied across larger spatial scales, function as reference values and be compared to those of other regions, time-periods and types of human impact.

     

Functional heterogencity in resources within landscapes and herbivore population dynamics

Large mammalian herbivores are notorious for their propensity towards population irruptions and crashes, yet many herbivore populations remain relatively stable. I explore how resource heterogeneity within landscapes dampens population instability, using a metaphysiological modelling approach condidering patch state distributions. Resource heterogeneity is functionally stabilizing through spreading consumption away from preferred resources before these critically depleted. Lower-quality resources act as a buffer against starvation during critical critical periods of the seasonal cycle. Enriching resource quality is destabilizing, even if patch diversity is maintained, because food quantity then becomes the limitation. The potential consequences of landscape fragmentation are explored using the Serengeti ecosystem, characterised by broadscale resource gradients, as a hypothetical example. Further insights provided by the model are illustrated with specific examples concerning the effects of patch scales and waterpoint distribution. A metaphysiological modelling approach enables the basic consequences of landscape heterogeneity to be distinguished from further effects that may arise from specific patch scales and configurations, without the distracting detail of spatially explicit models.     

Finding the functional grain: comparing methods for scaling resistance surfaces

The influence of landscape features on the movement of an organism between two point locations is often measured as an effective distance. Typically, raster models of landscape resistance are used to calculate effective distance. Because organisms may experience landscape heterogeneity at different scales (i.e. functional grains), using a raster with too fine or too coarse a spatial grain (i.e. analysis grain) may lead to inaccurate estimates of effective distance. We adopted a simulation approach where the true functional grain and effective distance for a theoretical organism were defined and the analysis grains of landscape connectivity models were systematically changed. We used moving windows and grains of connectivity, a recently introduced landscape graph method that uses an irregular tessellation of the resistance surface to coarsen the landscape data. We then used least-cost path metrics to measure effective distance and found that matching the functional and analysis grain sizes was most accurate at recovering the expected effective distance, affirming the importance of multi-scale analysis. Moving window scaling with a maximum function (win.max) performed well when the majority of landscape structure influencing connectivity consisted of high resistance features. Moving window scaling with a minimum function (win.min) performed well when the relevant landscape structure consisted of low resistance regions. The grains of connectivity method performed well under all scenarios, avoiding an a priori choice of window function, which may be challenging in complex landscapes. Appendices are provided that demonstrate the use of grains of connectivity models.     

Functional heterogeneity in resources within landscapes and herbivore population dynamics

Large mammalian herbivores are notorious for their propensity towards population irruptions and crashes, yet many herbivore populations remain relatively stable. I explore how resource heterogeneity within landscapes dampens population instability, using a metaphysiological modelling approach considering patch state distributions. Resource heterogeneity is functionally stabilizing through spreading consumption away from preferred resources before these become critically depleted. Lower-quality resources act as a buffer against starvation during critical periods of the seasonal cycle. Enriching resource quality is destabilizing, even if patch diversity is maintained, because food quantity then becomes the limitation. The potential consequences of landscape fragmentation are explored using the Serengeti ecosystem, characterised by broadscale resource gradients, as a hypothetical example. Further insights provided by the model are illustrated with specific examples concerning the effects of patch scales and waterpoint distribution. A metaphysiological modelling approach enables the basic consequences of landscape heterogeneity to be distinguished from further effects that may arise from specific patch scales and configurations, without the distracting detail of spatially explicit models.     

Spatial and temporal analysis of landscape patterns

A variety of ecological questions now require the study of large regions and the understanding of spatial heterogeneity. Methods for spatial-temporal analyses are becoming increasingly important for ecological studies. A grid cell based spatial analysis program (SPAN) is described and results of landscape pattern analysis using SPAN are presentedd. Several ecological topics in which geographic information systems (GIS) can play an important role (landscape pattern analysis, neutral models of pattern and process, and extrapolation across spatial scales) are reviewed. To study the relationship between observed landscape patterns and ecological processes, a neutral model approach is recommended. For example, the expected pattern (i.e., neutral model) of the spread of disturbance across a landscape can be generated and then tested using actual landscape data that are stored in a GIS. Observed spatial or temporal patterns in ecological data may also be influenced by scale. Creating a spatial data base frequently requires integrating data at different scales. Spatial is shown to influence landscape pattern analyses, but extrapolation of data across spatial scales may be possible if the grain and extent of the data are specified. The continued development and testing of new methods for spatial-temporal analysis will contribute to a general understanding of landscape dynamics.     

Resource grain scales mobility and adult morphology in butterflies

Relations between species mobility and life history traits and/or landscape and habitat features are of broad interest to ecologists and conservation biologists. Here we investigated the reliability of the relations between mobility and (1) resource grain and (2) morphological traits in butterflies. Results were used to assess the biological realism of morphological traits associated with flight as mobility proxies. We then investigated how biological, environmental and landscape variables affected these mobility proxies. We used a multi-species approach on two different sites. Morphological traits were measured on ca. 20 individuals per site, species and sex. Resource distribution was carefully monitored by investigating the spatial distribution and overlap of larval and adult feeding resources, together representing the resource grain. The spatial extent of individual station keeping movements was estimated from distances recorded between successive recaptures of individuals from mark-release-recapture experiments. Morphological traits seemed reliable proxies of mobility, as both variables were strongly correlated. Morphological variations were related to flight type and spatial dimension of nectar resource. The most striking point was the clear relation between the index of relative investment in mobility versus fecundity in females with the spatial dimension of adult feeding resource. Given the generally accepted relation between abdomen volume and female fecundity, this suggests that females might invest more in fecundity when nectar resources are widespread. Finally, we did not detected effects of landscape structure on mobility, which indicates that functional grain of resources is more likely to influence mobility and evolution of morphology in butterflies than landscape connectivity.     

Dynamic surface water distributions influence wetland connectivity within a highly modified interior landscape

Context

Animal movements are inherently linked to landscape structure. Understanding this relationship for highly-mobile species requires documenting their responses to spatiotemporal variability of resources. To that end, characterizing movement behaviors and resource distributions using the principles of habitat connectivity facilitates coordinated landscape planning efforts within highly modified landscapes.

Objectives and methods

We tracked locations and movements for 156 dunlin (Calidris alpina) and 109 long-billed dowitchers (Limnodromus scolopaceus) overwintering in two regions with distinct water distributions in California’s Central Valley. We then compared residency rates, functional connectivity to other regions, and associations between movement distances and average habitat availability and structural connectivity of habitat at multiple temporal and spatial scales.

Results

A widespread yet highly variable regional water distribution was associated with lower residency rates and substantially higher functional connectivity to nearby regions when compared to a stable regional water distribution characterized by a large, contiguous wetland complex. Longer movements were associated with decreasing average availability and spatial aggregation of surface water. Movement models suggested shorebirds primarily responded to habitat availability at smaller scales (<?10 km) and structural connectivity at larger scales (≥?10 km).

Conclusions

Differences in movement behaviors suggested that wintering shorebirds will avoid long distance movements and remain resident within a wetland region when possible. Conservation and management efforts should reliably flood individual wetlands and agricultural lands from November to April and prioritize locations that maximize structural wetland connectivity and limit spatiotemporal variability of surface water throughout the Central Valley.

     

Quantifying patch distribution at multiple spatial scales: Applications to wildlife-habitat models

Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing 1 of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.     

Quantifying patch distribution at multiple spatial scales: Applications to wildlife-habitat models

Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing 1 of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.     

Landscape effects on scales of movement by white-tailed deer in an agricultural–forest matrix

Understanding how organisms respond to landscape heterogeneity is foundational to landscape ecology. We characterized seasonal scales of movement of white-tailed deer (Odocoileus viginianus) in an agricultural–forest matrix using first-passage time analysis (FPT) for 62 GPS-collared individuals. We investigated whether those scales were driven by demographic or landscape features. We found FPT for each individual across all seasons was typically dominated by a peak in variance of FPT/area at scales (radii) from 425 to 1,675 m. These peaks occurred at scales consistent with seasonal space use. We observed additional lower magnitude peaks at larger scales (3,000–6,000 m) and small scales (25–150 m). Peaks at larger scales were associated with seasonal migrations and dispersal events. Small scale peaks may represent resting or foraging behavior. Female movements were organized at smaller scales than males in the spring/summer season. Models relating landscape features to movement scales suggest that deer perceive and move within the landscape differently as the roles of dominant land-cover types shift seasonally. During winter, configuration (interspersion/juxtaposition) of land-cover types is more important to deer than during spring/summer and fall. During spring/summer and fall, movement behavior may be dictated by reproductive and harvest activities.     

Foraging in a fractal environment: Spatial patterns in a marine predator-prey system

Spatial relationships between predators and prey have important implications for landscape processes and patterns. Highly mobile oceanic birds and their patchily distributed prey constitute an accessible model system for studying these relationships. High-frequency echosounders can be used together with simultaneous direct visual observations to quantitatively describe the distributions of seabird consumers and their resources over a wide range of spatial scales, yielding information which is rarely available in terrestrial systems.Recent fine-scale investigations which have used acoustics to study the distribution of foraging marine birds have reported weak or ephemeral spatial associations between the birds and their prey. These results are inconsistent with predictions of optimal foraging, but several considerations suggest that traditional foraging models do not adequately describe resource acquisition in marine environments. Relative to their terrestrial counterparts, oceanic landscapes are structurally very simple, but they generally lack visual cues about resource availability.An emerging view assumes that perceptually constrained organisms searching for food in multiscale environments should respond to patterns of resource abundance over a continuum of scales. We explore fractal geometry as a possible tool for quantifying this view and for describing spatial dispersion patterns that result from foraging behavior. Data on an Alaskan seabird (least auklet [Aethia pusilla]) and its zooplanktonic food resources suggest that fractal approaches can yield new ecological insights into complex spatial patterns deriving from animal movements.     

Spatial organisation of landscapes and its function in semi-arid woodlands,Australia

The spatial organisation of three major landscape types within the semi-arid woodlands of eastern Australia was studied by a detailed analysis of gradient-oriented transects (gradsects). The aim was to characterise the spatial organisation of each landscape, and to account for that organisation in functional terms related to the differential concentration of scarce resources by identifiable processes. Terrain, vegetation and soils data were collected along each gradsect. Boundary analysis was used to identify the types of landscape units at a range of scales. Soil analyses were used to determine the degree of differential concentration of nutrients within these units, and to infer the role of fluvial and aeolian processes in maintaining them. All three major landscape systems were found to be highly organised systems with distinctive resource-rich units or patches separated by more open, resource-poor zones. At the largest scale, distinct groves of trees were separated by open intergroves. At smaller-scales, individual trees, large shrubs, clumps of shrubs, fallen logs and clumps of grasses constituted discrete patches dispersed across the landscape. Our soil analyses confirmed that these patches act as sinks by filtering and concentrating nutrients lost from source areas (e.g., intergroves). We suggest that fluvial runoff-runon and aeolian saltation-deposition are the physical processes involved in these concentration effects, and in building and maintaining patches; biological activities also maintain patches. This organisation of patches as dispersed resource filters (at different scales) has the overall function of conserving limited resources within semi-arid landscape systems. Understanding the role of landscape patchiness in conserving scarce resources has important implications for managing these landscapes for sustainable land use, and for the rehabilitation of landscapes already degraded.     

Sensitivity of landscape resistance estimates based on point selection functions to scale and behavioral state: pumas as a case study

Estimating landscape resistance to animal movement is the foundation for connectivity modeling, and resource selection functions based on point data are commonly used to empirically estimate resistance. In this study, we used GPS data points acquired at 5-min intervals from radiocollared pumas in southern California to model context-dependent point selection functions. We used mixed-effects conditional logistic regression models that incorporate a paired used/available design to examine the sensitivity of point selection functions to the scale of available habitat and to the behavioral state of individual animals. We compared parameter estimates, model performance, and resistance estimates across 37 scales of available habitat, from 250 to 10,000 m, and two behavioral states, resource use and movement. Point selection functions and resistance estimates were sensitive to the chosen scale of the analysis. Multiple characteristic scales were found across our predictor variables, indicating that pumas in the study area are responding at different scales to different landscape features and that multi-scale models may be more appropriate. Additionally, point selection functions and resistance estimates were sensitive to behavioral state; specifically, pumas engaged in resource use behavior had an opposite selection response to some land cover types than pumas engaged in movement behavior. We recommend examining a continuum of scales and behavioral states when using point selection functions to estimate resistance.     

Using fractal analysis to assess how species perceive landscape structure

To develop a species-centered definition of landscapes, I suggest using a fractal analysis of movement patterns to identify the scales at which organisms are interacting with the patch structure of the landscape. Significant differences in the fractal dimensions of movement patterns of two species indicate that the species may be interacting with the patch structure at different scales. Fractal analysis therefore permits comparisons of landscape perceptions of different species within the same environment.I tested the utility of this fractal application by analyzing the movement patterns of three species of acridid grasshoppers (Orthoptera) in a grassland mosaic. The largest species moved up to 6 times faster than the two smaller species, and species exhibited different responses to microlandscape structure within 25-m² plots. Further, the largest species exhibited different responses to microlandscape structure in two pastures subjected to different intensities of cattle grazing. This species thus is able to integrate information on landscape structure at broad spatial scales. Fractal analysis of movement patterns revealed that the two small species had significantly more tortuous patterns than the larger species, which suggests that these species are interacting with patch structure at a finer scale of resolution than the large species. Fractal analysis can be used to identify the perceptive resolution of a species; that is, the spatial grain and extent at which they are able to perceive and respond to heterogeneity. Analysis of movement patterns across a range of spatial scale may reveal shifts in fractal dimension that reflect transitions in how species respond to the patch structure of the landscape at different scales.     

How to define a patch: a spatial model for hierarchically delineating organism-specific habitat patches

Landscape analysis and delineation of habitat patches should take into account organism-specific behavioral and perceptual responses to landscape structure because different organisms perceive and respond to landscape features over different ranges of spatial scales. The commonly used methods for delineating habitat based on rules of contiguity do not account for organism-specific responses to landscape patch structure and have undesirable properties, such as being dependent on the scale of base map used for analysis. This paper presents an improved patch delineation algorithm, “PatchMorph,” which can delineate patches across a range of spatial scales based on three organism-specific thresholds: (1) land cover density threshold, (2) habitat gap maximum thickness (gap threshold), and (3) habitat patch minimum thickness (spur threshold). This algorithm was tested on an “idealized” landscape with landscape gaps and spurs of known size, and delineated patches as expected. It was then applied to delineate patches from a neutral random fractal landscape, which showed that as the input gap and spur thickness thresholds were increased, the number of patches decreased from 59 (low thresholds) patches to 1 (high thresholds). The algorithm was then applied to model western yellow-billed cuckoo (Coccyzus americanus occidentalis) nesting habitat patches based on spur and gap thresholds specific to this organism. Both these analyses showed that fewer patches were delineated by PatchMorph than by rules of contiguity, and those patches were larger, had smoother edges, and had fewer gaps within the patches. This algorithm has many applications beyond those presented in this paper, including habitat suitability analysis, spatially explicit population modeling, and habitat connectivity analysis.     

Movement behavior in response to landscape structure: the role of functional grain

Landscape structure can influence the fine-scale movement behavior of dispersing animals, which ultimately may influence ecological patterns and processes at broader scales. Functional grain refers to the finest scale at which an organism responds to spatial heterogeneity among patches and extends to the limits of its perceptual range. To determine the functional grain of a model insect, red flour beetle (Tribolium castaneum), we examined its movement behavior in response to experimental flour landscapes. Landscape structure was varied by manipulating habitat abundance (0%, 10%, 30%, and 100%) and grain size of patches (fine-2 × 2 cm, intermediate-5 × 5 cm, and coarse-10 × 10 cm) in 50 × 50 cm landscapes. Pathway metrics indicated that beetles used a similar proportion of all landscape types. Several pathway metrics indicated a graded response from the fine to the coarse grain landscape. Lacunarity analysis of beetle pathways indicated a non-linear change in space use between the fine and intermediate landscapes and the coarse-grained landscape. Beetles moved more slowly and tortuously (with many turns), and remained longer in both the overall landscape and individual patches, in fine-grained compared to coarse-grained landscapes. Our research demonstrates how detailed examination of movement pathways and measures of lacunarity can be useful in determining functional grain. Spatially explicit, organism-centered studies focusing on behavioral responses to different habitat configurations can serve as an important first step to identify behavioral rules of movement that may ultimately lead to more accurate predictions of space use in landscapes.