Preface 1. Spatial concepts and notions 2. Ecological and spatial processes 3. Points, lines and graphs 4. Spatial analysis of complete point location data 5. Contiguous units analysis 6. Spatial analysis of sample data 7. Spatial relationship and multiscale analysis 8. Spatial autocorrelation and inferential tests 9. Spatial partitioning: spatial clusters and boundary detection 10. Spatial diversity analysis 11. Spatio-temporal analysis 12. Closing comments and future directions References Index.

Spatial Analysis A Guide for Ecologists

Recent advances in spatial ecology have improved our understanding of the role of large-scale animal movements. However, an unsolved problem concerns the inherent stochasticity involved in many animal search displacements and its possible adaptive value. When animals have no information about where targets (i.e., resource patches, mates, etc.) are located, different random search strategies may provide different chances to find them. Assuming random-walk models as a necessary tool to understand how animals face such environmental uncertainty, we analyze the statistical differences between two random-walk models commonly used to fit animal movement data, the Levy walks and the correlated random walks, and we quantify their efficiencies (i.e., the number of targets found in relation to total displacement) within a random search context. Correlated random-walk properties (i.e., scale-finite correlations) may be interpreted as the by-product of locally scanning mechanisms. Levy walks, instead, have fundamenta...

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Animal search strategies: a quantitative random-walk analysis

Summary 1. I synthesize the understanding of the relationship between landscape structure and animal movement in human-modified landscapes. 2. The variety of landscape structures is first classified into four categories: continuous habitat, patchy habitat with high-quality matrix, patchy habitat with low-quality matrix, and patchy, ephemeral habitat. Using this simplification I group the range of evolved movement parameters into four categories or movement types. I then discuss how these movement types interact with current human-caused landscape changes, and how this often results in non-optimal movement. 3. From this synthesis I develop a hypothesis that predicts the relative importance of the different population-level consequences of these non-optimal movements, for the four movement types. 4. Populations of species that have inhabited landscapes with high habitat cover or patchy landscapes with low-risk matrix should have evolved low boundary responses and moderate to high movement probabilities. These species are predicted to be highly susceptible to increased movement mortality resulting from habitat loss and reduced matrix quality. 5. In contrast, populations of species that evolved in patchy landscapes with high-risk matrix or dynamic patchy landscapes are predicted to be highly susceptible to decreased immigration and colonization success, due to the increasing patch isolation that results from habitat loss. 6. Finally, I discuss three implications of this synthesis: (i) ‘least cost path’ analysis should not be used for land management decisions without data on actual movement paths and movement risks in the landscape; (ii) ‘dispersal ability’ is not simply an attribute of a species, but varies strongly with landscape structure such that the relative rankings of species’ dispersal abilities can change following landscape alteration; and (iii) the assumption that more mobile species are more resilient to human-caused landscape change is not generally true, but depends on the structure of the landscape where the species evolved.

Non‐optimal animal movement in human‐altered landscapes

1. In order to study and predict population distribution, it is crucial to identify and understand factors affecting individual movement decisions at different scales. Movements of foraging animals should be adjusted to the hierarchical spatial distribution of resources in the environment and this scale-dependent response to environmental heterogeneity should differ according to the forager's characteristics and exploited habitats. 2. Using First-Passage Time analysis, we studied scales of search effort and habitat used by individuals of seven sympatric Indian Ocean Procellariiform species fitted with satellite transmitters. We characterized their search effort distribution and examined whether species differ in scale-dependent adjustments of their movements according to the marine environment exploited. 3. All species and almost all individuals (91% of 122 individuals) exhibited an Area-Restricted Search (ARS) during foraging. At a regional scale (1000s km), foraging ranges showed a large spatial overlap between species. At a smaller scale (100s km, at which an increase in search effort occurred), a segregation in environmental characteristics of ARS zones (where search effort is high) was found between species. 4. Spatial scales at which individuals increased their search effort differed between species and also between exploited habitats, indicating a similar movement adjustment for predators foraging in the same habitat. ARS zones of the two populations of wandering albatross Diomedea exulans (Crozet and Kerguelen) were similar in their adjustments (i.e. same ARS scale) as well as in their environmental characteristics. These two populations showed a weak spatial overlap in their foraging distribution, with males foraging in more southerly waters than females in both populations. 5. This study demonstrates that predators of several species adjust their foraging behaviour to the heterogeneous environment and these scale-dependent movement adjustments depend on both forager and environment characteristics.

At-sea distribution and scale-dependent foraging behaviour of petrels and albatrosses: a comparative study.

How to reliably estimate the tortuosity of an animal's path:. straightness, sinuosity, or fractal dimension?

Movement is a primary mechanism coupling animals to their environment, yet there exists little empirical analysis to test our theoretical knowledge of this basic process. We used correlated random walk (CRW) models and satellite telemetry to investigate long-distance movements of caribou, the most vagile, non-volant terrestrial vertebrate in the world. Individual paths of migratory and sedentary female caribou were quantified using measures of mean move length and angle, and net squared displacements at each successive move were compared to predictions from the models. Movements were modelled at two temporal scales. For paths recorded through one annual cycle, the CRW model overpredicted net displacement of caribou through time. For paths recorded over shorter intervals delineated by seasonal behavioural changes of caribou, there was excellent correspondence between model predictions and observations for most periods for both migratory and sedentary caribou. On the smallest temporal scale, a CRW model significantly overpredicted displacements of migratory caribou during 3 months following calving; this was also the case for sedentary caribou in late summer, and in late winter. In all cases of overprediction there was significant positive autocorrelation in turn direction, indicating that movements were more tortuous than expected. In one case of underprediction, significant negative autocorrelation of sequential turn direction was evident, indicating that migratory caribou moved in straightened paths during spring migration to calving grounds. Results are discussed in light of known migration patterns and possible limiting factors for caribou, and indicate the applicability of CRW models to animal movement at vast spatial and temporal scales, thus assisting in future development of more sophisticated models of population spread and redistribution for vertebrates.

C. M. Bergman

Papers

Caribou movement as a correlated random walk