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UBC Theses and Dissertations

Animal movements and landscape pattern : implications for assessing habitat use Wilson, Steven Foster


To understand ecological processes, it is important to study observed patterns at appropriate scales. Patterns of habitat use by animals have a spatial dimension that is usually ignored in analyses of habitat selection and preference. Hence, I studied the interaction between animal movement behaviour and landscape pattern, across a variety of spatial scales. The purpose of the study was to determine how these variables affect our ability to make inferences about the habitats used by animals. I simulated the movements of animals on maps of real and simulated landscapes. I modelled movements that were either insensitive or sensitive to the underlying distribution of habitats. The unequal proportions of different habitat types had the greatest influence on measures of habitat use and preference, but measures were also affected by the scale of animal movements, the affinity of animals for different habitats, the size and arrangement of habitat patches, and the method of analysis. Changing the scale of animal movements by varying the daily distances that simulated animals moved, had little effect on the mean use of different habitats, but scale affected the variance of habitat use among simulated animals. Small-scale movements produced the largest overall variances, and variances were greatest for the most abundant habitats. The correlation between variance in habitat use and proportions of habitat types was an expected result, although previous researchers have not assessed the implications of the correlation. Spatial effects were evident primarily where home ranges were less than about ten times the median size of habitat patches on the landscape. The relationship between variance in habitat use and scale of animal movements was similar among all simulations. Regions where variance did not change with scale were next to a region where variance changed mono tonically with scale (log-transformed). This suggested the existence of 'domains of scale' or regions where a given property (in this case, variance in habitat use) changes predictably with scale. Characteristics of these regions were a function of the proportions of habitat types on the landscape, the size and arrangement of habitat patches, and of the variances associated with other parameters of the model. Domains were not separated by sharp discontinuities; higher variances among variables such as home range size and patch size, as well as the random placement of simulated animals tended to make scaling properties less distinct. Preference analyses often distorted the true habitat affinities of simulated animals. These distortions were partly due to the unit-sum constraint which affected measures of both habitat use and availability (measures for different habitat types summed to one), and the analyses used to compare them. However, landscape pattern also affected the ability to make accurate inferences about habitat preference. The proportions of different habitat types, as well as their patch sizes and arrangement, constrained the ability of animals to exploit habitats according to their affinity for habitats. These constraints were reflected in the results of preference analyses, which rarely detected strong preference for rare habitat types, even when animals had a high affinity for those habitats. This result depended on the inability of simulated animals to learn the locations of high quality patches. I analysed radio telemetry data collected on grizzly bears (Ursus arctos) in the Flathead Valley, British Columbia to examine the degree to which landscape characteristics could produce similar patterns of habitat preference in real and simulated animal movement data. Results- suggested that simulated animals that did not discriminate among different habitat types could have rank orders of habitat preference similar to that observed in the actual grizzly bear data, but only when the movements of simulated animals were determined by a spatially explicit model. However, there was a 'boundary effect' in the spatially-explicit simulations that was largely responsible for the fit between simulated and actual data. The magnitudes of preference and avoidance of habitats were greater in the bear data than in the simulated data. Additional simulations based on a model of grizzly bear habitat capability revealed that methods of analysing preference differed in their ability to reflect the habitat affinities suggested by the bear data. These results underline the importance of considering the spatial dimension of habitat use data when mapping habitats, developing data collection protocols, and interpreting results.

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