Simple metrics to characterize inter-individual and temporal variation in habitat selection behaviour

被引:11
作者
Bastille-Rousseau, Guillaume [1 ,2 ,3 ]
Wittemyer, George [3 ,4 ]
机构
[1] Southern Illinois Univ, Cooperat Wildlife Res Lab, Carbondale, IL 62901 USA
[2] Southern Illinois Univ, Sch Biol Sci, Carbondale, IL 62901 USA
[3] Save Elephants, Nairobi, Kenya
[4] Colorado State Univ, Dept Fish Wildlife & Conservat Biol, Ft Collins, CO 80523 USA
基金
加拿大自然科学与工程研究理事会;
关键词
African elephant; GPS telemetry; individual variation; movement; resource selection; specialization; step-selection function; ECOLOGY; RISK; AUTOCORRELATION; ELEPHANTS; FORAGE; MODELS;
D O I
10.1111/1365-2656.13738
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Individual variation in habitat selection and movement behaviour is receiving growing attention, but primarily with respect to characterizing behaviours in different contexts as opposed to decomposing structure in behaviour within populations. This focus may be limiting advances in understanding the diversity of individual behaviour and its influence on population organization. We propose a framework for characterizing variation in space-use behaviour with the aim of advancing interpretation of its form and function. Using outputs from integrated step-selection analyses of 20 years of telemetry data from African elephants Loxodonta Africana, we developed four metrics characterizing differentiation in resource selection behaviour within a population (specialization [magnitude of the response independent of direction], heterogeneity [inter-individual variation], consistency [temporal shift in response] and reversal [frequency of directional changes in the response]). We contrasted insight from the developed metrics relative to the mean population response using an example focused on two covariates. We then expanded this contrast by evaluating if the metrics identify structurally important information on seasonal shifts in resource selection behaviours in addition to that provided by mean selection coefficients through principal component analyses (PCAs) and a random forest classification. The simplified example highlighted that for some covariates focusing on the population average failed to capture complex individual variation in behaviours. The PCAs revealed that the developed metrics provided additional information in explaining the patterns in elephant selection beyond that offered by population average covariate values. For elephants, specialization and heterogeneity were informative, with specialization often being a better descriptor of differences in seasonal resource selection behaviour than population average responses. Summarizing these metrics spatially and temporally, we illustrate how these metrics can provide insights on overlooked aspects of animal behaviour. Our work offers a new approach in how we conceptualize variation in space-use behaviour (i.e. habitat selection and movement) by providing ways of encapsulating variation that enables diagnoses of the drivers of individual-level variability in a population. The developed metrics explicitly distil how variation in a behaviour is structured among individuals and over time which could facilitate comparative work across time, populations or strata within populations.
引用
收藏
页码:1693 / 1706
页数:14
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