Cooperative Fish and Wildlife Research Units Program: all
Education, Research and Technical Assistance for Managing Our Natural Resources

Animal diel activity patterns can aid understanding of (a) how species behaviour-ally adapt to anthropogenic and natural disturbances, (b) mechanisms of speciesco-existence through temporal partitioning, and (c) community or ecosystem ef-fects of diel activity shifts.2. Activity patterns often vary spatially, a feature ignored by the kernel density es-timators (KDEs) currently used for estimating diel activity. Ignoring this source ofheterogeneity may lead to biased estimates of uncertainty and misleading conclu-sions regarding the drivers of diel activity. Thus, there is a need for more flexiblestatistical approaches for estimating activity patterns and testing hypotheses re-garding their biotic and abiotic drivers.3. We illustrate how trigonometric terms and cyclic cubic splines combined withhierarchical models can provide a valuable alternative to KDEs. Like KDEs, thesemodels accommodate circular data, but they can also account for site-to-site andother sources of variability, correlation amongst repeated measures, and variablesampling effort. They can also more readily quantify and test hypotheses relatedto the effects of covariates on activity patterns.4. Through empirical case studies, we illustrate how hierarchical models can quan-tify changes in activity levels due to seasonality and in response to biotic and abi-otic factors (e.g. anthropogenic stressors and co-occurrence). We also describefrequentist and Bayesian approaches for quantifying site- specific (conditional)and population-averaged (marginal) activity patterns.5. We provide guidelines and tutorials with detailed step-by-step instructions forfitting and interpreting hierarchical models applied to time-stamped data, such asthose recorded by camera traps and audio recorders. We conclude that this ap-proach offers a viable, flexible, and effective alternative to KDEs when modellinganimal activity patterns.