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Abstract Animal movement strategies, or suites of correlated traits reflecting how individuals respond to their environment, are often shaped by spatiotemporal heterogeneity and predictability in physicochemical conditions, resources or risk.While movement strategies have been well studied in terrestrial animals using high‐resolution satellite telemetry, our understanding of how seascape heterogeneity influences movement strategies in aquatic systems remains limited due to technological constraints.We used a non‐gridded passive acoustic telemetry array to identify and classify movement strategies of Common Snook (Centropomus undecimalis) and Atlantic Tarpon (Megalops atlanticus) within two estuarine systems in Everglades National Park, Florida. We then evaluated how seasonal heterogeneity and environmental predictability influenced movement strategy selection.Using a suite of movement metrics, we identified three statistically distinct movement strategies that varied in movement frequency, home range size and site fidelity. Fish in more homogeneous environments tended to adopt strategies involving frequent movements, larger home ranges and shorter stays in a given location. In contrast, increased seascape heterogeneity was associated with movement strategies characterized by less frequent movements, smaller home ranges and longer residence times. We also found species‐level differences in strategy use, with the predictability of dissolved oxygen, salinity and turbidity emerging as key environmental drivers of movement strategy selection.These results demonstrate that seascape heterogeneity and predictability strongly influence the emergence and selection of movement strategies in estuarine predators. Our findings provide a novel approach for identifying movement strategies in aquatic systems using passive acoustic telemetry and highlight the broader importance of seascape complexity in shaping animal behaviour and predicting responses to environmental change.
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Estimating encounter location distributions from animal tracking data
Abstract Ecologists have long been interested in linking individual behaviour with higher level processes. For motile species, this ‘upscaling’ is governed by how well any given movement strategy maximizes encounters with positive factors and minimizes encounters with negative factors. Despite the importance of encounter events for a broad range of ecological processes, encounter theory has not kept pace with developments in animal tracking or movement modelling. Furthermore, existing work has focused primarily on the relationship between animal movement and encounterrateswhile the relationship between individual movement and the spatiallocationsof encounter events in the environment has remained conspicuously understudied.Here, we bridge this gap by introducing a method for describing the long‐term encounter location probabilities for movement within home ranges, termed the conditional distribution of encounters (CDE). We then derive this distribution, as well as confidence intervals, implement its statistical estimator into open‐source software and demonstrate the broad ecological relevance of this distribution.We first use simulated data to show how our estimator provides asymptotically consistent estimates. We then demonstrate the general utility of this method for three simulation‐based scenarios that occur routinely in biological systems: (a) a population of individuals with home ranges that overlap with neighbours; (b) a pair of individuals with a hard territorial border between their home ranges; and (c) a predator with a large home range that encompassed the home ranges of multiple prey individuals. Using GPS data from white‐faced capuchinsCebus capucinus, tracked on Barro Colorado Island, Panama, and sleepy lizardsTiliqua rugosa,tracked in Bundey, South Australia, we then show how the CDE can be used to estimate the locations of territorial borders, identify key resources, quantify the potential for competitive or predatory interactions and/or identify any changes in behaviour that directly result from location‐specific encounter probability.The CDE enables researchers to better understand the dynamics of populations of interacting individuals. Notably, the general estimation framework developed in this work builds straightforwardly off of home range estimation and requires no specialized data collection protocols. This method is now openly available via thectmm Rpackage.
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- Award ID(s):
- 1915347
- PAR ID:
- 10387149
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Methods in Ecology and Evolution
- Volume:
- 12
- Issue:
- 7
- ISSN:
- 2041-210X
- Format(s):
- Medium: X Size: p. 1158-1173
- Size(s):
- p. 1158-1173
- Sponsoring Org:
- National Science Foundation
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