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Deterministic, random, or in between? Inferring the randomness level of wildlife movements
Teresa Goicolea1, Aitor Gastón2, Pablo Cisneros-Araujo2
1ETSI Montes, Forestal y del Medio Natural, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040, Madrid, Spain. t.goicolea@upm.es.
Movement Ecology
|June 30, 2021
Summary
Optimizing movement randomness in connectivity models improves corridor delineation for species conservation. Validating different randomness levels revealed intermediate settings best reflect species movement, outperforming traditional deterministic or random approaches for effective wildlife management.
Area of Science:
- Ecology and Conservation Biology
- Spatial Ecology and Connectivity Modeling
- Wildlife Movement Analysis
Background:
- Accurate connectivity modeling requires frameworks that incorporate species movement preferences and route selection randomness.
- Traditional connectivity approaches (least-cost path, circuit theory) unrealistically assume movements are entirely deterministic or random.
- The randomized shortest path approach allows for intermediate randomness, but optimal levels require validation against empirical data, a step seldom performed.
Purpose of the Study:
- To compare different validation methods for inferring the optimal level of movement randomness in connectivity studies.
- To assess the practical consequences of using traditional versus optimized randomness approaches for delineating wildlife corridors.
- To improve the biological basis and validation of connectivity models for effective conservation.
Main Methods:
- A case study on the Iberian lynx (endangered species) was used to assess connectivity among population nuclei.
- A conductance surface was created using point selection functions, considering behavioral states (territorial, exploratory).
- Movement randomness was optimized using independent GPS data and various validation techniques; corridors were delineated using randomized shortest path and traditional methods.
Main Results:
- Connectivity models incorporating intermediate levels of movement randomness consistently outperformed models with extreme (deterministic or random) randomness.
- While optimal randomness levels varied among validation methods, corridor delineation results were broadly similar.
- Traditional approaches and randomized shortest path models with extreme randomness produced comparable corridor networks, distinct from those derived from optimized randomness levels.
Conclusions:
- A robust connectivity model was developed that calibrates movement randomness using comprehensive validation methods.
- Optimized randomness levels provide a more biologically realistic basis for connectivity modeling than traditional approaches.
- This approach represents a significant advancement for improving the efficiency and success of conservation management actions.
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