Determining the optimal movement strategies in environments with heterogeneously distributed resources and toxicants

Environmental stress forces populations to move away from oppressive regions and look for desirable environments. Different species can respond to the same spatial distributions of resources and toxicants with distinct movement strategies. However, the optimal behavioral strategy may differ when resources and stressors occur simultaneously or if they are distributed in different patterns. We compared the total abundance of two strains of Caenorhabditis elegans with different locomotion speeds as they forage in various spatial distributions of resources and toxicants. Informed by the experimental observations, we proposed a new two‐state population model, wherein nutrient uptake and reproduction are modeled separately, as driven by the spatial distribution of resources and toxicants. We found that fast movers had an advantage when either the toxicant coverage or the overlap between toxicants and resources was increased. Also, to assess the effectiveness of designing refuges to conserve species in stressful cases, we compared different preferences of locations of refuge areas according to movement strategies. Our mathematical model explained that fast movement enables individuals to consume resources at one location and reproduce at a separate location to avoid the toxicant‐induced reduction in reproduction rate, which underlined its observed advantage in certain experimental settings. This work provided a better model to predict how species with different movement strategies respond to environmental stressors in natural systems.

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Publication Details

Journal
Oikos
Published
2025-03-28
DOI
https://doi.org/10.1111/oik.10962
Citations
1
Primary Topic
Diffusion and Search Dynamics
Type
article
Field-Weighted Citation Impact
0.81
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article

Determining the optimal movement strategies in environments with heterogeneously distributed resources and toxicants

Kevin M. Collins, King‐Yeung Lam, Jason B. Belden, Bo Zhang et al.
1 citations
Oikos
Diffusion and Search Dynamics
0.81
article

Determining the optimal movement strategies in environments with heterogeneously distributed resources and toxicants

Kevin M. Collins, King‐Yeung Lam, Jason B. Belden, Bo Zhang, Lin Wang, Ameir Ali, Ashley Baragary
article en
1 citations

Abstract

Environmental stress forces populations to move away from oppressive regions and look for desirable environments. Different species can respond to the same spatial distributions of resources and toxicants with distinct movement strategies. However, the optimal behavioral strategy may differ when resources and stressors occur simultaneously or if they are distributed in different patterns. We compared the total abundance of two strains of Caenorhabditis elegans with different locomotion speeds as they forage in various spatial distributions of resources and toxicants. Informed by the experimental observations, we proposed a new two‐state population model, wherein nutrient uptake and reproduction are modeled separately, as driven by the spatial distribution of resources and toxicants. We found that fast movers had an advantage when either the toxicant coverage or the overlap between toxicants and resources was increased. Also, to assess the effectiveness of designing refuges to conserve species in stressful cases, we compared different preferences of locations of refuge areas according to movement strategies. Our mathematical model explained that fast movement enables individuals to consume resources at one location and reproduce at a separate location to avoid the toxicant‐induced reduction in reproduction rate, which underlined its observed advantage in certain experimental settings. This work provided a better model to predict how species with different movement strategies respond to environmental stressors in natural systems.

OikosVol. 2025(6)
Oklahoma State University (US), University of Miami (US), The Ohio State University (US), Shaanxi Normal University (CN)
Openalex Percentile: Top 30%
Diffusion and Search Dynamics
0.81
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