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Purpose: Habitat selection in animals is a hierarchal process that operates across multiple temporal and spatial scales, adapting to changes in environmental conditions, human disturbances, and predation risks. Despite its significance, previous research often oversimplifies temporal dynamics by categorizing them into broad seasonal and diel patterns, overlooking the continuous nature of temporal variability and habitat specificity.
Methods: We investigated the temporal patterns in habitat selection of moose (Alces alces) in highly heterogenous landscapes at the southwestern edge of their European range using step-selection functions. Utilizing over 700,000 GPS locations from 34 adult moose, we aimed to assess seasonal and diel patterns in their selectivity for both natural and human-related habitats.
Results: Our findings revealed significant overall temporal variation in moose habitat selection at both seasonal and diel scales. Moose selectivity toward different habitats showed low repeatability over time, with 35% of cases displaying negative correlation between selectivity in different time windows. Diel changes were more pronounced, showing 5.6-fold difference in cumulative selectivity, compared to 1.4-fold difference in seasonal dynamics. Notably, moose exhibited lower selectivity during nighttime hours throughout the year compared to daytime hours. The study also highlighted distinct habitat selection patterns across different habitat types: natural habitats (deciduous forests, coniferous forests, wetlands) exhibited pronounced seasonal variation, while anthropogenic habitats (grasslands, arable land, roads and settlements) showed more diel variability. Moose generally avoided human-related habitats during daytime hours, but their preferences during nighttime varied depending on the habitat type and time of year.
Conclusion: This research advances our understanding of the complex temporal patterns in habitat selection by large herbivores and underscores the importance of considering temporal dynamics in habitat selection modelling.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11465569 | PMC |
http://dx.doi.org/10.1186/s40462-024-00508-3 | DOI Listing |
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College of Science, China Agricultural University, Beijing, China.
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Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
The rapid expansion of solar photovoltaic (PV) power generation raises concerns regarding its impact on terrestrial ecosystems. Although the influence of PV panels on soil conditions and plant biomass is acknowledged, their effects on the assembly processes and co-occurrence networks of soil microbial communities remain understudied. Clarifying this influence is crucial for understanding the effects of photovoltaic panels on soil ecosystem functions.
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Plant Molecular Biology and Biotechnology Laboratory, School of Agriculture, Food, and Ecosystem Sciences, The University of Melbourne, Parkville, Australia.
Climate change is leading to more frequent and severe extreme temperature events, negatively impacting agricultural productivity and threatening global food security. Plant reproduction, the process fundamental to crop yield, is highly susceptible to heatwaves, which disrupt pollen development and ultimately affect seed-set and crop yields. Recent research has increasingly focused on understanding how pollen grains from various crops react to heat stress at the molecular and cellular levels.
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Wild Minds Lab, School of Psychology and Neuroscience, University of St Andrews, Fife, United Kingdom.
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