Giroux, A. | bioRxiv Science

bioRxiv2025

Impacts of climate change on the movement ecology of an imperfect homeotherm

Rapid, human-induced climate change has posed significant challenges to wildlife. One key strategy animals use to cope with environmental temperature fluctuations is behavioral thermoregulation. Understanding how climate change is expected to influence animal behavior is crucial for assessing its impact on species survival and informing effective conservation efforts. Giant anteaters have been found to exhibit conspicuous behavioral responses to temperature changes. Despite their broad thermal neutral zone (15 - 36{degrees}C), climate projections indicate that this vulnerable mammal is increasingly likely to experience heat stress. We used GPS tracking and continuous-time analyses to investigate how environmental temperature influences the movement ecology of giant anteaters. We integrated our findings with climate change projections to link giant anteaters responses to present weather conditions with those expected under future climate scenarios. Giant anteaters movement speed exhibited a negative quadratic response to temperature, peaking at 23.7{degrees}C. 95% of their movement occurred between 15.0 - 32.3{degrees}C, which aligns with their thermal neutral zone. The increasing temperature led giant anteaters to increase selection for native forests, but had no effect on selection for exotic tree plantations. This shows the importance of native forests as these thermal shelters help to mitigate the negative consequences of high temperatures on anteaters movement. However, the warmer temperatures predicted for Brazil throughout the rest of the 21st century indicate that giant anteaters may experience a reduction of up to 84% in their movement speed. This would hinder the acquisition of sufficient energy resources and threaten the species persistence. We emphasize the need for conservation efforts that account for the impacts of climate change on species survival and stress the importance of preserving forests as essential refuges that help wildlife to cope with rising temperatures.

ecology↗

bioRxiv2023

Bridging the gap between movement data and connectivity analysis using the time-explicit Step Selection Function (tSSF)

BackgroundUnderstanding how to connect habitat remnants to facilitate the movement of species is a critical task in an increasingly fragmented world impacted by human activities. The identification of dispersal routes and corridors through connectivity analysis requires measures of landscape resistance but there has been no consensus on how to calculate resistance from habitat characteristics, potentially leading to very different connectivity outcomes. MethodsWe propose a new model called the time-explicit step selection function (tSSF) that can be directly used for connectivity analysis in the context of the spatial absorbing Markov chain (SAMC) framework without requiring arbitrary transformations. The tSSF model combines a time model with a standard selection function and can provide complementary information regarding how animals use landscapes by separately assessing the drivers of time to traverse the landscape and the drivers of habitat selection. These models are illustrated using GPS-tracking data from giant anteaters (Myrmecophaga tridactyla) in the Pantanal wetlands of Brazil. ResultsThe time model revealed that the fastest movements tended to occur between 8 pm and 5 am, suggesting a crepuscular/nocturnal behavior. Giant anteaters moved faster over wetlands while moving much slower over forests and savannas, in comparison to grasslands. We found that wetlands were consistently avoided whereas forest and savannas tended to be selected. Importantly, this model revealed that selection for forest increased with temperature, suggesting that forests may act as important thermal shelters when temperatures are high. Finally, the tSSF results can be used to simulate movement and connectivity within a fragmented landscape, revealing that giant anteaters will often not use the shortest-distance path to the destination patch (because that would require traversing a wetland, an avoided habitat) and that approximately 90% of the individuals will have reached the destination patch after 49 days. ConclusionsThe approach proposed here can be used to gain a better understanding of how landscape features are perceived by individuals through the decomposition of movement patterns into a time and a habitat selection component. This approach can also help bridge the gap between movement-based models and connectivity analysis, enabling the generation of time-explicit results.

animal behavior and cognition↗