Dispersal and connectivity in increasingly extreme climatic conditions.

While climate change has been shown to impact several life-history traits of wild-living animal populations, little is known about its effects on dispersal and connectivity. Here, we capitalize on the highly variable flooding regime of the Okavango Delta to investigate the impacts of changing environmental conditions on the dispersal and connectivity of the endangered African wild dog (Lycaon pictus). Based on remote sensed flood extents observed over 20 years, we derive two extreme flood scenarios: a minimum and a maximum flood extent, representative of very dry and very wet environmental periods. These conditions are akin to those anticipated under increased climatic variability, as it is expected under climate change. Using a movement model parameterized with GPS data from dispersing individuals, we simulate 12,000 individual dispersal trajectories across the ecosystem under both scenarios and investigate patterns of connectivity. Across the entire ecosystem, surface water coverage during maximum flood extent reduces dispersal success (i.e., the propensity of individuals to disperse between adjacent subpopulations) by 12% and increases dispersal durations by 17%. Locally, however, dispersal success diminishes by as much as 78%. Depending on the flood extent, alternative dispersal corridors emerge, some of which in the immediate vicinity of human-dominated landscapes. Notably, under maximum flood extent, the number of dispersing trajectories moving into human-dominated landscapes decreases by 41% at the Okavango Delta's inflow, but increases by 126% at the Delta's distal end. This may drive the amplification of human-wildlife conflict. While predicting the impacts of climate change on environmental conditions on the ground remains challenging, our results highlight that environmental change may have significant consequences for dispersal patterns and connectivity, and ultimately, population viability. Acknowledging and anticipating such impacts will be key to effective conservation strategies and to preserve vital dispersal corridors in light of climate change and other human-related landscape alterations.

Higher Mortality Is Not a Universal Cost of Dispersal: A Case Study in African Wild Dogs.

AbstractMortality is considered one of the main costs of dispersal. A reliable evaluation of mortality, however, is often hindered by a lack of information about the fate of individuals that disappear under unexplained circumstances (i.e., missing individuals). Here, we addressed this uncertainty by applying a Bayesian mortality analysis that inferred the fate of missing individuals according to information from individuals with known fate. Specifically, we tested the hypothesis that mortality during dispersal is higher than mortality among nondispersers using 32 years of mark-resighting data from a free-ranging population of the endangered African wild dog (Lycaon pictus) in northern Botswana. Contrary to expectations, we found that mortality during dispersal was lower than mortality among nondispersers, indicating that higher mortality is not a universal cost of dispersal. Our findings suggest that group living can incur costs for certain age classes, such as limited access to resources as group density increases, that exceed the mortality costs associated with dispersal. By challenging the accepted expectation of higher mortality during dispersal, we urge for further investigations of this key life history trait and propose a robust statistical approach to reduce bias in mortality estimates.

When to stay and when to leave? Proximate causes of dispersal in an endangered social carnivore.

Reliable estimates of birth, death, emigration and immigration rates are fundamental to understanding and predicting the dynamics of wild populations and, consequently, inform appropriate management actions. However, when individuals disappear from a focal population, inference on their fate is often challenging. Here we used 30 years of individual-based mark-recapture data from a population of free-ranging African wild dogs Lycaon pictus in Botswana and a suite of individual, social and environmental predictors to investigate factors affecting the decision to emigrate from the pack. We subsequently used this information to assign an emigration probability to those individuals that were no longer sighted within their pack (i.e. missing individuals). Natal dispersal (i.e. emigration from the natal pack) showed seasonal patterns with female dispersal peaking prior to the mating season and male dispersal peaking at the beginning of the wet season. For both sexes, natal dispersal rate increased in the absence of unrelated individuals of the opposite sex in the pack. Male natal dispersal decreased with increasing number of pups in the pack and increased in larger packs. Female natal dispersal decreased with increasing number of pups in larger packs, but increased with increasing number of pups in smaller packs. Individuals of both sexes were less likely to exhibit secondary dispersal (i.e. emigration from a pack other than the natal pack) if they were dominant and if many pups were present in the pack. Our models predicted that 18% and 25% of missing females and males, respectively, had likely dispersed from the natal pack, rather than having died. A misclassification of this order of magnitude between dispersal and mortality can have far-reaching consequences in the evaluation and prediction of population dynamics and persistence, and potentially mislead conservation actions. Our study showed that the decision to disperse is context-dependent and that the effect of individual, social and environmental predictors differs between males and females and between natal and secondary dispersal related to different direct and indirect fitness consequences. Furthermore, we demonstrated how a thorough understanding of the proximate causes of dispersal can be used to assign a dispersal probability to missing individuals. Knowledge of causes of dispersal can then be used within an integrated framework to more reliably estimate mortality rates.

A three-step approach for assessing landscape connectivity via simulated dispersal: African wild dog case study.

Context: Dispersal of individuals contributes to long-term population persistence, yet requires a sufficient degree of landscape connectivity. To date, connectivity has mainly been investigated using least-cost analysis and circuit theory, two methods that make assumptions that are hardly applicable to dispersal. While these assumptions can be relaxed by explicitly simulating dispersal trajectories across the landscape, a unified approach for such simulations is lacking. Objectives: Here, we propose and apply a simple three-step approach to simulate dispersal and to assess connectivity using empirical GPS movement data and a set of habitat covariates. Methods: In step one of the proposed approach, we use integrated step-selection functions to fit a mechanistic movement model describing habitat and movement preferences of dispersing individuals. In step two, we apply the parameterized model to simulate dispersal across the study area. In step three, we derive three complementary connectivity maps; a heatmap highlighting frequently traversed areas, a betweenness map pinpointing dispersal corridors, and a map of inter-patch connectivity indicating the presence and intensity of functional links between habitat patches. We demonstrate the applicability of the proposed three-step approach in a case study in which we use GPS data collected on dispersing African wild dogs (Lycaon pictus) inhabiting northern Botswana. Results: Using step-selection functions we successfully parametrized a detailed dispersal model that described dispersing individuals' habitat and movement preferences, as well as potential interactions among the two. The model substantially outperformed a model that omitted such interactions and enabled us to simulate 80,000 dispersal trajectories across the study area. Conclusion: By explicitly simulating dispersal trajectories, our approach not only requires fewer unrealistic assumptions about dispersal, but also permits the calculation of multiple connectivity metrics that together provide a comprehensive view of landscape connectivity. In our case study, the three derived connectivity maps revealed several wild dog dispersal hotspots and corridors across the extent of our study area. Each map highlighted a different aspect of landscape connectivity, thus emphasizing their complementary nature. Overall, our case study demonstrates that a simulation-based approach offers a simple yet powerful alternative to traditional connectivity modeling techniques. It is therefore useful for a variety of applications in ecological, evolutionary, and conservation research. Supplementary Information: The online version contains supplementary material available at 10.1007/s10980-023-01602-4.

Behavioral responses of terrestrial mammals to COVID-19 lockdowns.

COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals' 1-hour 95th percentile displacements declined by 12% and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.