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Animals are faced with a variety of dangers or threats, which are increasing in frequency with ongoing environmental change. While our understanding of fearfulness of such dangers is growing in the context of predation and parasitism risk, the extent to which non-trophic, interspecific dangers elicit fear in animals remains less appreciated. We provide an experimental test for fear responses of savannah ungulates to a dominant and aggressive megaherbivore, the African bush elephant (Loxodonta africana), and contrast responses to an apex predator known to elicit fear in this system. Using an automated behavioural response system, we contrast vigilance and run responses of ungulates to elephant, leopard (Panthera pardus), and control (red-chested cuckooCuculus solitarius) vocalizations. Overall, we find that ungulates responded to elephant calls, both in terms of an increase in run and vigilance responses relative to controls. The magnitude of most behavioural responses (four of six considered) to elephant vocalizations were not significantly different than responses to leopards. These results suggest that megaherbivores can elicit strong non-trophic fear responses by ungulates and call to broaden frameworks on fear to consider dominant species, such as megaherbivores, as key modifiers of fear-induced interactions. 

Balancing the competing, and often conflicting, needs of people and wildlife in shared landscapes is a major challenge for conservation science and policy worldwide. Connectivity is critical for wildlife persistence, but dispersing animals may come into conflict with people, leading to severe costs for humans and animals and impeding connectivity. Thus, conflict mitigation and connectivity present an apparent dilemma for conservation. We present a framework to address this dilemma and disentangle the effects of barriers to animal movement and conflict-induced mortality of dispersers on connectivity. We extend random-walk theory to map the connectivity–conflict interface, or areas where frequent animal movement may lead to conflict and conflict in turn impedes connectivity. We illustrate this framework with the endangered Asian elephantElephas maximus, a species that frequently disperses out of protected areas and comes into conflict with humans. We mapped expected movement across a human-dominated landscape over the short- and long-term, accounting for conflict mortality. Natural and conflict-induced mortality together reduced expected movement and connectivity among populations. Based on model validation, our conflict predictions that explicitly captured animal movement better explained observed conflict than a model that considered distribution alone. Our work highlights the interaction between connectivity and conflict and enables identification of location-specific conflict mitigation strategies that minimize losses to people, while ensuring critical wildlife movement between habitats. By predicting where animal movement and humans collide, we provide a basis to plan for broad-scale conservation and the mutual well-being of wildlife and people in shared landscapes. 

Abstract Consumers, including megaherbivores and fire, are considered important limiting forces for woody plants and canopy closure in African savannas. However, climatic events like drought can also play a significant role in limiting trees and maintaining tree‐grass coexistence in savannas. The extent to which top‐down control (e.g. megaherbivores) and bottom‐up resource limitation through drought and competition interact to influence savanna tree mortality and woody structure is unclear. Here, we compared the change in the number of large trees before and after a severe drought in a savanna with elephants ( Loxodonta africana ) and one without elephants. Elephants and drought both limited the number of large trees at our sites, but contrary to our predictions, there was no interactive effect of these drivers on overall changes in tree densities. However, there was a synergistic effect on the dominant tree species, Senegalia nigrescens , such that tree loss post‐drought was greater where elephants were present compared to where they were absent. Hence, our results suggest that species‐specific differences in drought resistance, as well as density‐dependent factors, likely impact the severity of drought effects on savanna tree communities. In savannas, drought has the potential to exert strong control on tree survival and prevent canopy closure, thus partially filling the role of megaherbivores in limiting large trees when these consumers are absent. As drought severity and frequency are predicted to increase in the future, the influence of drought on savanna vegetation structure becomes increasingly important to consider. 

Abstract Genetic connectivity lies at the heart of evolutionary theory, and landscape genetics has rapidly advanced to understand how gene flow can be impacted by the environment. Isolation by landscape resistance, often inferred through the use of circuit theory, is increasingly identified as being critical for predicting genetic connectivity across complex landscapes. Yet landscape impediments to migration can arise from fundamentally different processes, such as landscape gradients causing directional migration and mortality during migration, which can be challenging to address. Spatial absorbing Markov chains (SAMC) have been introduced to understand and predict these (and other) processes affecting connectivity in ecological settings, but the relationship of this framework to landscape genetics remains unclear. Here, we relate the SAMC to population genetics theory, provide simulations to interpret the extent to which the SAMC can predict genetic metrics and demonstrate how the SAMC can be applied to genomic data using an example with an endangered species, the Panama City crayfish Procambarus econfinae , where directional migration is hypothesized to occur. The use of the SAMC for landscape genetics can be justified based on similar grounds to using circuit theory, as we show how circuit theory is a special case of this framework. The SAMC can extend circuit‐theoretic connectivity modelling by quantifying both directional resistance to migration and acknowledging the difference between migration mortality and resistance to migration. Our empirical example highlights that the SAMC better predicts population structure than circuit theory and least‐cost analysis by acknowledging asymmetric environmental gradients (i.e. slope) and migration mortality in this species. These results provide a foundation for applying the SAMC to landscape genetics. This framework extends isolation‐by‐resistance modelling to account for some common processes that can impact gene flow, which can improve predicting genetic connectivity across complex landscapes.