Biology subjects

Dejeante, R.

Publications and source records attributed to Dejeante, R..

4 recordsLinked to original sources

bioRxiv2025

Are all waterholes equal from a lion's view? Exploring the role of prey abundance and catchability in waterhole visitation patterns in a savannah ecosystem

Prey abundance and catchability shape the spatial ecology of predators. Predators can select habitats where prey are more abundant to maximize encounter rate with prey or habitats where prey are more catchable to maximize prey capture. These hypotheses are commonly referred to as prey-abundance and prey-catchability hypotheses. Although these hypotheses are often tested at the landscape scale, little is known about how between-patch variations in prey abundance and catchability determine the space use of predators. In many savannah ecosystems, large herbivores aggregate around waterholes, which become hotspots of prey and their selection by predators is classically interpreted as supporting the prey-abundance hypothesis. Here, we investigated whether between-waterhole variations in prey abundance and catchability influence the frequency and duration of lion visits to waterholes, testing the prey-abundance and prey-catchability hypotheses at the resource-patch scale. We combined datasets on (1) lion movements recorded from GPS collars deployed on 20 adult males and 16 adult females between 2002 and 2015, (2) prey abundance evaluated from long-term, regular monitoring of waterholes and (3) prey catchability evaluated from remote-sensing satellite imagery of vegetation cover around waterholes in Hwange National Park (Zimbabwe). Lions did not use all waterholes in their territory equally: there was a high variability in the frequency and duration of visits. Surprisingly, between-waterhole variations in prey abundance and catchability only slightly explained these variations in frequency - and even less in duration - of lion visits to waterholes. Yet, the frequency of lion visits to waterholes decreased with the number of waterholes within their territory, and male lions more frequently visited the waterholes surrounded by more open habitats. We discuss the limits of our work, but also the ecological mechanisms that may explain these findings. First, lions and their prey are involved in a shell-game that leads them to adopt unpredictable movement strategies. Second, lions have only access to a limited number of waterholes amongst which to distribute their hunting effort. Lastly, lions visit waterholes not only to hunt but also to interact with social mates and competitors. This work challenges the implicit assumption that all waterholes are the same from a lions view and calls for further studies investigating the drivers of the variability in lion visits at the resource-patch scale.

ecology↗

bioRxiv2024

Do mixed-species groups travel as one? An investigation on large African herbivores using animal-borne video collars

Although prey foraging in mixed-species groups benefit from a reduced risk of predation, whether heterospecific groupmates move together in the landscape, and more generally to what extent mixed-species groups remain cohesive over time and space remains unknown. Here, we used GPS collars with video cameras to investigate the movements of plains zebras (Equus quagga) in mixed-species groups. Blue wildebeest (Connochaetes taurinus), impalas (Aepyceros melampus) and giraffes (Giraffa camelopardalis) commonly form mixed-species groups with zebras in savanna ecosystems. We found that zebras adjust their movement decisions solely to the presence of giraffes, being more likely to move in zebra-giraffe herds, and this was correlated to a higher cohesion of such groups. Additionally, zebras moving with giraffes spent longer time grazing, suggesting that zebras follow giraffes to forage in their proximity. Our results provide new insights on animal movements in mixed-species groups, contributing to a better consideration of mutualism in movement ecology.

ecology↗

bioRxiv2024

Can overlooking "invisible landscapes" bias habitat selection estimation and population distribution projections?

Species future distributions are commonly predicted using models that link the likelihood of occurrence of individuals to the environment. Although animals movements are influenced by physical landscapes and individual experiences (for example space familiarity), species distribution models developed from observations of unknown individuals cannot integrate these latter variables, turning them into invisible landscapes. In this theoretical study, we address how overlooking invisible landscapes impacts the estimation of habitat selection and thereby the projection of future distributions. Overlooking the attraction towards some invisible variable consistently led to over-estimating the strength of habitat selection. Consequently, projections of future population distributions were also biased, with animals tracking habitat changes less than predicted. Our results reveal an overlooked challenge faced by correlative species distribution models based on the observation of unknown individuals, whose past experience of the environment is by definition not known. Mechanistic distribution modelling integrating cognitive processes underlying movement should be developed.

ecology↗

bioRxiv2023

Time-varying habitat selection analysis: a model and applications for studying diel, seasonal and post-release changes

Resource selection functions are commonly employed to evaluate animals habitat selection, e.g. the disproportionate use of habitats relative to their availability. While environmental conditions or animal motivations may vary over time, sometimes in an unknown manner, studying changes in habitat selection usually requires a priori time discretization. This limits our ability to precisely answer the question when is an animals habitat selection changing?. Here, we present a straightforward and flexible alternative approach based on fitting dynamic logistic models to used/available data. First, using simulated dataset, we demonstrate that dynamic logistic models performed well to recover temporal variations in habitat selection. We then show real-world applications for studying diel, seasonal, and post-release changes in habitat selection of blue wildebeest (Connochaetes taurinus). Finally, we provide the relevant R scripts to facilitate the adoption of the method by ecologists. Dynamic logistic models allow to study temporal changes in habitat selection in a framework consistent with resource selection functions, but without the need to discretize time, which can be a difficult task when little is known about the process studied, or may obscure inter-individual variability in timing of change. These models should undoubtedly find their place in the movement ecology toolbox.

ecology↗