Spatio‐temporal factors impacting encounter occurrences between leopards and other large African predators is a research paper published in Journal of Zoology (2020). On theSindex it has a DataRank of 0.715. It has been cited 18 times, with 14 citing works in its 1-hop citation network.
AbstractEncounters between individuals can have implications for a range of processes, including disease transmission, information transfer and competition. For large carnivores, difficulties in directly observing individuals and historical hardware limitations of GPS collars mean that relatively little is known of the spatio‐temporal factors contributing to encounters. The African large predator guild represents one of the few remaining functionally intact guilds of large carnivores on the globe and so represents a unique study system for understanding competitor interactions. We explored the drivers of male leopard (Panthera pardus) encounters with lions (Panthera leo), African wild dogs (Lycaon pictus) and cheetahs (Acinonyx jubatus) in the context of habitat characteristics and temporal activity overlaps. Using high‐resolution (five minute GPS fixes) data from 48 large African carnivores from 2012 to 2018, we quantified encounter occurrences between male leopards and other guild species and related these to habitat type (open vs closed), activity overlaps and moonlight levels. Leopards met wild dogs 4.56 ± 1.15 (standard error), lions 3.11 ± 0.56 and cheetahs 2.27 ± 0.73 times per month. All species instigated encounters, but leopard instigated encounters with dominant competitors appeared to reflect imperfect information on risk, primarily occurring within habitats with limited visibility. Moreover, encounters peaked during periods of high temporal overlap, suggesting that, although previous research indicates temporal activity patterns may not be driven by predator avoidance, temporal overlap has implications for competitor dynamics. Our results show how habitat characteristics and niche overlaps contribute to encounters between competitors and provide an example of how niche shifts within competitor assemblages can impact competition between species.
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Base Score Contribution
0.442
From this paper's citation signal
Citation Network Contribution
0.273
From 11 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 62% comes from its base citations and 38% from the citation network (11 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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