Spatiotemporal co-occurrence of predators and prey in a neotropical mammal community in southern Mexico

Abstract

Predator-prey interactions are one of the central themes in ecology due to their importance as a key mechanism in structuring biotic communities. In the predator-prey systems, the behaviours of persecution and avoidance impact on the ecosystem dynamics as much as the trophic interactions. We aimed to analyse the spatiotemporal co-occurrences between prey and predators in a community of medium- and large-sized mammals in southern Mexico. We predict prey will avoid sites where a predator previously passed. Contrarily, we expect a search behaviour by predators and a synchronization in activity patterns among them. We found prey does not occur either in time or space where predators have passed, suggesting an avoidance behaviour. Contrary to our expectations, we did not find significant search behaviours from predators to prey. Synchronization in the daily temporal overlap between predators was higher (Δ = 0.77–0.82) than with their prey (Δ = 0.43 – 0.81). The results suggest prey perceives the risk of predation and displays avoidance behaviour both spatially and temporally, which is consistent with the fear theory. This study provides a complementary approach to understanding the behaviour mechanism between predators and prey through camera-trapping or similar data of spatiotemporal co-occurrences.

Drivers of jaguar (Panthera onca) and puma (Puma concolor) predation on endangered primates within a transformed landscape in southern Mexico

“…Our results show that primate predation by jaguar and puma in our study site was surprisingly high compared to that of other wild mammals found in the area and compared to previous studies of large cats' diet in Mexico (Aranda & Sánchez-Cordero, 1996;Galindo-Aguilar et al, 2022;Piña-Covarrubias et al, 2023;Rubio-Rocha et al, 2023). This is a marked difference from the general understanding that Neotropical primates are not usually targeted as prey TA B L E 1 Frequency of occurrence (FO) in predator scats and relative biomass (RBC) of prey consumed by jaguars, pumas, and large cats in the Uxpanapa Valley, Mexico.…”

“…Jaguar and puma are obligate carnivores and opportunistic hunters, highly dependent on a good prey base of medium to large sized mammals (Ávila‐Nájera et al, 2018; Paviolo et al, 2018; Hernández‐SaintMartín et al, 2015; Novack et al, 2005: Rubio‐Rocha et al, 2023). Their prey use varies greatly depending on geographical location, but both have a similar primary prey base consisting of peccaries, large rodents, deer, and armadillos (Foster et al, 2010; Foster & Harmsen, 2022; Galindo‐Aguilar et al, 2022; Piña‐Covarrubias et al, 2023). However, human pressures, together with landscape transformation, can prompt changes in their predation behavior (Craighead, 2019).…”

Spatiotemporal Coexistence of Mesopredators and Their Prey in a Defaunated Neotropical Rainforest

“…Lastly, we analyzed the latency times within species pairs between mesopredators and their potential prey, using their occurrence in the same camera trap station in 1-day intervals (24 h). Through binary matrices, we obtained species pair co-occurrences in a station on the same day, 1 day later, 2 days later, and so on up to 20 days later (latency times; Galindo-Aquilar et al, 2022). The observed latency times were contrasted against 10 runs of random models obtained by 100 iteration bootstraps; significant ( p < 0.05) latency times were shown in a species ecological network.…”

Using the multivariate Hawkes process to study interactions between multiple species from camera trap data

“…Most are based on the computation of time intervals between the detections of two species at a given place (e.g., Harmsen et al, 2009); here, we call this family of methods interevent times methods . The distribution of time intervals can then be contrasted according to the order of appearance of species (Parsons et al, 2016; Prat‐Guitart et al, 2020) or summarized by a statistic that is compared with values obtained under a null model (usually data permutation; Cusack et al, 2017; Galindo‐Aguilar et al, 2022; Karanth et al, 2017; Murphy et al, 2021). For a comparison of different approaches to infer reactive temporal avoidance with time interval measures, see Niedballa et al (2019).…”