BioOne.org will be down briefly for maintenance on 17 December 2024 between 18:00-22:00 Pacific Time US. We apologize for any inconvenience.
Open Access
How to translate text using browser tools
8 April 2022 Spatiotemporal Coexistence of Mesopredators and Their Prey in a Defaunated Neotropical Rainforest
José Juan Flores-Martínez, Rosamond Coates, Víctor Sánchez-Cordero, Jesús Alejandro Ríos-Solís, Beatriz Carely Luna-Olivera, Marcelino Ramírez-Ibáñez, Mario C. Lavariega
Author Affiliations +
Abstract

Background and Research Aims: Forest loss and fragmentation have a negative impact on large-sized predators and prey, whose populations are reduced or extirpated locally. We explored the spatiotemporal coexistence of the mesopredators (< 15 kg) coyote, ocelot, and white-nosed coati, with their potential prey (< 15 kg) Mexican agouti, lowland paca, and collared peccary in a defaunated rainforest.

Methods: We used two-species occupancy-detection models between mesopredators and their potential prey, overlap index of circular models, and latency time measurements to evaluate temporal and spatial segregation and habitat use of species.

Results: Presence of ocelot and coyote was influenced by an increase in the detectability and occupancy of the Mexican agouti. Among most mesopredator–prey species pairs, the correlation for both the capture rates at camera-trap stations and the 1-hr intervals were mainly moderate or low. Some mesopredator–prey species pairs showed low or inverse correlations suggesting species avoidance. The Mexican agouti exhibited a significant negative correlation with the presence of mesopredators. The coyote and ocelot showed a positive correlation with their use of low use trails by people.

Conclusions: Spatiotemporal tolerance was observed among mesopredator omnivores and prey herbivores. High temporal overlap of ocelots and potential prey (lowland paca) was observed compared to other tropical forests holding large-sized predators, suggesting behavioral shifts for increasing mesopredator–prey encounters. Furthermore, mesopredator coexistence was mediated by a displacement in the temporal peaks of activity and spatial segregation among species.

Implications for Conservation: Defaunated tropical forests need protection to ensure the conservation of remaining species and their ecological interactions.

Introduction

Species interactions are one of the main factors that influence the coexistence of species, community structure, and ecosystem functioning (Futuyma & Agrawal, 2009; Levin, 2009; Thompson, 1999). Although individual interactions in animals occur frequently in small time lapses, they have a great impact on population dynamics and the behavior of interacting species (Schmitz & Suttle, 2001; Werner, 1992). Predation is a common interaction that has a direct impact on populations of predators and prey, including complex behaviors between these species (Mittelbach, 1986; Saul & Jeschke, 2015). For instance, in terrestrial mammal communities, it has been observed that prey species accommodate their daily schedule to avoid activity peaks of predators (Di Bitetti et al., 2010; Harmsen et al., 2011; Herrera et al., 2018; Hernández-SaintMartín et al., 2013; Massara et al., 2015; Massara et al., 2018; Santos et al., 2019). Prey species also frequently avoid sites where predators occur (Boron et al., 2020; Davis et al., 2011). Such spatial and temporal segregation is stronger between predators and their main prey (Ávila-Nájera et al., 2016).

The temporal and spatial coexistence and the use of habitats involving predator and prey species have been explored in well-conserved Neotropical forests, which hold adequate completeness of their species composition and trophic guilds, for example, communities structured with large-sized predators and prey, and mesopredators (< 15 kg) and medium-sized prey (< 15 kg) (Buskirk, 1999; Gehrt & Clark, 2003). On the other hand, defaunated Neotropical forests show reduced terrestrial mammal communities of predator and prey species (Bogoni et al., 2020a, 2020b). In the absence of large-sized predator and prey species, it is expected that interactions between mesopredators and prey will increase, likely resulting in differences in their spatiotemporal use of habitat (Crooks & Soulé, 1999; Massara et al., 2015, 2016). Further, it has been proposed that human presence (e.g., trails and dirt roads) and habitat disturbances (e.g., logging) affect the presence of mesopredator species and prey in defaunated forest compared to well-conserved Neotropical forest (Gutiérrez-Granados & Dirzo, 2021).

The Los Tuxtlas region located in southeastern Mexico is the northernmost tropical rainforest in the Americas. This region has experienced elevated deforestation rates for decades leading to high habitat loss and fragmentation. For example, it is estimated that only 42% of the region still holds rainforest (Von Thaden et al., 2020). The reduction and fragmentation of rainforests have also resulted in high defaunation, where large-sized mammals have been regionally extirpated or show low population abundances (Estrada et al., 1994; Flores-Martínez et al., 2014; Ríos-Solís et al., 2021). Recent studies on mammal surveys have failed to record jaguar (Panthera onca), puma (Puma concolor), white-lipped collared peccary (Tayassu pecari), and Central American tapir (Tapirella bairdii), that once commonly occurred at Los Tuxtlas (Dirzo & Mendoza, 2007; Estrada et al., 1994; González-Christen & Coates, 2019). Other large-sized prey such as white-tailed deer (Odocoileus virginianus) and mazama (Mazama temama) show low population abundances (González-Christen & Coates, 2019).

The establishment of the Los Tuxtlas Tropical Biological Station (LTBS) of the Institute of Biology, UNAM in the 1960s, has provided protection for a large remaining rainforest fragment and its biodiversity, although large-sized predators and prey are regionally extinct due to high habitat loss and fragmentation in the surrounding areas (Ríos-Solís et al., 2021). Thus, LTBS provides an adequate site to explore the effects on the spatiotemporal coexistence of remaining mesopredator species and prey, in the absence of large-sized species of predators and prey. Here we assessed the detection and occupancy of mesopredators and compared the spatiotemporal co-occurrence with potential prey. We evaluated latency times in the detection and occurrence of species influencing the presence of mesopredators and their potential prey, as have been observed in other Neotropical forests (Briceño-Méndez et al., 2017). We were interested in determining if the habitat occupancy of mesopredator species will be influenced by their potential prey and the proximity to the LTBS and sources of disturbance. We hypothesized that LTBS provides higher protection to species (e.g., low use trails by people), in contrast to the rainforest borders (e.g., high use trails by people), where high habitat degradation and human activities are expected to negatively affect the presence of mesopredators. We also tested if elevation influences mesopredator and their potential prey species habitat use, as higher elevations have a low human presence at LTBS.

Methods

Study site

The study site is located in the protected tropical rainforest at the LTBS (95°04.45 W 18°35.18 N; 120 masl), a field station located within Los Tuxtlas Biosphere Reserve in southern Veracruz, Mexico (Figure 1). The Los Tuxtlas Biosphere Reserve includes 155,122 ha, of which the LTBS includes 640 ha of rainforests. The LTBS still holds a high diversity of terrestrial vertebrates including 166 species of amphibians and reptiles, 565 species of birds, and 139 species of mammals (Estrada et al., 1994). The LTBS is surrounded by forest fragments and deforested areas with cattle raising and agriculture (Figure 1). Settlements located inside the Los Tuxtlas Biosphere Reserve are mostly inhabited by indigenous communities belonging to the Nahuas, and Zoques-Popolucas. Climate is humid-warm, characterized by an average temperature higher than 22°C (temperature range is 19–30°C); and the elevation range is from 100 to 700 masl (García, 2004). The average annual precipitation ranges from 2000 to 4000 mm (Vidal-Zepeda, 1990).

Figure 1.

Location of camera-trap stations (white dots) and trails (gray dot lines) within the rainforest fragment at the LTBS (white polygon) located in southern Veracruz, Mexico. Note that three camera-trap stations were located in the surroundings of the polygon of the Los Tuxtlas Biological Station (LTBS).

10.1177_19400829221084261-fig1.tif

Data collection and analyses

We set 21 camera traps (LTL ACORN 12MP HUNTING TRAIL and LTL ACORD LTL-6210Mc 12MP FHD models) in trees at 30 cm aboveground and deployed 1–1.5 m from walking trails, between July 2012 and June 2013. A total of 18 camera traps were set inside the LTBS, and three camera traps were set in the surroundings of the LTBS, inside the Los Tuxtlas Biosphere Reserve (Figure 1). Camera traps were set to operate for 24 h at day, shooting one photograph each 40 s. The mean distance among cameras was 1.66 km (range was 0.06–5.57 km). Camera traps were in operation for 44.6 days on average (range was 27–60 days). Four camera traps were set from August to September 2012; five camera traps, from October to December 2012; four camera traps, from November 2012 to January 2013; three camera traps, from January to March 2013; one camera trap, from February to March 2013; one camera trap from March to May 2013, and three cameras from April to May 2013. The total trapping effort was 936 camera traps/days. Independent records were considered to be those of species of those photographs separated by 24 h or more. The capture rate was calculated as the number of independent records of each species multiplied by 100 and dividided by the total camera trapping effort. Species category of risk was obtained from the NOM-059-SEMARNAT (Secretaria de Medio Ambiente y Recursos Naturales, 2020) and of the Red List of the International Union for Conservation of Nature (IUCN, 2020) (Table 1). We followed Álvarez-Castañeda et al. (2017) species nomenclature.

Table 1.

Mammals species recorded with camera traps at the Los Tuxtlas Tropical Biological Station (LTBS).

10.1177_19400829221084261-table1.tif

Spatial and temporal species co-occurrence

We analyzed species pairs composed of a mesopredator species and a potential prey to test their spatial and temporal coexistence, using two-species and single-season occupancy models, Spearman’s correlation coefficient, temporal overlap in circular models, and the measuring of latency times. Two-species and single-season occupancy models incorporate detection values related to presence or absence of species in samples (occasions) at same sites with: temporal repetitions, site variables, variables that affect detection, and the detection histories of a second species (Mackenzie et al., 2002). We followed Richmond et al. (2010) parameterization, in which occupancy and detection values of one subordinate species (species B) is influenced by a dominant species (species A). We included probabilities of occupancy of species A (ΨA), probability of occupancy of B if A is absent (ΨBA), probability of detection of species A if B is absent (pA), probability of detection of species B if A is absent (pB), probability of detection of species A if both species are present (rA), probability of detection of species B if both are present but A was not detected (rBa), and probability of detection of species B if both are present, and A was detected (rBA). For each site, days of operation were divided into 8 day-occasions. The analyses were implemented in the package rPRESENCE (MacKenzie & Hines, 2021) for the R environment (R Core Team., 2014), including a species effect on occupancy (SP), and an occurrence-level interaction between species (INT).

We tested specific interaction effects and covariates effects on probabilities of occupancy and detection, respectively. Models were fitted with a maximum likelihood approach (Mackenzie et al., 2002). Occupancy models operate with two components, each one with independent variables. One component models probabilities of detection (p); the other component models probabilities of occupancy (Ψ) of species taking into account detection. For each site, and as covariables influencing occupancy, we calculated the Euclidean distance to LTBS facilities, the Euclidean distance to nearest human settlement, and elevation (masl). The covariables affecting detection were the sampling effort measured as the number of days that each camera trap operated, and trails where cameras were placed, differentiated by the intensity of use by field station researchers: vigilantes (low use trails by people, covered by herbaceous plants) and pathways (highly used trails by people); both were approximately 1 m wide. All trails had a natural soil substrate. These covariables were used to model occupancy and detection probabilities of species pairs between mesocarnivores and their potential prey. For each species pair, we tested 55 models with different covariables combinations. The best competitive models were selected with the Akaike information criterion estimator adjusted for small samples, for example, ΔAICc was < 2.0 (Burnham & Anderson, 2002). When two or more models were ΔAICc < 2.0, real parameters were averaged.

We used Spearman’s correlation coefficient to measure the relationship between species pairs in capture rates at stations, and total sums of occurrences within 24 intervals of 1 h (Chaudhary et al., 2020; Harmsen et al., 2011; Vinitpornsawan & Fuller, 2020). We assumed that high and positive correlations (∼ 1) indicated tolerance within species pairs, while high and negative correlations (∼ −1) indicated species pairs avoidances. Daily temporal overlap was compared against the fit of a smooth circular model using Kernel density (Meredith & Ridout, 2021; Sollmann, 2018). We also calculated an overlap index between the adjusted models, where a value near to 0 indicated a low daily temporal overlap, and values near to one indicated a high temporal overlap. Model fit and overlap index were calculated with overlap package (Meredith & Ridout, 2021).

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. Before conducting the analyses, we checked the similarity of data between stations and found a low value (< 47%).

Results

We obtained 726 independent records of 16 species of terrestrial mammals (Table 1), of which we analyzed three mesopredator species (coyote Canis latrans, white-nosed coati Nasua narica, and ocelot Leopardus pardalis) and three potential preys (lowland paca Cuniculus paca, Mexican agouti Dasyprocta mexicana, and collared peccary Dicotyles angulatus). Mesocarnivore species registered with a low number of records were margay Leopardus wiedii (12), striped hog-nosed skunk Conepatus semistriatus (12), tayra Eira barbara (9), racoon Procyon lotor (8), jaguarundi Herpailurus yagouaroundi (4), and grison Galictis vittata (1). The Mexican agouti was the prey species with the highest capture rate (33.97), followed by the lowland paca (7.91). Of the 16 species recorded, 7 species showed conservation risk categories assigned by the IUCN and the Mexican norm (Table 1).

Species pairs and single-season occupancy

Models perform well for the species pairs of coyote and Mexican agouti, and ocelot and Mexican agouti. For the coyote and Mexican agouti species pair, two models were well supported (ΔAICc < 0.2) ( Supplemental Material 1). We found a SP on probability of occupancy for both models. In the detection probabilities, we observed a SP plus type of trails (low use trails), although an occurrence-level INT was only present in the first best model (Table 2). For ocelot and the Mexican agouti species pairs, only one model was supported, with a species effect on probability of occupancy SP, and SP INT and type of trails (low use trails) in the probability of detection (Table 2).

Table 2.

Beta coefficients of two species occupancy models for mesopredators and their potential prey in LTBS.

10.1177_19400829221084261-table2.tif

We found that the probability of detection of coyotes was positively influenced by type of trail (low use trails by people) and was higher in the absence than in the presence of the Mexican agouti (p = 0.646, and p = 0.369, respectively). Conversely, the probability of detection of the Mexican agouti was high in the absence and slightly lower in the presence of the coyote (p = 0.927, and p = 0.812, respectively). The probability of detection of the ocelot was also influenced by low use trails by people, and was higher in the absence than in the presence of the Mexican agouti (p = 0.547, and p = 0.170, respectively). The probability of detection of the Mexican agouti was higher in the absence than in the presence of the ocelot (p = 0.958, and p = 0.768, respectively). Further, the probability of occupancy was moderate for coyote (Ψ = 0.730) and for ocelot (Ψ = 0.711). The probability of occupancy for the Mexican agouti was high in the presence of coyote (Ψ = 0.908) or of the ocelot (Ψ = 0.910). We did not observe a relationship between probabilities of occupancy of species pairs between mesopredators and their potential prey with distance to human settlements, distance to LTBS or elevation (Tables 2 and 3).

Table 3.

Real estimates of two species occupancy and detection models for mesopredators and their potential prey in LTBS.

10.1177_19400829221084261-table3.tif

Species capture rates

The white-nosed coati and the coyote showed significant (p < 0.05) and moderate positive correlations in their capture rates in relation to the ocelot (r = 0.46 and r = 0.40, respectively). There was a significant (p < 0.05) and moderate positive correlation between the coyote and the white-nosed coati (r = 0.48). The Mexican agouti had significant (p < 0.05) low inverse correlations with the white-nosed coati (r = −0.05), the coyote (r = −0.14), and the ocelot (r = −0.18) suggesting that sites with a high record rate of these species were avoided by the Mexican agouti. In their daily temporal activity, we observed significant (p < 0.05) high correlation values between the white-nosed coati and the Mexican agouti (r = 0.72), and between the white-nosed coati and the collared peccary (r = 0.58). On the other hand, there were significant (p < 0.05) negative temporal correlations between the white-nosed coati and the ocelot (r = −0.35), the ocelot and the Mexican agouti (r = −0.23), the Mexican agouti and the lowland paca (r = −0.31), and the white-nosed coati and the lowland paca (r = −0.05).

Most species pairs showed positive spatiotemporal correlations, but we found opposite significant (p < 0.05) spatial and temporal values between the coyote and Mexican agouti (spatial r = −0.14; temporal r = 0.41), and between the white-nosed coati and Mexican agouti (spatial r = −0.05; temporal r = 0.72). Conversely, the white-nosed coati and ocelot (spatial r = 0.46; temporal r = −0.35), white-nosed coati and lowland paca (spatial r = 0.23; temporal r = −0.05), and lowland paca and Mexican agouti (spatial r = 0.22; temporal r = −0.31) species pairs showed an opposite trend. No species pairs between mesopredators and their potential prey showed a negative relationship in both spatial and temporal dimensions. Likewise, the Kernell circular models overlap index showed that the highest daily temporal overlap were between the coyote and white-nosed coati, and the white-nosed coati and Mexican agouti, and the lowest were between the ocelot and Mexican agouti, and the white-nosed coati and lowland paca species pairs, respectively (Table 4;  Supplemental Material 2).

Table 4.

Temporal overlap index between species pairs of mesopredators and their potential prey in the LTBS rainforest. Confidence intervals at 95% are in parenthesis.

10.1177_19400829221084261-table4.tif

Latency times

From the 10 runs in the random models comparing species co-occurrences, we found high consistency (96.41%), i.e. almost all significant latencies were similar among runs. The latency times shown in the species ecological network exhibited that some species occurred only several days after the occurrence of other species (Figure 2). For example, we found 4 days of latency between the occurrence of coyote and white-nosed coati, and between ocelot and white-nosed coati. Five days of latency were observed between the Mexican agouti and coyote, the lowland paca and white-nosed coati, and the white-nosed coati and Mexican agouti. The longest latency time was observed between the coyote and the collared peccary, with a 13-day difference. On the other hand, species exhibiting a high coexistence were the white-nosed coati and the collared peccary, that occurred on the same day at the same sites. We found that ocelots appeared 3–4 days after white-nose coati, and white-nose coati appeared 5–6 days after the Mexican agouti (Figure 2).

Figure 2.

Ecological network of latency times between species pairs of mesopredators and their potential prey in the LTBS rainforest. The arrow-head indicates the first occurring species, and the arrow foot indicates the later occurring species. The color of the arrow indicates latency times in days, as indicated in the colored sidebar. Line thickness indicates average significance (p < 0.05); a wide arrow corresponds to a higher average significance.

10.1177_19400829221084261-fig2.tif

Discussion

Our study provides information on species coexistence of the mesopredators and their potential prey in a defaunated rainforest, where populations of large-sized predators (e.g., jaguar and puma) and their main prey (tapir, white-tailed deer, mazama, and white-lipped peccary) have been extirpated or occur at low numbers (Ríos-Solís et al., 2021). Overall, distance to the LTBS did not emerge as a variable explaining the probability of occupancy of mesopredators. These species used the rainforest fragments surrounding LTBS, irrespectively, neither considering it as a facility providing protection nor as a risky zone. It is possible that this fragmented landscape area is part of their home ranges (Ríos-Solís et al., 2021). The probability of occupancy of coyote and ocelot was associated with the covariable of low use trails by people, which may be explained by a preference to avoid human presence (Salom-Pérez et al., 2021).

The best-supported occupancy models showed that low use trails by people were positively correlated with the detection of ocelots. Ocelot occupancy showed no correlation with elevation, which has been documented positive and negative in other tropical forests (García-R et al., 2019; Nagy-Reis et al., 2017; Santos et al., 2019; Wang et al., 2019). We also observed that occupancy models showed that the probability of detection of the Mexican agouti decreased in the presence of coyote and ocelot likely to avoid encounters with these potential predator species.

Potential prey species were not related to the habitat use of mesopredators. Such findings could be explained by the fact that coyotes and white-nosed coatis are omnivorous species that do not strictly depend on vertebrates as their main food source (Bekoff, 1977; Gompper, 1995). Ocelots frequently visited sites where lowland pacas were common, although this species is not among their main prey (Murray & Gardner, 1997). The importance of lowland pacas on the feeding habits of ocelots in the defaunated LTBS rainforest deserves further study (see Moreno et al., 2006; Oliveira et al., 2010). In the absence of large-sized predators and prey, it is likely to expect a rearrangement of the spatiotemporal coexistence between mesopredators and potential prey. This hypothesis can be further tested by comparing well-conserved with defaunated tropical forests and quantitatively determined expected shifts in predator–prey interactions.

We observed that ocelots and lowland pacas were mainly nocturnal, whereas collared peccaries, white-nosed coatis, and the Mexican agoutis were diurnal, and the coyote was cathemeral. These daily activity patterns were in accordance with reports for these species in other Neotropical forests (Lira-Torres & Briones-Salas, 2012; Marqués & Fábian, 2018; Porfirio et al., 2016). However, we found slight differences in the daily activity patterns between ocelot and its potential prey, suggesting that changes in their activity have occurred due to the absence of large predators. Ocelots had high and low temporal overlaps with lowland paca and the Mexican agouti, respectively, which coincides with patterns observed in other Neotropical forests, even with the presence of large-sized predators and prey (de Matos et al., 2018; García-R et al., 2019; Herrera et al., 2018). Nonetheless, such temporal overlap was slightly higher in LTBS (0.81 with the lowland paca, and 0.40 with the Mexican agouti) than in sites of Brazil, Colombia, or Costa Rica, where the overlap ranged 0.67–0.80 for lowland paca, and 0.23–0.36 for Dasyprocta spp. (Botts et al., 2020; de Matos et al., 2018; García-R et al., 2019; Herrera et al., 2018; Porfirio et al., 2016). We also found that ocelots showed a higher temporal overlap with collared peccaries (0.46) and with white-nosed coatis (0.49) than reported for Costa Rica (0.36–41 and 0.25–0.39, respectively) (Botts et al., 2020; Herrera et al., 2018). Such higher temporal overlap with potential prey at the LTBS could indicate that ocelots are expanding their activity to increase the chances of encountering these potential prey species in this defaunated rainforest (Ríos-Solís et al., 2021). Changes in prey selection have been observed in ocelots in Barro Colorado Island, where they hunt frequently larger prey such as collared peccaries Dicotyles sp., once jaguar populations become extremely rare or locally extirpated (Moreno et al., 2006).

Further, the relationship between the capture rate of ocelots was low with lowland pacas, and negative with the Mexican agouti. In addition, we did not find any significant latency time between ocelots and lowland pacas or the Mexican agouti, suggesting that ocelots randomly visited the same sites of these potential prey. An alternate explanation is that the spatial overlap is occurring in sites not sampled in our camera traps design, such as refuges that ocelot usually visit to prey on Dasyprocta sp. (Emsens et al., 2014). This was also the case between ocelots and collared peccaries, where the spatial correlation was low and did not have latency times. Conversely, we observed a negative temporal correlation between ocelots and white-nosed coatis. Further, the analysis of latency times showed that white-nosed coatis took 3 days to occur after ocelots, but ocelots only took 1 day to appear in the same site as the white-nosed coati. Ocelots may seek out white-nosed coatis to prey on them (Bianchi et al., 2014; Oliveira et al., 2010), which may explain our observations of co-occurrence.

We observed low values of correlation between coyotes with lowland pacas and collared peccaries suggesting that these prey species avoid coyotes spatially and temporally. However, latency times did not provide evidence of any predatory behavior of coyotes over lowland pacas. Interestingly, we observed that coyotes and collared peccaries co-occurred in the same sites for long periods. Coyotes and white-nosed coatis showed a higher spatiotemporal overlap (0.36) than in other tropical forests (Botts et al., 2020). There was a moderate correlation between coyotes and white-nosed coatis in the capture rate in camera-trap stations and the 1-hour intervals, and the latency times showed that these species co-occurred cyclically in the same sites with a difference of 3 or 4 days. While white-nosed coatis are preyed upon by large-sized predators such as pumas and jaguars, no evidence exists of coyotes preying on them (Hass & Valenzuela, 2002). We did not find latency times co-occurrences between coyotes and ocelots, and the correlation indices showed a low spatial and temporal relationship. We also observed a moderate temporal overlap, similar to that reported in Costa Rica for both species (Herrera et al., 2018). It seems that coyotes spatially and temporally avoided ocelots at LTBS, where they are mainly seed predators competing with seed dispersers in our study site (Zambrano et al., 2015). Coyotes are opportunists concerning habitat use and feeding habits, they have been expanding their distribution in the Neotropics as a consequence of forest loss due to cattle ranching (Cove et al., 2012).

Overall, pairs of mesopredator species such as the coyote and white-nosed coatis, and coyotes and ocelots showed an intraguild tolerance behavior driven by a displacement on peaks of activity time and spatial segregation, allowing their coexistence in this defaunated rainforest. In another defaunated site in the Brazilian Atlantic forest, Massara et al. (2016) did not find changes in the spatial use and activity patterns of mesopredators as a response to ocelots. Although confidence intervals of the temporal overlap between species pairs did not differ, we found a slightly higher value at the LTBS rainforest than at the Atlantic forest site, suggesting that behavioral changes are likely occurring due to the absence of large-sized predators. Future studies in other defaunated Neotropical forests should address whether or not these behavioral shifts in mesopredators' spatiotemporal patterns are consistent with our observations.

Implications for Conservation

Deforestation is a major cause of habitat loss and fragmentation in tropical forests leading to biodiversity loss worldwide (Bogoni et al., 2020a, 2020b; Dirzo et al., 2014; Dirzo & Miranda, 1990; Galetti & Dirzo, 2013). As a consequence, many species in tropical forests have become extinct or their populations have been extirpated regionally. This is the case of the Los Tuxtlas Biosphere Reserve, where large-sized species of terrestrial mammals (e.g., jaguar, puma, tapir, white-tailed deer, mazama, and white-lipped peccary) have become extinct or their populations occur in low abundances (Flores-Martínez et al., 2014; Ríos-Solís et al., 2021). It is likely that remaining medium-to-small-sized predators and prey interactions in the defaunated tropical forests will modify spatially and temporally their coexistence (Massara et al., 2016). We studied interactions between mesopredators and their potential prey in the defaunated LTBR and observed spatial and temporal shifts leading to high overlap between ocelots and other mesopredators and their potential prey. Defaunated forests such as LTBR provide excellent sites to conduct long-term research to determine the impact of habitat loss and fragmentation of predator–prey interactions compared to non-defaunated tropical forests. Documenting spatiotemporal shifts in species co-occurrences in defaunated habitats contributes to determining adjustments of predator–prey interactions. Further, of the 16 species recorded in our study, 7 showed a conservation risk category assigned by the IUCN Red List (International Union for Conservation of Nature (IUCN), 2020) and the Mexican norm (Secretaria de Medio Ambiente y Recursos Naturales (SEMARNAT), 2020), which highlights the importance of their conservation. Defaunated tropical forests should also be prioritized to ensure the conservation of remaining species and their ecological interactions.

Acknowledgments

This work was supported by the Institute of Biology and the Los Tuxtlas Tropical Biological Station (National Autonomous University of Mexico). Trips and wildlife monitoring were conducted with the assistance of José Luis Villegas Gapi. MCL thanks to EDI-IPN and SIP for their logistical support. We thank the reviewers for their numerous comments that helped to improve the quality and clarity of this manuscript.

Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

FundingThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Institute of Biology, National Autonomous University of Mexico.

Supplemental Material

Supplemental material for this article is available online.

References

1.

Álvarez-Castañeda S. T. , Álvarez T. , González-Ruiz N. (2017). Guía para la identificación de los mamíferos de México. JHU Press. Google Scholar

2.

Ávila-Nájera D. M. , Chávez C. , Lazcano-Barreto M. A. , Mendoza G. D. , Pérez-Elizalde S. (2016). Overlap in activity patterns between big cats and their main prey in northern Quintana Roo, Mexico. Therya, 7(3), 439–448.  https://doi.org/10.12933/therya-16-379Google Scholar

3.

Bekoff M. (1977). Canis latrans. Mammalian Species, 79(79), 1–9.  https://doi.org/10.2307/3503817Google Scholar

4.

Bianchi R. D. C. , Campos R. C. , Xavier-Filho N. L. , Olifiers N. , Gompper M. E. , Mourão G. (2014). Intraspecific, interspecific, and seasonal differences in the diet of three mid-sized carnivores in a large neotropical wetland. Acta Theriologica, 59(1), 13–23.  https://doi.org/10.1007/s13364-013-0137-xGoogle Scholar

5.

Bogoni J. A. , Peres C. A. , Ferraz K. M. (2020a). Effects of mammal defaunation on natural ecosystem services and human well-being throughout the entire Neotropical realm. Ecosystem Services, 45(101173).  https://doi.org/10.1016/jecoser.2020.101173Google Scholar

6.

Bogoni J. A. , Peres C. A. , Ferraz K. M. (2020b). Extent, intensity and drivers of mammal defaunation: a continental-scale analysis across the neotropics. Scientific Reports, 10(1), 14750–14816.  https://doi.org/10.1038/s41598-020-72010-wGoogle Scholar

7.

Boron V. , Xofis P. , Link A. , Payan E. , Tzanopoulos J. (2020). Conserving predators across agricultural landscapes in Colombia: habitat use and space partitioning by jaguars, pumas, ocelots and jaguarundis. Oryx 54(4), 554–563.  https://doi.org/10.1017/S0030605318000327Google Scholar

8.

Botts R. T. , Eppert A. A. , Wiegman T. J. , Rodriguez A. , Blankenship S. R. , Asselin E. M. , Garley W. M. , Wagner A. P. , Ullrich S. E. , Allen G. R. , Mooring M. S. (2020). Circadian activity patterns of mammalian predators and prey in Costa Rica. Journal of Mammalogy, 101(5), 1313–1331.  https://doi.org/10.1093/jmammal/gyaa103Google Scholar

9.

Briceño M. , Naranjo Piñera E. , Pérez Irineo G. , Sandoval Serés E. , Contreras Perera Y. , Hidalgo M. M. (2017). Richness and trophic guilds of carnivorous mammals in ejido Nuevo Becal, Calakmul, Campeche, Mexico. Therya, 8(2), 145–150.  https://doi.org/10.12933/therya-17-472Google Scholar

10.

Burnham K. P. , Anderson R. P. (2002). Model selection and multimodel inference: A practical information-theoretic approach (2nd ed). Springer Verlag. Google Scholar

11.

Buskirk (1999). Mesocarnivores of yellowstone. In Clark T.W. , Curlee P.M , Minta S.C. , , and Kareiva P.M. , (Eds.), Carnivores in ecosystems: the Yellowstone experience. Yala University Press (pp. 165–188). Google Scholar

12.

Chaudhary R. , Zehra N. , Musavi A. , Khan J. A. (2020). Spatio-temporal partitioning and coexistence between leopard (Panthera pardus fusca) and Asiatic lion (Panthera leo persica) in Gir protected area, Gujarat, India. Plos One, 15(3), e0229045.  https://doi.org/10.1371/journal.pone.0229045Google Scholar

13.

Cove M. V. , Valladares L. E. P. , Spínola R. M. , Jackson V. L. , Sáenz J. C. (2012). Coyote canis latrans (carnivora: canidae) range extension in northeastern costa rica: possible explanations and consequences. Latin American Journal of Conservation, 2(1), 82–86. Google Scholar

14.

Crooks K. R. , & Soulé M. E. (1999). Mesopredator release and avifaunal extinctions in a fragmented system. Nature, 400(6744), 563–566.  https://doi.org/10.1038/23028Google Scholar

15.

Davis M. L. , Kelly M. J. , Stauffer D. F. (2011). Carnivore co-existence and habitat use in the mountain pine ridge forest reserve, Belize. Animal Conservation, 14(1), 56–65.  https://doi.org/10.1111/j.1469-1795.2010.00389.xGoogle Scholar

16.

de Matos Dias D. , de Campos C. B. , Guimarães R. F. H. (2018). Behavioural ecology in a predator-prey system. Mammalian Biology, 92(1), 30–36.  https://doi.org/10.1016/j.mambio.2018.04.005Google Scholar

17.

Di Bitetti M. S. , De Angelo C. D. , Di Blanco Y. E. , Paviolo A. (2010). Niche partitioning and species coexistence in a neotropical felid assemblage. Acta Oecologica, 36(4), 403–412.  https://doi.org/10.1016/j.actao.2010.04.001Google Scholar

18.

Dirzo R. , Mendoza E. , Ortíz P. (2007). Size-related differential seed predation in a heavily defaunated neotropical rain forest. Biotropica, 39(3), 355–362.  https://doi.org/10.1111/j.1744-7429.2007.00274.xGoogle Scholar

19.

Dirzo R. , & Miranda A. (1990). Contemporary neotropical defaunation and forest structure, function, and diversity—a sequel to John Terborgh. Conservation Biology, 4(4), 444–447.  https://doi.org/10.1111/j.1523-1739.1990.tb0032.xGoogle Scholar

20.

Dirzo R. , Young H. S. , Galetti M. , Ceballos G. , Isaac N. J. , Collen B. (2014). Defaunation in the anthropocene. Science, 345(6195), 401–406.  http://doi.org/10.1126/science.1251817Google Scholar

21.

Emsens W.-J. , Hirsch B. T. , Kays R. , Jansen P. A. (2014). Prey refuges as predator hotspots: ocelot (Leopardus pardalis) attraction to agouti (Dasyprocta punctata) dens. Acta Theriologica, 59(2), 257–262.  https://doi.org/10.1007/s13364-013-0159-4Google Scholar

22.

Estrada A. , Coates-Estrada R. , Meritt D. Jr.(1994). Non-flying mammals and landscape changes in the tropical rain forest region of Los Tuxtlas, Mexico. Ecography, 17(3), 229–241.  https://doi.org/10.1111/j.1600-0587.1994.tb00098.xGoogle Scholar

23.

Flores-Martínez J. J. , Coates I. R. , Sánchez-Cordero V. , Medina J. V. (2014). Mamíferos terrestres de la estación de biología tropical de Los Tuxtlas. Revista Digital Universitaria, 15(4), 1–10.  http://www.revista.unam.mx/vol.15/num4/art29/index.htmlGoogle Scholar

24.

Futuyma D. J. , & Agrawal A. A. (2009). Evolutionary history and species interactions. Proceedings of the National Academy of Sciences of the United States of America, 106(43), 18043–18044.  https://doi.org/10.1073/pnas.0910334106Google Scholar

25.

Galetti M. , & Dirzo R. (2013). Ecological and evolutionary consequences of living in a defaunated world. Biological Conservation, 163, 1–6.  http://doi.org/10.1016/j.biocon.2013.04.020Google Scholar

26.

Galindo-Aguilar E. , Luna-Olivera B. C. , Ramírez-Ibáñez M. , Lavariega M. C. (2022). Spatiotemporal co-occurrence of predators and prey in a neotropical mammal community in southern Mexico. Journal of Tropical Ecology.Accepted. Google Scholar

27.

García A. E. (2004). Modificación al sistema de la clasificación climática de Köppen. Instituto de Geografía, UNAM. Google Scholar

28.

García-R S. , Botero-Cañola S. , Sánchez-Giraldo C. , Solari S. (2019). Habitat use and activity patterns of Leopardus pardalis (Felidae) in the Northern Andes, Antioquia, Colombia. Biodiversity, 20(1), 5–19.  https://doi.org/10.1080/14888386.2019.1590235Google Scholar

29.

Gehrt S. D. , Clark W. R. (2003). Raccoons, coyotes, and reflections on the mesopredator release hypothesis. Wildlife Society Bulletin, 31(3), 836–842. Google Scholar

30.

Gompper M. E. (1995). Nasua narica. Mammalian Species, 487(487), 1–10.  https://doi.org/10.2307/3504195Google Scholar

31.

González-Christen A. , Coates R. (2019). Los mamíferos no voladores de la región de Los Tuxtlas, Veracruz, México. Revista Mexicana de Biodiversidad, 90(1), 1–15.  https://doi.org/10.22201/ib.20078706e.2019.90.2580Google Scholar

32.

Gutiérrez-Granados G. , Dirzo D. (2021). Logging drives contrasting animal body-size effects on tropical forest mammal communities. Forest Ecology and Management, 481(1), 1–8.  https://doi.org/10.1016/i.foreco.2020.118700Google Scholar

33.

Harmsen B. J. , Foster R. J. , Silver S. C. , Ostro L. E. T. , Doncaster C. P. (2011). Jaguar and puma activity patterns in relation to their main prey. Mammalian Biology, 76(3), 320–324.  https://doi.org/10.1016/j.mambio.2010.08.007Google Scholar

34.

Hass C. C. , Valenzuela D. (2002). Anti-predator benefits of group living in white-nosed coatis (Nasua narica). Behavioral Ecology and Sociobiology, 51(6), 570–578.  https://doi.org/10.1007/s00265-002-0463-5Google Scholar

35.

Hernández-SaintMartín A. D. , Rosas-Rosas O. C. , Palacio-Núñez J. , Tarango-Arámbula L. A. , Clemente-Sánchez F. , Hoogesteijn A. L. (2013). Patrones de actividad del jaguar, puma y sus presas potenciales en San Luis Potosí, México. Acta Zoológica Mexicana, 29(3), 520–533. Google Scholar

36.

Herrera H. , Chávez E. J. , Alfaro L. D. , Fuller T. K. , Montalvo V. , Rodrigues F. , Carrillo E (2018). Time partitioning among jaguar Panthera onca, puma Puma concolor and ocelot Leopardus pardalis (Carnivora: Felidae) in Costa Rica’s dry and rainforests. Revista de Biología Tropical, 66(4), 1559–1568.  https://dx.doi.org/10.15517/rbt.v66i4.32895Google Scholar

37.

International Union for Conservation of Nature (IUCN) (2020). The IUCN red list of threatened species. Version 2020-2.  https://www.iucnredlist.org/Google Scholar

38.

Levin S. A. (2009). Biodiversity and ecosystem functioning. The princeton guide to ecology. : Princeton University Press. Google Scholar

39.

Lira-Torres I. , Briones-Salas M. (2012). Abundancia relativa y patrones de actividad de los mamíferos de los Chimalapas, Oaxaca, México. Acta Zoológica Mexicana, 28, 566–585.  https://doi.org/10.21829/azm.2012.283859Google Scholar

40.

Massara R. L. , Paschoal A. M. D. O. , Bailey L. L , Doherty F. PJr. Hirsch A. , Chiarello G.A.(2018). Factors influencing ocelot occupancy in Brazilian Atlantic Forest reserves. Biotropica, 50(1), 125–134.  https://doi.org/10.1111/btp.12481Google Scholar

41.

MacKenzie D. I. , and Hines J. E. (2021). Package. RPresence. R Interface for program PRESENCE. R Package Version 13.17, 2021. Google Scholar

42.

Mackenzie D. I. , Nichols J. D. , Lachman G. B. , Droege S. , Royle J. A. , Langtimm C. A. (2002). Estimating site occupancy rates when detection probabilities are less than one. Ecology, 83(8), 0012–9658.  https://doi.org/10.1890/0012-9658(2002)083[2248:esorwd]2.0.co;2Google Scholar

43.

Marqués R. V. , Fábian M. E. (2018). Daily activity patterns of medium and large neotropical mammals during different seasons in an area of high- altitude Atlantic rain forest in the South of Brazil. Revista Brasileira de Zoociências, 19(3), 38–64.  https://doi.org/10.34019/2596-3325.2018.v19.24736Google Scholar

44.

Massara R. L. , Paschoal A. M. D. O. , Doherty F. P.Jr. Hirsch A. , Chiarello A. G. (2015). Ocelot population status in protected Brazilian Atlantic forest. Plos One, 10(11), e0141333.  https://doi:10.1371/journal.pone.0141333Google Scholar

45.

Massara R. L. , Paschoal A. M. O. , Bailey L. L. , Doherty P. F.Jr. Chiarello A. G. (2016). Ecological interactions between ocelots and sympatric mesocarnivores in protected areas of the Atlantic Forest, southeastern Brazil. Journal of Mammalogy, 97(6), 1634–1644.  https://doi.org/10.1093/jmammal/gyw129Google Scholar

46.

Meredith M. , Ridout M. (2021). Overview of the overlap package. R packages version 3.3.1.  https://cran.r-project.org/web/packages/overlap/overlap.pdfGoogle Scholar

47.

Mittelbach G. (1986). Predator-mediated habitat use: some consequences for species interactions. Environmental Biology of Fishes, 16(1), 159–170.  https://doi.org/10.1007/BF00005168Google Scholar

48.

Moreno R. S. , Kays R. W. , Samudio R. (2006). Competitive release in diets of ocelot (Leopardus pardalis) and puma (Puma concolor) after jaguar (Panthera onca) decline. Journal of Mammalogy, 87(4), 808–816.  https://doi.org/10.1644/05-MAMM-A-360R2.1Google Scholar

49.

Murray J. L. , Gardner G. L. (1997). Leopardus pardalis. Mammalian Species, 548(548), 1–10. Google Scholar

50.

Nagy-Reis M. B. , Nichols J. D. , Chiarello A. G. , Ribeiro M. C. , Setz E. Z. F. (2017). Landscape use and co-occurrence patterns of neotropical spotted cats. Plos One, 12(1), e0168441.  http://doi.org/10.1371/journal.pone.0168441Google Scholar

51.

Oliveira T. G. , Tortato M. A. , Silveira L. , Kasper C. H. , Mazim F. D. , Lucherini M. , Jácomo A. T. , Soares J. B. , Marques R. V. , Sunquist M. (2010). Ocelot ecology and its effect on the small-felid guild in the lowland Neotropics. In MacDonald D. , Loveridge A. , (Eds.), Biology and conservation of wild felids (pp. 559–580). Oxford University Press. Google Scholar

52.

Porfirio G. , Foster V. C. , Fonseca C. , Sarmento P. (2016). Activity patterns of ocelots and their potential prey in the Brazilian Pantanal. Mammalian Biology, 81(5), 511–517.  https://doi.org/10.1016/j.mambio.2016.06.006Google Scholar

53.

R Core Team.(2014). R: A language and environment for statistical computing. R foundation for statistical computing. Austria. URL.  http://www.R-project.org/Google Scholar

54.

Richmond O. M. , Hines J. E. , Beissinger S. R. (2010). Two-species occupancy models: a new parameterization applied to co-occurrence of secretive rails. Ecological Applications, 20(7), 2036–2046.  https://doi.org/10.1890/09-0470.1Google Scholar

55.

Ríos-Solís J. A. , Flores-Martínez J. J. , Sánchez-Cordero V. , Lavariega M. C. (2021). Diversity and activity patterns of medium - and large - sized terrestrial mammals at the Los Tuxtlas Biosphere Reserve, Mexico. Therya, 12(2), 237–248.  https://doi.org/10.12933/therya-21-1105Google Scholar

56.

Salom-Pérez R. , Corrales-Gutiérrez D. , Araya-Gamboa D. , Espinoza-Muñoz D. , Finegan B , Petracca L. S. (2021). Forest cover mediates large and medium-sized mammal occurrence in a critical link of the Mesoamerican biological corridor. Plos One, 16(3), e0249072.  https://doi.org/10.1371/journal.pone.0249072Google Scholar

57.

Santos F. , Carbone C. , Wearn O. R. , Rowcliffe J. M. , Espinosa S. , Lima M. G. M. , Peres C. A. (2019). Prey availability and temporal partitioning modulate felid coexistence in Neotropical forests. Plos One, 14(3), e0213671.  https://doi.org/10.1371/journal.pone.0213671Google Scholar

58.

Saul W. C. , Jeschke J. M. (2015). Eco-evolutionary experience in novel species interactions. Ecology Letters, 18(3), 236–245.  https://doi.org/10.1111/ele.12408Google Scholar

59.

Schmitz O. J. , Suttle K. B. (2001). Effects of top predator species on direct and indirect interactions in a food web. Ecology, 82(7), 2072–2081.  https://doi.org/10.1890/0012-9658(2001)082[2072:eotpso]2.0.co;2Google Scholar

60.

Secretaria de Medio Ambiente y Recursos Naturales (SEMARNAT)(2020). NORMA Oficial Mexicana NOM-059-SEMARNAT-2010. Protección ambiental-Especies nativas de México de flora y fauna silvestres-Categorías de riesgo y especificaciones para su inclusión, exclusión o cambio-Lista de especies en riesgo.  https://dof.gob.mx/nota_detalle_popup.php?codigo=5173091Google Scholar

61.

Sollmann R. (2018). A gentle introduction to camera-trap data analysis. African Journal of Ecology, 56(4), 740–749.  https://doi.org/10.1111/aje.12565Google Scholar

62.

Thompson J. N. (1999). The evolution of species interactions. Science, 284(5423), 2116–2118. . https//doi.org/10.1126/science.284Google Scholar

63.

Vidal-Zepeda R. (1990). ‘Precipitación media anual’ en Precipitación, IV.4.6. Atlas Nacional de México, II.Escala 1 :4000000. Instituto de Geografía, UNAM. México. Google Scholar

64.

Vinitpornsawan S. , Fuller T. K. (2020). Spatio-temporal correlations of large predators and their prey in western Thailand. Raffles Bulletin of Zoology, 68, 118–131.  htpp://doi.org/10.26107/RBZ-2020-0013Google Scholar

65.

Von Thaden J. J. , Laborde J. , Guevara S. , Mokondoko-Delgadillo P. (2020). Dinámica de los cambios en el uso del suelo y cobertura vegetal en la Reserva de la Biosfera Los Tuxtlas (2006-2016). Revista Mexicana de Biodiversidad, 91(2), 1–14.  https://doi.org/10.22201/ib.20078706e.2020.91.3190Google Scholar

66.

Wang B. , Rocha D. G. , Abrahams M. I. , Antunes A. P. , Costa H. C. M. , Gonçalves A. L. S. , Tan C. K. W. (2019). Habitat use of the ocelot (Leopardus pardalis) in the Brazilian Amazon. Ecology and Evolution, 9(9), 5049–5062. Google Scholar

67.

Werner E. E. (1992). Individual behavior and higher-order species interactions. The American Naturalist, 140, 5–32.  https://doi.org/10.1086/285395Google Scholar

68.

Zambrano J. , Coates R. , Howe H. F. (2015). Seed predation in a human-modified tropical landscape. Journal of Tropical Ecology, 31(4), 379–383.  https://doi.org/10.1017/S026646741500019XGoogle Scholar
© The Author(s) 2022
José Juan Flores-Martínez, Rosamond Coates, Víctor Sánchez-Cordero, Jesús Alejandro Ríos-Solís, Beatriz Carely Luna-Olivera, Marcelino Ramírez-Ibáñez, and Mario C. Lavariega "Spatiotemporal Coexistence of Mesopredators and Their Prey in a Defaunated Neotropical Rainforest," Tropical Conservation Science 15(1), (8 April 2022). https://doi.org/10.1177/19400829221084261
Received: 5 August 2021; Accepted: 14 February 2022; Published: 8 April 2022
KEYWORDS
activity patterns
habitat fragmentation
mesopredator–prey interactions
Mexico
species coexistence
terrestrial mammals
Back to Top