Assessing interactions between coypus and capybaras in urban habitats: spatial and temporal overlap

Assessing interactions between coypus and capybaras in urban habitats: spatial and temporal overlap | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessing interactions between coypus and capybaras in urban habitats: spatial and temporal overlap Maria Jose Corriale, Florencia Bottelli This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8020266/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Two competing species can coexist over time if they segregate along at least one key dimension of their ecological niche: space, time, or resources. Urban habitats influence these processes by homogenizing landscapes, reducing available niche space, and inducing behavioral adjustments that alter animals’ temporal activity, thereby affecting their capacity for segregation. In such contexts, coexistence may depend on subtle adaptations that minimize resource competition. This study examines spatio-temporal overlap between coypus ( Myocastor coypus ) and capybaras ( Hydrochoerus hydrochaeris ) inhabiting gated communities in the Metropolitan Area of Buenos Aires, Argentina. Our objectives were to: (1) assess spatial overlap and co-occurrence; (2) analyze overlap in daily activity patterns and their seasonal variation; and (3) evaluate simultaneous spatio-temporal co-occurrence and its seasonal dynamics. Results revealed a high degree of spatial and temporal overlap between coypus and capybaras, with both species showing greater tolerance to share space during warmer seasons, when food resources are more abundant. However, segregation emerged at the simultaneous spatio-temporal scale, mediated by differences in peak activity periods and likely related to mechanisms of direct encounter avoidance. This fine-scale segregation is consistent with the competitive exclusion principle and suggests that interference competition may occur when resources are limited, particularly in colder seasons. These findings highlight how urbanization constrains niche availability and promotes coexistence through behavioral and temporal adjustments, while also showing that interactions between both species may vary according to resource availability and seasonal conditions. Myocastor coypus Hydrochoerus hydrochaeris gated communities urban ecology coexistence Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Species interactions have long been recognized as a key factor in structuring ecological communities and shaping the spatial and temporal distribution of animals (Darwin 1859 ; Schoener 1974 ; Carothers and Jaksic 1984). Competition between species arises when they overlap the main dimensions of their ecological niche: space, time, resources, and predators (Chesson 2000 ). For two competing species to coexist in the long term, they must segregate, at least partially, one or more of these dimensions (competitive exclusion principle; Kylafis and Loreau 2011 ; Lesmeister et al. 2015 ). Dietary differentiation and spatial and/or temporal segregation are the most common mechanisms that enable coexistence among species (Schoener 1974 ; Pianka 1981 ; Jaksic and Marone 2002 ). Niche segregation is also facilitated by greater habitat heterogeneity within the niche space (Amarasekare 2003 ). In this regard, urban habitats strongly influence these ecological processes by homogenizing the landscape and resources (McKinney and Lockwood 1999 ), thereby reducing the available niche space (Moss et al. 2016 ). Moreover, animals living in urban habitats tend to modify their feeding behavior, reduce their activity periods, and increase nocturnality, thereby minimizing the risks associated with human contact (Gaynor et al. 2018 , Mella-Méndez et al. 2019 , Łopucki et al. 2021 ). These behavioral adjustments, in turn, influence their temporal segregation. Consequently, since niche segregation is more difficult in these habitats, coexistence can only be achieved through adaptations that reduce competition for shared resources (Amarasekare 2003 ). The coypu ( Myocastor coypus ) and the capybara ( Hydrochoerus hydrochaeris ) are two large herbivorous semi-aquatic rodents that coexist in sympatry across much of their distribution range (Carter and Leonard 2002 ; Moreira et al. 2012 ). The capybara is distributed from Panama to Argentina (Doumecq Milieu et al. 2012 ), while the coypu is native to southern South America (Carter and Leonard 2002 ). Both species are primarily crepuscular (Palomares et al. 1994 ; Corriale 2010 ; Salas et al. 2022 ) and show a high overlap in their diet (Espinelli et al. 2016 ). However, aquatic vegetation is more significant in the diet of the coypu (Espinelli et al. 2016 ), while the capybara selects grasses and sedges in the higher zones of the topographical gradient (Barreto and Quintana 2013 ; Corriale and Loponte 2015 ). Although the habits of these rodents are similar and they select sites with similar characteristics, the coypu builds its own shelters using vegetation and substrate and spends most of its time feeding in the water or within the first few meters of water bodies (D’Adamo et al. 2000 ). In contrast, the capybara, unlike the coypu and other caviomorphs, does not build its own shelters but instead uses existing vegetation, often outside the water, and usually forages on land (Aldana-Domínguez et al. 2007; Corriale et al.2013). Both the coypu and the capybara are present in anthropized habitats (Corriale et al. 2020 ) and have successfully adapted to urbanized areas (Paglia et al. 2012 ; Almeida and Biondi 2014 ; Salas et al. 2022 ). The accelerated expansion of the Metropolitan Area of Buenos Aires (AMBA, Argentina), the sixth-largest metropolis in the world with over 15 million inhabitants (United Nations 2024 ), has led to new forms of urbanization including gated communities, country clubs, and large-scale developments, many of which have been built on natural wetlands (Fernández et al. 2010 ; Vidal-Koppmann 2014 ). These types of urban developments are characterized by lower population and building density, resulting in a higher proportion of green spaces. Buildings are separated by vegetation, which serves as corridors, shelter, or forage for wildlife (Ditchkoff 2006). In many cases, there are also open spaces such as golf courses and natural or artificial water bodies (Pintos and Sgroi, 2012 ). The coypu is present in most gated communities across the AMBA, where it reaches high densities (Abdenur Araos et al. 2025 ). In the case of the capybara, its colonization is still in its early stages but advancing, and in the developments where it has established itself, it exhibits high densities (Corriale and Arenas 2021 ). The characteristics of water bodies in gated communities, which mostly lack aquatic vegetation, compel both coypus and capybaras to forage in parkland areas. This increases the overlap in forage resource use between the two species, a situation further exacerbated by the low diversity of grasses and sedges due to the dominance of planted grass. Consequently, this study aims to analyze the spatio-temporal overlap between coypus and capybaras in gated communities within the Metropolitan Area of Buenos Aires, in order to better understand their ecological interactions in an urban environment and assess whether niche segregation occurs. Three specific objectives were established: (1) Analyze spatial overlap and co-occurrence, (2) Analyze overlap in activity patterns and their seasonal variation, and (3) Analyze simultaneous spatiotemporal co-occurrence and its seasonal variation in the sites of the development used by both species. Furthermore, four working hypotheses were proposed: (1) Coypus and capybaras exhibit high spatial overlap, (2) Both species have a predominantly nocturnal activity pattern with high temporal overlap, (3) There is low simultaneous spatiotemporal overlap between coypus and capybaras, and (4) Spatial, temporal, and simultaneous spatiotemporal overlap is higher during seasons with lower food availability (autumn and winter). Material and methods Area of study The study was conducted in 18 gated communities within an urban development located north of the Metropolitan Area of Buenos Aires (34°25’S 58°38’W; Fig. 1 ). The urban development, known as a “town-like city”, covers approximately 1800 hectares, of which 320 hectares consist of water bodies. Currently, the urban core includes more than 26 gated communities, a large educational community, a medical center, a commercial hub, nautical areas, a full sports club, and the future Civic Center, which houses the Catholic Church and the Jewish Temple ( https://www.avnordelta.com/ciudad/historia-de-nordelta/ ). The urban development is located at the boundary between the ecoregion of the Rolling Pampa and the ecoregion of the Paraná Delta, which provides it with greater biological diversity (Morello et al. 2018 ). Originally, the area was a zone of lowlands and wetlands, but the land alterations made for the urbanization have substantially modified the structure of the vegetation and its components. As a result, the “town-like city” now corresponds to a park (Cabrera 1976 ) that has been seeded and forested for residential purposes, featuring artificial lagoons generally connected by canals to the main course of the Luján River (Pintos 2018). The vegetation is primarily represented by Axonopus compressus (commonly known as carpet grass or " grama Bahiana " in Spanish) and some ornamental species with low coverage. Some areas along the edges of the water bodies feature medium to tall marsh vegetation, such as bulrush ( Schoenoplectus californicus ) and yellow flag iris ( Iris pseudacorus ), and there is a lack of aquatic vegetation due to maintenance activities conducted on the lagoons (Corriale and Arenas 2016 ). The climate is humid temperate with average annual temperatures of 16.5°C, with an average of 23.4°C in summer and 10.2°C in winter. The average annual precipitation is around 1016 mm, with nearly 40% occurring between December and March (Climate data 2015). Spatial overlap and co-occurrence The spatial overlap and co-occurrence of capybaras and coypus were determined using two different methodologies, through linear transects and camera trap stations. Linear transects. Between December 2019 and January 2020, spatial overlap was analyzed by recording the spatial use of both species across all water bodies using transects parallel to the shoreline, the area of highest usage intensity for both species (Corriale et al. 2013 ; Porini et al. 2019 ). Initially, 300 m transects were conducted to assess spatial use. However, to incorporate different scales of analysis, three transect sizes were later considered: (i) 300 m transects, representing areas of greater mobility or displacement for both species, which could reveal strong segregation; (ii) 100 m transects, associated with effective use areas, where local aggregations or co-occurrence might occur without direct interactions (Guichón et al. 2003; Corriale et al. 2006 ; Corriale et al. 2013 ); and (iii) 30 m transects, corresponding to the average lot size, where direct interactions could take place, indicating a closer level of interaction between the species. A total of 154 transects were conducted at the 300 m scale, and 300 transects were carried out at the 100 m and 30 m scales. The transects were spaced approximately 200 meters apart. Each transect was surveyed by boat, canoe, or on foot, recording the presence of each species through direct observation or signs of activity, such as droppings, tracks, refuges, resting sites (for capybaras), and burrows or nests (for coypus). Based on the data obtained from each survey, spatial overlap between the two species was estimated using the Sorensen Index: 2a/(2a + b + c), where a is the number of transects with both species present, b is the number of transects with only capybara presence, and c is the number of transects with only coypu presence (Chao et al. 2006 ). This index ranges from 0 (no overlap) to 1 (complete overlap). On the other hand, a probabilistic model was applied to statistically test for a significant pattern of co-occurrence (Veech 2013 ) at the three scales of analysis, using the co-occurr package in R (Griffith et al. 2016 ). This model calculates the probability (p) that two species coexist with a frequency lower (p_lt) or higher (p_gt) than the observed frequency of co-occurrence. Thus, if p_lt < 0.05, the two species have a negative co-occurrence, and if p_gt < 0.05, there is positive co-occurrence between the two species. Camera traps . From winter of 2019 to fall of 2020, camera trap stations were deployed at a total of 27 sites (Fig. 1 ). The number of sites sampled varied seasonally, ranging from 7 to 22, with fall having the fewest sites sampled due to restrictions imposed by the Preventive and Mandatory Social Isolation mandated in Argentina (Emergency Decree 297/2020) during the COVID-19 pandemic, which restricted access to some private developments. Camera trap sites included both public areas and unoccupied lots. At each site, a camera was installed and set to record two-minute videos whenever the infrared sensors detected movement, with a fifteen-minute delay between consecutive recordings. Camera trap sites were spaced at least 400 m apart (Ridout and Linkie 2009 ; Salas et al. 2022 ). Cameras were mounted on wooden stakes at an approximate height of 30–40 cm from the ground and positioned 3–5 meters from the shoreline to capture the areas of highest activity for the species (Guichón et al. 2003; Corriale et al. 2013 ). Each video also recorded the date, time, and ambient temperature. To analyze whether the abundance and/or intensity of use of one species influenced the abundance or intensity of use of the other across seasons, a generalized linear mixed model (GLMM) with a Poisson error distribution and a logit link function was applied (Zuur et al. 2009 ). Since capybaras were recorded at all camera trap stations, whereas coypus exhibited greater variability, we considered it more relevant to examine whether this variability could be explained by the presence of capybaras at different sites. Thus, the response variable was the total number of coypu videos recorded at each site. The explanatory variables were the season and the number of capybara videos recorded per day, considering the interaction between these two factors. Additionally, the site was included as a random effect. Models with and without interaction were compared using Akaike’s Information Criterion (Burnham and Anderson 2002 ). Temporal overlap The temporal overlap between capybaras and coypus was analyzed by estimating their daily activity patterns. Kernel density plots (annual and seasonal) were generated for both species based on video recordings (Ridout and Linkie, 2009 ). Overlap coefficients (Δ) were then calculated using the overlap package in R. This coefficient ranges from 0 to 1, where 0 indicates no overlap in activity patterns and 1 indicates complete overlap. The degree of overlap was classified into three levels: low ( 0.80) (Cheng et al. 2020 ). Additionally, significant differences between the activity patterns of capybaras and coypus were assessed using the Mardia-Watson-Wheeler test (Mardia and Jupp 2000 ). Simultaneous spatio-temporal overlap A hierarchical Bayesian multinomial logistic regression model (Koster and McElreath 2017 ) was used to compare the probability of co-occurrence of both species in video records with the probability of individual occurrences of each species. A null model, without fixed explanatory variables, was implemented, where the response variable was the species detected in each video, categorized into three levels: only M. coypus, only H. hydrochaeris, or both species together. To account for the lack of independence between observations, the camera trap station was included as a random effect. A logit link function (ln odds) was used, where the odds represented the probability of recording one or both species relative to the probability of no detection. The analysis was conducted using the R packages brms v.2.15.0 (Bürkner 2017 ) and RStan v.2.21.2. The Bayesian hierarchical multinomial model was developed and implemented in the STAN language (Carpenter et al. 2017 ). The model consisted of four chains, each with a minimum of 2,000 iterations and 1,000 warm-up samples, successfully merging and converging to an Rhat value of 1.0. This approach generated posterior distributions for the parameters, from which estimates and credible intervals (CI) were derived. Additionally, seasonal variation in the probability of joint occurrence was analyzed using a generalized linear mixed model (GLMM) with a Bernoulli error distribution and a logit link function (Zuur et al. 2009 ). The response variable was the presence or absence of both species together in each video, while the explanatory variable was the season. To account for potential non-independence of observations, the camera trap station was included as a random effect. All statistical analyses were performed in R v.4.2.2 (R Core Team 2023 ). Finally, to estimate simultaneous spatiotemporal overlap, the Sørensen Index was recalculated, this time based on the number of videos per site showing only capybara presence, only coypu presence, or both species together. To assess seasonal differences in the index values across sites, a generalized linear mixed model (GLMM) was applied, with the Sørensen Index as the response variable, season as the explanatory variable, and site as a random effect. Results Spatial overlap and co-occurrence Sampling by linear transects. At the 300 m scale, 19% of the transects showed only capybara presence, 24% showed only coypu presence, and 45% showed signs of both species. The Sørensen Index was 0.71, indicating a moderate-to-high spatial overlap between capybaras and coypus. Furthermore, the probability of co-occurrence was 56.8% (p_lt = 0.81; p_gt = 0.33), suggesting that the spatial association between the two species at this scale is likely random. At the 100 m scale, 20.8% of the transects showed only capybara presence, 27.8% showed only coypu presence, and 27.4% showed signs of both species. The Sørensen Index was 0.53, indicating moderate spatial overlap between the species. The probability of co-occurrence was 27.1% (p_lt = 0.70; p_gt = 0.37), lower than that observed at the macrohabitat scale. However, no evidence was found to suggest that they co-occur more or less than expected by chance. At the 30 m scale, 21.3% of the transects showed only capybara presence, 27.7% showed only coypu presence, and 12% showed signs of both species. The Sørensen Index was 0.33, indicating low spatial overlap between capybaras and coypus. The probability of co-occurrence was 13.2% (p_lt = 0.21; p_gt = 0.85), the lowest among all scales. However, as with the other scales, no evidence was found to suggest that they co-occur more or less than expected by chance. Sampling through camera traps . A total of 2312 videos were obtained, recording the presence of either coypu or capybara. In 85% of the sampled sites, both species were recorded, while 15% recorded only capybara presence. No sites recorded the presence of only coypu. The analysis revealed that the association between coypu activity and the relative activity of capybaras varied across seasons (significant interaction, ꭕ² = 61.6; p < 0.001). In fall, a negative association was observed (slope = − 1.26; Z = − 7.30; p < 0.001), differing from the other seasons, which showed no significant relationship, such as spring and winter (slope = 0.30; Z = − 1.90; p = 0.06 and slope = 0.03; Z = 0.115; p = 0.908, respectively), or a slightly positive association, as seen in summer (slope = 0.14; Z = 4.07; p < 0.001) (Fig. 2 ). Temporal overlap Capybaras and coypus exhibited a high degree of overlap in their daily activity patterns when data collected throughout the year were integrated (Fig. 3 ), with a calculated value of 0.81 (95% CI: 0.78–0.85). However, significant differences were detected between them (p-value < 0.001). This could be attributed to the fact that coypus displayed greater nocturnal activity with a unimodal pattern, peaking at night between 00:00 and 02:00 AM, whereas capybaras exhibited a bimodal pattern, with a major activity peak at dusk and a smaller one at dawn. Regarding the seasonal analysis, summer showed the highest overlap in activity between both species (0.90, 95% CI: 0.83–0.96) and was the only season in which no significant differences were found between capybara and coypu activity patterns (p-value = 0.072). In decreasing order of overlap, the following seasons were spring (0.77, 95% CI: 0.71–0.83), winter (0.74, 95% CI: 0.68–0.79), and finally autumn (0.70, 95% CI: 0.64–0.76), with significant differences found in all cases (p-value < 0.001). Across all seasons, capybaras exhibited more diurnal behavior than coypus, a difference that became more pronounced during the colder months (Fig. 4 ). Simultaneous spatio-temporal overlap Of the 2312 videos obtained, only 1% showed capybaras and coypus sharing the same space simultaneously. The hierarchical Bayesian multinomial model indicated that the probability of both species appearing together in the same video record differs from the probability of recording capybaras or coypus separately. The odds of a joint record were 93–98.3% lower than those of a capybara record and 33.3–89.4% lower than those of a coypu record. When analyzing seasonal variation in co-occurrence, significant differences were found (χ² = 9.62, p = 0.022). Due to high data variability and the low frequency of joint occurrences, resulting in limited statistical power, the generalized linear mixed model was used only to compare each season with spring, which showed the highest probability of co-occurrence (Fig. 5 ). Significant differences were detected between spring and autumn (F = -2.46, p = 0.014) and between spring and winter (F = -1.24, p = 0.025). In turn, the Sørensen Index calculated from the entire video record yielded a value of 0.084, which is an order of magnitude lower than the Sørensen Index calculated from the transect data (spatial overlap). Using the GLMM, the indices were calculated for each season, all of which also showed very low values (Table 1 ), with no significant differences observed between them (F = 4.78; p = 0.180). Table 1 Mean values of the Sørensen Index for each season, along with their 95% confidence intervals (CI). Season Mean value CI Lower Upper Spring 0,072 0,031 0,110 Winter 0,035 0,062 0,087 Summer 0,092 0,015 0,171 Autumn 0,075 0,010 0,140 Discussion In this study, a high overlap between coypus and capybaras was observed in urban habitats at both spatial and temporal scales, with segregation being evident only at the simultaneous spatio-temporal scale. This high degree of overlap may be associated with the characteristics and constraints of urban habitats, where limitations in space and available resources reduce the diversity of ecological niches (Moss et al. 2016 ). At the spatial scale, no clear evidence of segregation between coypus and capybaras was found across the spatial resolutions analyzed (300 m, 100 m, and 30 m), supporting the proposed hypothesis. The moderate to high overlap and the random distribution of both species suggest similar habitat use. This pattern may be linked to the homogenization of the landscape, a characteristic feature of urban habitats (McKinney 2005 ). The different neighborhoods within the urbanized area exhibit high similarity in land cover types and spatial arrangement (Iglesias 2020 ), likely resulting in a uniform availability of resources for both species. The absence of aquatic vegetation forces coypus to feed on terrestrial vegetation in landscaped areas adjacent to water bodies, thereby sharing the same habitats that capybaras use for foraging and resting. This likely increases spatial overlap compared to natural areas or agroecosystems, where coypus primarily feed within or along the edges of water bodies (D’Adamo et al. 2000 ; Guichón et al. 2003), while capybaras prefer higher areas along the topographic gradient (Aldana-Domínguez et al. 2007; Corriale 2010 ; Corriale et al. 2013 ). Previous studies in natural habitats indicate a high degree of dietary overlap between the two species, with 72% of their food items in common, primarily grasses (Espinelli et al. 2016 ). However, the key distinction lies in the greater consumption of aquatic plants by coypus (Espinelli et al. 2016 ; D’Adamo et al. 2000 ). In the study area, the low diversity of grasses, both in richness and evenness, results from the widespread use of sod, specifically Bahia grass ( Axonopus compressus ), in gardens and communal spaces. This homogeneity further increases both dietary and spatial overlap, as both species utilize the same sites for foraging. At the temporal scale, a high overlap in the annual activity pattern of capybaras and coypus was observed, as well as a moderate to high overlap in seasonal patterns, which supports the hypothesis proposed at this scale. Although both species are predominantly crepuscular in natural conditions, they exhibited moderate to high nocturnal activity in the urban environment, possibly due to the tendency of such environments to increase nocturnality in animals in an effort to minimize interactions with human activities (Gaynor et al. 2018 ). This shift was particularly evident in the coypu, which showed predominantly nocturnal activity. Except for summer, significant differences in activity patterns suggest a differentiation in their peak activity times. In the case of capybaras, previous studies reported very similar activity patterns, though with more diurnal activity, highlighting peaks around 6:00 and 18:00 hours (Corriale 2010 ; Di Bitetti et al. 2020 ; Corriale and Arenas 2021 ; Serra-Medeiros et al. 2021 ; Ávila et al. in press). In the study area, it was observed that capybaras tend to be more diurnal than coypus, especially in autumn and winter, likely due to their greater sensitivity to cold temperatures (Corriale 2010 ). Ávila et al. (in press) found that on cool days, capybaras exhibited a fully diurnal activity pattern. Regarding the coypu, its activity patterns can be highly variable, ranging from crepuscular-nocturnal (Palomares et al. 1984; Mori et al. 2020 ) to fully diurnal (Meyer et al. 2005 ). A study in a similar urban setting showed a unimodal pattern, with activity concentrated between 18:00 and 00:00 hours (Salas et al. 2022 ), while our results indicate that coypu activity remains high from 00:00 to 06:00 hours. This difference could be due to the presence of capybaras, which might lead to a reduction in the coypu’s spatial niche, causing it to concentrate its activity in the early morning to reduce temporal overlap. It is acknowledged that the coypu is a highly plastic species, capable of adapting its temporal behavior to local environmental conditions (Mori et al. 2020 ). At the simultaneous space-time scale, high segregation between capybaras and coypus was observed, in accordance with Hypothesis 3. Although both species are distributed in the same areas and share similar activity patterns, they tend to avoid using the same space at the same time, minimizing direct encounters and reducing the frequency of interference interactions. This segregation could be evidence of the competitive exclusion principle, indicating that niche segregation can manifest at multiple scales, including more subtle ones. As mentioned earlier, this simultaneous space-time segregation is likely mediated by differences in the activity peaks of both species. Such fine-scale temporal segregation has been previously documented in carnivores with high spatial and temporal overlap (Hayward and Slotow 2009 ; Gerber et al. 2012 ; Farris et al. 2015 ; Cronk and Pillay 2020 ), though it has been less studied in herbivores. Furthermore, our results highlight that simultaneous space-time overlap does not necessarily reflect the overlap observed at the spatial or temporal scale separately (Karanth et al. 2017 ; Cronk and Pillay 2020 ). This apparent avoidance of direct encounters is supported by the negative association observed between the intensity of habitat use by capybaras and that by coypus during autumn. This dynamic suggests possible interference competition under conditions of low resource availability, where direct or indirect interactions between the two species could limit the coypu’s access to available resources. Our results showed a higher tolerance by coypus and capybaras to share space during the warmer seasons, which contradicts our Hypothesis 4. This pattern may be related to seasonal differences in forage availability. When resources are limited, competition appears to play a stronger role, leading to spatial and temporal segregation between the species. Conversely, during periods of greater resource abundance, food does not seem to be a limiting factor, allowing for increased spatial overlap. Such competition can result in reduced intake rates for the affected species (Goss-Custard 1980 ) and may drive them to use habitats with lower-quality resources or to adjust their activity periods to minimize competitive interactions. A study on a community of herbivores in Africa demonstrated that subordinate species altered their temporal niche to avoid interference competition with the dominant species (the elephant), particularly during the dry season when resources were scarce (Valeix et al. 2007 ). A similar dynamic could be occurring between capybaras, as the dominant species, and coypus, aligning with the patterns observed in our study. Competition between species can have significant effects, not only by promoting niche segregation but also by leading to the dispersal of subordinate species or a decrease in their abundance (Amarasekare 2003 , Mori et al. 2022). In the study area, since 2017, a notable increase and expansion in the capybara population has been observed, accompanied by a decrease in the coypu population (Corriale et al. 2019; Abdenur Araoz et al. 2025). Although the relationship between these trends has not been thoroughly investigated nor has a clear causal link been established, studies in similar contexts have shown that larger species tend to displace smaller species with which they share ecological niches. In the United Kingdom, the expansion of the otter ( Lutra lutra ) has displaced the American mink ( Neovison vison ), significantly reducing its local densities (Bonesi and Macdonald 2004 ; Bonesi et al. 2004 ). Similarly, in northeastern Italy, populations of the Eurasian red squirrel ( Sciurus vulgaris ) have displaced those of the Siberian striped squirrel ( Eutamias sibiricus ), resulting in a decrease in its local density (Mori et al. 2018 ). However, it should not be discounted that both populations may not yet have reached the carrying capacity and resource limitations of the habitat, and therefore, the pressure on these closely related rodent species to acquire interspecific differentiation may still be too weak, allowing for their coexistence even in the presence of broad niche overlap (Tobias et al. 2020 ). Furthermore, high-disturbance regimes, such as urban areas, tend to allow the coexistence of generalists with overlapping niches (Moi et al. 2020 ). This underscores the need to analyze in greater detail the interactions between capybaras and coypus, as well as the ecological and social factors that may be shaping the dynamics observed in the study area. A more thorough approach to these interactions will help better understand the underlying mechanisms and develop effective management strategies for both species. Declarations Conflict of interest statement The authors declare no conflict of interest. Ethics declaration Not applicable. This study was based on non-invasive observational methods. Author contributions Conceptualization: M.J. Corriale; Methodology: M.J. Corriale; Formal analysis and investigation: F. Bottelli and M.J. Corriale; Writing – original draft: F. Bottelli; Writing – review and editing: M.J. Corriale; Funding acquisition: M.J. Corriale; Resources: M.J. Corriale; Supervision: M.J. Corriale. Acknowledgments This study was supported by the Agencia Nacional de Promoción Científica y Técnica (PICT FONCyT 2019 − 0983), the COMFAUNA Fellowship Fund – Gordon and Betty Moore Foundation, and Fundación Natura, Colombia. We are grateful to the Nordelta Neighborhood Association, Lic. Morena Peltzer, and Lic. Florencia Abdenur Araos for their invaluable assistance and contributions to the development of this work. Data availability statement The datasets generated and analyzed during the current study are available from the corresponding author upon request. 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10:11:26","extension":"png","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":25566,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8020266/v1/d47e1447a1f0a1294e7f045f.png"},{"id":96709531,"identity":"fd68fac1-0ade-41e2-a3a1-9bd6035416d2","added_by":"auto","created_at":"2025-11-25 10:09:15","extension":"png","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8805,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8020266/v1/dd752d853847e81f790f4822.png"},{"id":96709675,"identity":"30145c51-6d59-41d4-9a06-fa27772adec1","added_by":"auto","created_at":"2025-11-25 10:09:30","extension":"xml","order_by":30,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":125952,"visible":true,"origin":"","legend":"","description":"","filename":"MAMBD25002950structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8020266/v1/543e9fac96b0b449a328aa5b.xml"},{"id":96662874,"identity":"fab2e213-e254-4237-a925-c958bbeac2f5","added_by":"auto","created_at":"2025-11-24 19:02:24","extension":"html","order_by":31,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":134939,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8020266/v1/3b3458c6c4deef52f762678c.html"},{"id":96710382,"identity":"b4d835f9-bf34-4cf1-8cf5-30968e52900c","added_by":"auto","created_at":"2025-11-25 10:10:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":7029822,"visible":true,"origin":"","legend":"\u003cp\u003eOn the left, the location of the Tigre Partido, Buenos Aires municipality (highlighted in green). On the right, a satellite image of the private urban development where the work was conducted (Google Earth Pro 2020). Marked in red is the location of the camera trap stations\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-8020266/v1/3bf1ca78e5463918d392a566.png"},{"id":96662841,"identity":"16024741-ac81-4d8f-bcdb-38e0a04eb72b","added_by":"auto","created_at":"2025-11-24 19:02:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":93819,"visible":true,"origin":"","legend":"\u003cp\u003ePredicted relationship between the number of coypu (\u003cem\u003eMyocastor coypus\u003c/em\u003e) detections and the number of capybara (\u003cem\u003eHydrochoerus hydrochaeris\u003c/em\u003e) detections per day across seasons, based on a generalized linear mixed model in a private urban development in the Buenos Aires Province. Shaded areas represent 95% confidence intervals. A negative association was found in fall, whereas relationships were non-significant in spring and winter and slightly positive in summer\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-8020266/v1/bd093bb52d00bd0bdd3bfcae.png"},{"id":96662844,"identity":"1870968e-3ba6-4a18-903d-4814273cd58b","added_by":"auto","created_at":"2025-11-24 19:02:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":152982,"visible":true,"origin":"","legend":"\u003cp\u003eOverlap in daily activity patterns throughout the year between capybara (\u003cem\u003eHydrochoerus hydrochaeris\u003c/em\u003e) and coypu (\u003cem\u003eMyocastor coypus\u003c/em\u003e) in a private urban development in Buenos Aires Province (Argentina)\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-8020266/v1/d86c1b3b8ec77832af0c85d4.png"},{"id":96710181,"identity":"d4185bc4-9d8b-418e-bfca-0c2cb99e1f3c","added_by":"auto","created_at":"2025-11-25 10:10:16","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":150064,"visible":true,"origin":"","legend":"\u003cp\u003eOverlap in the seasonal activity patterns of capybara (\u003cem\u003eHydrochoerus hydrochaeris\u003c/em\u003e) and coypu (\u003cem\u003eMyocastor coypus\u003c/em\u003e) in a private urban development in Buenos Aires Province, Argentina\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-8020266/v1/fac6f16f2620fe4cbf2e6a56.png"},{"id":96709649,"identity":"3fa55ea5-768d-44ed-aaf9-2f1249134ff3","added_by":"auto","created_at":"2025-11-25 10:09:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":69325,"visible":true,"origin":"","legend":"\u003cp\u003eEstimated co-occurrence probability of coypus (\u003cem\u003eMyocastor coypus\u003c/em\u003e) and capybaras (\u003cem\u003eHydrochoerus hydrochaeris\u003c/em\u003e) across seasons in a private urban development in Buenos Aires Province, based on generalized linear mixed model. Blue circles indicate the estimated mean values; vertical bars represent 95% confidence intervals. Different letters indicate statistically significant differences between seasons (p\u0026lt;0.05)\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-8020266/v1/c11642eb9b397ca3bf7907cb.png"},{"id":96712881,"identity":"262c6d4c-0537-4e9d-9fdb-b980b5ee09dc","added_by":"auto","created_at":"2025-11-25 10:17:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8056212,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8020266/v1/4d0a381f-24e8-4000-b794-a39560a736d2.pdf"}],"financialInterests":"","formattedTitle":"Assessing interactions between coypus and capybaras in urban habitats: spatial and temporal overlap","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSpecies interactions have long been recognized as a key factor in structuring ecological communities and shaping the spatial and temporal distribution of animals (Darwin \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1859\u003c/span\u003e; Schoener \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e1974\u003c/span\u003e; Carothers and Jaksic 1984). Competition between species arises when they overlap the main dimensions of their ecological niche: space, time, resources, and predators (Chesson \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). For two competing species to coexist in the long term, they must segregate, at least partially, one or more of these dimensions (competitive exclusion principle; Kylafis and Loreau \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Lesmeister et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Dietary differentiation and spatial and/or temporal segregation are the most common mechanisms that enable coexistence among species (Schoener \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e1974\u003c/span\u003e; Pianka \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1981\u003c/span\u003e; Jaksic and Marone \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Niche segregation is also facilitated by greater habitat heterogeneity within the niche space (Amarasekare \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). In this regard, urban habitats strongly influence these ecological processes by homogenizing the landscape and resources (McKinney and Lockwood \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), thereby reducing the available niche space (Moss et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Moreover, animals living in urban habitats tend to modify their feeding behavior, reduce their activity periods, and increase nocturnality, thereby minimizing the risks associated with human contact (Gaynor et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Mella-M\u0026eacute;ndez et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Łopucki et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These behavioral adjustments, in turn, influence their temporal segregation. Consequently, since niche segregation is more difficult in these habitats, coexistence can only be achieved through adaptations that reduce competition for shared resources (Amarasekare \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe coypu (\u003cem\u003eMyocastor coypus\u003c/em\u003e) and the capybara (\u003cem\u003eHydrochoerus hydrochaeris\u003c/em\u003e) are two large herbivorous semi-aquatic rodents that coexist in sympatry across much of their distribution range (Carter and Leonard \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Moreira et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The capybara is distributed from Panama to Argentina (Doumecq Milieu et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), while the coypu is native to southern South America (Carter and Leonard \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Both species are primarily crepuscular (Palomares et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Corriale \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Salas et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and show a high overlap in their diet (Espinelli et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, aquatic vegetation is more significant in the diet of the coypu (Espinelli et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), while the capybara selects grasses and sedges in the higher zones of the topographical gradient (Barreto and Quintana \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Corriale and Loponte \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Although the habits of these rodents are similar and they select sites with similar characteristics, the coypu builds its own shelters using vegetation and substrate and spends most of its time feeding in the water or within the first few meters of water bodies (D\u0026rsquo;Adamo et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In contrast, the capybara, unlike the coypu and other caviomorphs, does not build its own shelters but instead uses existing vegetation, often outside the water, and usually forages on land (Aldana-Dom\u0026iacute;nguez et al. 2007; Corriale et al.2013). Both the coypu and the capybara are present in anthropized habitats (Corriale et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and have successfully adapted to urbanized areas (Paglia et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Almeida and Biondi \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Salas et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe accelerated expansion of the Metropolitan Area of Buenos Aires (AMBA, Argentina), the sixth-largest metropolis in the world with over 15\u0026nbsp;million inhabitants (United Nations \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), has led to new forms of urbanization including gated communities, country clubs, and large-scale developments, many of which have been built on natural wetlands (Fern\u0026aacute;ndez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Vidal-Koppmann \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). These types of urban developments are characterized by lower population and building density, resulting in a higher proportion of green spaces. Buildings are separated by vegetation, which serves as corridors, shelter, or forage for wildlife (Ditchkoff 2006). In many cases, there are also open spaces such as golf courses and natural or artificial water bodies (Pintos and Sgroi, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The coypu is present in most gated communities across the AMBA, where it reaches high densities (Abdenur Araos et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In the case of the capybara, its colonization is still in its early stages but advancing, and in the developments where it has established itself, it exhibits high densities (Corriale and Arenas \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The characteristics of water bodies in gated communities, which mostly lack aquatic vegetation, compel both coypus and capybaras to forage in parkland areas. This increases the overlap in forage resource use between the two species, a situation further exacerbated by the low diversity of grasses and sedges due to the dominance of planted grass.\u003c/p\u003e\u003cp\u003eConsequently, this study aims to analyze the spatio-temporal overlap between coypus and capybaras in gated communities within the Metropolitan Area of Buenos Aires, in order to better understand their ecological interactions in an urban environment and assess whether niche segregation occurs. Three specific objectives were established: (1) Analyze spatial overlap and co-occurrence, (2) Analyze overlap in activity patterns and their seasonal variation, and (3) Analyze simultaneous spatiotemporal co-occurrence and its seasonal variation in the sites of the development used by both species. Furthermore, four working hypotheses were proposed: (1) Coypus and capybaras exhibit high spatial overlap, (2) Both species have a predominantly nocturnal activity pattern with high temporal overlap, (3) There is low simultaneous spatiotemporal overlap between coypus and capybaras, and (4) Spatial, temporal, and simultaneous spatiotemporal overlap is higher during seasons with lower food availability (autumn and winter).\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eArea of study\u003c/h2\u003e\u003cp\u003eThe study was conducted in 18 gated communities within an urban development located north of the Metropolitan Area of Buenos Aires (34\u0026deg;25\u0026rsquo;S 58\u0026deg;38\u0026rsquo;W; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The urban development, known as a \u0026ldquo;town-like city\u0026rdquo;, covers approximately 1800 hectares, of which 320 hectares consist of water bodies. Currently, the urban core includes more than 26 gated communities, a large educational community, a medical center, a commercial hub, nautical areas, a full sports club, and the future Civic Center, which houses the Catholic Church and the Jewish Temple (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.avnordelta.com/ciudad/historia-de-nordelta/\u003c/span\u003e\u003cspan address=\"https://www.avnordelta.com/ciudad/historia-de-nordelta/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe urban development is located at the boundary between the ecoregion of the Rolling Pampa and the ecoregion of the Paran\u0026aacute; Delta, which provides it with greater biological diversity (Morello et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Originally, the area was a zone of lowlands and wetlands, but the land alterations made for the urbanization have substantially modified the structure of the vegetation and its components. As a result, the \u0026ldquo;town-like city\u0026rdquo; now corresponds to a park (Cabrera \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1976\u003c/span\u003e) that has been seeded and forested for residential purposes, featuring artificial lagoons generally connected by canals to the main course of the Luj\u0026aacute;n River (Pintos 2018). The vegetation is primarily represented by \u003cem\u003eAxonopus compressus\u003c/em\u003e (commonly known as carpet grass or \"\u003cem\u003egrama Bahiana\u003c/em\u003e\" in Spanish) and some ornamental species with low coverage. Some areas along the edges of the water bodies feature medium to tall marsh vegetation, such as bulrush (\u003cem\u003eSchoenoplectus californicus\u003c/em\u003e) and yellow flag iris (\u003cem\u003eIris pseudacorus\u003c/em\u003e), and there is a lack of aquatic vegetation due to maintenance activities conducted on the lagoons (Corriale and Arenas \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe climate is humid temperate with average annual temperatures of 16.5\u0026deg;C, with an average of 23.4\u0026deg;C in summer and 10.2\u0026deg;C in winter. The average annual precipitation is around 1016 mm, with nearly 40% occurring between December and March (Climate data 2015).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSpatial overlap and co-occurrence\u003c/h3\u003e\n\u003cp\u003eThe spatial overlap and co-occurrence of capybaras and coypus were determined using two different methodologies, through linear transects and camera trap stations.\u003c/p\u003e\u003cp\u003e\u003cem\u003eLinear transects.\u003c/em\u003e Between December 2019 and January 2020, spatial overlap was analyzed by recording the spatial use of both species across all water bodies using transects parallel to the shoreline, the area of highest usage intensity for both species (Corriale et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Porini et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Initially, 300 m transects were conducted to assess spatial use. However, to incorporate different scales of analysis, three transect sizes were later considered: (i) 300 m transects, representing areas of greater mobility or displacement for both species, which could reveal strong segregation; (ii) 100 m transects, associated with effective use areas, where local aggregations or co-occurrence might occur without direct interactions (Guich\u0026oacute;n et al. 2003; Corriale et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Corriale et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e); and (iii) 30 m transects, corresponding to the average lot size, where direct interactions could take place, indicating a closer level of interaction between the species. A total of 154 transects were conducted at the 300 m scale, and 300 transects were carried out at the 100 m and 30 m scales. The transects were spaced approximately 200 meters apart. Each transect was surveyed by boat, canoe, or on foot, recording the presence of each species through direct observation or signs of activity, such as droppings, tracks, refuges, resting sites (for capybaras), and burrows or nests (for coypus). Based on the data obtained from each survey, spatial overlap between the two species was estimated using the Sorensen Index: 2a/(2a\u0026thinsp;+\u0026thinsp;b\u0026thinsp;+\u0026thinsp;c), where \u003cem\u003ea\u003c/em\u003e is the number of transects with both species present, \u003cem\u003eb\u003c/em\u003e is the number of transects with only capybara presence, and \u003cem\u003ec\u003c/em\u003e is the number of transects with only coypu presence (Chao et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). This index ranges from 0 (no overlap) to 1 (complete overlap).\u003c/p\u003e\u003cp\u003eOn the other hand, a probabilistic model was applied to statistically test for a significant pattern of co-occurrence (Veech \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) at the three scales of analysis, using the \u003cem\u003eco-occurr\u003c/em\u003e package in R (Griffith et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This model calculates the probability (p) that two species coexist with a frequency lower (p_lt) or higher (p_gt) than the observed frequency of co-occurrence. Thus, if p_lt\u0026thinsp;\u0026lt;\u0026thinsp;0.05, the two species have a negative co-occurrence, and if p_gt\u0026thinsp;\u0026lt;\u0026thinsp;0.05, there is positive co-occurrence between the two species.\u003c/p\u003e\u003cp\u003e\u003cem\u003eCamera traps\u003c/em\u003e. From winter of 2019 to fall of 2020, camera trap stations were deployed at a total of 27 sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The number of sites sampled varied seasonally, ranging from 7 to 22, with fall having the fewest sites sampled due to restrictions imposed by the Preventive and Mandatory Social Isolation mandated in Argentina (Emergency Decree 297/2020) during the COVID-19 pandemic, which restricted access to some private developments. Camera trap sites included both public areas and unoccupied lots.\u003c/p\u003e\u003cp\u003eAt each site, a camera was installed and set to record two-minute videos whenever the infrared sensors detected movement, with a fifteen-minute delay between consecutive recordings. Camera trap sites were spaced at least 400 m apart (Ridout and Linkie \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Salas et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Cameras were mounted on wooden stakes at an approximate height of 30\u0026ndash;40 cm from the ground and positioned 3\u0026ndash;5 meters from the shoreline to capture the areas of highest activity for the species (Guich\u0026oacute;n et al. 2003; Corriale et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Each video also recorded the date, time, and ambient temperature.\u003c/p\u003e\u003cp\u003eTo analyze whether the abundance and/or intensity of use of one species influenced the abundance or intensity of use of the other across seasons, a generalized linear mixed model (GLMM) with a Poisson error distribution and a logit link function was applied (Zuur et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Since capybaras were recorded at all camera trap stations, whereas coypus exhibited greater variability, we considered it more relevant to examine whether this variability could be explained by the presence of capybaras at different sites. Thus, the response variable was the total number of coypu videos recorded at each site. The explanatory variables were the season and the number of capybara videos recorded per day, considering the interaction between these two factors. Additionally, the site was included as a random effect. Models with and without interaction were compared using Akaike\u0026rsquo;s Information Criterion (Burnham and Anderson \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eTemporal overlap \u003c/h3\u003e\n\u003cp\u003eThe temporal overlap between capybaras and coypus was analyzed by estimating their daily activity patterns. Kernel density plots (annual and seasonal) were generated for both species based on video recordings (Ridout and Linkie, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Overlap coefficients (Δ) were then calculated using the overlap package in R. This coefficient ranges from 0 to 1, where 0 indicates no overlap in activity patterns and 1 indicates complete overlap. The degree of overlap was classified into three levels: low (\u0026lt;\u0026thinsp;0.5), moderate (0.50\u0026ndash;0.80), and high (\u0026gt;\u0026thinsp;0.80) (Cheng et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Additionally, significant differences between the activity patterns of capybaras and coypus were assessed using the Mardia-Watson-Wheeler test (Mardia and Jupp \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eSimultaneous spatio-temporal overlap\u003c/h3\u003e\n\u003cp\u003eA hierarchical Bayesian multinomial logistic regression model (Koster and McElreath \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) was used to compare the probability of co-occurrence of both species in video records with the probability of individual occurrences of each species. A null model, without fixed explanatory variables, was implemented, where the response variable was the species detected in each video, categorized into three levels: only M. coypus, only H. hydrochaeris, or both species together. To account for the lack of independence between observations, the camera trap station was included as a random effect. A logit link function (ln odds) was used, where the odds represented the probability of recording one or both species relative to the probability of no detection.\u003c/p\u003e\u003cp\u003eThe analysis was conducted using the R packages brms v.2.15.0 (B\u0026uuml;rkner \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and RStan v.2.21.2. The Bayesian hierarchical multinomial model was developed and implemented in the STAN language (Carpenter et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The model consisted of four chains, each with a minimum of 2,000 iterations and 1,000 warm-up samples, successfully merging and converging to an Rhat value of 1.0. This approach generated posterior distributions for the parameters, from which estimates and credible intervals (CI) were derived.\u003c/p\u003e\u003cp\u003eAdditionally, seasonal variation in the probability of joint occurrence was analyzed using a generalized linear mixed model (GLMM) with a Bernoulli error distribution and a logit link function (Zuur et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The response variable was the presence or absence of both species together in each video, while the explanatory variable was the season. To account for potential non-independence of observations, the camera trap station was included as a random effect. All statistical analyses were performed in R v.4.2.2 (R Core Team \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFinally, to estimate simultaneous spatiotemporal overlap, the S\u0026oslash;rensen Index was recalculated, this time based on the number of videos per site showing only capybara presence, only coypu presence, or both species together. To assess seasonal differences in the index values across sites, a generalized linear mixed model (GLMM) was applied, with the S\u0026oslash;rensen Index as the response variable, season as the explanatory variable, and site as a random effect.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eSpatial overlap and co-occurrence\u003c/h2\u003e\u003cp\u003e\u003cem\u003eSampling by linear transects.\u003c/em\u003e At the 300 m scale, 19% of the transects showed only capybara presence, 24% showed only coypu presence, and 45% showed signs of both species. The S\u0026oslash;rensen Index was 0.71, indicating a moderate-to-high spatial overlap between capybaras and coypus. Furthermore, the probability of co-occurrence was 56.8% (p_lt\u0026thinsp;=\u0026thinsp;0.81; p_gt\u0026thinsp;=\u0026thinsp;0.33), suggesting that the spatial association between the two species at this scale is likely random.\u003c/p\u003e\u003cp\u003eAt the 100 m scale, 20.8% of the transects showed only capybara presence, 27.8% showed only coypu presence, and 27.4% showed signs of both species. The S\u0026oslash;rensen Index was 0.53, indicating moderate spatial overlap between the species. The probability of co-occurrence was 27.1% (p_lt\u0026thinsp;=\u0026thinsp;0.70; p_gt\u0026thinsp;=\u0026thinsp;0.37), lower than that observed at the macrohabitat scale. However, no evidence was found to suggest that they co-occur more or less than expected by chance.\u003c/p\u003e\u003cp\u003eAt the 30 m scale, 21.3% of the transects showed only capybara presence, 27.7% showed only coypu presence, and 12% showed signs of both species. The S\u0026oslash;rensen Index was 0.33, indicating low spatial overlap between capybaras and coypus. The probability of co-occurrence was 13.2% (p_lt\u0026thinsp;=\u0026thinsp;0.21; p_gt\u0026thinsp;=\u0026thinsp;0.85), the lowest among all scales. However, as with the other scales, no evidence was found to suggest that they co-occur more or less than expected by chance.\u003c/p\u003e\u003cp\u003e\u003cem\u003eSampling through camera traps\u003c/em\u003e. A total of 2312 videos were obtained, recording the presence of either coypu or capybara. In 85% of the sampled sites, both species were recorded, while 15% recorded only capybara presence. No sites recorded the presence of only coypu.\u003c/p\u003e\u003cp\u003eThe analysis revealed that the association between coypu activity and the relative activity of capybaras varied across seasons (significant interaction, ꭕ\u0026sup2; = 61.6; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In fall, a negative association was observed (slope = \u0026minus;\u0026thinsp;1.26; Z = \u0026minus;\u0026thinsp;7.30; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), differing from the other seasons, which showed no significant relationship, such as spring and winter (slope\u0026thinsp;=\u0026thinsp;0.30; Z = \u0026minus;\u0026thinsp;1.90; p\u0026thinsp;=\u0026thinsp;0.06 and slope\u0026thinsp;=\u0026thinsp;0.03; Z\u0026thinsp;=\u0026thinsp;0.115; p\u0026thinsp;=\u0026thinsp;0.908, respectively), or a slightly positive association, as seen in summer (slope\u0026thinsp;=\u0026thinsp;0.14; Z\u0026thinsp;=\u0026thinsp;4.07; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eTemporal overlap\u003c/h3\u003e\n\u003cp\u003eCapybaras and coypus exhibited a high degree of overlap in their daily activity patterns when data collected throughout the year were integrated (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e3\u003c/span\u003e), with a calculated value of 0.81 (95% CI: 0.78\u0026ndash;0.85). However, significant differences were detected between them (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This could be attributed to the fact that coypus displayed greater nocturnal activity with a unimodal pattern, peaking at night between 00:00 and 02:00 AM, whereas capybaras exhibited a bimodal pattern, with a major activity peak at dusk and a smaller one at dawn.\u003c/p\u003e\u003cp\u003eRegarding the seasonal analysis, summer showed the highest overlap in activity between both species (0.90, 95% CI: 0.83\u0026ndash;0.96) and was the only season in which no significant differences were found between capybara and coypu activity patterns (p-value\u0026thinsp;=\u0026thinsp;0.072). In decreasing order of overlap, the following seasons were spring (0.77, 95% CI: 0.71\u0026ndash;0.83), winter (0.74, 95% CI: 0.68\u0026ndash;0.79), and finally autumn (0.70, 95% CI: 0.64\u0026ndash;0.76), with significant differences found in all cases (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Across all seasons, capybaras exhibited more diurnal behavior than coypus, a difference that became more pronounced during the colder months (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eSimultaneous spatio-temporal overlap\u003c/h3\u003e\n\u003cp\u003eOf the 2312 videos obtained, only 1% showed capybaras and coypus sharing the same space simultaneously. The hierarchical Bayesian multinomial model indicated that the probability of both species appearing together in the same video record differs from the probability of recording capybaras or coypus separately. The odds of a joint record were 93\u0026ndash;98.3% lower than those of a capybara record and 33.3\u0026ndash;89.4% lower than those of a coypu record.\u003c/p\u003e\u003cp\u003eWhen analyzing seasonal variation in co-occurrence, significant differences were found (χ\u0026sup2; = 9.62, p\u0026thinsp;=\u0026thinsp;0.022). Due to high data variability and the low frequency of joint occurrences, resulting in limited statistical power, the generalized linear mixed model was used only to compare each season with spring, which showed the highest probability of co-occurrence (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Significant differences were detected between spring and autumn (F = -2.46, p\u0026thinsp;=\u0026thinsp;0.014) and between spring and winter (F = -1.24, p\u0026thinsp;=\u0026thinsp;0.025).\u003c/p\u003e\u003cp\u003eIn turn, the S\u0026oslash;rensen Index calculated from the entire video record yielded a value of 0.084, which is an order of magnitude lower than the S\u0026oslash;rensen Index calculated from the transect data (spatial overlap). Using the GLMM, the indices were calculated for each season, all of which also showed very low values (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), with no significant differences observed between them (F\u0026thinsp;=\u0026thinsp;4.78; p\u0026thinsp;=\u0026thinsp;0.180).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMean values of the S\u0026oslash;rensen Index for each season, along with their 95% confidence intervals (CI).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSeason\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMean value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eCI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLower\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUpper\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,072\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWinter\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,087\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSummer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,171\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAutumn\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,075\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,140\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, a high overlap between coypus and capybaras was observed in urban habitats at both spatial and temporal scales, with segregation being evident only at the simultaneous spatio-temporal scale. This high degree of overlap may be associated with the characteristics and constraints of urban habitats, where limitations in space and available resources reduce the diversity of ecological niches (Moss et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAt the spatial scale, no clear evidence of segregation between coypus and capybaras was found across the spatial resolutions analyzed (300 m, 100 m, and 30 m), supporting the proposed hypothesis. The moderate to high overlap and the random distribution of both species suggest similar habitat use. This pattern may be linked to the homogenization of the landscape, a characteristic feature of urban habitats (McKinney \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The different neighborhoods within the urbanized area exhibit high similarity in land cover types and spatial arrangement (Iglesias \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), likely resulting in a uniform availability of resources for both species. The absence of aquatic vegetation forces coypus to feed on terrestrial vegetation in landscaped areas adjacent to water bodies, thereby sharing the same habitats that capybaras use for foraging and resting. This likely increases spatial overlap compared to natural areas or agroecosystems, where coypus primarily feed within or along the edges of water bodies (D\u0026rsquo;Adamo et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Guich\u0026oacute;n et al. 2003), while capybaras prefer higher areas along the topographic gradient (Aldana-Dom\u0026iacute;nguez et al. 2007; Corriale \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Corriale et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Previous studies in natural habitats indicate a high degree of dietary overlap between the two species, with 72% of their food items in common, primarily grasses (Espinelli et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, the key distinction lies in the greater consumption of aquatic plants by coypus (Espinelli et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; D\u0026rsquo;Adamo et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In the study area, the low diversity of grasses, both in richness and evenness, results from the widespread use of sod, specifically Bahia grass (\u003cem\u003eAxonopus compressus\u003c/em\u003e), in gardens and communal spaces. This homogeneity further increases both dietary and spatial overlap, as both species utilize the same sites for foraging.\u003c/p\u003e\u003cp\u003eAt the temporal scale, a high overlap in the annual activity pattern of capybaras and coypus was observed, as well as a moderate to high overlap in seasonal patterns, which supports the hypothesis proposed at this scale. Although both species are predominantly crepuscular in natural conditions, they exhibited moderate to high nocturnal activity in the urban environment, possibly due to the tendency of such environments to increase nocturnality in animals in an effort to minimize interactions with human activities (Gaynor et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This shift was particularly evident in the coypu, which showed predominantly nocturnal activity. Except for summer, significant differences in activity patterns suggest a differentiation in their peak activity times. In the case of capybaras, previous studies reported very similar activity patterns, though with more diurnal activity, highlighting peaks around 6:00 and 18:00 hours (Corriale \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Di Bitetti et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Corriale and Arenas \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Serra-Medeiros et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; \u0026Aacute;vila et al. in press). In the study area, it was observed that capybaras tend to be more diurnal than coypus, especially in autumn and winter, likely due to their greater sensitivity to cold temperatures (Corriale \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). \u0026Aacute;vila et al. (in press) found that on cool days, capybaras exhibited a fully diurnal activity pattern. Regarding the coypu, its activity patterns can be highly variable, ranging from crepuscular-nocturnal (Palomares et al. 1984; Mori et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) to fully diurnal (Meyer et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). A study in a similar urban setting showed a unimodal pattern, with activity concentrated between 18:00 and 00:00 hours (Salas et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), while our results indicate that coypu activity remains high from 00:00 to 06:00 hours. This difference could be due to the presence of capybaras, which might lead to a reduction in the coypu\u0026rsquo;s spatial niche, causing it to concentrate its activity in the early morning to reduce temporal overlap. It is acknowledged that the coypu is a highly plastic species, capable of adapting its temporal behavior to local environmental conditions (Mori et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAt the simultaneous space-time scale, high segregation between capybaras and coypus was observed, in accordance with Hypothesis 3. Although both species are distributed in the same areas and share similar activity patterns, they tend to avoid using the same space at the same time, minimizing direct encounters and reducing the frequency of interference interactions. This segregation could be evidence of the competitive exclusion principle, indicating that niche segregation can manifest at multiple scales, including more subtle ones. As mentioned earlier, this simultaneous space-time segregation is likely mediated by differences in the activity peaks of both species. Such fine-scale temporal segregation has been previously documented in carnivores with high spatial and temporal overlap (Hayward and Slotow \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Gerber et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Farris et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Cronk and Pillay \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), though it has been less studied in herbivores. Furthermore, our results highlight that simultaneous space-time overlap does not necessarily reflect the overlap observed at the spatial or temporal scale separately (Karanth et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Cronk and Pillay \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This apparent avoidance of direct encounters is supported by the negative association observed between the intensity of habitat use by capybaras and that by coypus during autumn. This dynamic suggests possible interference competition under conditions of low resource availability, where direct or indirect interactions between the two species could limit the coypu\u0026rsquo;s access to available resources.\u003c/p\u003e\u003cp\u003eOur results showed a higher tolerance by coypus and capybaras to share space during the warmer seasons, which contradicts our Hypothesis 4. This pattern may be related to seasonal differences in forage availability. When resources are limited, competition appears to play a stronger role, leading to spatial and temporal segregation between the species. Conversely, during periods of greater resource abundance, food does not seem to be a limiting factor, allowing for increased spatial overlap. Such competition can result in reduced intake rates for the affected species (Goss-Custard \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1980\u003c/span\u003e) and may drive them to use habitats with lower-quality resources or to adjust their activity periods to minimize competitive interactions. A study on a community of herbivores in Africa demonstrated that subordinate species altered their temporal niche to avoid interference competition with the dominant species (the elephant), particularly during the dry season when resources were scarce (Valeix et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). A similar dynamic could be occurring between capybaras, as the dominant species, and coypus, aligning with the patterns observed in our study.\u003c/p\u003e\u003cp\u003eCompetition between species can have significant effects, not only by promoting niche segregation but also by leading to the dispersal of subordinate species or a decrease in their abundance (Amarasekare \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e, Mori et al. 2022). In the study area, since 2017, a notable increase and expansion in the capybara population has been observed, accompanied by a decrease in the coypu population (Corriale et al. 2019; Abdenur Araoz et al. 2025). Although the relationship between these trends has not been thoroughly investigated nor has a clear causal link been established, studies in similar contexts have shown that larger species tend to displace smaller species with which they share ecological niches. In the United Kingdom, the expansion of the otter (\u003cem\u003eLutra lutra\u003c/em\u003e) has displaced the American mink (\u003cem\u003eNeovison vison\u003c/em\u003e), significantly reducing its local densities (Bonesi and Macdonald \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Bonesi et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Similarly, in northeastern Italy, populations of the Eurasian red squirrel (\u003cem\u003eSciurus vulgaris\u003c/em\u003e) have displaced those of the Siberian striped squirrel (\u003cem\u003eEutamias sibiricus\u003c/em\u003e), resulting in a decrease in its local density (Mori et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, it should not be discounted that both populations may not yet have reached the carrying capacity and resource limitations of the habitat, and therefore, the pressure on these closely related rodent species to acquire interspecific differentiation may still be too weak, allowing for their coexistence even in the presence of broad niche overlap (Tobias et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, high-disturbance regimes, such as urban areas, tend to allow the coexistence of generalists with overlapping niches (Moi et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This underscores the need to analyze in greater detail the interactions between capybaras and coypus, as well as the ecological and social factors that may be shaping the dynamics observed in the study area. A more thorough approach to these interactions will help better understand the underlying mechanisms and develop effective management strategies for both species.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflict of interest statement\u003c/h2\u003e\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eEthics declaration\u003c/h2\u003e\u003cp\u003eNot applicable. This study was based on non-invasive observational methods.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e\u003cp\u003eConceptualization: M.J. Corriale; Methodology: M.J. Corriale; Formal analysis and investigation: F. Bottelli and M.J. Corriale; Writing \u0026ndash; original draft: F. Bottelli; Writing \u0026ndash; review and editing: M.J. Corriale; Funding acquisition: M.J. Corriale; Resources: M.J. Corriale; Supervision: M.J. Corriale.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThis study was supported by the Agencia Nacional de Promoci\u0026oacute;n Cient\u0026iacute;fica y T\u0026eacute;cnica (PICT FONCyT 2019\u0026thinsp;\u0026minus;\u0026thinsp;0983), the COMFAUNA Fellowship Fund \u0026ndash; Gordon and Betty Moore Foundation, and Fundaci\u0026oacute;n Natura, Colombia. We are grateful to the Nordelta Neighborhood Association, Lic. Morena Peltzer, and Lic. Florencia Abdenur Araos for their invaluable assistance and contributions to the development of this work.\u003c/p\u003e\u003ch2\u003eData availability statement\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed during the current study are available from the corresponding author upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdenur Araos F, Cavia R, Corriale MJ (2025) Between walls and wilds: \u003cem\u003eMyocastor coypus\u003c/em\u003e Molina, 1782 abundance and occurrence in gated and open communities in Buenos Aires, Argentina. Urban Ecosyst 28, 3. https://doi.org/10.1007/s11252-024-01661-8\u003c/li\u003e\n\u003cli\u003eAldana-Dominguez J, Vieira-Mu\u0026ntilde;oz MI, Angel-Escobar DC (2007) Estudios sobre la ecolog\u0026iacute;a del chig\u0026uuml;iro (\u003cem\u003eHydrochoerus hydrochaeris\u003c/em\u003e), enfocados a su manejo y uso sostenible en Colombia. Instituto Alexander von Humboldt. 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Springer Science \u0026amp; Business Media.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"mammalian-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mamb","sideBox":"Learn more about [Mammalian Biology](https://link.springer.com/journal/42991)","snPcode":"42991","submissionUrl":"https://www.editorialmanager.com/mamb/default2.aspx","title":"Mammalian Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Myocastor coypus, Hydrochoerus hydrochaeris, gated communities, urban ecology, coexistence","lastPublishedDoi":"10.21203/rs.3.rs-8020266/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8020266/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTwo competing species can coexist over time if they segregate along at least one key dimension of their ecological niche: space, time, or resources. Urban habitats influence these processes by homogenizing landscapes, reducing available niche space, and inducing behavioral adjustments that alter animals\u0026rsquo; temporal activity, thereby affecting their capacity for segregation. In such contexts, coexistence may depend on subtle adaptations that minimize resource competition. This study examines spatio-temporal overlap between coypus (\u003cem\u003eMyocastor coypus\u003c/em\u003e) and capybaras (\u003cem\u003eHydrochoerus hydrochaeris\u003c/em\u003e) inhabiting gated communities in the Metropolitan Area of Buenos Aires, Argentina. Our objectives were to: (1) assess spatial overlap and co-occurrence; (2) analyze overlap in daily activity patterns and their seasonal variation; and (3) evaluate simultaneous spatio-temporal co-occurrence and its seasonal dynamics. Results revealed a high degree of spatial and temporal overlap between coypus and capybaras, with both species showing greater tolerance to share space during warmer seasons, when food resources are more abundant. However, segregation emerged at the simultaneous spatio-temporal scale, mediated by differences in peak activity periods and likely related to mechanisms of direct encounter avoidance. This fine-scale segregation is consistent with the competitive exclusion principle and suggests that interference competition may occur when resources are limited, particularly in colder seasons. These findings highlight how urbanization constrains niche availability and promotes coexistence through behavioral and temporal adjustments, while also showing that interactions between both species may vary according to resource availability and seasonal conditions.\u003c/p\u003e","manuscriptTitle":"Assessing interactions between coypus and capybaras in urban habitats: spatial and temporal overlap","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-24 19:02:18","doi":"10.21203/rs.3.rs-8020266/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-11-13T13:14:25+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-13T11:54:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-05T04:10:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Mammalian Biology","date":"2025-11-03T09:34:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"mammalian-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mamb","sideBox":"Learn more about [Mammalian Biology](https://link.springer.com/journal/42991)","snPcode":"42991","submissionUrl":"https://www.editorialmanager.com/mamb/default2.aspx","title":"Mammalian Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7b2e4288-1169-44d3-9799-46cb70477516","owner":[],"postedDate":"November 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T15:50:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-24 19:02:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8020266","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8020266","identity":"rs-8020266","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}