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The transformation of natural ecosystems caused by human activities has considerably reduced the extent of functional habitats for large carnivores worldwide. Deforestation in tropical regions fragments the landscape and forces felids to adapt to smaller territories, thereby altering their spatial use patterns (Anderson et al. 2024). From an ecological perspective, wild felids, as they occupy upper trophic levels, require extensive, continuous areas to maintain their regulatory role in the ecosystem, making them sensitive indicators of habitat degradation (Sunquist et al. 2014). Moreover, although some species may exhibit similar body sizes, they do not necessarily share the same trophic niche. Coexistence in the same space and time is only possible when resources are diverse and abundant, or when niche partitioning occurs, whether in terms of diet, space, or time, which reduces competition (Ruiz-Gutiérrez et al. 2023). Even in protected areas, human presence continues to exert pressure on the spatial occupation of these predators, affecting their distribution and behavior (Poulain et al. 2023).

In this context, camera traps emerge as a fundamental tool for studying and monitoring cryptic predators, such as wild felids. These cameras are particularly valuable alternatives in contexts where direct observation is difficult, either because animals are elusive or because understory vegetation is dense (Burton et al. 2015). They also make it possible to record, without direct interference, presence, behavior, individual traits, and demographic variation, including patterns of hourly activity, key aspects for understanding the response and adaptation of mammals to anthropogenic change (Jiménez et al. 2010; Allen and Allan 2024).

In the Cordillera Escalera Regional Conservation Area San Martín, Perú, for example, nocturnal records have been obtained of Panthera onca (Linnaeus 1758), the largest felid in the Americas and the main apex predator of the Neotropics (Saucedo-Bazalar et al. 2023). Similarly, Castagnino Vera (2017) used camera traps in the Peruvian Amazon to study the ecology of the Leopardus tigrinus (Schreber 1775), demonstrating their effectiveness for identifying individuals, estimating population density, and analyzing habitat use in tropical environments. Likewise, Mena et al. (2020) used spatial capture–recapture models with camera traps to estimate densities of P. onca and other vertebrates in fragmented Amazonian landscapes, confirming the value of this methodology for generating robust data to support conservation strategies.

In Perú, Parque Nacional Tingo María (PNTM) stands out as an area of high biological value in the Huánuco region, recognized for its remarkable biodiversity and for the increasing fragmentation of its natural habitats in the surrounding matrix (Puerta and Iannacone 2023; Zuloaga-Obregón and Gabriel-Campos 2023). This area harbors a diverse community of mammals, both prey and predators, that persists in a relatively pristine core despite the anthropogenic pressures recorded in its immediate surroundings (Cossios and Zevallos 2019; Briceño et al. 2025). According to Clavijo and Ramírez (2009), the ecological complexity of PNTM and its environmental variability favor the presence of different species along altitudinal gradients. However, systematic studies on felids in this area have been scarce and punctual. Although the presence of several felid species has been confirmed across different sectors of the park, there is still no integrated evidence to explain their ecological interactions, distribution patterns, or spatial use. In this context, Ruiz-Gutiérrez et al. (2023) highlight the need to strengthen the scientific basis for decision-making in the conservation and sustainable management of wildlife, especially for felids, which, as apex predators, serve as key indicators of ecosystem health.

Therefore, the present study aims to report the coexis-tence of four wild felid species, Herpailurus yagouaroundi (É. Geoffroy Saint-Hilaire, 1803), L. tigrinus, P. onca, and Puma concolor (Linnaeus 1771), in a habitat of reduced extent, such as PNTM, using camera-trap records. Specifically, it proposes to (i) determine the location and frequency of felid records in the park and (ii) analyze the hourly activity patterns of the recorded species. The results provide ecological information that enables the interpretation of coexistence mechanisms, particularly temporal segregation and spatial use. Likewise, this study seeks to contribute to the design of management and conservation strategies grounded in scientific evidence, strengthening the protection of felids and their habitats, and providing technical inputs for the sustainable management of PNTM and the conservation of biodiversity in Andean–Amazonian ecosystems.

Materials and Methods

Study area. The study was carried out in PNTM, located approximately between 9°19'48" S and 9°09'36" S latitude, and 76°03'36" W and 75°58'12" W longitude (equivalent to the UTM coordinates 382000–392000 m E and 8952000–8970000 m N, zone 18S), the administration of the Servicio Nacional de Áreas Naturales Protegidas por el Estado (SERNANP 2022), in the province of Leoncio Prado, Huánuco region, Perú (Figure 1). The park covers approximately 4,777 hectares and is part of the Premontane Humid Forest of the Peruvian Yungas. It is not formally declared as part of a biological corridor, but it is not completely isolated either, which constitutes partial functional connectivity for large species from an ecological perspective. The area lies between 750 and 1,748 m a.s.l. and has a warm and humid climate, with average temperatures between 22 °C and 29 °C and annual precipitation greater than 3,000 mm, conditions typical of the humid montane forests of the central sector of the Peruvian Amazon, where the dense vegetation cover favors the presence of carnivorous mammals with cryptic habits such as felids.

Felid data source within PNTM. Wildlife monitoring was conducted using 19 Browning camera traps (Recon Force Edge model, BTC-7E) strategically installed across the PNTM from January to December 2024. With the support of park ranger staff, accessible sectors showing evidence of wildlife movement were identified, and monitoring points were selected in accordance with the recommendations of the Peruvian Ministry of the Environment (MINAM 2015). The cameras were distributed along transects, separated by a minimum distance of 250 m to ensure spatial independence among sampling stations and reduce the probability of recording the same individuals at nearby cameras. Their placement prioritized trails, water sources, and areas frequently used by wildlife. During installation, the geographic coordinates of each station were recorded using high-precision GPS receivers. The devices, equipped with passive infrared (PIR) motion sensors, an integrated digital thermometer, a color screen for field configuration, and an invisible infrared flash system, can capture images of up to 20 megapixels and record high-definition videos (1080p) with sound, while also storing metadata such as date, time, and approximate temperature at the moment of capture (Browning 2018).

Each camera was installed at an average height of 60 cm above ground and oriented toward trails or common crossing areas used by felids, a configuration considered one of the most effective methods for estimating species presence. Each unit was programmed to capture a burst of three photographs followed by a 20-second video, with a 30-minute interval before reactivation to avoid the overrepresentation of the same individuals. The system operated continuously throughout the study period, and periodic inspections (approximately every two months) were conducted to check battery status and memory cards, ensuring uninterrupted operation of the equipment.

Data processing. The information obtained from photographs and videos recorded by the camera traps was carefully reviewed, organized, and filtered to ensure its quality and consistency before analysis. All records not directly attributable to the presence of felids were excluded. Likewise, indirect evidence, such as the presence of prey or other indicators of their occurrence, was not considered; only images and videos in which individuals of the target felid species were clearly observed were included. Before conducting any analysis, it was ensured that the field-collected information was reliable and accurate for the evaluated area. Photographic and video records were interpreted, recorded, and classified in Microsoft Excel (version 2602, Microsoft 365) by species. Each record was associated with the date, time, and geographic location recorded by each camera. Events were considered inde-pendent when a different individual appeared in front of the camera or when they were separated by intervals of more than 30 minutes, as determined by the camera’s technical configuration, for both photographs and videos. (Karanth and Nichols 1998; Zhao et al. 2020). For spatial representation, QGIS v.3.34.9 was used; for the generated information, the geographic coordinate system with the WGS 84 datum in UTM zone 18 was used.

Data analysis. Since the study is exploratory and descriptive, simple analyses were employed. Once the database was consolidated, field sightings were quantified by species to determine frequency of occurrence and abundance in the study area. The time intervals analyzed record frequencies in months and by schedule, allowing classification of species according to their activity habits (diurnal, nocturnal, or hourly and monthly). The organization of the data also enabled observation of the frequency of sightings at the spatial level (map) based on recorded coordinates.

To evaluate whether the sampling effort was sufficient to characterize felid richness, a rarefaction analysis of species richness was conducted using camera-trap records. An abundance matrix was constructed with the total number of independent records per felid species, considering camera-days as the unit of effort. Using this matrix, the sample-size–based rarefaction curve was estimated with iNEXT Online version 3.0.2, which implements diversity and sample-coverage estimators for abundance data (Chao et al. 2014; 2016). The curve was generated for the diversity order q = 0 (species richness). It included 95% confidence intervals, and the sampling effort was considered to reach the asymptote when the expected richness approached a constant value and the confidence intervals no longer overlapped with lower richness values, that is, when the addition of new camera-days did not produce appreciable increases in the expected number of felid species in the study area. In addition, a sample coverage index greater than 0.95 was considered sufficient to justify and complement the sampling effort.

Results

The 19 cameras installed in the PNTM recorded 2,681 images and videos of various mammals, totaling 5,861 camera-days total sampling effort, for a capture rate of 45.7 records per 100 camera-days. Of these, 14 out of the 19 cameras detected four felid species, with 17 records of H. yagouaroundi, 12 of L. tigrinus, 12 of P. onca, and 11 of P. concolor, for a total of 52 independent records; examples of some captures of the four felid species are shown in Figure 2. For more details, see Table 1, which presents all records of felid consolidations, detailing for each event the corresponding camera, date, number of individuals observed, and the UTM coordinates of the detection point, information that serves as the basis for the ecological and comparative analyses developed in this study.

A rapid increase in the number of felid species detected is observed as the number of camera-days increases (Figure 3), with a pronounced rise from 1 to approximately 4 species in the first 12 camera-days (sample coverage index = 0.97). From that threshold onward, the curve approaches an asymptote near 4 species. It remains practically stable up to the maximum sampling effort (52 camera-days), while the 95% confidence band (gray-shaded area) narrows progressively, indicating a decrease in uncertainty in the richness estimate. This stabilization of the curve suggests that the sampling effort employed was sufficient to record most, or possibly all, of the felid species present in the study area and that a further increase in effort would have a very low probability of adding new felid species to the inventory.

Figure 4 shows the spatial distribution of records of H. yagouaroundi, L. tigrinus, P. onca, and P. concolor in PNTM, where the size of the circles indicates the number of sightings per sampling station. In H. yagouaroundi and L. tigrinus, a higher concentration of records is observed in the northern and central sectors of the park, with several points showing multiple sightings, suggesting areas of preferential use and a broader spatial distribution. Despite this broad distribution, both species overlap at a few stations (at four common points), suggesting a degree of fine-scale spatial segregation.

By contrast, the records of P. onca and P. concolor are fewer and appear more dispersed, a pattern that may be related to more solitary habits, lower population densities, or a wider use of space within the study area. Nevertheless, both species show a core of records in the central part of the park and, in the case of P. onca, an additional sighting was documented in the northern sector, near the Cueva de las Lechuzas, where visitor presence and human activity are significant.

Activity pattern. In H. yagouaroundi (Figure 5A–B), the records were concentrated mainly in February, May, and November, with peaks of up to three events in cameras 14, 12, 18, 8, 13, and 5. Activity was markedly diurnal, with the highest number of sightings between 10:00 and 16:00 h, where two to six events were recorded, indicating a clear preference for daylight hours. In L. tigrinus (Figure 5C–D), maximum records were observed in February and April, with up to three events in cameras 1, 6, and 3. Its activity was predominantly nocturnal, with a higher frequency of sightings between 22:00 and 02:00 h, indicating a strong preference for hours of darkness. For P. onca (Figure 5E–F), records were concentrated in September (four events) and in August, October, and November (two records in each month), mainly in cameras 1, 9, and 5. Activity was distributed both at night and during the day, with peaks between 04:00 and 09:00 h (one to two records) and between 18:00 and 00:00 h (one record), without showing a clearly defined hourly pattern in the context of this study. In P. concolor (Figure 5G–H), the highest number of records occurred in January, with four events in cameras 7, 13, and 12. Its activity was spread throughout the day and night, with one peak between 01:00 and 06:00 h (two records) and another between 18:00 and 19:00 h (one and two records, respectively), reflecting a mixed activity pattern that could be related to variation in environmental conditions and prey availability.

Discussion

Our results partially agree with those reported by Cossios and Zeballos (2019) for the same park, who, with a sampling effort of 2,940 camera-days over four years of monitoring, recorded 26 events of P. concolor, 7 of H. yagouaroundi, and 1 of L. tigrinus. Taken together, both studies indicate low detectability of felids, consistent with their cryptic behavior and low population densities. Nevertheless, our study, which focused on documenting the coexistence of these species, provides important contributions. We recorded the presence of P. onca, a species previously unreported, expanding current knowledge of the felid community in PNTM. In addition, our work involved a more intensive sampling effort over a shorter period: we conducted simultaneous monitoring for one year by deploying 19 active camera traps, accumulating a large number of camera-days compared with the previous study, which was conducted over four years. Similarly, Cossios et al. (2022) reported only four Leopardus pardalis events in the Allpahuayo Mishana National Reserve, reaffirming the low detectability of felids and their generally low population densities in Amazonian ecosystems. This low recording rate has also been documented by Ruiz-Gutiérrez et al. (2023) in the Sierra Madre del Sur, Mexico, where 362 detections of three felids are interpreted as evidence of coexistence mediated by spatial and temporal overlap rather than high abundance. Likewise, Behnke (2015) showed in the lowland Peruvian Amazon that an effort of 2,614 camera-days generated 108,558 photographs of mammals but with very few captures of large felids, suggesting that prolonged efforts are required to detect apex predators and that the low numbers of records reflect reduced densities and extensive home ranges rather than actual absence.

Our results concerning monthly and hourly activity patterns agree with Cossios and Zevallos (2019) in PNTM, where H. yagouaroundi was exclusively diurnal, and L. tigrinus was completely nocturnal, which supports the predominant diurnality and nocturnality observed in this study, as well as P. concolor, which showed 30.77% of diurnal records and 53.85% nocturnal. Contrary to what Mosquera-Guerra et al. (2018) reported, L. tigrinus in the forests of the Bita River (Colombia) exhibits a cathemeral pattern, suggesting some flexibility in its activity. In general, variations among diurnal, nocturnal, and cathemeral habits are usually associated with temperature, humidity, prey availability, and the need to avoid predators or competitors. In the Allpahuayo Mishana Reserve, Cossios et al. (2022) pointed out that hunting and tourism can reduce diurnal activity and shift it toward nighttime hours with lower human presence, so the nocturnality of L. tigrinus and the mixed patterns of P. concolor and P. onca in PNTM could be interpreted as behavioral adjustments to coincide with their prey and minimize contact with people.

The spatial distribution of records of H. yagouaroundi and L. tigrinus is concentrated mainly in the northern and central sectors of PNTM, although with relatively wide dispersion among sampling stations. In contrast, records of P. onca and P. concolor are less frequent and occur in more restricted areas, suggesting lower-density populations or a more limited use of space. This distribution may be related to food availability. In the northern and western sectors of the park, the presence of this felid species appears to be associated with greater prey availability, both domestic (such as chickens) and wild, which constitute its food base. This situation is particularly relevant in areas occupied by users within the Buffer Zone and the Special Use Zone of the protected area (Anderson et al. 2024; Briceño et al. 2025).

The simultaneous presence of these four species in a relatively small, protected area can be explained by the fact that PNTM acts as one of the few remaining minimally disturbed habitats within a matrix heavily transformed by agriculture, deforestation, urbanization, and hunting, processes documented for the area (Guillén and Reátegui 2014; Puerta and Iannacone 2023). These anthropogenic pressures reduce and fragment the available range, “cornering” felid populations and limiting the availability of safe sites to obtain food, water, and shelter. This scenario has direct implications for both the conservation of apex predators and for wildlife that finds the park one of the few remaining refuges in the landscape (Massara et al. 2015).

In addition, the presence of P. concolor in the PNTM, a species widely distributed from the Andes to the Amazon, suggests functional ecological connectivity between surrounding montane forests and adjacent forested landscapes. A similar interpretation may apply to P. onca, whose occasional records suggest that the park may be part of a broader movement network rather than a fully isolated habitat. Given the extensive spatial requirements of both large felids, it is likely that individuals move through the park while maintaining connections with surrounding forest remnants and buffer zones (Arias-Alzate et al. 2022). However, the present study was not designed to estimate population densities or to identify specific corridors, so the degree of connectivity and the size of the populations using the area remain subjects for future research.

The results of this study are relevant to the conservation and management of felids in PNTM because they provide important information on species presence and the sites with the highest activity levels. These data can be incorporated directly into the design of monitoring programs, allowing prioritization of camera placement at stations with concentrated records and focusing effort on areas with a higher probability of detection. In this regard, what was stated by Mosquera-Guerra et al. (2018) is relevant, as the information generated through camera traps on activity patterns and spatial distribution of medium- and large-sized mammals constitutes a fundamental input for management planning.

The 52 independent records obtained from 14 monitoring stations confirm the active use of the area by the four species evaluated. A limitation of the study is that no specific individual-identification design was implemented, nor were photographic capture–recapture models applied, which prevents robust estimation of population size or the minimum number of individuals. However, the confirmed evidence of presence, together with information on spatial distribution and observed temporal segregation, provides a strategic baseline to guide zoning processes, threat control, and long-term monitoring programs in the PNTM and in other protected natural areas with similar characteristics.

Nevertheless, the work has limitations that must be considered when interpreting the results: the number of records is relatively low (52 events across 14 cameras), which limits more detailed analyses of diversity, such as overlap in activity or differential habitat use among species. In addition, prey availability and the intensity of human activities at each station were not specifically quantified, so their influence on distribution and activity schedules can only be inferred in general terms. Finally, as in any study based on camera traps, the records reflect the use of the sampled points and not the entire movement range of the felids; therefore, the described patterns should be interpreted with caution and considered an initial approximation of the coexistence of these species in the PNTM. In this regard, future studies could strengthen these results by designing surveys specifically to estimate occupancy, incorporating standardized temporal replicates, increasing station density, and using hierarchical models that allow estimation of detection probability and actual site use. This approach would enable more robust inferences about spatial dynamics and population persistence within the protected area.

Conclusions

This study documents the coexistence of four felid species (H. yagouaroundi, L. tigrinus, P. onca, and P. concolor) within the relatively small area of PNTM, supported by 52 independent camera-trap records obtained over 5,861 camera-days. The stabilization of the rarefaction curve and the high sample coverage index (0.97) further indicate that the sampling was sufficient to characterize the local felid community. Clear temporal segregation was observed among species: H. yagouaroundi was predominantly diurnal, L. tigrinus mainly nocturnal, and P. onca and P. concolor exhibited cathemeral activity. This pattern suggests that temporal niche partitioning is a key mechanism facilitating their coexistence. Considering the wide movement ranges of large felids, particularly P. onca and P. concolor, PNTM likely functions not only as a local refuge but also as part of a network of connected habitats that supports movement between buffer zones and surrounding fragmented landscapes. In this context, the park may serve as a resident habitat for smaller felids while acting as a functional corridor or use area for larger carnivores within Andean–Amazonian landscapes.

From a management perspective, the results provide strategic information on the sectors of the PNTM where greater felid activity was recorded and on the periods of the day in which each species shows a higher probability of detection. It is recommended to prioritize installing camera traps in microhabitats, along movement routes, and in sectors of the park where the probability of recording is higher, and to adjust inspection, maintenance, and repositioning of the equipment to the periods of greater species activity. Likewise, it is recommended to expand the sampling effort by increasing the number of stations and extending the temporal series, and to incorporate complementary variables such as prey abundance, human pressure, and microclimate. The integration of these factors, along with the use of occupancy and density models, would allow more precise estimates of space use and a better understanding of how these populations respond to processes such as agricultural expansion, hunting, and other threats in the surrounding landscape.

Acknowledgments

The authors express their gratitude to the Vice-Rectorate for Research of the Universidad de Huánuco for logistical support for the project “Efecto del cambio de uso del suelo en la distribución potencial de especies de mamíferos en el Área de Conservación Regional (ACR) Bosque Montano de Carpish”. We also express our gratitude to the staff of the Servicio Nacional de Áreas Naturales Protegidas por el Estado (SERNANP), especially park ranger Alex Ricra, for their support and for the facilities provided for access and fieldwork in PNTM.

Declaration of artificial intelligence use

During the preparation of this manuscript, the authors used Perplexity AI (Grok 4.1) and GPT-5.3 solely to improve the grammar, style, the logical cohesion and translation of the text. These tools were not employed for data generation, statistical analysis, the creation of figures or tables, or the scientific interpretation of the results. The authors critically reviewed and edited the AI-assisted content and hold full responsibility for the integrity, originality, and conclusions presented in this work.

Author contributions

Deyvis Cano: Conceptualization, methodology, research supervision, data analysis and interpretation, visualization, and writing - original draft, review and editing. Frank Cámara: Data collection (fieldwork), data analysis and interpretation, and writing - review and editing. Niler Chahua-García: Data analysis and interpretation, visualization, and writing- review and editing. Jhendy Inga: Visualization and writing -review and editing. Homer Sandoval: Methodology, data collection (fieldwork), visualization, and writing - review and editing.

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Associated editor: Miguel Ángel León Tapia

Submitted: January 20, 2026; Reviewed: February 17, 2026

Accepted: March 11, 2026; Published online: March 23, 2026

Table 1. Geographic records of the four felid species in PNTM, Perú.

Scientific name	UTM coordinates – Zone 18S		No. /Camera	Date	Recording time (24h format)
Scientific name	X	Y	No. /Camera	Date	Recording time (24h format)
Herpailurus yagouaroundi	386677	8965312	Camera 18	15/5/2024	13:30
	386677	8965312	Camera 18	22/5/2024	12:50
	386745	8968617	Camera 5	24/10/2024	16:30
	386745	8968617	Camera 5	8/11/2024	07:32
	386902	8966488	Camera 16	11/8/2024	14:47
	386902	8966488	Camera 16	1/9/2024	16:30
	386902	8966488	Camera 16	23/10/2024	11:07
	386902	8966488	Camera 16	19/12/2024	07:40
	388732	8963046	Camera 8	20/5/2024	11:30
	388732	8963046	Camera 8	11/7/2024	15:48
	388956	8963374	Camera 9	28/3/2024	16:39
	389408	8965396	Camera 12	25/2/2024	18:35
	389482	8965996	Camera 13	8/11/2024	10:02
	389482	8965996	Camera 13	12/11/2024	16:26
	389507	8966190	Camera 14	2/2/2024	16:05
	389507	8966190	Camera 14	9/2/2024	15:34
	390020	8967352	Camera 3	22/4/2024	16:18
Leopardus tigrinus	386745	8968617	Camera 5	23/8/2024	22:23
	386902	8966488	Camera 16	10/6/2024	18:02
	386902	8966488	Camera 16	27/9/2024	23:39
	388073	8963584	Camera 19	21/3/2024	22:40
	388732	8963046	Camera 1	10/1/2024	02:01
	388732	8963046	Camera 1	19/2/2024	03:31
	388732	8963046	Camera 8	31/5/2024	20:04
	389172	8962080	Camera 6	24/2/2024	00:33
	389172	8962080	Camera 6	25/2/2024	00:21
	389172	8962080	Camera 6	16/4/2024	00:54
	389172	8962080	Camera 6	23/4/2024	22:13
	390020	8967352	Camera 3	14/4/2024	23:25
Panthera onca	386745	8968617	Camera 5	23/8/2024	22:23
	386745	8968617	Camera 5	4/10/2024	04:07
	386745	8968617	Camera 5	12/10/2024	06:16
	386745	8968617	Camera 5	6/11/2024	07:26
	386745	8968617	Camera 5	24/11/2024	12:24
	388732	8963046	Camera 1	29/8/2024	12:32
	388732	8963046	Camera 8	7/5/2024	18:20
	388956	8963374	Camera 9	1/9/2024	00:32
	388956	8963374	Camera 9	1/9/2024	05:25
	388956	8963374	Camera 9	1/9/2024	07:07
	388956	8963374	Camera 9	2/9/2024	15:25
	389162	8962544	Camera 7	30/1/2024	09:05
Puma concolor	386902	8966488	Camera 16	22/12/202	22:02
	388956	8963374	Camera 9	22/8/2024	19:49
	388956	8963374	Camera 9	22/11/2024	12:12
	389162	8962544	Camera 7	29/1/2024	06:45
	389162	8962544	Camera 7	29/1/2024	18:45
Puma concolor	389408	8965396	Camera 12	17/1/2024	07:21
	389482	8965996	Camera 13	17/1/2024	06:53
	389482	8965996	Camera 13	30/3/2024	04:00
	389482	8965996	Camera 13	22/9/2024	01:28
	390020	8967352	Camera 3	29/5/2024	03:16
	390027	8967372	Camera 2	6/6/2024	19:50