Research Paper

INTRODUCTION

Understanding the causes of avian population decline in tropical forests is of crucial importance for conservation (Robinson and Sherry 2012, Tobias et al. 2013). Indeed, a large part of avian diversity, including the most threatened bird species, occurs in this highly vulnerable ecosystem (Sodhi et al. 2011). The decline of tropical forest bird species has been associated with various drivers, such as habitat loss and fragmentation (Feeley and Terborgh 2008, Korfanta et al. 2012), invasive species (Harper and Bunbury 2015, Doherty et al. 2016, Thibault et al. 2018), hunting pressure (Sreekar et al. 2015, Benítez-López et al. 2017), and climate change (Şekercioğlu et al. 2012). However, the relative importance of such drivers and of their interactions may differ between mainland and island species (Doherty et al. 2016), and in relation to diet composition (Curtis et al. 2021).

One avian group of particular concern are tropical, omnivorous ground-dwelling species living on islands, mainly because of their restricted range, habitat loss, high vulnerability to introduced mammal predators, and declining insect populations (Şekercioğlu et al. 2002, Lamarre et al. 2020, Sherry 2021). Many tropical ground-dwelling bird species tend to have omnivorous and generalist food habits, with seasonal variation in their use of fruits, seeds, invertebrates (Herrera et al. 2006, Riehl and Adelson 2008) and, occasionally for some species, small vertebrates (Sandoval et al. 2008). However, avian omnivory is associated with higher extinction rates compared to other specialist diets, possibly constituting a macroevolutionary sink (Burin et al. 2016). In addition, unlike tropical ground-dwelling species living on the mainland (González-Castro et al. 2012), insular ones have limited possibilities to expand their home range in response to reduced food availability, particularly during the dry season (Williams and Middleton 2008). Ground-dwelling bird species living on tropical islands are also particularly vulnerable to predation on nests, juveniles, and adults by various introduced exotic mammals, such as rats, Rattus spp. (Duron et al. 2017b, 2017a), domestic cats, Felis catus (Hervías et al. 2014, Medina et al. 2014, Sreekar et al. 2015, Loss et al. 2022) and the small Indian mongoose, Urva auropunctata (Lewis et al. 2011, Morley and Winder 2013, Berentsen et al. 2020). However, although trade-offs between predation risk and access to food resources can shape habitat use by landbirds (McCabe and Olsen 2015, Johnston‐González and Abril 2019), little is known about their joint influence on the spatial distribution and abundance of ground-dwelling tropical bird species.

We investigated the extent to which spatial variation in the abundance of the Caribbean-endemic Forest Thrush (FT), Turdus lherminieri (Collar 2020) in Guadeloupe, French West Indies, can be explained by habitat type and variation in both food availability and risk of encounter with mammalian predators, with a focus on the small Indian mongoose. This species was introduced in Guadeloupe, and elsewhere in the West Indies, in the late 19th century mainly to control rodent populations in sugar cane plantations (Lorvelec et al. 2021). However, this introduction did not have the desired effect, as mongooses are diurnal and rodents nocturnal. Instead, the small Indian mongoose has become a ferocious predator of many small terrestrial vertebrates in the West Indies (Nellis and Everard 1983, Hays and Conant 2007).

Forest Thrush is listed as Near Threatened (BirdLife International 2019) as its distribution is restricted to the forested habitats of only four islands in the Lesser Antilles, where it is threatened by habitat destruction and fragmentation, exotic invasive species, and hunting pressure (Arnoux et al. 2014, Collar 2020). The species prefers mature mesic forest with a dense canopy and is thought to feed mainly on the ground, on invertebrates and fallen berries collected in the leaf-litter (Raffaele et al. 1998, Parashuram et al. 2015). The breeding season extends from February to August (Benito-Espinal and Hautcastel 2003, Raffaele et al. 2003), although detailed local studies of the Forest Thrush’s breeding phenology are lacking.

A recent study (Jean-Pierre et al. 2023) found that FT was relatively abundant in Guadeloupe with, however, some spatial variation according to forest type, canopy openness, and temperature. We went further by assessing the relative influence of forest type, invertebrate prey availability, and abundance of potential diurnal mammalian predators on spatial variation in FT abundance. We relied on camera traps to assess the abundance of both FT and mammal predators at different stations located in three different forested habitats in Guadeloupe, French West Indies. Because known variation in biotic conditions and vegetation structure within forest types in Guadeloupe (Imbert et al. 1996, 2000, Loranger et al. 2002) may affect habitat selection by FT (Parashuram et al. 2015), we characterized each camera-trap site based on temperature, canopy openness, leaf litter biomass, and mongoose abundance. In addition, we assessed prey availability (both biomass and abundance) by sampling the leaf litter invertebrate community at each sampling site. We conducted our study during the dry season, at which time reduced resource availability may have a larger influence on foraging decisions and spatial distribution of ground-dwelling birds (Tanaka and Tanaka 1982, Williams and Middleton 2008, Gumede et al. 2022).

METHODS

Study area

Our study was conducted in Guadeloupe, an archipelago composed of several islands in the central Lesser Antilles arc. We focused on Basse-Terre and Grande-Terre, the two main islands of the Guadeloupe archipelago, located between the Caribbean Sea and the Atlantic Ocean (16°15′N, 61°35′W). These islands are separated by a narrow strait (Rivière Salée) connected by land bridges (Fig. 1). Although the western island of Basse-Terre is mainly mountainous, with a maximum height of 1467 m (Gadalia et al. 1988), the eastern island of Grande-Terre consists of limestone formation, with a maximum height of 177m (Lasserre 1961). Variation in elevation, rainfall, and temperature result in distinct vegetal formations linked to the bioclimatic sectors (Murphy and Lugo 1986, Myers et al. 2000), mainly including tropical rainforest (TRF), tropical dry forest (TDF), and tropical swamp forest (TSF; Rousteau 1996). TRF is characterized by a rainy and cold climate due to the higher elevation of the southern half of Basse-Terre (Grubb 1971, Van Laere et al. 2016). More precisely, TRF experiences high annual rainfall coupled with low temperatures (NASA Earth Observatory 2023), whereas TDF is subject to a 5-month period of pronounced drought with high temperatures (Holdridge 1967, Bullock et al. 1995). TSF is intermediate in rainfall regime and temperature, and is characterized by the accumulation of partially decayed organic matter at low altitudes (Posa et al. 2011). Canopy openness tends to be higher in TDF than in TRF or TSF on the island of Guadeloupe. Indeed, TDF mainly consists of small trees with poorly developed foliage and little overlap, resulting in open canopy. In contrast, in TRF and, to a lesser extent, in TSF, trees generally have larger leaves and reach higher heights because of competition for light (Carvalho et al. 2021).

Data collection

Based on prior information (Jean-Pierre et al. 2023), we collected data on FT abundance and that of potential predators (diurnal exotic mammals) at 12 different stations (i.e., 6 TRF stations, 3 TDF stations, and 3 TSF stations; Fig. 1). Stations were set along an altitudinal gradient, in order to cover the diversity of forest habitats in relation to local topography (Smith 2004, Talvitie et al. 2006, Louppe et al. 2021, Jean-Pierre et al. 2022). Five trap locations were established per station, each equipped with a single passive infrared camera (Moultrie© M-40i, 125° field of view). Camera-trap locations within a station were spaced 200 meters apart along a straight line to ensure spatial independence of detections. Each camera-trap location was treated as an independent sampling unit, resulting in a total of 60 locations across all stations. We attached each single camera to a robust tree about 20–30 cm above the ground, to maximize the probability of detection of the relatively small-sized FT (O’Connell et al. 2011). We selected trees with little surrounding vegetation, to allow for an optimal range of camera sensor in the closed habitat. We applied a 30-s delay between pictures to avoid multiple photographs of the same individual over short periods of time (Smith et al. 2017). We conducted our study over three weeks, from 2 March to 22 March 2020. Because we only had 20 camera traps, the different stations were sampled on a random rotation basis. At each station, each camera trap remained active for 24 h to document the presence of FT and mammalian species for seven consecutive days, resulting in 420 trapping days. Images collected from camera traps were manually reviewed by a single trained observer (AJP) to ensure consistency. Each independent detection event was defined as a sequence of photographs separated by a minimum of 30 min between consecutive records of the same species at the same camera-trap location (O’Connell et al. 2011). Forest Thrush and mongoose abundance at each camera-trap location was estimated as the total number of independent detection events during the sampling period.

At each camera-trap location, we assessed surrounding biotic and abiotic factors as putative drivers of FT abundance. Following Cook et al. (2020) and Jean-Pierre et al. (2023), we used an ordinal categorical scale with three categories, to characterize canopy openness (CO) as closed (0–1/3), partially open (1/3–2/3), or open (2/3–1). We obtained ambient temperature (TEMP) data from the metadata associated with the camera-trap recordings. For each camera-trap location, the mean temperature was calculated from all detection events over the seven-day sampling period. Because the leaf-litter is considered as a prey reservoir (Sánchez et al. 2014, Smith et al. 2017, Mansor et al. 2018, 2019, Martay and Pearce-Higgins 2020, Gumede et al. 2022), we estimated leaf-litter biomass (LLB) at each camera-trap location. To that end, we used 1-m² quadrat frames to sample the ground leaf-litter on the four cardinal points around each camera trap, at a distance of 5 m. After collection of invertebrates (see below), we dried the collected leaf litter in an oven for one week at 60 °C, and then weighed it with a balance (with a 0.1 g accuracy, BH 3000 A). We estimated prey availability from both the abundance and total biomass of invertebrates. Although exhaustive sample sorting is a reliable method for fully describing the structure and composition of a macroinvertebrate community (Courtemanch 1996, Cao et al. 1998), it requires considerable time and effort (Ciborowski 1991, Vlek et al. 2006). Among the less time-consuming techniques developed, we chose the sieving method to study the ground leaf-litter arthropod communities (Belshaw and Bolton 1993, Dietl et al. 2009, Vasconcelos et al. 2009, Cole et al. 2016, Araùjo and Souza 2022, Aponte Rolón and Perfecto 2023). Because we were only interested in macroinvertebrates (> 2 mm), we manually collected all arthropods from each sieve during a standardized time of 30 minutes, using fine tweezers (Kattan et al. 2006, Niedbala and Ermilov 2022). More precisely, after pooling the four litter samples from each camera-trap location, we used a succession of sieves stacked in decreasing order (4 mm, 3 mm, and 2 mm mesh). We considered invertebrate abundance (IA) per camera-trap location as the number of individuals recorded per camera-trap location. We estimated invertebrate biomass (IB) per camera-trap location by weighing the individuals collected using a precision balance (with a 0.001 g accuracy, PIONEER™ PRÉCISION PX323M).

Data analysis

Comparison of biotic and abiotic factors between forest types

We first investigated to what extent our sampling stations located in the three recognized forest types differed according to biotic and abiotic factors. A Shapiro-Wilk test (Mohd Razali and Bee Wah 2011) indicated that only TEMP followed a normal distribution (W_TEMP = 0.98, p = 0.52). Therefore, we relied on generalized linear model (Nelder and Wedderburn 1972), to assess variation in TEMP between forest types. GLM were fitted with a Gaussian distribution using the R package Stats v3.6.2. Because IB, IA, and LLB did not follow a normal distribution (W_IB = 0.69, p < 0.001; W_IA = 0.85, p < 0.001; W_LLB = 0.92, p < 0.001), we transformed these variables into ordinal variables based on quantile distributions and relied on ordinal logistic regression to assess variation in CO, IB, IA, and LLB between forest types, using the R package Ordinal v.2022.11-16 (sensu Gorczynski and Beaudrot 2021). For all models, we included station as a random effect nested in forest type, because each camera-trap location belonged to one of the 12 different stations, themselves distributed in three different forest types. We used the R software 3.6.2 (R Core Team 2019) to perform all analyses and figures. Results were considered significant at the 5% level.

Modeling FT abundance

We relied on random effect models, i.e., generalized linear mixed models (Bolker et al. 2009), to assess the influence of forest type (included as the categorical variable FOREST with three levels: TRF, TDF, TSF), prey availability (i.e., IB and IA) and potential predator (i.e., mongoose abundance MONA and mongoose presence MONP, see results) on FT abundance. Highly correlated variables (Spearman rank-correlation coefficient, r_s ≥ 0.7) were not included together in the same model (Dormann et al. 2013). For all models, we included nested random effect parameters (i.e., stations nested within forest type). The dataset included 60 camera-trap locations, of which 39 failed to detect any Forest Thrush during the sampling period, resulting in a substantial proportion of zero counts. Given this data structure, characterized by excess zeros and overdispersion, we considered Poisson, zero-inflated Poisson, negative binomial, and zero-inflated negative binomial distributions to model FT abundance (Lapin et al. 2013). The zero-inflated negative binomial distribution (log link) provided the best fit to the data (White and Bennetts 1996). Models were built using the R package glmmTMB 1.0.0 (Brooks et al. 2017). All possible combinations of covariates were investigated using the R package MuMIn 1.43.6, resulting in 18 models without interactions (Bartoń 2019). We ranked models using the Akaike information criterion corrected for small sample size, AICc, using the R package AICcmodavg 2.3-1 (Mazerolle 2017) and considered models with ΔAICc < 2 as equivalent for explaining variation in FT local abundance (Burnham et al. 2011). We checked for goodness-of-fit for all valid models using the R package DHARMa 0.2.7 (Hartig 2020). We relied on the R package glmmTMB 1.0.0 (Brooks et al. 2017) to obtain coefficient (βi) of model parameters and their associated p values.

RESULTS

Comparison of biotic and abiotic factors between forest types

Temperature was significantly lower at camera-trap locations dominated by TRF than at those dominated by TDF or TSF (β = -3.23, p < 0.001; Appendix 1). On the other hand, canopy openness was higher at camera trap locations dominated by TDF than those dominated by TSF or TRF (β = 4.00, p < 0.01; Table S1). Conversely, leaf-litter biomass was lower at camera-trap locations dominated by TDF than those dominated by TSF or TRF (β = -7.81, p < 0.01; Appendix 1).

Factors affecting FT abundance

We obtained 158 captures of FTs at 21 different camera-trap locations (35% of all camera-trap locations), 103 captures of mongooses at 28 different camera-trap locations (46.7%), compared to only 16 captures of domestic cats at 4 different camera-trap locations (6.7%). Given their rare occurrence, the abundance of domestic cats was not included in the analyses. In terms of habitat type, FT were detected at 16 camera-trap locations in TRF (141 captures), 2 camera-trap locations in TDF (13 captures), and 4 camera-trap locations in TSF (4 captures). Detection rates of FT varied significantly among forest types (Fisher’s exact test, p = 0.03), with FT being more frequently detected in tropical rainforest than in tropical dry or swamp forests.

When comparing models based on abundance at all camera-trap locations, the best model (Table 1, Appendix 2) included IB, MONA, and FOREST as meaningful parameters. More precisely, IB and MONA were positively associated with FT abundance (β_IB = 0.98, p < 0.001, Fig. 2a; β_MONA = 0.91, p < 0.001, Fig. 2b). Moreover, FT abundance was higher at camera-trap locations dominated by TRF than at those dominated by TSF or TDF (β = 3.71, p < 0.001; Fig. 2c). Analysis of residuals detected no deviation from the expected distributions (see Supplementary Information Appendix 3).

DISCUSSION

Our results suggest that the Forest Thrush may be relatively common in the tropical rainforests of Guadeloupe, as shown by previous studies (Jean-Pierre et al. 2023). More importantly, our results revealed a positive influence of spatial variation in leaf-litter invertebrate biomass on spatial variation in FT abundance, as well as a positive association between FT abundance and that of one of its potential exotic predators, the small Indian mongoose. Such findings have direct relevance for the conservation and management of this near-threatened species.

Influence of invertebrate biomass and forest type on the abundance of the Forest Thrush

Spatial variation in invertebrate biomass was the most influential factor explaining spatial variation in FT abundance across forest types. Although FT can feed on both invertebrates and fruits, its diet has not been documented though quantitative data. Future research, possibly based on fecal content and stable isotope analysis (Bosenbecker and Bugoni 2020), would therefore be helpful to assess the extent of FT dietary plasticity and seasonal variation, particularly in the global context of invertebrate loss (Şekercioğlu et al. 2002, Lamarre et al. 2020). However, McKinnon et al. (2017) found that the ecologically similar and omnivorous Wood Thrush, Hylocichla mustelina, mainly consumed arthropods, particularly during the driest times of the non-breeding season. In addition, our results are consistent with previous studies of both temperate and tropical forest passerine bird species. For instance, Brown et al. (2011) found that both the taxonomic richness and abundance of large arthropods were significantly greater at sites occupied by Swainson’s Warblers, Limnothlypis swainsonii, than at unoccupied sites in the southeastern U.S. Consistent with this, Mizuta (2014) found that earthworm abundance associated with forest maturity was a critical factor influencing habitat selection by the Amami Thrush (Zoothera major). Similarly, arthropod abundance was the best predictor of the abundance of the White-breasted Wood-Wren, Henicorhina leucosticta, in Caribbean lowland forests of Costa Rica (Sánchez et al. 2014).

However, the overall evidence for species of the genus Turdus is less conclusive. On the one hand, Martay and Pearce-Higgins (2020) found a positive association between counts of several thrush species and earthworm abundance in the UK. On the other hand, Newmark and Stanley (2016) found that invertebrate abundance did not differ between territories of the Usambara Thrush, T. roehli, whereas habitat structure, in terms of tree density and ground cover, did. Similarly, Jirinec et al. (2016) found that habitat structure was more important than prey availability to explain the relative space use of 37 radiotracked male Wood Thrushes on their breeding grounds in coastal Virginia.

Although we did not include measures of habitat structure in our models, forest type significantly influenced FT abundance, with higher abundance in TRF compared to both TDF and TSF, in accordance with previous studies (Arnoux et al. 2013, Parashuram et al. 2015). However, invertebrate abundance as well as invertebrate biomass did not differ between forest types, such that the influence of forest type and prey availability were not confounded in our analyses. At a broad scale, the three forest types differ markedly in terms of vegetation structure in the Caribbean islands (Areces-Mallea et al. 1999, Banda-Rodríguez et al. 2016), and, more specifically, in Guadeloupe (Imbert et al. 1996, 2000, Imbert and Portecop 2008). In the present study, stations differed significantly according to forest type in terms of temperature, canopy openness, and leaf-litter biomass. Temperature was significantly lower in rainforest stations, as a direct consequence of their higher elevation compared to both dry forest and swamp forest stations. On the other hand, canopy was significantly more open in dry forest stations compared to stations located in the two other forest types. Our results thus suggest that FT may prefer specific light and thermal niches, and favor dim and cool microclimates when foraging for food on the ground as reported for other tropical forest insectivorous bird species (Jirinec et al. 2022). In addition to the observed relationships between FT abundance and biotic predictors, several other factors may influence the long-term persistence of the species in Guadeloupe. Given its preference for mature, shady forests, FT may benefit from the protection of large forested areas, particularly within the boundaries of the Parc National de la Guadeloupe, where habitat conservation and hunting regulations are enforced. However, future threats such as climate change may affect the species both directly, through heat stress and reduced fitness (Pollock et al. 2021), and indirectly, by altering canopy structure, soil moisture (Scholl et al. 2021), and invertebrate prey availability (Kaspari et al. 2017). Furthermore, the recent colonization of Guadeloupe by the Spectacled Thrush (T. nudigenis), known for its aggressive behavior toward other thrushes, may lead to competitive interactions that are potentially detrimental to forest thrush populations (Levesque et al. 2005).

These potential threats highlight the importance of implementing long-term monitoring programs to document population trends and to better inform conservation strategies for the species, especially given the current lack of comprehensive abundance data in Guadeloupe. However, because studies on turdids and other ground-dwelling forest birds differ in several respects, including methodology, geographical area, and time of the year, a meta-analysis would be of interest to provide an overall assessment of the relative influence of food availability and habitat structure on spatial variation in occupancy and abundance.

Spatial covariation in abundance with the small Indian mongoose

We found a positive spatial covariation between the abundance of FT and that of the small Indian mongoose in Guadeloupe. Our results thus confirm previous reports of spatial co-occurrence between the two species in Guadeloupe based on camera-trap data (Louppe et al. 2021). Still, the causes and consequences of this association deserve particular attention.

First, expectations about spatial covariation between prey and predators are not straightforward. On the one hand, positive spatial co-occurrence can be expected if predators concentrate where their prey are mostly abundant in order to increase encounter rate (Kittle et al. 2017). On the other hand, active avoidance of predators by prey (Gaynor et al. 2019) or strong prey depletion by predators (Amar et al. 2008, Holt et al. 2008) may result in negative spatial co-variation in abundance (Murphy et al. 2019). Accordingly, the few results documenting the influence of mongoose presence on the presence or abundance of avian species have provided mixed evidence. Morley and Winder (2013) concluded that three ground bird species were negatively influenced by the presence of mongoose, as they were observed only on mongoose-free islands among 16 small islands within Fiji. On the other hand, Louppe et al. (2021) recorded the presence of the small Indian mongoose in Martinique in sites known to be restricted territories of two threatened endemic bird species, the Martinique Oriole, Icterus bonana, and the ground-dwelling, White-breasted Thrasher, Ramphocinclus brachyurus. Similarly, Mizuta et al. (2017) found that the distribution and recovery of the Amami Thrush in the Ryukyu Archipelago was strongly influenced by the density of the small Indian mongoose, with thrush populations recovering following mongoose eradication efforts. This finding highlights the potential for significant predator-prey interactions even where spatial co-occurrence is observed. Therefore, the observed positive association between FT and mongoose abundance is in itself poorly informative about their possible interaction as prey and predator.

An alternative explanation for the observed correlation between FT and the small Indian mongoose is that their co-occurrence is simply due to similar habitat preferences associated to a third variable. Although mongoose may prey on birds, they are largely omnivorous and the largest part of their diet on Caribbean islands generally consists of invertebrates, reptiles, small mammals, and fruits (Pimentel 1955, Seaman and Randall 1962, Nellis and Everard 1983). According to a more recent study (Lewis et al. 2011), invertebrates and lizards accounted for 93% of identified prey items in the stomach content of 217 mongooses in Jamaica. Mongooses in the forests of Guadeloupe may therefore concentrate in areas that provide favorable conditions for invertebrates and reptiles. For instance, leaf-litter moisture is crucial for microhabitat choice in both invertebrates and lizards, which tend to seek out shaded areas during dry periods in order to minimize water loss and thermal stress (Vonesh 2001, McGee et al. 2020).

Regardless of its ultimate drivers, spatial co-occurrence may expose FT to predation by mongoose. Direct evidence, based on diet or remains analysis, indicates that the small Indian mongoose can prey upon various bird species (Engeman et al. 2006, Lewis et al. 2011, Akrim et al. 2019). The importance of mongoose predation on birds is also supported by indirect evidence based on bird extinctions and population trends (Hays and Conant 2007, Berentsen et al. 2020, Yagihashi et al. 2021), or by morphological changes in birds following mongoose introduction, such as increased body size, longer wings (Black-faced Grassquit, Melanospiza bicolor) and longer tarsi (Common Ground Dove, Columbina passerina), which may reflect improved flight performance for predator avoidance, as suggested by Heathcote et al. (2021). If such predation pressure is confirmed, it may have detrimental consequences for Forest Thrush populations, especially if reproductive adults or juveniles are preferentially targeted. The introduction of the small Indian mongoose has historically contributed to the decline and extinction of several ground-nesting bird species in Caribbean and Pacific islands, including the Jamaican Petrel (Pterodroma caribbaea; Hays and Conant 2007, Berentsen et al. 2020, Yagihashi et al. 2021). Assessing the precise impact of predation by mongooses on FT and other species in various habitats in Guadeloupe, possibly through fecal or stomach content analysis (Mahmood and Adil 2017, Dabholkar and Devkar 2020, Subrata et al. 2021), would allow a precise estimation of its impact on FT and the local avifauna.

Limitations and perspectives

Although our results provide new and valuable insights about the factors potentially affecting the spatial distribution of FT in Guadeloupe, some limitations must be acknowledged. First, the present study was relatively limited in time and space, such that it is not possible to generalize the results. In particular, because of the predominance of tropical rainforest among the sampled sites, it might be necessary to increase the number of camera-trap stations at dry and swamp forest in order to increase the representativeness of these habitat types. However, our sampling design reflects the natural distribution of forest habitats in Guadeloupe, where tropical rainforest covers more than 40% of the forested landscape. Second, our study took place over three weeks in March, such that the observed pattern of spatial association between FT and mammal predators might not be representative of what happens at other times of the year, particularly during the wet season when food availability is likely to differ. Third, the choice of camera-trap placement may have influenced detection rates. To optimize sensor performance, cameras were installed on trees with relatively sparse surrounding vegetation, potentially favoring more open microhabitats and possibly introducing a bias in Forest Thrush detectability. Although this method minimized technical errors such as false triggers, standardization of vegetation structure around camera-trap locations is recommended in future studies to limit microhabitat-related biases. Finally, although several associations were statistically significant, the wide confidence intervals around parameter estimates indicate a considerable degree of uncertainty, likely because of the relatively short sampling period and limited sample size. Therefore, these results should be interpreted with caution. Long-term studies with extended temporal and spatial replication are needed to confirm these patterns and to improve our understanding of the seasonal and spatial dynamics of Forest Thrush populations.

CONCLUSION

Our study confirms the efficiency of camera traps to monitor ground-dwelling bird species, such as FT, in tropical forest and document their spatial occurrence with other species, particularly potential predators. A long-term and extended survey of the FT population in Guadeloupe relying on this technique may therefore prove quite useful in documenting spatial variation in presence and abundance, assessing local conservation status, and informing management decisions for this species of high patrimonial and hunting value.

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