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Evaluating relative abundance indices for terrestrial herbivores from large-scale camera trap surveys
... Among the analytical methods used for assessing camera-trap data, relative abundance index (RAI) measures the relative abundance per 100 days of camera capture for each species (O'Brien et al. 2003;Henschel et al. 2011;Palmer et al. 2018). Analytical methods for quantifying relative abundance differences based on RAI are relatively economical and simple, and can estimate the abundance of species that lack specific morpho logical characteristics (O'Brien et al. 2003;Jenks et al. 2011;O'Brien 2011;Ancrenaz et al. 2012). ...
... Analytical methods for quantifying relative abundance differences based on RAI are relatively economical and simple, and can estimate the abundance of species that lack specific morpho logical characteristics (O'Brien et al. 2003;Jenks et al. 2011;O'Brien 2011;Ancrenaz et al. 2012). Further, RAI can be used to conserve and manage wildlife at the regional level, as it tends to be linearly correlated with the overall abundance (Caughley 1977;Jennelle et al. 2002;O'Brien et al. 2003;Sollmann et al. 2013;Srbek-Araujo and Chiarello 2013;Palmer et al. 2018). ...
... The RAI was calculated as (number of independent pictures / total monitoring days) × 100 (Henschel et al. 2011;Palmer et al. 2018). All analyses of the relationship between trapping effort and species richness were performed using R 3.5.3 ...
In Jangsudae of Seoraksan National Park, South Korea, 14 mammal species have been listed, including ten medium- and large-sized species; additionally, this region is an important habitat for the endangered long-tailed goral (Naemorhedus caudatus). In this study, a camera trap survey was conducted over 103 monitoring days at 18 sites in Jangsudae to evaluate the minimum trapping effort (MTE) needed to detect the ten listed mammal species. The most photographed species were the long-tailed goral, wild boar (Sus scrofa), and Asian badger (Meles leucurus), accounting for 77.1% (n = 366) of the total independent photographs. Long-tailed goral, the most frequently captured mammal species (44.8%), was captured at 17 camera sites (relative abundance index = 206.8). According to the rarefaction analysis, 1840 camera days (102.2 monitoring days at 18 camera sites) were required to photograph all ten resident species. Moreover, at least 1010 and 664 camera days were required to detect 95% and 90% of the ten residential species, respectively. MTE was evaluated in summer when wild species were highly detectable owing to their high activity. Future studies should evaluate MTE through one-year long-term monitoring that includes all four seasons, and compare the results with those of this study.
Published online 22 May, 2023; Print publication July 31, 2023
... To assess the population trend, for each camera trap site within the core area, monitored in different years, we calculated a trapping rate per year accounting for group size, i.e. total number of recorded aoudads divided by total effective working days for each camera (Palmer et al., 2018;Ferretti et al., 2023). We fitted generalized mixed models using the glmmTMB package (Brooks et al., 2017) in R (R Core R Studio Team, 2020), with the total number of aoudad recorded by each camera trap per year within the core area of the species as the response, accounting for different sampling effort by adding the logarithm of camera trap days as an offset (which essentially allows to model aoudad counts as a trapping rate), and the different sampling years (n=4, 2017-2020) as independent variable; camera site ID was fitted as a random intercept, since some sites were repeatedly sampled in different years. ...
... Trapping rate applied to large-bodied, non-migratory herbivores have proved an effective index of abundance (Carbone et al., 2001;O'Brien et al., 2003;Rowcliffe et al., 2008;Tobler et al., 2008;Rovero and Marshall, 2009;Palmer et al., 2018;Ferretti et al., 2023). Unfortunately, we could not validate our trapping rate estimates with density estimates obtained by independent methods (as suggested by Palmer et al., 2018;Ferretti et al., 2023), due to lack of funding and personnel. ...
... Trapping rate applied to large-bodied, non-migratory herbivores have proved an effective index of abundance (Carbone et al., 2001;O'Brien et al., 2003;Rowcliffe et al., 2008;Tobler et al., 2008;Rovero and Marshall, 2009;Palmer et al., 2018;Ferretti et al., 2023). Unfortunately, we could not validate our trapping rate estimates with density estimates obtained by independent methods (as suggested by Palmer et al., 2018;Ferretti et al., 2023), due to lack of funding and personnel. ...
Alien species are species that are introduced into an area where they are not naturally present. Some of them may exert negative ecological impacts, thus being defined as invasive. The aoudad or Barbary sheep Ammotragus lervia is a north-African ungulate commercialised and introduced for game hunting to Europe, South Africa, and America. As a generalist herbivore, the aoudad has a high capacity to adapt to new habitat conditions, possibly representing a threat to local biodiversity. We studied the aoudad population present in the Beigua Natural Regional Park in Liguria, northwestern Italy. By using historical data and camera trapping data, we reconstructed the colonization process and current distribution, estimated minimum abundance, assessed population trends over the years, and investigated habitat selection and activity rhythms. Aoudads most likely escaped from a game reserve in Ponzone Municipality, Piedmont, and settled in the park at least since 2009. The minimum number alive doubled in 10 years, from 9 to 23, and the population shows an increasing trend. Aoudads showed a preference for steep, rocky and woody areas in the southern and warmer part of the Beigua massif, especially at intermediate elevations. Some observations have recently occurred in the northern part of the Park, potentially due to geographical expansion. Aoudads show mostly diurnal activity, unlike native ungulates such as roe deer Capreolus capreolus and wild boar Sus scrofa which were most active at dawn, dusk and during the night, possibly reflecting anti-predator behaviour towards wolf Canis lupus. Our results are in line with other studies, though births occurred across a wider period of time compared with native populations. As the potential ecological impacts of this alien species in the study area have never been investigated, it will be important to monitor the population and evaluate its ecological effects to provide the most appropriate management solutions.
... This sampling method has been widely used to calculate RAI and subsequent models (Mangas and Rodríguez-Estival, 2010;Güthlin et al., 2013), although it is often limited by the difficulty of accurately assigning signals to a species (Kohn and Wayne, 1997;Hansen and Jacobsen, 1999;Davidson et al. 2001) and the lack of validation of the index with actual abundance data (Anderson, 2003). Alternatively, recent methods based on camera-trapping (Bengsen et al., 2011;Karanth and Nichols, 2011;Palmer et al., 2018) are used to estimate the actual abundance or population density of a species when individual body characteristics or artificial markings (e.g. radio collars, tags) of photographed animals can be used. ...
... radio collars, tags) of photographed animals can be used. A relative abundance index is then calculated by considering the frequency of capture as the number of captures (photographs) per the total number of capture occasions (Carbone et al., 2001;O'Brien, 2011, Palmer et al., 2018. This is a common and widely used index in relative abundance models (O'Brien et al., 2003;Kinnaird and O'brien, 2012;Gil-Sánchez et al., 2021). ...
... In this vein, previous research focusing on the relationship between indices of relative abundance and tiger population size showed that the number of camera days/tiger photographs (RAI index) correlated with independent estimates of tiger density (Carbone et al., 2001). Similarly, evaluation of relative abundance indices of African herbivore species showed a strong correlation of the RAI index with independent abundance estimates from aerial surveys (Palmer et al., 2018). The number of identified individuals has been widely used to estimate abundance in species populations using capture-recapture methods (Karanth, 1995;Silver et al., 2004;Jackson et al. 2006;Sarmento et al. 2010). ...
The correct interpretation of relative abundance indices provided by different sampling methods is essential to correctly estimate population size. Although multiple indices and models have been proposed, their ability to estimate relative abundances and their performance in models explaining abundance trends remains unclear. We used the red fox (Vulpes vulpes) as a model species to compare the relationship and derived models of relative abundance between three indices of relative abundance: RAI (number of captures/total occasions); NI (number of photo-identified individuals) obtained by camera-trapping, and NSE (number of segments with scats) obtained by the scat census sampling method. In addition, we modelled the relationship between a set of habitat predictors and fox relative abundance for each of the three estimated relative abundance indices. We compared the relative abundance models explained for each index against N-mixture models that estimate abundance controlled for variation in detection. Results showed a positive correlation between the RAI and NI indices, while both indices showed a negative relationship with the NSE index. Relative abundance models and N-Mixture models showed a different selection of predictors to explain abundance trends. NSE and RAI indices selected predictors that could explain variability in fox detection rather than fox abundance. In contrast, the NI index and N-Mixture models selected the same predictors to explain fox abundance. Our results suggest the use of the NI index for abundance models without the need to control for variation in detection. Relative abundance indices based on scats and captures per occasion are suboptimal indices for species abundance studies due to possible bias caused by animal behaviour. If count-based methods on captures per occasion (RAI) are selected, we suggest using session-based data processing to incorporate detectability variation in N-mixture models.
... Camera trapping is a direct observation often used to measure the relative abundance of shy and elusive species like deer. This method is non-invasive, requires minimal labor, and yields robust data (Kays et al. 2011, Palmer et al. 2018). This study used ten camera traps, including four HCO Scoutguard SG560C and six Bushnell Trophy Cam HD Aggressor No-Glow Trail camera traps. ...
... Relative Abundance Index (RAI) is the ratio between deer detection based on the photographic capture rates from camera trap surveys and the entire trapping days. This is a less complicated estimation method when true abundance is difficult or costly to measure (Palmer et al. 2018). As a population estimation tool, this can be used as a baseline to employ more comprehensive species monitoring initiatives, such as tagging and radio telemetry (Rovero et al. 2014, Iannarilli et al. 2021. ...
The Philippine Brown Deer (Rusa marianna Desmarest, 1822) is an endangered species endemic to the Philippines. Deforestation, habitat loss, and subsistence hunting continue to cause its rapidly declining population. To increase knowledge on deer’s conservation and population status in Mindanao, the researchers assessed its abundance and distribution within the Obu Manuvu Ancestral Domain (OMAD) in Mindanao Island, Philippines. Five hundred four-camera trap days were conducted from June to August 2016, followed by 500 days from January to March 2020. Camera trapping was used to detect deer presence and calculate its relative abundance index (RAI). A total of ten cameras were installed in areas with preliminary evidence of deer presence, such as trails, dens, and fecal pellets, and were distributed at 250m minimum distance intervals. Key Informant Interviews (KIIs) were also undertaken to document indigenous ecological knowledge. A total of four independent detections were documented in 2016 (RAI=0.79), while another four independent sequences were recorded in 2020 (RAI=0.80). Overall, the deer has a low population status and broad distribution across primary and secondary forests at an elevation of 1518 to 1709 m.a.s.l. Meanwhile, the deer was declared a cultural keystone species with several ethnozoological uses. They are important to the life, history, and culture of the Obu Manuvu indigenous community. However, hunting and habitat loss remained the leading anthropogenic threats against the deer despite local conservation efforts. Thus, there is a need to sustain and strengthen conservation efforts through the stringent implementation of wildlife monitoring and enforcement of culture-based protection policies.
... Indices of relative abundance assume that the capture rate varies in a constant and linear manner with the real abundance of the species (Pollock et al., 2002). This linear relationship has been documented for a large number of species, including felids and their potential prey (Carbone et al., 2001;Palmer et al., 2018;Rovero & Marshall, 2009). However, the biases that these simple indices may have by not considering the temporal and spatial variation in species detection have also been documented in recent years (Kolowski et al., 2021;Sollmann et al., 2013). ...
The distribution range and population abundance of species provide fundamental information on the species–habitat relationship required for management and conservation. Abundance inherently provides more information about the ecology of species than do occurrence data. However, information on abundance is scarce for most species, mainly at large spatial scales. The objective of this work was, therefore, to provide information regarding the population status of six wild felids inhabiting territories in Mexico that are inaccessible or politically unstable. This was done using species distribution models derived from occurrence data. We used distribution data at a continental scale for the wild felids inhabiting Mexico: jaguar ( Panthera onca ), bobcat ( Lynx rufus ), ocelot ( Leopardus pardalis ), cougar ( Puma concolor ), margay ( Leopardus wiedii ), and jaguarundi ( Herpailurus yagouaroundi ) to predict environmental suitability (estimated by both Maxent and the distance to niche centroid, DNC). Suitability was then examined by relating to a capture rate‐based index, in a well‐monitored area in central western Mexico in order to assess their performance as proxies of relative abundance. Our results indicate that the environmental suitability patterns predicted by both algorithms were comparable. However, the strength of the relationship between the suitability and relative abundance of local populations differed across species and between algorithms, with the bobcat and DNC, respectively, having the best fit, although the relationship was not consistent in all the models. This paper presents the potential of implementing species distribution models in order to predict the relative abundance of wild felids in Mexico and offers guidance for the proper interpretation of the relationship between suitability and population abundance. The results obtained provide a robust information base on which to outline specific conservation actions and on which to examine the potential status of endangered species inhabiting remote or politically unstable territories in which on‐field monitoring programs are not feasible.
... We regarded the 'best' model to be the one with the lowest AICc value but considered those within two AICc as equally plausible. To measure precision around our estimates, we calculated the percentage relative standard error (RSE) as the standard error of the coefficient divided by the estimate; an RSE > 20% was assumed to indicate low precision and, therefore, low statistical power to detect a change in the population size (Williams et al. 2002;Palmer et al. 2018;Efford and Boulanger 2019). All statistical analyses were performed in in R v4.2.1 (R Core Team 2022). ...
... For each game camera included in the study, we calculated the rate of opossum detection defined as the number of opossum detections divided by the number of days the camera was deployed. While this detection rate should not be confused with true abundance, it is a commonly used index of relative abundance derived and reported from camera trapping studies and is often reliable (Gerber et al., 2010;O'Brien, 2011;Palmer et al., 2018). ...
As human development continues to expand, wildlife must relocate or adapt to survive. Many mammalian mesopredators, such as the Virginia opossum (Didelphis virginiana), have adapted to living alongside human development. Furthermore, top-down predation pressure may be altered in nuanced ways within the human environment. Species such as opossums may be shielded from predation by human development or behavioral changes in predators. Understanding how dominant and subordinate mesopredators co-exist across natural and developed areas will provide insight into how wildlife communities are structured. Our objective was to evaluate how opossum occupancy, abundance, and activity were associated with human development and the relative abundance of their predators. We used data from a nationwide camera trapping study, Snapshot USA, to estimate opossum occupancy, abundance, and activity. We related these measures to the surrounding landscape and urbanization variables. We found that opossum occupancy was positively associated with anthropogenic sound (a surrogate for human activity). Furthermore, opossums in heavily forested areas were more likely to be detected in locations with higher predicted anthropogenic sounds. In areas with a high density of human housing, opossum relative abundance increased when predator abundance increased. We also found opossums were strictly nocturnal and shifted their activity to earlier in the evening in the presence of high predator abundance. Our results suggest that humans and their urban development can have multidimensional impacts on opossum behavior and occurrence, and could facilitate changes in predator-prey dynamics. Future research should evaluate if the association of opossums with urban areas is due to human-subsidized resources or caused by reduced mortality from altered predator-prey dynamics.
... We considered the sum of independent records of all medium and large-sized mammal species in each sampling unit as a proxy for the total mammal abundance. This sum of records (hereafter named 'relative' abundance) is considered to be an adequate surrogate for true abundance and is positively related with independent density and abundance estimates (Carbone et al. 2001;Palmer et al. 2018). We also estimated the taxonomic richness of mammals using the Chao2 index for incidence data, with 1000 randomizations and camera days as the number of samples (Gotelli and Colwell 2010). ...
Understanding how species respond to the environmental heterogeneity created by fire (i.e., pyrodiversity) is essential to protect biodiversity in the face of current changes in the natural fire regime. Pyrodiversity is hypothesized to promote biodiversity, but this hypothesis has mixed support and has never been tested for medium- and large-sized mammals in a neotropical savanna. Here, we investigated how mammalian communities respond to fire frequency, fire age, and spatiotemporal variations in these fire regime elements (pyrodiversity) at multiple spatial scales (from 0.8 to 78.5 ha). We sampled medium- and large-sized mammals using camera traps distributed on 30 sites in grassland and typical savanna formations. We applied multiple regression analysis to describe the relationships between fire regime variables and mammal communities. Mammals responded to the fire regime only when the spatiotemporal variation was considered. Taxonomic and functional mammal richness increased with variations in fire age, but mammal diversity and functional dispersion were greater at intermediate pyrodiversity. Moreover, mammal abundance responded positively to diversity of fire frequency but negatively to fire age diversity. Our results indicate that pyrodiversity can lead to taxonomically and functionally rich communities, probably due to more forage, shelter, and movement opportunities for different species in heterogeneous environments. Nonetheless, its effect on abundance seems limited. We recommend focusing fire management in savanna landscapes on the diversity of fire age mosaics, at least for medium and large mammals. Moreover, management conducted on intermediate scales (~ 80 ha) is sufficient to generate pyrodiversity that affects mammal communities.
... This further helps us to understand the ecology of several elusive species and assist managers in maximizing conservation in biodiversity rich areas. Thus, camera trapping is now one of the most reliable techniques in monitoring wildlife globally and widely used for monitoring terrestrial vertebrates to understand their relationship towards various anthropogenic pressure (Palmer et al. 2018;Jhala et al. 2021;Chakraborty et al. 2021). ...
A camera trap study was conducted in the mangrove of Krishna Wildlife Sanctuary, the eastern coast of India, to understand the assemblage, temporal segregation and dial activity pattern of small and medium-sized mammals. Forty-one pairs of passive infrared camera traps were deployed and monitored for 30 consecutive days, making a total of 1,230 trap days effort. The study reveals that the jackals accounted for 40.5%, while fishing cats and jungle cats accounted for 6.09% and 2.42% of all recorded animals, respectively. The analysis of the relative abundance index shows that the jackal is the most abundant mammal in the sanctuary (36.74). Free-ranging dogs, humans and cattle were recorded mostly during the daytime. The jackal showed a higher temporal overlap with the fishing cat (0.76, 95% CI (0.59-0.93)) and the jungle cat (0.72, 95% CI (0.62-0.82)). The jungle cat showed peak activity at dawn, while fishing cats showed peak activity at dusk. Both species temporally overlapped with the bimodal activity of the jackal. Moreover, the available prey may be shared between the three dominant predatory species by minimising the competition (effective resource partitioning). The anthropogenic threats can be a reason for a comparatively lower abundance of the fishing cat, and necessary steps are sought to protect this ecosystem.
... Indices based on photographic capture rates per effort are commonly used as proxies for population abundance (Palmer et al., 2018) and have been shown to accurately estimate relative abundance for range of mammals in a variety of environments (Rowcliffe et al., 2008;Villette et al., 2016Villette et al., , 2017Lambert et al., 2018). However, this continues to be an area of contention in Ecology (Stephens et al., 2015). ...
Effective wildlife population management requires an understanding of the abundance of the target species. In the United Kingdom, the increase in numbers and range of the non-native invasive grey squirrel Sciurus carolinensis poses a substantial threat to the existence of the native red squirrel S. vulgaris , to tree health, and to the forestry industry. Reducing the number of grey squirrels, is crucial to mitigate their impacts. Camera traps are increasingly used to estimate animal abundance, and methods have been developed that do not require the identification of individual animals. Most of these methods have been focussed on medium to large mammal species with large range sizes and may be unsuitable for measuring local abundances of smaller mammals that have variable detection rates and hard to measure movement behaviour. The aim of this study was to develop a practical and cost-effective method, based on a camera trap index, that could be used by practitioners to estimate target densities of grey squirrels in woodlands to provide guidance on the numbers of traps or contraceptive feeders required for local grey squirrel control. Camera traps were deployed in ten independent woods of between 6 and 28 ha in size. An index, calculated from the number of grey squirrel photographs recorded per camera per day had a strong linear relationship ( R ² = 0.90) with the densities of squirrels removed in trap and dispatch operations. From different time filters tested, a 5 min filter was applied, where photographs of squirrels recorded on the same camera within 5 min of a previous photograph were not counted. There were no significant differences between the number of squirrel photographs per camera recorded by three different models of camera, increasing the method’s practical application. This study demonstrated that a camera index could be used to inform the number of feeders or traps required for grey squirrel management through culling or contraception. Results could be obtained within 6 days without requiring expensive equipment or a high level of technical input. This method can easily be adapted to other rodent or small mammal species, making it widely applicable to other wildlife management interventions.
... (R Core Team, 2020). We calculated the Relative Abundance Index (RAIs) for all identified meso-mammals as the number of videos obtained for each species, divided by the overall number of camera days (Rovero et al., 2010;Palmer et al., 2018). We excluded multiple capture events of the same species on the same camera day from analyses. ...
... We used the number of records of game birds and medium-(> 1 kg) and large-sized (> 20 kg) mammals recorded per camera trap as surrogates for animal abundance (Haugaasen and Peres 2007;Galetti et al. 2009;Hawes and Peres 2014;Hong et al. 2015;Michalski et al. 2015;Alvarenga et al. 2018;Scabin and Peres 2021). Although the use of camera trap records as a measure of animal abundance does not account for imperfect and variable detection (Sollmann et al. 2013), some studies have shown that they are correlated (Rovero and Marshall 2009;Parsons et al. 2017;Palmer et al. 2018). Observations of the same species at a camera trap station were considered independent records only after an interval of 24 h between them. ...
Vertebrates play key roles as seed dispersers, herbivores, and top predators in tropical ecosystems. Therefore, obtaining population estimates for these species and understanding the factors that affect them are essential for wildlife management since changes in their populations have consequences for entire ecosystems. Vertebrate abundances in tropical forest may be related to habitat characteristics, resource seasonality, and human pressure. However, how ecological variables and human pressure concurrently influence animal abundances is not well understood. We investigated the associations between the number of records of vertebrates (ground-dwelling birds and medium- and large-sized mammals) and habitat features, food availability, and human pressure in a sustainable protected area in the Brazilian Amazon of western Pará, Brazil. Our study design included the recording of animals at 38 camera trap stations, sampling of environmental variables (canopy cover, leaf area index, tree height, and local altitude) and food resources (fruit or prey biomass), and measurement of a hunting pressure proxy (distance from human settlements). Our results indicated that groups responded in different ways: omnivorous mammals were affected positively by local altitude, canopy openness, and leaf area index; game birds were affected positively by local altitude and leaf area index; ungulates were affected negatively by local altitude and positively by food resources; and large rodents were affected only by food resources (positively). In contrast, insectivorous mammals and mesopredators were not affected by any variable we tested. Surprisingly, no groups responded to distance from human access, although the low number of records of large species, such Tapirus terrestris and Dicotyles tajacu, suggests that the sampled area may suffer from significant hunting pressure.
... Human disturbance factors are measured in three dimensions, including human activity, distance to roads, and distance to settlements. The intensity of human activity at each survey station was measured by the human's relative abundance index (RAI), which was calculated as the photographic rate (i.e., the number of detections per day averaged over the total number of camera-days) of humans captured by the camera [46]. We also calculated the distance to roads and human settlements of each station, respectively, as two variables that could impact the animal's behavior. ...
Simple Summary
Humans alter how carnivores interact with one another by changing landscapes and inciting fear. We investigated how four mesocarnivores (medium-sized carnivores), the red fox, leopard cat, Asian badger, and hog badger, partition their activity pattern to co-occur under varying human influences in the Taihang Mountains of China. Using camera-trapping data collected from 2016 to 2020, we revealed that the leopard cats and the badgers reduced their activities during the day at sites with high-level human disturbance, possibly a behavioral mechanism to avoid risks while living in human-dominated landscapes. However, the activity pattern overlap did not increase between mesocarnivore pairs, suggesting that they may use strategies other than niche segregation along the temporal dimension to coexist.
Abstract
Mesocarnivores play essential roles in terrestrial ecosystems, but anthropocentric disturbances have profoundly transformed their intraguild interactions worldwide. In this study, we explored how a guild of four mesocarnivores (red fox Vulpes vulpes, leopard cat Prionailurus bengalensis, Asian badger Meles leucurus, and hog badger Arctonyx collaris) partition their temporal niche in the temperate montane forests in North China under different human influences. We conducted a systemic camera-trapping survey on the study species in the central Taihang Mountains from 2016 to 2020. With an extensive survey effort of 111,063 camera-days from 187 camera stations, we obtained 10,035 independent detections of the four mesocarnivores and examined the activity patterns of each species under different levels of human disturbance and their overlaps. The results showed that, while the leopard cat and the badgers shifted their activity towards nocturnality, the red fox showed no significant change. The leopard cat’s degree of nocturnality varied between growing and non-growing seasons, likely a response to avoid humans and other competitors. However, the activity overlaps between species pairs demonstrated no statistically significant difference, indicating a long-developed coexistence mechanism that is homogenous across the landscape. Demonstrating how mesocarnivores shift activity patterns in response to human risks while partitioning resources, this study enhances our understanding of mesocarnivore behavioral changes and interspecific interactions at human–nature interfaces.
... The species detection rate was computed as the mean number of independent events occurring at one sampling point for 100 days (Rovero & Marshall, 2009). This index was chosen as it correlates to relative abundance and is frequently used when other methods to estimate abundance are too difficult to implement (Palmer et al., 2018). Beyond local abundance, a range of factors may however affect species' detectability including species' behaviour and biomass, micro-habitat characteristics, and methodology (Lijun et al., 2019;Sollmann et al., 2013). ...
Estimating the richness and abundance of animal species remains central to any conservation strategy of a given area. In remote and challenging environments such as tropical forests, camera traps have proven to be successful in documenting secretive wildlife communities compared to other survey methods, as they allow continuous monitoring without the presence of a human observer. Here, we used camera traps to characterise the community of medium and large terrestrial mammals in the community zone of Lobéké National Park, in southeastern Cameroon. We deployed a grid of 40 camera traps over a 5-week period, recording 5156 independent detection events over 1284 camera days. We recorded 35 species, many of them showing high detection rates compared to other sites in central Africa. These results highlight the little disturbance of the studied area within the park despite its accessibility to local communities. These results obtained from a standardised approach using an expanding technology offer valuable information about the wildlife community of Lobéké, and new insights for reconciling human activities with wildlife conservation. K E Y W O R D S camera traps, Congo Basin, detection rate, Lobéké, richness, wildlife communities Résumé Évaluer la richesse et l'abondance des espèces animales reste un élément clé de toute
... Relative abundance indices (RAI; i.e., number of events, where an "event" is defined as any image sequence for a given species occurring after an interval of ≥60 min from a previous sequence of that species, per 100 days of camera trapping; Karanth & Nichols, 1998;Amin et al., 2018) per camera-trap station were calculated for known main prey species of leopards in the study area, sympatric meso-carnivores-caracal (Caracal caracal, Schreber, 1776) and black-backed jackal (Canis mesomelas, Schreber, 1775)-and leopards, and used as biotic covariates during occupancy modelling (Table S1). Despite being influenced by sampling design or species' behaviour (Sollmann et al., 2013), RAI is still considered a suitable tool for assessing species occurrence (Hedwig et al., 2018;Palmer et al., 2018). ...
Apex predators ideally require vast intact spaces that support sufficient prey abundances to sustain them. In a developing world, however, it is becoming extremely difficult to maintain large enough areas to facilitate apex predators outside of protected regions. Free-roaming leopards ( Panthera pardus ) are the last remaining apex predator in the Greater Cape Floristic Region, South Africa, and face a multitude of threats attributable to competition for space and resources with humans. Using camera-trap data, we investigated the influence of anthropogenic land modification on leopards and the availability of their natural prey species in two contrasting communities—primarily protected (Cederberg) and agriculturally transformed (Piketberg). Potential prey species composition and diversity were determined, to indicate prey availability in each region. Factors influencing spatial utilisation by leopards and their main prey species were also assessed. Estimated potential prey species richness (Cederberg = 27, Piketberg = 26) and diversity indices (Cederberg— H′ = 2.64, Ds = 0.90; Piketberg— H′ = 2.46, Ds = 0.89), supported by both the Jaccard’s Index ( J = 0.73) and Sørensen’s Coefficient ( CC = 0.85), suggested high levels of similarity across the two regions. Main leopard prey species were present in both regions, but their relative abundances differed. Grey rhebok, klipspringer, and rock hyrax were more abundant in the Cederberg, while Cape grysbok, Cape porcupine, chacma baboon, and common duiker were more abundant in Piketberg. Leopards persisted across the agriculturally transformed landscape despite these differences. Occupancy modelling revealed that the spatial dynamics of leopards differed between the two regions, except for both populations preferring areas further away from human habitation. Overall, anthropogenic factors played a greater role in affecting spatial utilisation by leopards and their main prey species in the transformed region, whereas environmental factors had a stronger influence in the protected region. We argue that greater utilisation of alternative main prey species to those preferred in the protected region, including livestock, likely facilitates the persistence of leopards in the transformed region, and believe that this has further implications for human-wildlife conflict. Our study provides a baseline understanding of the potential direct and indirect impacts of agricultural landscape transformation on the behaviour of leopards and shows that heavily modified lands have the potential to facilitate mammalian diversity, including apex predators. We iterate that conservation measures for apex predators should be prioritised where they are present on working lands, and encourage the collaborative development of customised, cost-effective, multi-species conflict management approaches that facilitate coexistence.
... The Relative Abundance Index (RAI) for each year was calculated as the number of independent observations divided by the number of camera trap days, all multiplied by 100 to convert this ratio to a percentage (Palmer et al., 2018). Camera trap days were calculated as the number of camera traps times the number of days they were deployed. ...
Despite the widespread adoption of motion-triggered camera traps, studies using camera traps to characterize wildlife communities in residential areas in North America are limited. To fill this data gap, we placed camera traps over three seasons in 22 residential neighborhoods within Dutchess County, NY. To account for imperfect detection, we applied individual-level and community-level Bayesian site-occupancy models to these data. Overall, we captured 64,639 independent detections over 17,820 camera trap days. We detected between 17 and 22 mammal and non-passerine bird species in each of the seasons of data collection, while our community models estimated between 24 and 33 mammal and non-passerine bird species in each season. Small, cryptic species were not reliably captured by camera traps, limiting our ability to model their occupancy. We identified five species: raccoons (Procyon lotor), eastern gray squirrels (Sciurus carolinensis), red foxes (Vulpes vulpes), Virginia opossums (Didelphis virginiana), and white-tailed deer (Odocoileus virginianus) found in all neighborhoods. The most common covariate included in our final occupancy models was the percent of area within each neighborhood that was an impervious surface, which positively affected occupancy for some species, and negatively affected occupancy for others. Forest cover, the second most common variable in our final models, negatively affected occupancy for all species. Our estimates characterize a baseline for quantifying species richness and composition in residential areas of Dutchess County, NY and surrounding regions, and offer a comparison to similar studies in natural areas. Overall, the results improve understanding of how residential landscapes affect individual species and communities.
... We calculated the relative abundance index (RAI) as: RAI = (E/TN) * 1000, where E is the number of events and TN is the total number of trap nights (Allen et al. 2019) We used RAI because it is considered an accurate index of abundance (Parsons et al. 2017;Palmer et al. 2018;Bengsen et al. 2022) or site use (Sollmann 2018; though see Stewart et al. 2018). While RAI is subject to various forms of bias (Sollman et al. 2013;Anile and Devillard 2015;Innarilli et al. 2021), RAI may be useful for simplistic assessment of differences in relative abundance for species and assessing changes in time for particular speciesespecially if using similar methodology year after year (Wearn and Glover 2017). ...
... If the aim is to study population dynamics, for instance by means of time series analyses (Barraquand et al., 2017;Cornulier et al., 2013;Stenseth, 1999), simple indices of abundance can be used if there is a proportionate relationship between true abundance and the abundance index (Gilbert et al., 2021;Hanski et al., 1994;Lambin et al., 2000;Yoccoz et al., 2001). Counts of motiontriggered photos appear to be a promising abundance index for large-to medium-sized mammals (Palmer et al., 2018). Recent studies suggest that this may also be the case for some small rodent species (Parsons et al., 2021;Villette et al., 2015). ...
Camera traps have become popular labor‐efficient and non‐invasive tools to study animal populations. The use of camera trap methods has largely focused on large animals and/or animals with identifiable features, with less attention being paid to small mammals, including rodents. Here we investigate the suitability of camera‐trap‐based abundance indices to monitor population dynamics in two species of voles with key functions in boreal and Arctic ecosystems, known for their high‐amplitude population cycles. The targeted species—gray‐sided vole (Myodes rufocanus) and tundra vole (Microtus oeconomus)—differ with respect to habitat use and spatial‐social organization, which allow us to assess whether such species traits influence the accuracy of the abundance indices. For both species, multiple live‐trapping grids yielding capture‐mark‐recapture (CMR) abundance estimates were matched with single tunnel‐based camera traps (CT) continuously recording passing animals. The sampling encompassed 3 years with contrasting abundances and phases of the population cycles. We used linear regressions to calibrate CT indices, based on species‐specific photo counts over different time windows, as a function of CMR‐abundance estimates. We then performed inverse regression to predict CMR abundances from CT indices and assess prediction accuracy. We found that CT indices (for windows maximizing goodness‐of‐fit of the calibration models) predicted adequately the CMR‐based estimates for the gray‐sided vole, but performed poorly for the tundra vole. However, spatially aggregating CT indices over nearby camera traps enabled reliable abundance indices also for the tundra vole. Such species differences imply that the design of camera trap studies of rodent population dynamics should be adapted to the species in focus, and adequate spatial replication must be considered. Overall, tunnel‐based camera traps yield much more temporally resolved abundance metrics than alternative methods, with a large potential for revealing new aspects of the multi‐annual population cycles of voles and other small mammal species they interact with. Camera traps provide a non‐invasive and labor‐efficient method for year round monitoring of wildlife. Here we validate abundance indices from tunnel‐based camera traps for two common cyclic species of small rodents. This work paves the way for camera traps to be included in year round monitoring programs of small rodents.
... where D is the number of detections of a given species at a given site and TN is the total number of trap nights that the camera trap at that site was active (Jenks et al. 2011;Farmer and Allen 2019). RAI is a more accurate indicator of both abundance (Palmer et al. 2018; ...
While protected areas are often considered strongholds for wildlife populations, recent research in protected areas has highlighted that both human activity (i.e. presence) and footprint (i.e. structures) can influence wildlife. To determine how human activity and structures affect the spatiotemporal activity of wildlife on the Apostle Islands National Lakeshore, Wisconsin, United States, we monitored the carnivore community for 5 years (2014–2018) using camera traps. We found that lighthouses had a negative impact on carnivore community richness, while historical sites had a positive impact. Responses of individual carnivore species to anthropogenic structures varied depending on structure type, with most of the canids and mustelids exhibiting negative associations with campgrounds. When examining the seasonal effects of human activity and footprint (i.e., when park visitation is relatively high or low), we found that carnivore richness was lower during the high human activity season, suggesting that seasonal variation in human activity influences carnivore activity. We also compared carnivore nocturnality along a gradient of anthropogenic activity, but our results indicate that the carnivore community did not become more nocturnal with increasing anthropogenic activity as expected. However, the carnivore community did display spatial avoidance of current anthropogenic structures, especially campgrounds. Our study indicates that human footprint in the form of structures and seasonal variation in human activity can influence wildlife activity within protected areas. Based on this study, species-specific research that includes multiple representations of potential human effects (i.e., including categories of human footprint and activity) will allow for a more nuanced and cohesive understanding of the impacts of humans on the spatial and temporal distributions of wildlife species.
... Camera trapping is considered a superior sampling tool when compared with alternative methods, such as live traps or scat surveys, due to their ability to efficiently detect a high number of species and generate a large number of detections for individual species (Wearn and Glover-Kapfer 2019). Camera traps are particularly useful in determining animal occupancy (Gálvez et al. 2016), creating species inventories (Silveira et al. 2003), estimating abundance indices (Palmer et al. 2018), and increasing understanding of population dynamics (Karanth et al. 2006). However, these techniques generally depend on reliable and accurate classification of animals at either the species, sex, age, or individual level (Rovero et al. 2013). ...
Use of camera trap data in wildlife research is reliant on accurate classification of animals at the species, sex–age category or individual level. One such example is white-tailed deer (Odocoileus virginianus) camera surveys, which are often conducted to produce demographic estimates used by managers to establish harvest goals for a population. Previous research suggests that misclassification of deer by sex–age category (e.g. adult male, adult female, fawn) is common in these surveys, and represents a source of bias that could misinform important management decisions. To examine whether training material has an effect on classification accuracy of white-tailed deer and explore other observer-based, experiential factors as they relate to classification accuracy. We developed and tested the efficacy of species-specific training material designed to reduce sex–age misclassifications associated with white-tailed deer images. Exposure to training material resulted in the greatest improvement in classification accuracy of deer images compared with any other respondent-based factors we investigated. Other factors, such as professional experience as a wildlife biologist, field experience viewing white-tailed deer and experience viewing deer images from camera traps, were positively associated with classification accuracy of deer images. Our findings suggest that training material has the ability to reduce misclassifications, leading to more accurate demographic estimates for white-tailed deer populations. We also found that prior experience using camera traps and familiarity with target species was positively related to classification accuracy. Species-specific training material would provide a valuable resource to wildlife managers tasked with classifying animals at the species, sex–age category or individual level.
... Camera traps were deployed in either the spring (March-May) or fall (October-December) of 2018 and a total of 30 and 31 locations (total = 61 unique locations) were surveyed for each season, respectively. Camera trap data are commonly used to calculate a relative abundance index (RAI) for the target species, typically calculated as the number of observations per camera trap days (O'Brien et al. 2003;Palmer et al. 2018). As the number of camera trap days was standardized (2 weeks) across all survey locations for this study, we calculated the relative abundance of wild pigs at each site by averaging the total number of camera captured observations by the number of cameras deployed at each survey location. ...
Background
Non-native wild pigs ( Sus scrofa ) threaten sensitive flora and fauna, cost billions of dollars in economic damage, and pose a significant human–wildlife conflict risk. Despite growing interest in wild pig research, basic life history information is often lacking throughout their introduced range and particularly in tropical environments. Similar to other large terrestrial mammals, pigs possess the ability to shift their range based on local climatic conditions or resource availability, further complicating management decisions. The objectives of this study were to (i) model the distribution and abundance of wild pigs across two seasons within a single calendar year; (ii) determine the most important environmental variables driving changes in pig distribution and abundance; and (iii) highlight key differences between seasonal models and their potential management implications. These study objectives were achieved using zero-inflated models constructed from abundance data obtained from extensive field surveys and remotely sensed environmental variables.
Results
Our models demonstrate a considerable change in distribution and abundance of wild pigs throughout a single calendar year. Rainfall and vegetation height were among the most influential variables for pig distribution during the spring, and distance to adjacent forest and vegetation density were among the most significant for the fall. Further, our seasonal models show that areas of high conservation value may be more vulnerable to threats from wild pigs at certain times throughout the year, which was not captured by more traditional modeling approaches using aggregated data.
Conclusions
Our results suggest that (i) wild pigs can considerably shift their range throughout the calendar year, even in tropical environments; (ii) pigs prefer dense forested areas in the presence of either hunting pressure or an abundance of frugivorous plants, but may shift to adjacent areas in the absence of either of these conditions; and (iii) seasonal models provide valuable biological information that would otherwise be missed by common modeling approaches that use aggregated data over many years. These findings highlight the importance of considering biologically relevant time scales that provide key information to better inform management strategies, particularly for species whose ranges include both temperate and tropical environments and thrive in both large continental and small island ecosystems.
... Gathering accurate information of the population-level response of animals to the human-ecosystem edge is challenging. Camera traps have become a popular and versatile tool for ecological studies due to their relatively low cost and ability to sample continuously over long periods of time, which allows robust estimation of the distribution and abundance of animals (Henschel & Ray, 2003;Palmer et al., 2018;Pettorelli et al., 2010;Silveira et al., 2003). The increased use of camera traps has resulted in acquisition of millions of images (Swinnen et al., 2014) rendering conventional (expert annotation) image processing protocols infeasible. ...
Human activities are transforming landscapes and altering the structure and functioning of ecosystems worldwide and often result in sharp contrasts between human‐dominated landscapes and adjacent natural habitats that lead to the creation of hard edges and artificial boundaries. The configuration of these boundaries could influence local biotic interactions and animal behaviours.
Here, we investigate whether boundaries of different degrees of ‘hardness’ affect space utilization by migratory species in Serengeti National Park, Tanzania. We deployed camera traps along transects perpendicular to the national park boundary at three different locales. The transects were located in areas that consisted of two types of human–wildlife interface: a sudden transition from the national park into agro‐pastoral land use (termed a ‘hard’ boundary) and a more gradual transition mediated by a shared usage area (termed a ‘soft’ boundary).
Camera traps were placed at 2 km intervals along each 10 km transect from the edge towards the core of the park and were programmed to collect images hourly between dawn and dusk between June 2016 and March 2019. We used a deep neural network to detect the presence of wildlife within images and then used a Bayesian model with diffuse priors to estimate parameters of a generalized linear model with a Bernoulli likelihood. We explored the binomial probability of either wildebeest or zebra presence as a function of distance to the boundary, the rate of grass greening or drying (dNDVI) and the concentration of grass protein.
There was a strong negative effect of distance to boundary on the probability of detecting wildebeest or zebra; however, this was only observed where the transition from human‐dominated landscape to protected areas was sudden. Conversely, soft boundaries had little to no effect on the probability of detecting wildebeest or zebra. The results suggest that boundary type affects migratory species occurrence.
The implications of these findings suggest that hard boundaries reduce the effective size of conservation areas; for many species, the area used by wildlife is likely less than the gazetted area under protection. The impacts may be severe especially for narrow protected areas or dispersal corridors.
... Here, the sum of independent capture events d i of species i multiplied by 100, and then divided by total effective trap nights at the ith location, tn i . RAI gives an estimation of overall abundance for a species in a particular area as both are linearly correlated (Azlan & Sharma 2006, Jenks et al. 2012, Palmer et al. 2018. ...
Riparian, hilly, trans-border mixed-evergreens of eastern Bangladesh and Tripura, India, present an uncharted territory where carnivore research is non-existent. To address the issue, in 2018–2019 and 2020–2021, we conducted camera-trapping in three reserve forests that also hold protected areas, PAs: Raghunandan Hill Reserve (RHR, category II PA), Tarap Hill Reserve (THR, category IV PA and Key Biodiversity Area), and West Bhanugach Reserve (WBR, category II PA). We surveyed RHR in both rounds; THR and WBR in 2020–21. Herein, by sampling for 4,216 trap nights, we present our observations on the movement of the leopard cat Prionailurus bengalensis. We obtained 128 notionally independent capture events of the species (99 in RHF, 28in THR, 1 in WBR; 56 in 2018–2019, 72 in 2020–2021); of which, 16 capture events (8 in RHF, 8 in THR) were of mother-and-cubs. We made an inter-site comparison, also compared the activities of single individuals to that of mother-and-cubs. In RHR, we observed cats’ responses to human activity and free-roaming livestock. Altogether, the cat appeared nocturnal with a bimodal crepuscular activity peak. We observed diurnal activities (13:30–16:00 h); however, mother-and-cubs exhibited strict avoidance. In 2020–21, anthropogenic movement skyrocketed in RHR; in response, the cat reduced its activity at dawn and showed a night-time peak. This work is the second only on leopard cats in Bangladesh, and a first in the region. The finding, despite showcasing breeding populations, is a testament to man-made impacts on small cats. We suggest a yearly camera-trapping programme, and a curb on anthropogenic movement as eastern forests are subject to heavy, unmonitored usage.
... The Relative Abundance Index (RAI) is used to depict the photographic capture rates of species which may or may not have natural markings on their bodies for individual identification. The variation of RAI provided by Carbone et al. (2001) has been followed by a wide variety of studies (Datta et al. 2008;Jenks et al. 2011;O'Brien et al. 2003;Palmer et al. 2018). Hence, in order to analyze the annual and seasonal trends of animal movement in the corridor patch, the RAI was calculated by using the formula: N × 100/A; where N is the number of events the individual species was captured by the camera trap, multiplied by 100 and divided by A, which is equal to the total number of trap days (total number of trap days = number of camera traps × number of active days). ...
To assess the corridor's functionality and prioritize protection of one of the corridors connecting Kaziranga National Park and the forests of Karbi Anglong District in Assam, India, we conducted a camera-trap study from 2011 to 2016. A total of 10,895 trap nights revealed 39 mammal and avian species, several of which were new records for the area. Relative Abundance Index was calculated as a measure of photo-capture rates from the photographic events, and annual trend for selected species and seasonal trend for elephants were analyzed. The indices showed that elephants used the corridor patch most frequently (RAI = 8.81), followed by hog deer (RAI = 2.77), while hog badgers were most rarely recorded (RAI = 0.02). Seasonality of the movement pattern of elephants showed increased use during the monsoon season. Records of nine individual tigers and six individual leopards, along with other rare and endangered species indicate functionality and regular use of the critical corridor by wildlife, crossing over between Kaziranga and Karbi Anglong hills, maneuvering through the busy National Highway-37 that cuts across the historically connected landscape. The results obtained from the study can be used to prepare a conservation action strategy to secure the corridor for safe passage of wildlife.
... Due to the difficulty of estimating true abundance of species at a national scale and for species which individuals are not uniquely identifiable, we used RAB that offers a simple and accurate index of abundance ), but does not account for potential bias arising from imperfect detection (Palmer et al. 2018). ...
Mammalian carnivores are elusive and enigmatic species that often play keystone roles in ecosystems through direct and indirect effects. Growing evidence shows that human activity can impact carnivore behavior and community structure by altering predator-prey interactions, shifting diel activity patterns, and altering wildlife movement. Our goal was to investigate the ecological role of bobcats (Lynx rufus) across carnivore communities in the continental USA by quantifying variation in spatiotemporal patterns and determining what environmental and human factors influenced carnivore community interactions. Using camera trap data from the inaugural nationwide Snapshot USA project dataset collected from September-October 2019, we constructed diel activity density curves, applied multispecies occupancy models, and calculated attraction-avoidance ratios. Our results suggest that bobcats display the greatest flexibility in their diel activity among the suite of carnivores sampled. Further, bobcats respond differentially at large spatial scales relative to the presence of dominant or subordinate carnivores, with fluctuating impacts mediated by human and environmental factors. Bobcats' co-occurrence with dominant carnivores (i.e., wolves Canis sp., pumas Puma concolor) was influenced primarily by human-related factors, whereas co-occurrence with subordinate carnivores (i.e., foxes) was more influenced by environmental factors (i.e., precipitation, gross primary production [GPP]). Bobcats appear to interpret humans as the apex predator on the landscape regardless of the presence of dominant or subordinate species. Understanding the influence of humans as "super predators'', as well as the importance of environmental factors that impact intraguild carnivore interactions across the USA is critical for establishing successful management practices to promote functioning communities.
... Each of the 24 does sourced from a captive breeding facility cost $3,500, a price we believe fairly represents this category of deer marketed in the region and time that this study was conducted. Camera traps are particularly useful in determining animal occupancy (Gálvez et al. 2016), creating species inventories (Silveira et al. 2003), estimating abundance indices (Palmer et al. 2018), and increasing understanding of population dynamics (Karanth et al. 2006). However, these techniques generally depend on reliable and accurate classification of animals at either the species, sex, age, or individual level (Rovero et al. 2013). ...
Thousands of captive white-tailed deer (Odocoileus virginianus) facilities exist across North America for the purpose of producing trophy-quality deer (i.e., exceptionally large-antlered). Many of these deer get marketed to private landowners with the expectation that introduced deer will enhance genetics in the population, resulting in larger-antlered male deer. Previous research suggests that white-tailed deer experience highly variable survival and reproductive success post-translocation, however, little is known about the fate of translocated white-tailed deer sourced from captive-breeding operations. We translocated 24 adult female deer over a 3-year period into a private, 300-ha high-fence enclosure in east-central Alabama. We monitored survival, reproductive success, and fawn recruitment of the translocated deer using VHF radio collars and vaginal implant transmitters (VITs). We found that survival rates were greater than studies where deer were translocated from the wild, but fawn survival and recruitment was poor. We believe our findings provide a baseline of expectations for captive deer translocations. Our following research objectives focus on improving camera survey output for white-tailed deer by reducing sex-age misclassifications. Previous research suggests that misclassifications may be an important source of error in wildlife camera surveys. We developed and tested the effects of species-specific training material designed to reduce sex-age misclassification associated with white-tailed deer images. We found exposure to training material produced the greatest significant improvement on classification accuracy of deer images compared to any other respondent-based factors we investigated. We also found that other experiential factors were positively associated with classification accuracy of deer images. Our findings suggest that use of species-specific training material can reduce misclassifications, leading to more reliable data.
... The majority ( (Liu et al., 2013;Palmer et al., 2018;Stein et al., 2008) and increase the level of replication per sample site, which is likely to increase the detection probability of rare species. ...
Fauna monitoring often relies on visual monitoring techniques such as camera trapping , which have biases leading to underestimates of vertebrate species diversity. Environmental DNA (eDNA) metabarcoding has emerged as a new source of biodiversity data that may improve biomonitoring; however, eDNA-based assessments of species richness remain relatively untested in terrestrial environments. We investigated the suitability of fallen log hollow sediment as a source of vertebrate eDNA, across two sites in southwestern Australia-one with a Mediterranean climate and the other semi-arid. We compared two different approaches (camera trapping and eDNA meta-barcoding) for monitoring of vertebrate species, and investigated the effect of other factors (frequency of species, timing of visits, frequency of sampling, and body size) on vertebrate species detectability. Metabarcoding of hollow sediments resulted in the detection of higher species richness in comparison (29 taxa: six birds, three reptiles , and 20 mammals) to metabarcoding of soil at the entrance of the hollow (13 taxa: three birds, two reptiles, and eight mammals). We detected 31 taxa in total with eDNA metabarcoding and 47 with camera traps, with 14 taxa detected by both (12 mammals and two birds). By comparing camera trap data with eDNA read abundance, we were able to detect vertebrates through eDNA metabarcoding that had visited the area up to two months prior to sample collection. Larger animals were more likely to be detected, and so were vertebrates that were identified multiple times in the camera traps. These findings demonstrate the importance of substrate selection, frequency of sampling, and animal size, on eDNA-based monitoring. Future eDNA experimental design should consider all these factors as they affect detection of target taxa.
... We also calculated the Relative abundance Indices (RAI) for humans per site as covariates. RAI was calculated as RAI = E/TNx100, where E is the number of events (photo-captures), and TN is the total number of trap nights [52]. We used the RAI of a hyena (i.e., detection rate) per camera trap station as a response variable, while landscape and anthropogenic variables as a predictor variable. ...
Understanding the mechanism of coexistence, where carnivores adapt to humans and vice versa in the shared landscape, is a key determinant of long-term carnivore conservation but is yet to be comprehensively examined. We explored the coexistence mechanism of striped hyena (Hyaena hyaena) and humans in the shared landscape of Sawai Mansingh Wildlife Sanctuary (SMS WLS), Rajasthan, from November 2019 to March 2021. We used data derived from motion sensors-based surveys, satellite remote sensing images, and household questionnaires to understand socio-ecological, environmental and anthropogenic factors facilitating hyena persistence in the shared landscape. The high density (12 individuals/ 100 km 2) striped hyena in the landscape revealed the coexistence with humans. Being scavengers , they get subsidised food sources and are perceived as low-risk species by humans. Striped hyena minimised temporal activity during the daytime when human activity peaked. However, the highest activity overlap was observed in the agricultural area (Δ1 = 0.39), and likely depicts the high activity due to agricultural practices. While the human settlement was positively associated with the detection of hyenas, the probability of striped hyena captures increased with decreasing distance from human settlement, possibly influenced by high carcass availability, providing the easiest food resources to striped hyena, and allowing them to coexist with humans. This study demonstrates the coexistence of hyenas and humans in the shared landscape supported by mutual benefits, where hyenas benefit from anthropo-genic food from scavenging, while humans benefit from waste removal and the non-lethal nature hyenas.
... (R Core Team, 2020). We calculated the Relative Abundance Index (RAIs) for all identified meso-mammals as the number of videos obtained for each species, divided by the overall number of camera days (Rovero et al., 2010;Palmer et al., 2018). We excluded multiple capture events of the same species on the same camera day from analyses. ...
Vast stretches of East and Southern Africa are characterized by a mosaic of deciduous woodlands and evergreen riparian forests, commonly referred to as “miombo,” hosting a high diversity of plant and animal life. However, very little is known about the communities of small-sized mammals inhabiting this heterogeneous biome. We here document the diversity and abundance of 0.5–15 kg sized mammals (“meso-mammals”) in a relatively undisturbed miombo mosaic in western Tanzania, using 42 camera traps deployed over a 3 year-period. Despite a relatively low diversity of meso-mammal species (n = 19), these comprised a mixture of savanna and forest species, with the latter by far the most abundant. Our results show that densely forested sites are more intensely utilized than deciduous woodlands, suggesting riparian forest within the miombo matrix might be of key importance to meso-mammal populations. Some species were captured significantly more often in proximity to (and sometimes feeding on) termite mounds (genus Macrotermes), as they are a crucial food resource. There was some evidence of temporal partitioning in activity patterns, suggesting hetero-specific avoidance to reduce foraging competition. We compare our findings to those of other miombo sites in south-central Africa.
... Early applications focused on species with marked populations and applied well-established capture-recapture techniques to estimate population size (Karanth & Nichols, 1998). However, individual identification is impossible or impractical for many applications and species (Palmer et al., 2018;Rayan et al., 2012), warranting alternative approaches. Methods proposed to allow estimation of abundance for unmarked animal populations include space-to-event (Moeller et al., 2018), distance sampling (Howe et al., 2017), and spatial count models (Chandler & Andrew Royle, 2013;Gilbert et al., 2021). ...
Estimating animal abundance and density are fundamental goals of many wildlife monitoring programs. Camera trapping has become an increasingly popular tool to achieve these monitoring goals due to recent advances in modeling approaches and the capacity to simultaneously collect data on multiple species. However, estimating the density of unmarked populations continues to be problematic due to the difficulty in implementing complex modeling approaches, low precision of estimates, and absence of rigor in testing of model assumptions and their influence on results. Here, we describe a novel approach that uses still image camera traps to estimate animal density without the need for individual identification, based on the time spent in front of the camera (TIFC). Using results from a large‐scale multispecies monitoring program with nearly 3000 cameras deployed over 6 years in Alberta, Canada, we provide a reproducible methodology to estimate parameters and we test key assumptions of the TIFC model. We compare moose (Alces alces) density estimates from aerial surveys and TIFC, including incorporating correction factors for known TIFC assumption violations. The resulting corrected TIFC density estimates are comparable to aerial density estimates. We discuss the limitations of the TIFC method and areas needing further investigation, including the need for long‐term monitoring of assumption violations and the number of cameras necessary to provide precise estimates. Despite the challenges of assumption violations and high measurement error, cameras and the TIFC method can provide useful alternative or complementary animal density estimates for multispecies monitoring when compared to traditional monitoring methods.
... For each species, we calculated a relative abundance index (RAI) as the total number of independent photographs divided by the total number of working camera days over the course of the survey. Simple RAI-based approaches yielded relative abundance estimates that correlated strongly with independent estimates of animal abundance for large mammals [30]. ...
Do hotspots of plant biodiversity translate into hotspots in the abundance and diversity of large mammalian herbivores? A common expectation in community ecology is that the diversity of plants and animals should be positively correlated in space, as with the latitudinal diversity gradient and the geographic mosaic of biodiversity. Whether this pattern ‘scales down’ to landscape-level linkages between the diversity of plants or the activities of highly mobile megafauna has received less attention. We investigated spatial associations between plants and large herbivores by integrating data from a plant-DNA-barcode phylogeny, camera traps, and a comprehensive map of woody plants across the 1.2-km2 Mpala Forest Global Earth Observatory (ForestGEO) plot, Kenya. Plant and large herbivore communities were strongly associated with an underlying soil gradient, but the richness of large herbivore species was negatively correlated with the richness of woody plants. Results suggest thickets and steep terrain create associational refuges for plants by deterring megaherbivores from browsing on otherwise palatable species. Recent work using dietary DNA metabarcoding has demonstrated that large herbivores often directly control populations of the plant species they prefer to eat, and our results reinforce the important role of megaherbivores in shaping vegetation across landscapes.
... Capture probability can be modeled as a function of social parameters such as sex and then added to a complete density model later in the analysis (Foster and Harmsen 2012). Clan and/or territory sizes in a study area should also be included as covariates that may influence capture probability, as seen in other camera trap studies of ungulates (Massei et al. 2018;Palmer et al. 2018). Clan size can be estimated by assessing the gradual increase (and asymptotic stagnation) in the number of different hyenas detected in a territory (Stratford et al. 2020). ...
The use of remote camera traps has accelerated rapidly in the field of large carnivore science since the 1990s. Members of the Hyaenidae are important components of functional ecosystems in Africa and parts of the Middle East and South Asia, and make good candidates for study using camera traps. However, camera trap studies of hyenas remain rare in the literature when compared to species like tigers Panthera tigris, leopards Panthera pardus, and snow leopards Panthera uncia. In this paper, we examine the published use of camera traps for hyenas (n = 34 studies implemented between 2007 and 2020) and examine the logistical challenges of using camera traps, such as individual identification, limited sexual dimorphism, and complex social structures, for studies of hyena population biology, behavioral ecology, and conservation. We highlight what these challenges may mean for data analyses and interpretation. We also suggest potential benefits of further camera trap studies of this taxonomic family, including new insights into social behavior, range extensions, and robust density estimates.
... Knowledge of species abundance is necessary for decision making in biological management and conservation and for understanding the dynamics of population (Yin and He, 2014). Estimating abundance helps in setting hunting quotas, gauging prey availability for carnivores and managing wildlife areas for tourism (Palmer et al., 2018). Conservation efforts are assessed by using abundance estimates, it also provides insight into how a community functions (Danell et al., 2006;Verberk, 2011;Cox et al., 2017). ...
Chitral Gol National Park (CGNP) harbors a large number of mammals. However, population size, estimated density or any other ecological parameter is not available for those species except annual census counts for markhor Capra falconeri. Management and conservation efforts are assessed by using relative abundance estimates. The current study aimed to estimate relative abundance of mammalian fauna of CGNP. During the current study, 30 camera traps (motion triggered camera (Reconyx™) with infrared flash were deployed for a period of 47 days. The survey resulted in 1052 functional trap nights obtaining 5906 photographs. Results of the study show that large carnivores like common leopard, grey wolf, Himalayan lynx are present in the National Park. Snow leopard which used to be a symbol of fame for the National Park was not detected in the current study. Among other meso-carnivores golden jackal, leopard cat and red fox were also captured at different stations while small mammals included stone marten, Kashmir flying squirrel, Himalayan wood mouse, and golden marmot. Relative abundance of markhor (RAI= 49.631), cape hare (RAI= 23.832) and red fox (RAI= 6.879) were found to be higher as compared to other species. Relative abundance of other mammals like common leopard, leopard cat, grey wolf, golden marmot and Himalayan wood mouse was lower than one. Overall, 13 mammal species were recorded during the study whereas some of the previously reported species were not detected. This may probably be due to single season survey; conducting a multi-season camera trapping and targeting all different types of microhabitats is recommended for future studies.
... The capture frequency of the camera trap data was used as a RAI, which was calculated as the number of captured species per camera trap days (i.e., number of cameras times with number of operational days; Carbone et al., 2002). We followed published guidelines of Carbone et al. (2002) and Palmer et al. (2018) to calculate RAI for Crab-eating mongoose. ...
Small carnivores are able to adapt to patchy forests and human dominated landscape in proximity to water sources. Small carnivore’s population is declining due to anthropogenic effects, and in most of the areas, their occurrence is little known. We aimed to identify the spatial occurrence of crab-eating mongoose, the factors affecting the occurrence of species and coexistence with other species using camera trap. The crab-eating mongoose mostly preferred the shrub-land habitat (65%) and followed by agriculture land, forest and grassland. Almost all preferred habitats were near to water sources. The occurrence of crab-eating mongoose was influenced by human disturbances. Their occurrences were decreased with increasing disturbances. In addition, the crab-eating mongoose’s occurrence was also decreased with increasing distance to water sources. The movement activities of crab-eating mongoose were varied according to time period (F = 6; df = 14; p < 0.013), and was mostly active at day to mid-night (16.00 to 12.00 hours) and mid-night to early morning (12.00 to 8.00 hours). The crab-eating mongoose co-exists with other carnivores including Leopard, Jungle cat, Masked-palm civet, Small Indian mongoose, Leopard cat, Yellow-throated martin, and Large Indian civet. In addition, its occurrence was affected by human interference. The data available from this study can be used to develop site/species-specific conservation plans that aid stewardship for biodiversity conservation.
... To avoid pseudo-replication, we defined an event as any photo-series of a species and considered subsequent photos of the same species within 30 minutes of a previous photo to be the same event (O'Brien et al., 2003;Naing et al. 2015;Allen et al. 2019). We calculated the relative abundance index (RAI) as: RAI = (E/TN) * 1000, where E is the number of events and TN is the total number of trap nights (Allen et al. 2019) We used RAI because it is considered an accurate index of abundance (Parsons et al. 2017;Palmer et al. 2018) or site use (Sollmann 2018; though see Stewart et al. 2018). For individual identification of jaguars, E.R. Olson identified individuals based on spot patterns and other physical features, and determined sex based on the presence of male genitalia (Harmsen et al. 2017). ...
... The rapid development and improvement of camera traps, as well as analytical frameworks to process data generated from cameras, makes them an important tool to inform conservation decision-making (Gilbert, Clare, Stenglein & Zuckerberg, 2021). For example, camera-trap data can be used to estimate the density and relative abundance indices of a given species even if individuals are unmarked (Palmer, Swanson, Kosmala, Arnold & Packer, 2018;Gilbert et al., 2021). Volunteers can identify oribi captured in images and selected images can be verified by experts, akin to Snapshot Serengeti (Swanson, Kosmala, Lintott & Packer, 2016). ...
Effective monitoring programmes are critical to understand and mitigate declining wildlife populations. In South Africa, the majority of oribi antelope (Ourebia ourebi ourebi ) occur on private rangelands as broadly distributed and highly-fragmented populations. Thus, to effectively manage such a species, conservation organizations rely on citizen science-led conservation initiatives, whereby members of the public provide data on oribi population demographics and potential threats. Using these data, we estimated the total oribi population size and assessed the population trend of oribi in KwaZulu-Natal, South Africa, over a 14-year period (2001–2014). We found that the oribi population has declined by 30% over the 14 years. However, oribi population estimates were highly correlated with the number of returned survey forms. This relationship makes it difficult to accurately assess population trends and almost impossible to determine if any changes in conservation management have influenced oribi populations. Thus, issues associated with citizen science and data quality (i.e. participation levels), may limit the ability of the oribi census to accurately inform oribi conservation and management. We discuss the value and limitations of citizen science in oribi conservation with the ultimate goal of improving citizen-led oribi conservation.
... Here, the sum of independent detections d i of species i multiplied by 100, and then divided by total effective trap nights at the ith location, tn i . RAI gives an estimation of overall abundance for a species in a particular area as both are linearly correlated (Azlan and Sharma 2006;Jenks et al. 2012;Palmer et al. 2018). ...
Bangladesh holds 191 km2 semi-evergreen northeastern (NE) forests where systematic
camera-trapping has never been carried out. An effort of 587 trap nights in Satchari National Park,
a NE forest, revealed ten carnivores, two ungulates, two primates, two rodents, and one treeshrew
(12 threatened in Bangladesh; of which three globally threatened; dhole and northern treeshrew were
new discoveries). Pairwise circadian homogeneity, coefficient of temporal overlap (Δ̂ ), and spatial
cooccurrence pattern were measured. High values (Δ̂ > 0.75) were noted in 36 pairwise comparisons,
and positive spatial association (Pgt < 0.05) in five. Anthropogenic activities overlapped with diurnal
species
(0.65 ≤ Δ̂ 1 ≤ 0.88) but stood dissimilar (P < 0.05 in the Mardia-Watson-Wheeler test) except
for yellow-throated marten–livestock movement (Δ̂ 1 = 0.70). Although species-specific dietary or
temporal
preference explains the observed associations, low detection of the jungle cat (2) compared
to the leopard cat (56), absence of the fishing cat, homogenous activity (P > 0.05) in yellow-throated
marten–crab-eating mongoose (Δ̂ 1 = 0.83) and rhesus macaque–pig-tailed macaque (Δ̂ 4 = 0.93) pairs
need further research. These insights are remarkable as NE forests, the western cusp of the Indo-Burma
biodiversity hotspot, are contrarily deemed ‘empty’, receiving least scientific investments.
... We considered animal detections to be independent if the time between consecutive images or photos of the samespecies was more than 30 min apart. Photos with more than one individual in the frame were counted as one detection for the species (Palmer et al., 2018). We assessed the conservation status of each mammal species included in our study by referencing the IUCN Red List website (https://www.iucnredlist. ...
Due to recent socio-political unrest in Côte d’Ivoire, information data gaps of mammals, including the western roan antelope (Hippotragus equinus koba), have persisted. This study therefore aims at measuring the diversity and population status of mammals and their relative abundance at Mount Sangbé National Park (MSNP for conservation. We conducted camera trapping surveys from February until May 2018 at two sites in the northern and eastern sections of MSNP. After 731 trap days, we confirmed the presence of H. Equinuskoba and 26 other mammals’ species belonging to five Orders: Cetartiodactyls, Carnivores, Primates, Rodents, and Tubulidentata with 15, five, four, two, and one species observed within the orders, respectively. The roan antelope occurred in the surveyed sites with a Relative Abundance Index (RAI) of 8.91 and 0.27, respectively. The RAI varied among three species: Potamochoerus porcus, Tragelaphus scriptus,
and Philantomba maxwellii which we found to have relatively high RAI values of 11.76, 10.67, and 10.40, respectively. Alpha diversity indices differed between the woodland and savanna habitats in species richness (p<0.001), in their Shannon indices (p<0.001), in their dominance indices (p<0.001) and for the equitability index (p=0.008). Similarly, we found differences between the dry forest and savanna habitats in species
richness (p<0.001), Shannon indices (p<0.001), in dominance indices (p<0.001), but no difference the equitability indices of these habitats (p=0.424). We recommend further studies in all habitat types of the entire park to better understand the population status of mammals inhabiting MSNP in order to ensure the conservation of its biodiversity.
... Early applications focused on species with marked populations and applied well-established capture-recapture techniques to estimate population size (Karanth and Nichols, 1998). However, individual identification is impossible or impractical for many applications and species (Rayan et al., 2012;Palmer et al., 2018), warranting alternative approaches. Methods proposed to allow estimation of abundance for unmarked animal populations include space-to-event (Moeller et al., 2018), distance sampling (Howe et al., 2017) and spatial count models (Chandler and Royle, 2013;Gilbert et al., 2021). ...
Estimating animal abundance and density are fundamental goals of many wildlife monitoring programs. Camera trapping has become an increasingly popular tool to achieve these monitoring goals due to recent advances in modeling approaches and the capacity to simultaneously collect data on multiple species. However, estimating the density of unmarked populations continues to be problematic due to the difficulty in implementing complex modeling approaches, low precision of estimates, and absence of rigor in testing of model assumptions and their influence on results. Here, we describe a novel approach that uses still image camera traps to estimate animal density without the need for individual identification, based on the Time spent In Front of the Camera (TIFC). Using results from a large-scale multi-species monitoring program with nearly 3,000 cameras deployed over six years in Alberta, Canada, we provide a reproducible methodology to estimate parameters and we test key assumptions of the TIFC model. We compare moose (Alces alces) density estimates from aerial surveys and TIFC, including incorporating correction factors for known TIFC assumption violations. The resulting corrected TIFC density estimates are comparable to aerial density estimates. We discuss the limitations of the TIFC method and areas needing further investigation, including the need for long-term monitoring of assumption violations and the number of cameras necessary to provide precise estimates. Despite the challenges of assumption violations and high measurement error, cameras and the TIFC method can provide useful alternative or complementary animal density estimates for multi-species monitoring when compared to traditional monitoring methods.
... Additionally, we calculated the relative abundance index (RAI) for all species as: RAI = (E/TN) × 100 days/trap, where E is the number of events photographed, TN is the total number of trap nights and 100 trap days (Lira- Torres et al. 2014). We used RAI because it is considered an accurate index of abundance for some species (Parsons et al. 2017;Palmer et al. 2018). However, the use of this index without calibration and its comparison across time, space, or species is extremely problematic (O'Brien 2011); as a consequence, the use of the RAI can lead to erroneous conclusions about species abundance (Sunarto et al. 2013). ...
La Encrucijada Biosphere Reserve (REBIEN) and Puerto Arista Estuarine System (SEPA) are natural protected areas and Ramsar sites in Chiapas, Mexico. In this study, we conducted an inventory of medium-sized and large mammals using camera trapping. We recorded 23 species in the REBIEN and 13 species in the SEPA. In addition, 35% of the species recorded in the two sites are at some category of risk of extinction at the national or international level. The most abundant species in the REBIEN were Northern Raccoon ( Procyon lotor (Linnaeus, 1758)) and White-Nosed Coati ( Nasua narica (Linnaeus, 1766)). In the SEPA, White-tailed Deer ( Odocoileus virginianus (Zimmermann, 1780)), Collared Peccary ( Dicotyles crassus (Merrian, 1901)), and White-Nosed Coati ( Nasua narica ). Our results highlight the importance of both study sites in the conservation of medium-sized and large mammals and underline the urgent need to develop conservation strategies for these areas.
... The relative abundance index (RAI) of each species recorded by the camera traps was calculated using the ratio between the presence of the image and the total number of trap nights, which is a widely used method e.g., according to the publications of Ouboter and Kadosoe )2016(, Palmer et al. (2018( andSteinbeiser et al. (2019). The calculation uses the formula presented below. ...
Pla-ard M, Hoonheang W, Kaewdee B, Panganta T, Charaspet K, Khoiesri N, Paansri P, Kanka P, Chanachai Y, Thongbanthum J, Bangthong P, Sukmasuang R. 2021. Abundance, diversity and daily activity of terrestrial mammal and bird species in disturbed and undisturbed limestone habitats using camera trapping, Central Thailand. Biodiversitas 22: 3620-3631. This study on the abundance, diversity and daily activity of terrestrial mammal and bird species was conducted in the limestone mountainous area of Central Thailand, located on the east of Dong Phaya Yen-Khao Yai forest complex. Camera traps were placed in both habitats disturbed by limestone mining and undisturbed habitat areas. From the study, a total of 38 species of mammals and birds from 27 families in 13 orders were recorded, including 15 species of mammals from 6 orders, 12 families and 23 species of birds from 14 families in 7 orders. Fifteen species of mammals were recorded in the undisturbed area and 11 were recorded in the disturbed area, with the Malayan Pangolin, Small Indian Civet and Grey-bellied Squirrel found in the undisturbed area. However, the number of bird species in the limestone mining area was larger than in the undisturbed area. It was also found that there was no difference in the overall abundance and diversity of mammalian species between disturbed and undisturbed areas, which is not in accordance with the hypothesis. But in the case of wild birds, the relative abundance of wild birds was found to differ significantly between areas. A high number was found in the areas with mining activities, although there was no difference in the diversity index of the two areas. However, it was found that when the combined data was analyzed, there was a significant difference in the daily activity of both mammals and wild birds in both areas. Many rare wildlife species were recorded during this study, for example, the Malayan Pangolin, Serow, Northern Pig-tailed Macaque, Rufous Limestone-babbler, Golden Jackal, Leopard Cat, Large-toothed Ferret Badger, Small Asian Mongoose, Common Palm Civet, Small Indian Civet, Malayan Porcupine. The key measure proposed is to preserve some natural habitats within the areas with mining activities, as wildlife remains in the area.
Wildlife, such as non-volant mammals and birds, play a vital role in the maintenance of ecosystem health. They are considered ecological engineers that influence forest vegetation. However, due to deforestation, habitat loss, and human persecution, its population status has declined over the years. This study aimed to conduct a species inventory and assess the relative abundance of non-volant mammals and birds in the unprotected regions of the Mt. Apo Range, Philippines, through camera trapping methods. Furthermore, the anthropogenic threats observed in the study areas were also documented. A total of 1,106 camera trap days were carried out in 2016 and another 500 days in 2020. Based on 260 independent sequences for both the 2016 and 2020 surveys, 12 species were identified, consisting of eight non-volant mammals and four birds. Among the identified species are the Endangered Philippine Brown Deer Rusa marianna & Philippine Long-tailed Macaque Macaca fascicularis philippensis and the Vulnerable Giant Scops-owl Otus gurneyi & the Philippine Warty Pig Sus philippensis. Video evidence of the Philippine Warty Pig Sus philippensis performing an important ecological role as an ecological engineer in the Philippine tropical forests were also captured for the first time. Another 61 independent sequences of unidentified rodents were detected in the camera traps, requiring further species monitoring techniques. Conservation must be strengthened beyond the protected landscapes of the Mt. Apo Range through community-based forest governance. This will ensure that the forest vertebrates are protected and conserved from further anthropogenic pressures.
This handbook is an overview of density estimation using camera traps. It summarizes how 15 camera trap density models work, lists the assumptions they make and the effects of violating assumptions, lists model advantages and disadvantages, and discusses how models have performed in simulations and field tests. It also includes tools to help practitioners decide which camera trap density models are best-suited to their circumstances. Importantly, this handbook gathers all of this information in one place.
The use of species detection rates gathered from motion‐sensitive cameras as relative abundance indices (RAIs) could be a cost‐effective tool to monitor wildlife populations; however, validations based on comparisons with reference methods are necessary. We considered 3 ungulates, wild boar (Sus scrofa), roe deer (Capreolus capreolus), and fallow deer (Dama dama), and compared 2 different RAIs with independent indices of density obtained through feces counts across 3 summers (2019–2021) in a protected area of central Italy. We estimated the number of detections per day (RAIevents), and the number of individuals per day (RAIindividuals) from remote camera videos. Both indices were correlated with density estimates, yet only RAIindividuals correctly ranked interspecific densities. Values of RAIevents for the most abundant and gregarious ungulate (i.e., wild boar) were biased low and were lower than those of fallow deer. The uncertainty of RAIs was acceptable for the 2 most abundant study species (CVs ≤ 25%) but was greater for roe deer. At the intra‐specific level, density estimates and RAIs showed comparable but slight inter‐annual variation. Our results support the use of RAIs derived from motion‐sensitive cameras as a promising and cost‐effective tool to monitor ungulate populations, and researchers should incorporate group size into monitoring. We advocate the necessity of field tests based on comparison with locally reliable reference methods to validate the use of motion‐sensitive cameras. Cameras could be used to estimate relative abundance indices (RAIs) as cost‐effective tools to monitor wildlife populations, but validation tests based on comparisons with reference methods are necessary. For 3 ungulate species, we found that RAIs based on species' group size correlated with independent estimates better than traditional RAIs based on the raw count of species' detections. For gregarious species, RAIs based on camera detections should consider group size.
Analysis of spatiotemporal partitioning is pivotal to shed light on interspecific coexistence. Most research efforts have involved large-sized carnivores and their prey species, whereas little attention has been given to ungulate in the predator-free ecosystems. We assessed seasonal activity patterns and spatiotemporal overlap among the Siberian roe deer (Capreolus pygargus tianschanicus) and its sympatric species through camera-trapping from October 2017 and September 2020 in Jeju Island, South Korea. Trap events when compared seasonally, roe deer show higher activity in summer (34.9%), a pronounced low in winter (14.1%), and a moderate in autumn (23.8%) and in spring (26.9%). Roe deer exhibited bimodal activity patterns and had the highest spatiotemporal overlap and composite score with sika deer (Cervus nippon). Our results are among the few available data on the interaction of sympatric species and suggest strong overlapping with sika deer. This study provides important insight into species coexistence in predator-free habitats, which would be important for management initiatives.
The U Minh wetlands of southern Vietnam in Ca Mau and Kieng Giang provinces are a degraded, peat-swamp wetland mosaic known to retain several globally threatened species. We deployed intensive, targeted camera-traps across U Minh Thuong National Park and U Minh Ha National Park from December 2019 to May 2020, and from November 2020 to June 2021, respectively. Our aim was to detect threatened otters, wild cats, and pangolins in each protected area, to identify what potential threats they may face, and to inform conservation priorities for park managers. Our results showed that both protected areas harbour significant regionally important populations of globally threatened Sunda pangolins ( Manis javanica ), and Hairy-nosed otters ( Lutra sumatrana ). However, Fishing cats ( Prionailurus viverrinus ) and Large-spotted civet ( Viverra megaspila ) previously recorded from U Minh Thuong National Park, were not observed. Other than wide-ranging species insensitive to human disturbance (i.e., Common palm civets and Leopard cats), all small carnivores were most active in Melaleuca and swamp/ Melaleuca habitats in U Minh Thuong, and both the wetland plantations and disturbed forests of U Minh Ha according to their photographic rates. Human and domestic dogs’ activity periods in both protected areas overlapped strongly with Hairy-nosed otters, which could influence their dispersal abilities and access to resources. Furthermore, dogs in this part of southern Vietnam are often used for hunting, so there is a strong possibility the overlap could lead to deadly interactions as well. Long-term and short-term threats are discussed with relevance to U Minh ecosystem health and future recommendations.
Leitfaden zum Monitoring von Wildhuftieren.
Herausgeber: AG Wildhuftiere, Schweizerische Gesellschaft für Wildtierbiologie SGW
Layout: Claude Andrist, Wildtier Schweiz
publiziert auf:
https://mitglied.scnat.ch/sgw-ssbf/uuid/i/efa11827-3432-5984-b945-0a4da1865b57-SGW-Leitfaden_Monitoring_Wildhuftiere
Understanding the interspecific interactions (spatial and temporal) between predators and their prey species is important to understanding the prey preferences for conservation and management decisions. However, due to large predators’ wide-ranging, nocturnal, and cryptic behaviour, it is often difficult to assess their interactions with prey species. Therefore, we determined the spatial and temporal interactions of leopard (Panthera pardus) with potential prey species in Kalesar National Park (KNP) using camera traps from January 2020 to April 2020. KNP is situated in the foothills of the Shiwalik mountain range of Himalaya, North India. We used encounter rates and activity patterns to understand the spatial and temporal overlap between leopards and prey species. We used composite scores to predict the potential prey preferences using the photo-capture data. A total sampling effort of 1150 trap nights documented 92 photo-captures of leopards with a detection rate of 17.3 leopards per 100/trap nights. Leopards exhibited bimodal peaks and were active throughout the day and night but showed more diurnal activity. Leopards had the highest temporal overlap with chital (Axis axis) and wild boar (Sus scrofa) and the highest spatial overlap with wild boar, peafowl (Pavo cristatus), and sambar (Rusa unicolor). Due to their high composite scores, wild boar, sambar, peafowl, and chital were predicted the most preferred prey species for leopards. Our results suggest that effective management of preferred prey species in the area is required to ensure the conservation of the leopard population.
Globally, species extinctions are driven by multiple interacting factors including altered fire regimes and introduced predators. In flammable ecosystems, there is great potential to use fire for animal conservation, however most fire‐based conservation strategies do not explicitly consider interacting factors. In this study, we sought to understand the interrelationships between the endangered heath mouse Pseudomys shortridgei, fire, resource availability and the introduced fox Vulpes vulpes in southeast Australia. We predicted that heath‐mouse relative abundance would respond indirectly to post‐fire age class (recently burnt; 0–3 years since fire, early; 4–9 years, mid; 10–33 years and late; 34–79 years) via the mediating effects of resources (shrub cover and plant‐group diversity) and fox relative abundance. We used structural equation modelling to determine the strength of hypothesized pathways between variables, and mediation analysis to detect indirect effects. Both the cover of shrubs (0–50 cm from the ground) and fox relative abundance were associated with post‐fire age class. Shrub cover was highest 0–9 years after fire, while fox relative abundance was highest in recently burnt vegetation (0–3 years after fire). Heath mice were positively correlated with shrub cover and plant‐group diversity, and negatively correlated with fox relative abundance. We did not detect a direct relationship between heath mice and post‐fire age class, but they were indirectly associated with age class via its influence on both shrub cover and fox relative abundance. Our findings suggest that heath mice will benefit from a fire regime promoting dense shrub regeneration in combination with predator control. Understanding the indirect effects of fire on animals may help to identify complementary management practices that can be applied concurrently to benefit vulnerable species. Analytical and management frameworks that include multiple drivers of species abundance and explicitly recognize the indirect effects of fire regimes will assist animal conservation. In flammable ecosystems, there is great potential to use fire for animal conservation, however most fire‐based conservation strategies do not explicitly consider interacting factors. In this study, we sought to understand the interrelationships between the endangered heath mouse (Pseudomys shortridgei), fire, resource availability and the introduced fox (Vulpes vulpes) in southeast Australia. We used structural equation modelling to identify pathways between variables, and mediation analysis to detect indirect effects. We did not detect a direct relationship between heath mice and post‐fire age class, but they were indirectly associated with age class via its influence on both shrub cover and fox relative abundance. Our findings suggest that heath mice will benefit from a fire regime promoting dense shrub regeneration in combination with predator control. Understanding the indirect effects of fire on animals may help to identify complementary management practices that can be applied concurrently to benefit animal conservation.
100 YEARS OF HISTORY
Over the last decade, millions of people around the world have become aware of the camera trap. The candid images and videos that camera traps produce have been featured in countless documentaries, are widely shared on social media, and have been the focus of hugely popular citizen science projects. Less well known is the fact that the camera trap has a long history that extends back more than 100 years. Over this time, they have gone from being an experimental technology used by just a handful of people to a commercialised technology being used by many thousands of photographers, hobbyists, hunters and biologists.
THE MODERN CAMERA TRAP
The modern camera trap is simply a digital camera connected to an infrared sensor which can “see” warm objects that are moving, like animals. When an animal moves past the sensor it causes the camera to fire, recording an image or video to the memory card for later retrieval. Camera traps can be left in the field to continuously watch an area of habitat for weeks or even months, recording the rarest events which occur in nature. This can include everything from a big cat patrolling its territory, to the raiding of a bird´s nest by a predator. Camera traps are also “wildlife friendly”, in that they cause little or no disturbance to wildlife. At the same time, they produce permanent and verifiable records of animals, akin to traditional museum voucher specimens.
HIGHLY EFFECTIVE TOOLS
Camera traps provide data on exactly where species are, what they are doing, and how large their populations are. They can be used to build up a picture of whole communities of species, including how they are structured and how species are interacting over space and time. Camera traps are also being deployed to understand how humans and livestock interact with wildlife. The development of networked camera traps, capable of sending images over phone or satellite networks in near real-time, has provided a new tool in the fight against poaching. New software tools and statistical models are also making it much easier and faster to obtain high quality information from the thousands of images that camera traps can quickly generate. This is improving our understanding of human impacts on wildlife, and helping land managers make better decisions at both small and large scales.
CHALLENGES
Despite the great potential of camera traps, there are a number of significant challenges involved in working with them. This can be frustrating for first-time users of the technology and can lead to wasted time and resources. Here we provide all the information needed to get up and running with camera traps as quickly as possible. Our aim is to maximise the effectiveness of camera traps for conservation and ecological research. We introduce the technology, help you decide if camera traps are right for your needs, provide the information you need when shopping for camera traps, and then give detailed recommendations on how exactly to deploy camera traps in the field.
Conservation management is strongly shaped by the interpretation of population trends. In the Serengeti ecosystem, Tanzania, aerial total counts indicate a striking increase in elephant abundance compared to all previous censuses. We developed a simple age-structured population model to guide interpretation of this reported increase, focusing on three possible causes: (1) in situ population growth, (2) immigration from Kenya and (3) differences in counting methodologies over time. No single cause, nor the combination of two causes, adequately explained the observed population growth. Under the assumptions of maximum in situ growth and detection bias of 12.7% in previous censuses, conservative estimates of immigration from Kenya were between 250 and 1,450 individuals. Our results highlight the value of considering demography when drawing conclusions about the causes of population trends. The issues we illustrate apply to other species that have undergone dramatic changes in abundance, as well as many elephant populations. This article is protected by copyright. All rights reserved
Knowledge of population density is necessary for effective management and conservation of wildlife, yet rarely are estimators compared in their robustness to effects of ecological and observational processes, which can greatly influence accuracy and precision of density estimates. In this study, we simulate biological and observational processes using empirical data to assess effects of animal scale of movement, true population density, and probability of detection on common density estimators. We also apply common data collection and analytical techniques in the field and evaluate their ability to estimate density of a globally widespread species. We find that animal scale of movement had the greatest impact on accuracy of estimators, although all estimators suffered reduced performance when detection probability was low, and we provide recommendations as to when each field and analytical technique is most appropriately employed. The large influence of scale of movement on estimator accuracy emphasizes the importance of effective post-hoc calculation of area sampled or use of methods that implicitly account for spatial variation. In particular, scale of movement impacted estimators substantially, such that area covered and spacing of detectors (e.g. cameras, traps, etc.) must reflect movement characteristics of the focal species to reduce bias in estimates of movement and thus density.
Automated cameras have become increasingly common for monitoring wildlife populations and estimating abundance. Most analytical methods, however, fail to account for incomplete and variable detection probabilities, which biases abundance estimates. Methods which do account for detection have not been thoroughly tested, and those that have been tested were compared to other methods of abundance estimation. The goal of this study was to evaluate the accuracy and effectiveness of the N-mixture method, which explicitly incorporates detection probability, to monitor white-tailed deer (Odocoileus virginianus) by using camera surveys and a known, marked population to collect data and estimate abundance. Motion-triggered camera surveys were conducted at Auburn University’s deer research facility in 2010. Abundance estimates were generated using N-mixture models and compared to the known number of marked deer in the population. We compared abundance estimates generated from a decreasing number of survey days used in analysis and by time periods (DAY, NIGHT, SUNRISE, SUNSET, CREPUSCULAR, ALL TIMES). Accurate abundance estimates were generated using 24 h of data and nighttime only data. Accuracy of abundance estimates increased with increasing number of survey days until day 5, and there was no improvement with additional data. This suggests that, for our system, 5-day camera surveys conducted at night were adequate for abundance estimation and population monitoring. Further, our study demonstrates that camera surveys and N-mixture models may be a highly effective method for estimation and monitoring of ungulate populations.
Countries committed to implementing the Convention on Biological Diversity's 2011–2020 strategic plan need effective tools to monitor global trends in biodiversity. Remote cameras are a rapidly growing technology that has great potential to transform global monitoring for terrestrial biodiversity and can be an important contributor to the call for measuring Essential Biodiversity Variables. Recent advances in camera technology and methods enable researchers to estimate changes in abundance and distribution for entire communities of animals and to identify global drivers of biodiversity trends. We suggest that interconnected networks of remote cameras will soon monitor biodiversity at a global scale, help answer pressing ecological questions, and guide conservation policy. This global network will require greater collaboration among remote-camera studies and citizen scientists, including standardized metadata, shared protocols, and security measures to protect records about sensitive species. With modest investment in infrastructure, and continued innovation, synthesis, and collaboration, we envision a global network of remote cameras that not only provides real-time biodiversity data but also serves to connect people with nature.
Citizen science has the potential to expand the scope and scale of research in ecology and conservation, but many professional researchers remain skeptical of data produced by nonexperts. We devised an approach for producing accurate, reliable data from untrained, nonexpert volunteers. On the citizen science website www.snapshotserengeti.org, more than 28,000 volunteers classified 1.51 million images taken in a large-scale camera-trap survey in Serengeti National Park, Tanzania. Each image was circulated to, on average, 27 volunteers, and their classifications were aggregated using a simple plurality algorithm. We validated the aggregated answers against a data set of 3829 images verified by experts and calculated 3 certainty metrics-level of agreement among classifications (evenness), fraction of classifications supporting the aggregated answer (fraction support), and fraction of classifiers who reported "nothing here" for an image that was ultimately classified as containing an animal (fraction blank)-to measure confidence that an aggregated answer was correct. Overall, aggregated volunteer answers agreed with the expert-verified data on 98% of images, but accuracy differed by species commonness such that rare species had higher rates of false positives and false negatives. Easily calculated analysis of variance and post-hoc Tukey tests indicated that the certainty metrics were significant indicators of whether each image was correctly classified or classifiable. Thus, the certainty metrics can be used to identify images for expert review. Bootstrapping analyses further indicated that 90% of images were correctly classified with just 5 volunteers per image. Species classifications based on the plurality vote of multiple citizen scientists can provide a reliable foundation for large-scale monitoring of African wildlife.
A survey of the extent and impact of game ranching on the natural resources of the Northern Province was conducted during 1998. Approximations of the annual turnover, game numbers and socio-economic impact of game ranching were obtained. Questionnaires were distributed to game ranch owners and managers and exemption permits issued by the Provincial conservation authority were analyzed for trends. An estimated 2 300 game ranches existed in the Northern Province by August 1998. These ranches covered approximately 3.6 million hectares, which represents 26% of the total area of the Province. The main concentrations of game ranches in the Northern Province are in the Northern, Western and Bushveld sub-regions. Game ranching contributes significantly to the economy of the Northern Province, especially through hunting and live game trade. It attracts investors from other provinces and countries, and earns foreign currency through ecotourism and trophy hunting. Hunting makes the largest contribution to the annual turnover of the game-ranching industry, followed by live game trade and ecotourism.
Camera traps can be used to address large-scale questions in community ecology by providing systematic data on an array of wide-ranging species. We deployed 225 camera traps across 1,125 km(2) in Serengeti National Park, Tanzania, to evaluate spatial and temporal inter-species dynamics. The cameras have operated continuously since 2010 and had accumulated 99,241 camera-trap days and produced 1.2 million sets of pictures by 2013. Members of the general public classified the images via the citizen-science website www.snapshotserengeti.org. Multiple users viewed each image and recorded the species, number of individuals, associated behaviours, and presence of young. Over 28,000 registered users contributed 10.8 million classifications. We applied a simple algorithm to aggregate these individual classifications into a final 'consensus' dataset, yielding a final classification for each image and a measure of agreement among individual answers. The consensus classifications and raw imagery provide an unparalleled opportunity to investigate multi-species dynamics in an intact ecosystem and a valuable resource for machine-learning and computer-vision research.
In the early 1990s, biologists began experimenting with camera traps to estimate the abundance of tigers Panthera tigra in the Nagarahole National Park (Karanth 1995), marking the first time that camera traps were used to sample a wildlife population in a statistically rigorous manner. Since that time, camera traps have been employed for a wide variety of uses in behavioral and ecological studies. Camera trap studies can result in capture histories of species whose members are individually recognizable via distinct natural traits or artificial markings (e.g. radio collars, tags) as well as capture histories of species that are not reliably identified as individuals. In either case, dependent on study objectives, each type of data may be used to estimate population size, species richness, site occupancy or relative abundance indices. In addition, well-designed camera trap studies usually include data on covariates at the sites where the cameras are set. Ideally, covariates are chosen based on their purported influence on abundance or other parameters of interest, including detectability (White 2005). The challenge to biologists is to use these data to the greatest extent possible, to make unbiased inferences about the state of the target wildlife population under investigation.
Large wild herbivores are crucial to ecosystems and human societies. We highlight the 74 largest terrestrial herbi-vore species on Earth (body mass > – 100 kg), the threats they face, their important and often overlooked ecosystem effects, and the conservation efforts needed to save them and their predators from extinction. Large herbivores are generally facing dramatic population declines and range contractions, such that ~60% are threatened with extinction. Nearly all threatened species are in developing countries, where major threats include hunting, land-use change, and resource depression by livestock. Loss of large herbivores can have cascading effects on other species including large carnivores, scavengers, mesoherbivores, small mammals, and ecological processes involving vegetation , hydrology, nutrient cycling, and fire regimes. The rate of large herbivore decline suggests that ever-larger swaths of the world will soon lack many of the vital ecological services these animals provide, resulting in enormous ecological and social costs.
1.Reliable assessment of animal populations is a long-standing challenge in wildlife ecology. Technological advances have led to widespread adoption of camera traps (CTs) to survey wildlife distribution, abundance, and behaviour. As for any wildlife survey method, camera trapping must contend with sources of sampling error such as imperfect detection. Early applications focused on density estimation of naturally marked species, but there is growing interest in broad-scale CT surveys of unmarked populations and communities. Nevertheless, inferences based on detection indices are controversial and the suitability of alternatives such as occupancy estimation is debatable.2.We reviewed 266 CT studies published between 2008 and 2013. We recorded study objectives and methodologies, evaluating the consistency of CT protocols and sampling designs, the extent to which CT surveys considered sampling error, and the linkages between analytical assumptions and species ecology.3.Nearly two-thirds of studies surveyed more than one species, and a majority used response variables that ignored imperfect detection (e.g. presence–absence, relative abundance). Many studies used opportunistic sampling and did not explicitly report details of sampling design and camera deployment that could affect conclusions.4.Most studies estimating density used capture-recapture methods on marked species, with spatially explicit methods becoming more prominent. Few studies estimated density for unmarked species, focusing instead on occupancy modelling or measures of relative abundance. While occupancy studies estimated detectability, most did not explicitly define key components of the modelling framework (e.g. a site), or discuss potential violations of model assumptions (e.g. site closure). Studies using relative abundance relied on assumptions of equal detectability, and most did not explicitly define expected relationships between measured responses and underlying ecological processes (e.g. animal abundance and movement).5.Synthesis and applications. The rapid adoption of camera traps represents an exciting transition in wildlife survey methodology. We remain optimistic about the technology's promise, but call for more explicit consideration of underlying processes of animal abundance, movement, and detection by cameras, including more thorough reporting of methodological details and assumptions. Such transparency will facilitate efforts to evaluate and improve the reliability of camera trap surveys, ultimately leading to stronger inferences and helping to meet modern needs for effective ecological inquiry and biodiversity monitoring.This article is protected by copyright. All rights reserved.
Inference and estimates of abundance are critical for quantifying population dynamics and impacts of environmental change. Yet imperfect detection and other phenomena that cause zero inflation can induce estimation error and obscure ecological patterns.
Recent statistical advances provide an increasingly diverse array of analytical approaches for estimating population size to address these phenomena.
We examine how detection error and zero inflation in count data inform the choice of analytical method for estimating population size of unmarked individuals that are not uniquely identified. We review two established ( GLM s and distance sampling) and nine emerging methods that use N ‐mixture models (Royle–Nichols model, and basic, zero inflated, temporary emigration, beta‐binomial, generalized open‐population, spatially explicit, single visit and multispecies) to estimate abundance of unmarked populations, focusing on their requirements and how each method accounts for imperfect detection and zero inflation.
Eight of the emerging methods can account for both imperfect detection and additional variation in population size in the forms of non‐occupancy, temporary emigration, correlated detection and population dynamics.
Methods differ in sampling design requirements (e.g. count vs. detection/non‐detection data, single vs. multiple visits, covariate data), and their suitability for a particular study will depend on the characteristics of the study species, scale and objectives of the study, and financial and logistical considerations.
Most emerging methods were developed over the past decade, so their efficacy is still under study, and additional statistical advances are likely to occur.
1.Activity level (the proportion of time that animals spend active) is a behavioural and ecological metric that can provide an indicator of energetics, foraging effort and exposure to risk. However, activity level is poorly known for free-living animals because it is difficult to quantify activity in the field in a consistent, cost-effective and non-invasive way.2.This paper presents a new method to estimate activity level with time-of-detection data from camera-traps (or more generally any remote sensors), fitting a flexible circular distribution to these data in order to describe the underlying activity schedule, and calculating overall proportion of time active from this.3.Using simulations and a case study for a range of small to medium-sized mammal species, we find that activity level can reliably be estimated using the new method.4.The method depends on the key assumption that all individuals in the sampled population are active at the peak of the daily activity cycle. We provide theoretical and empirical evidence suggesting that this assumption is likely to be met for many species, but may be less likely in large predators, or in high latitude winters. Further research is needed to establish stronger evidence on the validity of this assumption in specific cases, however, the approach has the potential to provide an effective, non-invasive alternative to existing methods for quantifying population activity levels.This article is protected by copyright. All rights reserved.
Medium-to-large mammals within tropical forests represent a rich and functionally diversified component of this biome; however, they continue to be threatened by hunting and habitat loss. Assessing these communities implies studying species' richness and composition, and determining a state variable of species abundance in order to infer changes in species distribution and habitat associations. The Tropical Ecology, Assessment and Monitoring (TEAM) network fills a chronic gap in standardized data collection by implementing a systematic monitoring framework of biodiversity, including mammal communities, across several sites. In this study, we used TEAM camera trap data collected in the Udzungwa Mountains of Tanzania, an area of exceptional importance for mammal diversity, to propose an example of a baseline assessment of species' occupancy. We used 60 camera trap locations and cumulated 1,818 camera days in 2009. Sampling yielded 10,647 images of 26 species of mammals. We estimated that a minimum of 32 species are in fact present, matching available knowledge from other sources. Estimated species richness at camera sites did not vary with a suite of habitat covariates derived from remote sensing, however the detection probability varied with functional guilds, with herbivores being more detectable than other guilds. Species-specific occupancy modelling revealed novel ecological knowledge for the 11 most detected species, highlighting patterns such as 'montane forest dwellers', e.g. the endemic Sanje mangabey (Cercocebus sanjei), and 'lowland forest dwellers', e.g. suni antelope (Neotragus moschatus). Our results show that the analysis of camera trap data with account for imperfect detection can provide a solid ecological assessment of mammal communities that can be systematically replicated across sites.
The distribution of species and population attributes are critical data for biodiversity conservation. As a tool for obtaining such data, camera traps have become increasingly common throughout the world. However, there are disagreements on how camera-trap records should be used due to imperfect species detectability and limitations regarding the use of capture rates as surrogates for abundance. We evaluated variations in the capture rates and community structures of mammals in camera-trap surveys using four different sampling designs. The camera traps were installed on internal roads (in the first and fourth years of the study), at 100-200 m from roads (internal edges; second year) and at 500 m from the nearest internal road (forest interior; third year). The mammal communities sampled in the internal edges and forest interior were similar to each other but differed significantly from those sampled on the roads. Furthermore, for most species, the number of records and the capture success varied widely among the four sampling designs. A further experiment showed that camera traps placed on the same tree trunk but facing in opposing directions also recorded few species in common. Our results demonstrated that presence or non-detection and capture rates vary among the different sampling designs. These differences resulted mostly from the habitat use and behavioral attributes of species in association with differences in sampling surveys, which resulted in differential detectability. We also recorded variations in the distribution of records per sampling point and at the same spot, evidencing the stochasticity associated with the camera-trap location and orientation. These findings reinforce that for species whose specimens cannot be individually identified, the capture rates should be best used as inputs for presence and detection analyses and for behavior inferences (regarding the preferential use of habitats and activity patterns, for example). Comparisons between capture rates or among relative abundance indices, even for the same species, should be made cautiously.
A survey of the extent and impact of game ranching on the natural resources of the Northern Province was conducted during 1998. Approximations of the annual turnover, game numbers and socio-economic impact of game ranching were obtained. Questionnaires were distributed to game ranch owners and managers and exemption permits issued by the Provincial conservation authority were analyzed for trends. An estimated 2300 game ranches existed in the Northern Province by August 1998. These ranches covered approximately 3.6 million hectares, which represents 26% of the total area of the Province. The main concentrations of game ranches in the Northern Province are in the Northern, Western and Bushveld sub-regions. Game ranching contributes significantly to the economy of the Northern Province, especially through hunting and live game trade. It attracts investors from other provinces and countries, and earns foreign currency through ecotourism and trophy hunting. Hunting makes the largest contribution to the annual turnover of the game-ranching industry. followed by live game trade and ecotourism.
Reducing the loss of biodiversity is key to ensure the future well being of the planet. Indicators to measure the state of biodiversity should come from primary data that are collected using consistent field methods across several sites, longitudinal, and derived using sound statistical methods that correct for observation/detection bias. In this paper we analyze camera trap data collected between 2008 and 2012 at a site in Costa Rica (Volcan Barva transect) as part of an ongoing tropical forest global monitoring network (Tropical Ecology Assessment and Monitoring Network). We estimated occupancy dynamics for 13 species of mammals, using a hierarchical modeling approach. We calculated detection-corrected species richness and the Wildlife Picture Index, a promising new indicator derived from camera trap data that measures changes in biodiversity from the occupancy estimates of individual species. Our results show that 3 out of 13 species showed significant declines in occupancy over 5 years (lowland paca, Central American agouti, nine-banded armadillo). We hypothesize that hunting, competition and/or increased predation for paca and agouti might explain these patterns. Species richness and the Wildlife Picture Index are relatively stable at the site, but small herbivores that are hunted showed a decline in diversity of about 25%. We demonstrate the usefulness of longitudinal camera trap deployments coupled with modern statistical methods and advocate for the use of this approach in monitoring and developing global and national indicators for biodiversity change.
This chapter discusses recent historical changes in the Serengeti ecosystem and possible future changes. It sets the scene for the later analysis and modeling of the human-nature interactions. First, it describes the Serengeti in terms of geography, climate, soils, habitats, and animals, and places it in the human context of surrounding tribes and the larger region. Second, it gives an overview of available information on the ecosystem. Third, it outlines the various changes to the system that are either currently occurring or are expected in the future. These are treated as experimental perturbations, with which to alter the models in later chapters. These changes are described, and why and how they may occur.