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... Camera trap data was used to estimate relative abundance indices (RAI) of prey species, = ( ) 100 where E is the number of event (photo-captures) and TN is the total number of trap nights (Palmer et al. 2018). RAI gave an approximate index of abundance (Parsons et al. 2017;Palmer et al. 2018). ...
... Camera trap data was used to estimate relative abundance indices (RAI) of prey species, = ( ) 100 where E is the number of event (photo-captures) and TN is the total number of trap nights (Palmer et al. 2018). RAI gave an approximate index of abundance (Parsons et al. 2017;Palmer et al. 2018). The photographs of prey species were considered as an independent photo-capture event (O'Brien et al. 2003) when (1) the time interval between the consecutive photographs of the same species was more than 30 min, (2) non-consecutive images of individual of the same species. ...
... Jenks et al. 2011) estimated the relative abundance indices of predator and mammalian species from camera trapping to test wildlife conservation hypothesis in Khao Yai National Park, Thailand.(Palmer et al. 2018) estimated relative abundance indices for terrestrial herbivores from ...
Thesis
The ecology of leopard (Panthera pardus) was studied from 5 January to 5 April 2020 in Kalesar National Park (KNP), India. Population size and density of leopard were estimated using mark-recapture framework and maximum likelihood (ML) based on spatial explicit capture-recapture model. Activity patterns and temporal overlap of leopard and its prey species were assessed from camera trap data. The relative abundance indices (RAI) were calculated for prey species of leopard and assessed the group size, composition, sex ratio, and fawn/100 female ratio of chital and sambar by using photo capture data from camera traps. I evaluated the habitat use of leopard by taking a 10 m radius circular plot at every used (leopard present) and available locations to collect habitat data. The 10 habitat variables were recorded at every sampling plot: tree height (m), canopy cover (%), GBH (cm), canopy height (m), the total number of shrubs and trees in each plot, shrub height (m), shrub cover (%), distance from water (km) and distance from road (km). A sampling effort of 1150 trap nights over 92 days yields 93 photo captures of 22 unique leopards (based on individual markings and visual identification); the estimated population size was 27.3 ± 4.2 leopards while the density of leopard was estimated at 19.31 ±5.10 individuals/100 km2 using the maximum likelihood (ML) based spatially explicit capture-recapture (SECR) model. Leopards were active throughout the day and night and showed the bimodal peak of activities. The highest degree of activity overlap was observed between leopard and chital Δ4= 0.87 (±0.02) followed by wild boar Δ4= 0.83 (±0.03). Relative abundance indices were calculated highest for sambar (43.4) and chital (28.83) followed by wild boar (20.86). The mean group size for chital and sambar was 4.52 ±0.29 and 1.98 ±0.98 respectively. Among chital and sambar, the largest group observed has 16 and 10 individuals respectively. The sex ratio for chital was 58.76 males/100 females and 78.87 males/100 females for sambar. The fawn/100 female ratio for chital and sambar was 59 fawn/100 females and 37.95 fawn/100 females respectively. The results for habitat use of leopard in KNP was strongly associated with canopy cover. Canopy cover (P=0.025) was the only habitat variable found to be statistically significant which influence the habitat use of leopard.
... Camera trap capture frequencies (captures/100 camera days) are often used as a relative abundance index (RAI) when absolute abundance is difficult and costly to measure (Amin et al., 2015;Palmer et al., 2018). However, camera trap capture frequencies, from which RAIs are derived, should be used with caution as they do not account le sud du Malawi. ...
... Despite the controversy that RAIs invoke, their use can still offer some meaningful insights into the abundance of wildlife populations (Wearn & Glover-Kapfer, 2017). For example, the reliability of RAIs from camera traps has been tested against robust density estimates, with correlations found to be positive and linear (Carbone et al., 2001;Rovero & Marshall, 2009), and in the Serengeti, RAIs from camera traps provided a good approximation of aerial census abundance data (Palmer et al., 2018). ...
... Rodwell et al. (1995) recommended excluding warthog from aerial censuses as their counts are too inaccurate due to their poor detection potential; however, warthog is included in other studies using aerial census data (e.g. Palmer et al., 2018;Redfern et al., 2002). The study of Palmer et al. (2018) in particular found RAIs based on camera trap data to compare very well to aerial count data, and their data set include warthog. ...
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en Biological monitoring in protected areas is essential for making management decisions, especially in small (<1000 km²), fenced reserves which require intensive intervention to maintain core habitat characteristics. Estimates of species richness and community structure provide important information for planning and evaluating conservation strategies. Majete Wildlife Reserve (MWR) is a small (691 km²), isolated reserve in southern Malawi in the Miombo Woodland Ecoregion. We investigated species richness and community structure of the terrestrial medium and large mammals at MWR through a standardised camera trap survey. During the 2018 dry season, 140 camera locations were sampled for 40 days each. Thirty-five mammal species were detected and Chao 2, ICE and Jackknife 1 and 2 richness estimators indicated between 36–41 species present which aligns closely with historic accounts. Non-detection of some species is attributed to species specialised habitat requirements not catered for in the systematic camera trap survey design. Mammal community structure, calculated from the camera detected species’ relative abundance indices (RAI), was atypical for Miombo woodland, with an underrepresentation of elephants. Camera trap-derived RAI was positively related with 2018 aerial census species encounter data. These results can assist management in refining survey techniques and act as a baseline to monitor conservation efforts. Résumé fr La surveillance biologique des aires protégées est essentielle aux prises de décision en matière de gestion, en particulier dans les petites réserves clôturées (< 1 000 km²) qui nécessitent une intervention intensive visant à maintenir les caractéristiques principales de l’habitat. Les estimations de la richesse en espèces et l’étude de la structure de la communauté fournissent des informations importantes aux fins de planification et l’évaluation des stratégies de conservation. La réserve faunique de Majete (MWR) est une petite réserve isolée (691 km²) située dans l’écorégion de la forêt de Miombo, dans le sud du Malawi. Nous avons étudié la richesse en espèces et la structure de la communauté des mammifères terrestres de taille moyenne et grande au sein de la MWR, en nous appuyant sur une enquête normalisée et réalisée par piège photographique. Au cours de la saison sèche de l’année 2018, 140 emplacements d’appareils photo ont été échantillonnés pendant 40 jours chacun. Trente-cinq espèces de mammifères ont été identifiées, et les estimateurs de richesse en espèces Chao 2, ICE et Jackknife 1 et 2 ont indiqué la présence de 36 à 41 espèces, ce qui correspond étroitement aux résultats des évaluations réalisées par le passé.. La non-détection de certaines espèces est attribuée aux exigences particulières liées à l’habitat de ces dernières, auquel la méthode d’échantillonnage par piège photographique ne peut être appliquée. La structure de la communauté de mammifères, calculée à partir des indices d’abondance relative (IAR) des espèces détectées par l’appareil photo, était atypique pour la forêt claire de Miombo et mettait en évidence une sous-représentation des éléphants. L’IAR dérivé des pièges photographiques était en corrélation positive avec les données de présence des espèces issues du recensement aérien réalisé en 2018. Ces résultats peuvent aider la Direction à affiner les techniques d’enquête et servir de référence aux fins de suivi des efforts de conservation.
... 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). ...
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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.
... One difficulty in conserving wildlife populations is estimating population abundance. Accurate and precise 1 estimates of abundance are essential to conserve and manage wildlife, especially large mammals (Bowler et al., 2019;Palmer et al., 2018;Ripple et al., 2017), as they are used to monitor populations and provide other meaningful population metrics (Bowden et al., 1984;Freddy et al., 2004;McClintock & White, 2007). These metrics enable biologists to effectively respond to disease, human encroachment and habitat loss (Wearn & Glover-Kapfer, 2019). ...
... The technology used in camera traps has advanced rapidly over the past two decades (Rowcliffe, 2017;Wearn & Glover-Kapfer, 2019), allowing these devices to become an integral tool in wildlife assessment and monitoring (Cutler & Swann, 1999;Rowcliffe & Carbone, 2008;Sanderson & Trolle, 2005). While camera traps are being used at a rapidly increasing rate (Palmer et al., 2018;Rowcliffe & Carbone, 2008;Wearn & Glover-Kapfer, 2019), simultaneous comparisons are needed to determine how comparable the effectiveness and cost of camera traps are to other methods (e.g., ground and aerial surveys) (G alvez et al., 2016;Meek et al., 2015;Silveira et al., 2003), especially across years. The usefulness of camera traps to estimate the abundance of ungulates is limited at times when analytical methods require some individuals be marked so that individuals within the population can be differentiated. ...
... Two common methods of estimating population abundance for ungulates that can be viewed easily in landscapes with limited vegetation are aerial surveys (Holl et al., 2004;Palmer et al., 2018;Walter & Hone, 2003), and resight surveys performed from the ground (Johnson et al., 2010;McClintock & White, 2007;Zaccaroni et al., 2018). Helicopter surveys have been used increasingly during the past 20 years to produce population estimates of ungulates (Bleich et al., 1994;Krausman & Hervert, 1983;McClintock & White, 2007). ...
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Abstract Many global wildlife populations are experiencing unprecedented declines. Estimates of population abundance are needed to effectively manage common species and to conserve vulnerable species. Camera traps have advanced as wildlife monitoring tools for ungulates and can provide improved methods of estimating population abundance. Little is known, however, about how camera traps set for ungulates compare with traditional methods (e.g., ground and aerial surveys) used simultaneously. From 2012 to 2014, we captured and radio collared 34 female and 32 male bighorn sheep (Ovis canadensis) in a closed population in Utah, USA. Each collar had a unique letter and number combination. We then estimated number of young, females and yearlings, males and population abundance using multiple methods simultaneously: helicopter surveys, resight surveys performed from the ground, camera trap surveys using marked but not individually identifiable individuals and camera trap surveys using marked and individually identifiable animals. All methods estimated similar abundance. Across years, ages and sexes, however, camera trap surveys produced the most consistent and precise estimates of abundance for adult females and yearlings, lambs and the population. That method was less intrusive and safer than helicopter surveys. Our results indicate that camera trap surveys using photographs of marked animals in which the majority of the population visits a specific resource can produce precise estimates of abundance that are safer, as well as less intrusive and expensive than traditional methods. Using camera traps also creates a permanent record of photographs that can be archived and reanalyzed to answer future ecological and population questions. Finally, this method of estimating abundance can be used in other areas with ungulates that congregate around resources (e.g., watering sites or mineral licks).
... The number of passes of animals of each species was determined by the field of view of the station's camera traps (the number of animals was taken into account for each of the passages) (Jenks et al., 2011;Palmer et al., 2018). If the camera fixed two individuals in the same frame, we registered it as two passes. ...
... Data calculation was carried out using several methods. We calculated the relative abundance index (RAI) for each mammalian species for each camera-trap as the number of animal passes through separate camera traps per 100 trapping days (Jenks et al., 2011;Palmer et al., 2018). Statistical analysis was performed using R software version 4.0.3 ...
Article
The Russian Far East is a unique location that may be considered a hot spot of biodiversity in Russia. In 2010, a new illuminated highway for high-speed traffic was built on its territory. The aim of this study was to evaluate the impact of this highway on the distribution and activity of various mammalian species. We set up camera traps in five lines near the road and obtained photos of 1372 passes of various animals. In total, 15 species of wild mammals were captured by camera traps. Animals preferred to stay far away from the road. This highway became a serious barrier separating the local populations of ungulates and carnivores. Only domestic animals and Amur wild cat used the underpasses more often than other areas. The distance from the road did not affect the daily activity of the mammals.
... They also do not give the count of animals in the image. Estimating population of unmarked animals is a difficult task and people have been working on getting estimation indexes [11] from camera-trap images. Historically, models like N-Mixture models [16], Spatial Count models [1], Random Encounter Models [15], etc. have been used to estimate the animal population. ...
... This is not feasible for many species, and especially for the herd and obfuscated images, and I suggest to send the images with low detection scores to Zooniverse Volunteers for annotations. And lastly, I recommend using the count numbers from this model for estimation of abundance using ecology models [9] [11]. We know that the yearly aerial surveys can be expensive and timeconsuming, and outputs from my model can give a more real-time and non-expensive view of animal population estimations. ...
Thesis
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Deep Learning based object detection models have shown a lot of potential in localizing and identifying multiple objects in images. Earlier works have shown that they can be trained on wildlife camera-trap images to automatically detect animals in the wild [19] [10]. Camera-traps are a rich source of ecological data that capture wildlife images without being intrusive in their natural habitat. Getting accurate population estimates of wildlife is very important to ecologists and conservationists. Mining the camera-trap data to detect animals and get their count within the image can be very useful for population estimation models. In this report, I lay down the problem at hand, the experiment steps, results, and future work. I used transfer learning and fine-tuning of the Faster R-CNN architecture with a Resnet-101 encoder to build a model for detecting African wildlife species. I also designed and experimented on a novel technique that uses weak supervision to generate bounding box level data needed for training an object detection architecture like the Faster R-CNN [14], SSD [7], YOLO [13], etc. My most valuable contribution to this work has been the training of the object detection model for African wildlife and the development of a weakly supervised learning loop for generating training data and subsequent model fine-tuning. I also identified the sensitivity of object detection architecture to noise and class imbalance, particularly in the case of transfer learning and at the time of fine-tuning on fewer data. My work on weak supervision framework for model training not only reduces the effort of human volunteers in creating the dataset for training, but it also proves that we could start training the model with fewer data and build a robust and fully trained model with minimum effort.
... It is often used to measure relative abundance and observe 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). ...
... 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). While the deer is often cautious and elusive from humans, RAI is widely used to monitor its abundance and distribution in the wild. ...
Thesis
The Philippine Brown Deer (Rusa marianna) 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 Davao City from January to March 2020. Camera trapping was used to detect deer presence and calculate its relative abundance index (RAI). A total of ten (10) 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 interval. Key Informant Interviews (KIIs) were undertaken to document local conservation efforts. A total of 4 deer individuals were observed after 500 camera trap days (RAI=0.8). Two individuals were recorded in Barangay Carmen (RAI=1.6), 1 in Barangay Salaysay (RAI=0.8), 1 in Barangay Tawan-tawan (RAI=0.8), and 0 in Barangay Tambobong (RAI=0.0). Overall, the deer has a very low RAI and broad distribution across primary and secondary forests located at an elevation of 1518 masl to 1709 masl. Meanwhile, hunting and habitat loss remain the leading anthropogenic threats to the deer despite local conservation efforts by the Obu Manuvu indigenous community. Thus, there is a need to strengthen conservation efforts through the stringent implementation of wildlife monitoring and enforcement of culture-based protection policies.
... 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; ...
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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.
... In order to reduce potential bias caused by multiple records of the same individual at a camera station, photographs that were recorded within 30 min of previous photographs of the same species at same camera station were not used (O'Brien et al. 2003;Linkie and Ridout 2011). Camera captures of multiple individuals of social species were considered single events (Palmer et al. 2018). Data from the camera traps were collected monthly by exchanging SD-cards, and if necessary at the time, batteries were replaced. ...
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Background Sika deer, Cervus nippon , were originally introduced to South Korea from Japan and Taiwan for commercial farming purposes. Unfortunately, they were released into the wild during religious events and have since begun to impact the native ecosystem and species endemic to South Korea. The study of activity patterns can improve our understanding of the environmental impact of non-native species and their association with sympatric species. Using camera traps, we studied the diel and seasonal activity patterns of non-native sika deer and quantified the temporal overlap with sympatric mammalian species in the Muljangori-oreum wetlands of Hallasan National Park, South Korea. Results A total of 970 trap events were recorded for five mammalian species from nine locations during the camera-trap survey. Siberian roe deer ( Capreolus pygargus tianschanicus ) had the highest number of recorded events (72.0%), followed by sika deer ( Cervus nippon ) (16.2%), wild boar ( Sus scrofa ) (5.0%), Asian badger ( Meles leucurus ) (4.5%), and the Jeju weasel ( Mustela sibirica quelpartis ) (2.0%). Sika deer had bimodal activity patterns throughout the year, with peaks throughout the spring-autumn twilight, and day and night time throughout the winter. Relating the daily activity of sika deer with other mammalian species, roe deer expressed the highest degree of overlap (∆ 4 = 0.80) while the Asian badger demonstrated the lowest overlap (∆ 4 = 0.37). Conclusions Our data show that sika deer are a crepuscular species with seasonal variations in daily activity patterns. Additionally, we identified the temporal differences in activity peaks between different mammals in the Muljangori-oreum wetlands and found higher degree of overlap between sika deer and roe deer during twilight hours.
... 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. ...
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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.
... 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. ...
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Hakim L, Widyorini R, Nugroho WD, Prayitno TA. 2021. Radial variability of fibrovascular bundle properties of salacca (Salacca zalacca) fronds cultivated on Turi Agrotourism in Yogyakarta, Indonesia. Biodiversitas 22: 3594-3603. Fibrovascular bundles have properties variability not only based on species and varieties but also parts of species. This study, therefore, aims to characterize the FVB fundamental properties (anatomical, chemical, physical and mechanical) of Salacca zalacca (Gaertn.) Voss fronds, based on radial direction. The salacca fronds were divided into three parts, outer, middle as well as inner positions. Then the FVB's anatomical and physical properties were observed by light microscope and gravimetry analysis, respectively. Meanwhile, the variability of chemical and mechanical properties was investigated based on the ASTM standard. According to the results, the outer position has a higher variability of diameter, density, cellulose, lignin, and mechanical properties than the inner position, but has a lower hemicellulose value than the middle and inner position. Furthermore, the relationships between the anatomical, physical, chemical, and mechanical properties were discovered to form a pattern where increasing the mechanical properties is influenced by density and ratio vascular tissue area to total transverse area. Based on the results, the fibrovascular bundle of S. zalacca frond was concluded to possess anatomical, physical, chemical, and mechanical properties variability on the radial direction. There was a correlation between anatomical properties and mechanical properties.
... In contrast, camera traps were set 50 cm above the ground, generally within woodlots between shooting lines, and lacked bait. Detection areas are not typically accounted for in relative abundance estimates obtained through camera trapping (e.g., Jenks et al. 2011;Palmer et al. 2018), but they are essential to estimate the density of unmarked animal species (Rowcliffe et al. 2008;Hofmeester et al. 2017;Howe et al. 2017). Differential habitat use between wildlife trails (where cameras were set up) and shooting lines (with bait stations) might favor sighting to camera-trap detections, in an analogous way as the differential outcomes recorded by random and trail-oriented placement of camera traps (Cusack et al. 2015). ...
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Monitoring wildlife population trends is essential for resource management and invasive species control, but monitoring data are hard to acquire. Citizen science projects may monitor species occurrence patterns in time and space in a cost-effective way. A systematic management program of exotic wild boar (Sus scrofa) and axis deer (Axis axis) in a protected area of northeastern Argentina (El Palmar National Park) provided a framework for implementing a wildlife monitoring system based on park-affiliated hunters. We assessed the level of agreement between three indices of relative abundance: hunter sightings and camera trapping for wild boar, axis deer, capybaras (Hydrochoerus hydrochaeris), brown brocket deer (Mazama guazoubira), and crab-eating and pampas foxes combined (Cerdocyon thous and (Lycalopex gymnocercus), and catch per unit effort (CPUE) for both exotic ungulates only. Most (74%) hunting parties participated in the monitoring program and contributed to its sustainability. Bland-Altman plots displayed large levels of agreement between methods across species, with larger systematic differences between sighting and camera-trapping indices for native species. Restricting camera-trapping to the same time window as hunter sightings substantially increased the agreement between methods across species. Sighting and CPUE indices revealed similar temporal trends and large variations in spatial patterns between species. Comparison of the number of sighted and killed exotic ungulates indicated that, on average, 17% of wild boar and 75% of axis deer escaped hunters. The three indices were appropriate metrics for management purposes and corroborated the sustained, high-level abundance of axis deer and low numbers of wild boar in recent years.
... However, in this study, the primary goal is to estimate the S. philippensis population status. RAIs are less complicated and often used for species that are difficult or costly to monitor (Palmer et al. 2018). The total detection counts in every barangay were tallied and divided by 125 trap-days. ...
Article
The Philippine warty pig (Sus philippensis) is endemic to the Philippines, where habitat loss, hunting, and hybridization continue to cause population decline. To increase knowledge about the understudied Mindanao subspecies, an assessment of its conservation and population status within the 36,000-ha Obu Manuvu Ancestral Domain (OMAD) in Davao City was undertaken. Specifically, this study aims to determine the relative abundance of S. philippensis and document the existing conservation efforts. The species was documented through camera trapping to calculate the relative abundance index (RAI). Also, key informant interviews with 12 Obu Manuvus were undertaken to investigate local efforts to conserve the species. A total of 18 individuals of S. philippensis were detected after 500 camera trap-days (RAI=2.0). Eight individuals were observed in Tambobong (RAI=3.2), ten individuals in Salaysay (RAI=4.8), but none were observed in both Tawan-tawan and Carmen (RAI=0.0). The results indicate a low relative abundance of S. philippensis in the study areas. The interview results revealed that hunting and habitat loss are the major anthropogenic threats within the ancestral domain. Current policies and strategies for species protection and forest management must be amended and the improved guidelines must be strictly enforced.
... For example, absolute estimates of population size can be obtained through statistical methods such as capture-mark-recapture (Schwarz and Seber 1999) or distance sampling (Buckland et al. 2015), which, however, may be expensive and time-consuming. Less expensive relative abundances indices (RAIs) can be obtained using simpler methodologies, for example ground counts (e.g., block counts: Corlatti et al. 2015), camera traps (Palmer et al. 2018), track counts (Fryxell et al. 1988) or ecological indicators (Morellet et al. 2007). The use of RAIs, however, requires validation against some known standard (Morellet et al. 2007). ...
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Reliable and cost-effective monitoring tools to track population size over time are of key importance for wildlife management and conservation. Deterministic cohort analysis may be used to this aim, especially in hunted populations, but it requires that all mortality events are recorded and that individual age at death is known exactly. In this study, we investigated the reliability of cohort analysis as a relative index to track overtime variation in red deer (Cervus elaphus) abundance, in the absence of exact information about natural mortality and age. Visual tooth inspection was used to age 18,390 individuals found dead or hunted between 1982 and 2020 within the Trentino sector of the Stelvio National Park and the Val di Sole hunting district (Central Italian Alps). Temporal trend of reconstructed population size was checked using spring spotlight counts as a benchmark, through the Buishand range test and a linear model. Our results showed a significant and positive relationship between reconstructed population size and spring spotlight counts between 1982 and 2013, suggesting that cohort analysis could reliably track red deer population trend up to 7 years in the past. With a relative error of + 1.1 (SD = 1.5) years in the estimation of age, and fairly stable hunting pressure, our results support the use of deterministic cohort analysis as a relative index of abundance for monitoring red deer over time, even in the absence of exact information about natural mortality. Under violation of assumptions, however, the performance of deterministic reconstruction should be carefully inspected at the management scale.
... Species richness was expressed as the total number of species recorded at each sampling period and site, while relative abundance index (RAI) was estimated as the ratio between the total number of images for all species at each site and the total sampling effort at each site expressed as the total number of images/total camera traps-days (Carbone et al., 2001;O'Brien, 2011). Relative abundance provides information on population abundance, especially when it's difficult to estimate true species abundance, and it is positively related with independent density and abundance estimates (Carbone et al., 2001;O'Brien, 2011;Palmer et al., 2018). ...
Article
In a scenario where escalating human activities lead to several environmental changes and, consequently, affect mammal abundance and distribution, β-diversity may increase due to differences among sites. Using the ecological uniqueness approach, we analyzed β-diversity patterns of ground-dwelling mammal communities recorded through comprehensive camera trap monitoring within eight tropical forests protected areas in Mesoamerica and South America under variable landscape contexts. We aimed to investigate whether the contribution of single sites (LCBD) and single species (SCBD) to overall β-diversity could be explained by community metrics and environmental variables, and by species metrics and biological traits, respectively. Total β-diversity was also partitioned into species replacement and richness difference. We related LCBD to species richness, total relative abundance, functional indices, and environmental variables (tree basal area, protected area size, NDVI, and precipitation seasonality), and SCBD to species naïve occupancy, relative abundance, and morphoecological traits via beta regression. Our findings showed that LCBD was primarily explained by variation in species richness, rather than relative abundance and functional metrics. Protected area size and tree basal area were also important in explaining variation in LCBD. SCBD was strongly related to naïve occupancy and relative abundance, but not to biological traits, such as body mass, trophic energy level, activity cycle, and taxonomic category. Local β-diversity was a result of species replacements and to a lesser extent differences in species richness. Our approach was useful in examining and comparing the ecological uniqueness among different sites, revealing the regional scale current status of mammal diversity. High LCBD values comprised sites embedded within smaller habitat extents, hosting lower tree basal areas, and harboring low species richness. SCBD showed that relatively ubiquitous species that occur at variable abundances across sites contributed most to β-diversity.
... To assess the relative abundance of mammal species we computed a relative abundance index (RAI) which scales the number of independent camera events to 100 trap nights; in line with other camera trap research, we omitted consecutive captures of the same species that were within one hour of the initial capture of the same species unless separated by camera trap events of other species [66,68,69]. Please note that this approach scores the presence or absence of a species, and does not account or adjust for differences in detectability, or weight scores by the number of individuals seen in a frame. ...
Article
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In many regions of sub Saharan Africa large mammals occur in human-dominated areas, yet their community composition and abundance have rarely been described in areas occupied by traditional hunter-gatherers and pastoralists. Surveys of mammal populations in such areas provide important measures of biodiversity and provide ecological context for understanding hunting practices. Using a sampling grid centered on a Hadza hunter-gatherer camp and covering 36 km ² of semi-arid savannah in northern Tanzania, we assessed mammals using camera traps (n = 19 stations) for c. 5 months (2,182 trap nights). In the study area ( Tli’ika in the Hadza language), we recorded 36 wild mammal species. Rarefaction curves suggest that sampling effort was sufficient to capture mammal species richness, yet some species known to occur at low densities in the wider area (e.g. African lions, wildebeest) were not detected. Relative abundance indices of wildlife species varied by c. three orders of magnitude, from a mean of 0.04 (African wild dog) to 20.34 capture events per 100 trap-nights (Kirk’s dik dik). To contextualize the relative abundance of wildlife in the study area, we compared our study’s data to comparable camera trap data collected in a fully protected area of northern Tanzania with similar rainfall (Lake Manyara National Park). Raw data and negative binomial regression analyses show that wild herbivores and wild carnivores were generally detected in the national park at higher rates than in the Hadza-occupied region. Livestock were notably absent from the national park, but were detected at high levels in Tli’ika, and cattle was the second most frequently detected species in the Hadza-used area. We discuss how these data inform current conservation efforts, studies of Hadza hunting, and models of hunter-gatherer foraging ecology and diet.
... Pictures from Snapshot Serengeti, Tanzania, between July 2010 and April 2013. Raw data: all sequences produced during the survey; blank sorting: sequences with animals; species sorting 1: sequences with study species according to the volunteers; young sorting 1: sequences with at least one volunteer identifying 'young'; species sorting 2: sequences with study species corrected by trained observers; young sorting 2: sequences with at least one young according to the trained observers; young sorting 3: sequences with at least one young < 1 month old according to the trained observers; resight sorting: independent sequences once sequences taken less than 10 minutes after the previous one by the same camera trap and presenting the same species have been removed (following Palmer et al. 2018). Note the log scale for the ordinate axis, vertical bars represent the standard deviations. ...
Article
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Ecologists increasingly rely on camera-trap data to estimate biological parameters such as population abundance. Because of the huge amount of data camera trap can generate, the assistance of non-scientists is often sought after, but an assessment of the data quality is necessary. We tested whether volunteers data from one of the largest citizen science projects – Snapshot Serengeti – could be used to study breeding phenology. We tested whether the presence of juveniles (less than one or 12 months old) of species of large herbivores in the Serengeti: topi, kongoni, Grant’s gazelle, could be reliably detected by the ‘naive’ volunteers versus trained observers. We expected a positive correlation between the proportion of volunteers identifying juveniles and their effective presence within photographs, assessed by the trained observers. The agreement between the trained observers was good (Fleiss’ κ > 0.61 for juveniles of less than one and 12 month(s) old), suggesting that morphological criteria can be used to determine age of juveniles. The relationship between the proportion of volunteers detecting juveniles less than a month old and their actual presence plateaued at 0.45 for Grant’s gazelle, reached 0.70 for topi and 0.56 for kongoni. The same relationships were much stronger for juveniles younger than 12 months, reaching 1 for topi and kongoni. The absence of individuals < one month and the presence of juveniles < 12 months could be reliably assumed, respectively, when no volunteer and when all volunteers reported a presence of a young. In contrast, the presence of very young individuals and the absence of juveniles appeared more difficult to ascertain from volunteers’ classification, given how the classification task was presented to them. Volunteers’ classification allows a moderately accurate but quick sorting of photograph with/without juveniles. We discuss the limitations of using citizen science camera-traps data to study breeding phenology, and the options to improve the detection of juveniles.
... A relative abundance index (RAI) was calculated for each species as the number of independent events divided by the total number of days in which camera-traps were active, multiplied by 100 (O'Brien et al. 2003). RAI represents a measure of activity or 'density of detections' rather than an abundance index (Monterroso et al. 2013) because it does not consider detection probability and home-range size of each species (Sollmann et al. 2013;Palmer et al. 2018). Prey activity patterns to reduce predation risk Wildlife Research C So as to classify each species according to its selection of diel periods, we considered the following four periods, as described in Monterroso et al. (2013): Day, defined as the period between 1 h after sunrise and 1 h before sunset; Night, the period between 1 h after sunset and 1 h before sunrise; Dawn, the period between 1 prior and 1 h after sunrise; and Dusk, the period between 1 h prior and 1 h after sunset. ...
Article
Context. Some prey species can shift their daily activity patterns to reduce the risk of encountering predators, and, in turn, predators develop strategies to increase their chances of meeting prey. European rabbit (Oryctolagus cuniculus) is a key species in Iberian Mediterranean ecosystems. It is the main prey for many vertebrate predators. It is also a game species and is often the target of management measures such as translocations. Aims. To test whether rabbits adjust their activity patterns in response to differing predation regimes in a management context. Methods. Rabbits were translocated from a donor area, with a high rabbit density, to a release area in central Spain, with a semi-permeable fenced plot and an unfenced plot, which had no rabbits before the translocation. We estimated daily activity patterns and relative abundance index (RAI) for mesocarnivores and rabbits by using camera-traps, and calculated Jacobs selection index (JSI) to classify each species in a diel period. Additionally, we calculated the activity overlap between prey and mesocarnivores in the different areas. Key results. Rabbits were nocturnal in the donor area, where only two mesocarnivore species were detected, red fox (Vulpes vulpes, with a high RAI) and Egyptian mongoose (Herpestes ichneumon, with a low RAI). However, in the unfenced area, where five mesocarnivore species were present, rabbits showed a crepuscular trend with two activity peaks, around sunrise and around sunset. In contrast, rabbits showed a nocturnal activity in the fenced plot, where four mesocarnivore species were detected but where only the Egyptian mongoose (strictly diurnal) had a high RAI value. Conclusions and implications. The results suggest that rabbits in the fenced plot adapted their activity to avoid the diurnal mongooses. Conversely, rabbits in unfenced areas showed a trend towards day/twilight activity patterns as an adaptation to a diverse community of mesocarnivores. Rabbits can adapt their daily activity patterns to reduce predation risk depending on the pressure exerted by different predator species, with conservation and management implications. These adaptations would allow higher success of rabbit translocations despite the risk of predation by carnivores and could help in the management design of future translocations of this key species.
... Furthermore, this index is the best alternative when it is not possible to identify individuals (e.g., Wearn and Glover-Kapfer, 2017;Pardo et al., 2018). RAI values derived from large scale camera trapping have been shown to correlate strongly with independent density estimates for a range of species (Palmer et al., 2018). Variations in species richness over time at the wildlife-friendly farm were evaluated by a repeated measures ANOVA and paired-T test analysis using the rstatix package (Kassambara, 2020). ...
Article
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Agriculture is an essential production system used to feed the growing human population, but at the same time has become a major driver of biodiversity loss and environmental degradation. Employing production methods that restore degraded landscapes can have a positive impact on biodiversity, whilst improving food production. We assessed how mammalian biodiversity, specifically richness and their relative abundances varied on five Karoo farms in South Africa that had been amalgamated and subjected to a transition from traditional livestock grazing techniques (sporadic rotational grazing and lethal predator control) to wildlife-friendly non-lethal predator management, using human shepherding of livestock under a high-density short-duration grazing regime. We used camera trap data collected over a four-year period, to measure mammalian species richness, distribution and relative abundance on the wildlife-friendly farm to investigate temporal changes throughout the conversion from traditional farming practices. In the last year of the study (2019) additional cameras were used to provide a spatial comparison of mammalian species on the wildlife-friendly farm to two neighbouring farms, a traditional livestock farm using lethal predator controls, and a game farm. We found that mammalian species richness increased year on year resulting in a significant increase of 24% over the duration of the study. Herbivores showed an increase of 33% in the number of species detected over the years, while predator species increased by 8%. The relative abundance and distribution of most species also showed increases as the conversion process took place. For example, 73% of the herbivore species detected throughout the study increased in their relative abundance. Similarly, 67% of all species showed an increase in the number of sites occupied over the years. In the final year of the study the wildlife-friendly farm had more mammalian species compared to the game farm and traditional livestock farm, with the latter two sites having a similar number of species when compared to the commencement of the conversion of the wildlife-friendly site. These broad improvements in mammalian biodiversity demonstrate that livestock production can benefit local mammalian biodiversity through a combination of herder grazing management and wildlife-friendly farming.
... For species without unique markings, there is great interest in using photo capture rate as an index of relative abundance. While robust use of photo rate as an abundance index assumes that photo rate varies consistently and linearly with actual animal abundance (Pollock et al. 2002), those few studies that have investigated this critical assumption have come to varied conclusions (Rovero and Marshall 2009, Sollmann et al. 2013, Parsons et al. 2017, Palmer et al. 2018. Where the index fails, the confounding of abundance and detection is a critical challenge, and robust use of photo rate must necessarily address temporal and spatial variation in detection. ...
Article
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Abstract Counts of independent photo events from camera traps are commonly used to make inference about species occupancy, the density of unmarked populations, and the relative abundance of species across time and space. These applications rest on the untested assumption that data collected from individual cameras are representative of the landscape location in which they are placed, and that nearby cameras would record similar data when any additional micro‐site differences are accounted for. We established a high‐density camera trapping grid (100 × 100 m; 27 cameras) in Virginia, USA, to explicitly test these assumptions, investigating variation in capture rates and detection probabilities for a range of terrestrial mammals during four 2‐month seasonal surveys. Despite controlling for numerous habitat and placement factors, we documented, across all 5 focal species, large ranges and coefficients of variation in both capture rate and detection probabilities, which were similar to those seen across 2 sets of independent forest sampling sites from a larger, more typical camera trap sampling design. We also documented a lack of spatial autocorrelation in capture rate at any distance. Measured local covariates relevant to the camera viewshed (stem density, camera height, log presence, effective detection distance [EDD], total dbh of oak trees) rarely explained any significant portion of observed variation in capture rates or detection probabilities across the grid. The influence of EDD, measured here for the first time for individual camera stations, was inconsistently important and varied in direction of effect depending on species and season. Our study indicates single‐camera stations may fail to sample animal presence and frequency of use in a robust and repeatable way, primarily resulting from the influence of both idiosyncrasies in animal movement and measured and unknown micro‐site characteristics. We recommend spatial replication within sites (e.g., small‐scale shifting of cameras or use of multiple stations) should be considered to minimize impacts of relevant micro‐site characteristics, some of which may be difficult to identify.
... Data collected prior to the 2000s were not used in this analysis because it did not include the information necessary to calculate species RAI. 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) for some mammals. Sollmann (2018) indicated that RAI is sensitive to differences in sampling design. ...
Article
Documenting longitudinal changes in small mammal communities provides insights into ecosystem dynamics. We examined changes in small mammal communities of the Apostle Islands archipelago (Wisconsin, USA) since the establishment of the Apostle Islands National Lakeshore in 1970. We trapped small mammals from 20 of the 22 islands of the archipelago (2017–2020) and compared those results to historical (1961–2004) records. Microtus pennsylvanicus (p = 0.0076) and Sorex cinereus (p = 0.0268) exhibited significant changes in distribution. Microtus pennsylvanicus was likely extirpated from 10 of the 11 islands where it was previously detected, while S. cinereus increased in distribution. Peromyscus spp. colonized at least three islands since the establishment of the National Lakeshore, potentially through human-facilitated dispersal (i.e., boating, kayaking). Myodes gapperi remained widespread and abundant. Recent trends (2003–2004 to 2017–2020) in abundance indicated that S. cinereus may be declining locally on the islands, whereas Tamiasciurus hudsonicus may be increasing. Community diversity was driven by island size, regardless of variation over time. Long-term changes in small mammal populations across the archipelago likely reflect reduction of human extractive activities following the establishment of the National Lakeshore and the corresponding succession of vegetative communities. Our work suggests that even though small mammal communities of the archipelago have changed over time, larger islands may be able to better retain species that have been lost on others; therefore, island size remains an important predictor of community diversity.
... 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). ...
Article
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.
... 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). ...
Article
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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.
... 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). ...
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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.
... 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. ...
Article
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.
... 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). ...
Article
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.
... 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. ...
Article
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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. ...
... 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. ...
Article
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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.
... 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. ...
Article
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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.
... 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). ...
Article
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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). ...
Article
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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). ...
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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. ...
Article
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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. ...
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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. ...
Article
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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.
... It is also possible that RAI lacks the precision to tease out these effects, and covariates such as absolute leopard (Panthera pardus) density may perform differently to leopard RAI, although these data are not yet available. Although RAI can be biased by ecological factors and sampling design 47 , numerous camera trapping studies use RAI as a proxy for covariates, especially when density estimates are unavailable 39,46,48 . ...
Article
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Wildlife population density estimates provide information on the number of individuals in an area and influence conservation management decisions. Thus, accuracy is vital. A dominant feature in many landscapes globally is fencing, yet the implications of fence permeability on density estimation using spatial capture‐recapture modelling are seldom considered. We used camera trap data from 15 fenced reserves across South Africa to examine the density of brown hyaenas (Parahyaena brunnea). We estimated density and modelled its relationship with a suite of covariates when fenced reserve boundaries were assumed to be permeable or impermeable to hyaena movements. The best performing models were those that included only the influence of study site on both hyaena density and detection probability, regardless of assumptions of fence permeability. When fences were considered impermeable, densities ranged from 2.55 to 15.06 animals per 100 km2, but when fences were considered permeable, density estimates were on average 9.52 times lower (from 0.17 to 1.59 animals per 100 km2). Fence permeability should therefore be an essential consideration when estimating density, especially since density results can considerably influence wildlife management decisions. In the absence of strong evidence to the contrary, future studies in fenced areas should assume some degree of permeability in order to avoid overestimating population density.
... 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]. ...
Article
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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). ...
Article
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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). ...
Article
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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. ...
Article
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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). ...
Technical Report
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
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Shrub encroachment into arid grasslands occurs globally with the potential to affect vertebrates and their interactions. In the Chihuahuan Desert of southern New Mexico, shrub encroachment has prompted intensive efforts by land management agencies to remove shrubs and restore historical grassland habitats. We asked if restoration actions involving shrub removal affected dynamics of intraguild predation (IGP) including an IGP predator (coyote, Canis latrans), an IGP prey (kit fox, Vulpes macrotis), plus their shared lagomorph prey. We used camera traps on 14 sites with paired treated and untreated areas to examine spatial and temporal niche partitioning of coyotes and kit foxes. Shrub removal did not produce straightforward effects on abundances of coyotes, kit foxes, or their prey resources. Instead, abundances of kit foxes were constrained when coyote abundance reached a threshold. Below this threshold, kit foxes were more common on areas with low shrub cover, possibly due to lack of hiding cover for lagomorph prey that increased their predation risk. Our system included two alternative states: IGP predator dominated and coexistence of IGP predator and prey. Coexistence may have been facilitated by temporal niche partitioning as diel activity patterns differed for coyotes and kit foxes. Future research on intraguild predation should integrate spatial and temporal niches to understand species coexistence including on dynamic landscapes undergoing restoration.
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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.
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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.
Article
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Camera traps - remote cameras that capture images of passing wildlife - have become a ubiquitous tool in ecology and conservation. Systematic camera trap surveys generate ‘Big Data’ across broad spatial and temporal scales, providing valuable information on environmental and anthropogenic factors affecting vulnerable wildlife populations. However, the sheer number of images amassed can quickly outpace researchers’ ability to manually extract data from these images (e.g., species identities, counts, and behaviors) in timeframes useful for making scientifically-guided conservation and management decisions. Here, we present ‘Snapshot Safari’ as a case study for merging citizen science and machine learning to rapidly generate highly accurate ecological Big Data from camera trap surveys. Snapshot Safari is a collaborative cross-continental research and conservation effort with 1500+ cameras deployed at over 40 eastern and southern Africa protected areas, generating millions of images per year. As one of the first and largest-scale camera trapping initiatives, Snapshot Safari spearheaded innovative developments in citizen science and machine learning. We highlight the advances made and discuss the issues that arose using each of these methods to annotate camera trap data. We end by describing how we combined human and machine classification methods (‘Crowd AI’) to create an efficient integrated data pipeline. Ultimately, by using a feedback loop in which humans validate machine learning predictions and machine learning algorithms are iteratively retrained on new human classifications, we can capitalize on the strengths of both methods of classification while mitigating the weaknesses. Using Crowd AI to quickly and accurately ‘unlock’ ecological Big Data for use in science and conservation is revolutionizing the way we take on critical environmental issues in the Anthropocene era.
Article
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.
Article
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.
Technical Report
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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1.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.2.Recent statistical advances provide an increasingly diverse array of analytical approaches for estimating population size to address these phenomena.3.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 (GLMs 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.4.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.5. 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.6.Most emerging methods were developed over the past decade, so their efficacy is still under study and additional statistical advances are likely to occur.This article is protected by copyright. All rights reserved.
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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.
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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.
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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.
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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.