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NDVI values for habitat type a) savanna b) intermediate/shrub habitat type c) forest. Dark filled dots represent reliable, good quality measurements used in the analysis, and grey circles represent unreliable or low quality measurements.
Source publication
The Gran Sabana is a region of great biogeographical and conservation value that has been recently threatened due to increasing overexploitation, of natural resources and illegal mining. Systematic survey methods are required in order to study species responses to landscape transformation.
The main objectives of this study were: 1) to test the rela...
Contexts in source publication
Context 1
... show the NDVI values for the camera locations classified for each vegetation group (Figure 3). The NDVI value for savanna group is mostly between 0.4 and 0.7, with some seasonal observations below 0.4 (beginning of 2015 and 2016, but not evident in 2017, Figure 3a) and forest is above 0.8 for most of the year with some isolated observation are below this value (Figure 3c). ...
Context 2
... show the NDVI values for the camera locations classified for each vegetation group (Figure 3). The NDVI value for savanna group is mostly between 0.4 and 0.7, with some seasonal observations below 0.4 (beginning of 2015 and 2016, but not evident in 2017, Figure 3a) and forest is above 0.8 for most of the year with some isolated observation are below this value (Figure 3c). The shrub -transitional habitat has intermediate (values of NDVI (0.5 to 0.9; Figure 3b), but they are frequently below 0.8 (value for forest group). ...
Context 3
... show the NDVI values for the camera locations classified for each vegetation group (Figure 3). The NDVI value for savanna group is mostly between 0.4 and 0.7, with some seasonal observations below 0.4 (beginning of 2015 and 2016, but not evident in 2017, Figure 3a) and forest is above 0.8 for most of the year with some isolated observation are below this value (Figure 3c). The shrub -transitional habitat has intermediate (values of NDVI (0.5 to 0.9; Figure 3b), but they are frequently below 0.8 (value for forest group). ...
Context 4
... NDVI value for savanna group is mostly between 0.4 and 0.7, with some seasonal observations below 0.4 (beginning of 2015 and 2016, but not evident in 2017, Figure 3a) and forest is above 0.8 for most of the year with some isolated observation are below this value (Figure 3c). The shrub -transitional habitat has intermediate (values of NDVI (0.5 to 0.9; Figure 3b), but they are frequently below 0.8 (value for forest group). In some localities the NDVI values might be closer to the forest habitat (localities with negative silhouette width in Figure 2). ...
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Background and Research Aims
Forest loss and fragmentation have a negative impact on large-sized predators and prey, whose populations are reduced or extirpated locally. We explored the spatiotemporal coexistence of the mesopredators (< 15 kg) coyote, ocelot, and white-nosed coati, with their potential prey (< 15 kg) Mexican agouti, lowland paca, a...
Citations
... The resource selection model and the indicator value analysis agree on the importance of the forest as the most important habitat for native fauna. Half of the species indicated by both models displayed a similar preference for forest habitat 20 . Accounting for imperfect detection in the current analysis improves our ability to detect habitat preferences of species with restricted ranges, such as the endangered P. maximus and T. terrestris (Fig. 6a). ...
... For this vulnerable and cryptic species, deforestation is of the most important threats 46 . Two species avoid human communities L. pardalis and C. thous and the last is the only one with a strong preference for the savanna ecosystem (Fig. 6a, d) 20 . The species attracted to conuco were C. paca and E. barbara, which is consistent with The Garden Hunting hypothesis (Fig. 6c, 21 ). ...
... In Warapata camera trap surveys were conducted between September 2015 and April 2016 for three 60-day periods. In each period, we placed the cameras (n = 30) following a stratified random sampling design that allowed us to cover 86 sampling units (details in 20 ). ...
Efficient monitoring of biodiversity-rich areas in conflict-affected areas with poor rule of law requires a combination of different analytical approaches to account for data biases and incompleteness. In the upland Amazon region of Venezuela, in Canaima National Park, we initiated biodiversity monitoring in 2015, but it was interrupted by the establishment of a large-scale mining development plan in 2016, compromising the temporal and geographical extent of monitoring and the security of researchers. We used a resource selection function model framework that considers imperfect detectability and supplemented detections from camera trap surveys with opportunistic off-camera records (including animal tracks and direct sighting) to (1) gain insight into the value of additional occurrence records to accurately predict wildlife resource use in the perturbated area (deforestation, fire, swidden agriculture, and human settlements vicinity), (2) when faced with security and budget constraints. Our approach maximized the use of available data and accounted for biases and data gaps. Adding data from poorly sampled areas had mixed results on estimates of resource use for restricted species, but improved predictions for widespread species. If budget or resources are limited, we recommend focusing on one location with both on-camera and off-camera records over two with cameras. Combining camera trap records with other field observations (28 mammals and 16 birds) allowed us to understand responses of 17 species to deforestation, 15 to fire, and 13 to swidden agriculture. Our study encourages the use of combinations of methods to support conservation in high-biodiversity sites, where access is restricted, researchers are vulnerable, and unequal sampling efforts exist.
R esu men El monitoreo de fauna silvestre se basa en conteos directos o indirectos de animales o sus rastros, en unidades de muestreo (cámaras, transectos, trampas, redes, grabadores, u otro). Los conteos por unidad o esfuerzo de muestreo se expresan como tasa de encuentro, tasa fotográfica, tasa de captura, etc. Cuando se asume que la tasa está relacionada con el tamaño poblacional, entonces es considerada como un índice de abundancia relativa (IAR). Los cuales son empleados como al-ternativa a las estimaciones absolutas de la abundancia o densidad. Los IAR son utilizados para monitorear el cambio de una población a través del tiempo, o bien para comparar poblaciones de la misma especie en localidades diferentes. Con el incremento en el uso de las trampas cámara se ha popularizado el cálculo de los IAR para todas las especies fotografiadas en el área de estudio. Sin embargo, se debe tener precaución con esta interpretación ya que los IAR están sesgados por la detectabilidad que varía entre especies. En este artículo se 1) revisa las definiciones, los supues-tos y las limitaciones de los IAR; 2) explica la diferencia conceptual entre los IAR y las tasas de encuentro; 3) enfatiza la importancia de la probabilidad de detección como factor que afecta a los conteos y por ende a las tasas de encuentro; 4) sugiere usar los IAR solo para comparar a la misma especie temporal y espacialmente, mientras que la tasa de encuentro usarla para comparar entre especies; y 5) sugiero algunas alternativas de análisis estadísticos basados en modelos jerárquicos. Este artículo pretende aclarar que, si bien los IAR y las tasas de encuentro aritméticamente se calculan empleando la misma fórmula, conceptualmente son diferentes. La tasa de encuentro se puede interpretar como un IAR, solo si satisfacen los supuestos de 1) los conteos están correlacio-nados lineal y positivamente con la abundancia, y 2) la detección no varía a través del tiempo o entre localidades geográficas. Sin embargo, usualmente se desconoce si estos supuestos se cum-plen para todas las especies en el área de estudio. Por lo tanto, se sugiere solo emplear a los IAR para monitorear cambios poblacionales de una misma especie a través del tiempo y espacio, y en lo posible evitar comparar entre especies con diferente detectabilidad. Pal ab ras clave: monitoreo, tamaño poblacional, detectabilidad, modelos. Ab stract Wildlife monitoring is based on counts (direct of animals or indirect of their tracks) in sampling units (cameras, transects, traps, nets, recorders, or others). Counts per unit or sampling effort are expressed as rates (encounter rate, photographic rate, capture rate, or other). When it is assumed
El monitoreo de fauna silvestre se basa en conteos directos o indirectos de animales o sus rastros, en unidades de muestreo (cámaras, transectos, trampas, redes, grabadores, u otro). Los conteos por unidad o esfuerzo de muestreo se expresan como tasa de encuentro, tasa fotográfica, tasa de captura, etc. Cuando se asume que la tasa está relacionada con el tamaño poblacional, entonces es considerada como un índice de abundancia relativa (IAR). Los cuales son empleados como alternativa a las estimaciones absolutas de la abundancia o densidad. Los IAR son utilizados para monitorear el cambio de una población a través del tiempo, o bien para comparar poblaciones de la misma especie en localidades diferentes. Con el incremento en el uso de las cámaras trampa se ha popularizado el cálculo de los IAR para todas las especies fotografiadas en el área de estudio. Sin embargo, se debe tener precaución con esta interpretación ya que los IAR están sesgados por la detectabilidad que varía entre especies. En este artículo se 1) reviso las definiciones, los supuestos y las limitaciones de los IAR; 2) explica la diferencia conceptual entre los IAR y las tasas de encuentro; 3) enfatiza la importancia de la probabilidad de detección como factor que afecta a los conteos y por ende a las tasas de encuentro; 4) sugiere usar los IAR solo para comparar a la misma especie temporal y espacialmente, mientras que la tasa de encuentro usarla para comparar entre especies; y 5) sugiero algunas alternativas de análisis estadísticos basados en modelos jerárquicos.
The Amazon biome spans 6.7 million km2 across nine South American countries and is increasingly facing anthropogenic pressures. In this setting, we find a rich assemblage of carnivores composed of six species of felids, three canids, four procyonids, seven mustelids, and two mephitids. Several of these species are of conservation concern, both globally and regionally. Obtaining data on species occurrence and abundance is crucial for effective conservation actions. To this end, we gathered as much data as possible on Amazonian carnivores, focusing on relative abundance and population density. We also calculated and estimated population size for species of conservation concern, considering suitable habitat that remains. The results suggest a wide heterogeneity in species composition and abundance across the Amazon, with coatis, ocelots, and tayras being the most abundant species, while bush dogs, small cats, and greater grisons are the least abundant. The current analysis also illustrates the global importance of the Amazon biome for carnivore conservation, as the population estimates for most of the species of conservation concern are/appear to be robust enough for long-term persistence, and for some of these species, Amazonia is their last stronghold. Therefore, we recommend that more vigorous conservation actions across the biome be implemented.
Background
Human encroachment and overexploitation of natural resources in the Neotropics is constantly increasing. Indigenous communities all across the Amazon, are trapped between a population rise and a hot debate about the sustainability of hunting rates. The Garden Hunting hypothesis states that shifting cultivation schemes (conucos) used by Amazon indigenous communities may generate favorable conditions, increasing abundance of small and medium wildlife species close to the ‘gardens’ providing game for indigenous hunters.
Methods
Here, we combined camera trap surveys and spatially explicit interview dataset on Pemón indigenous hunting scope and occurrence in a mosaic of savanna and forest in the Gran Sabana, Venezuela to evaluate to what extent the wildlife resource use corresponds to Garden Hunting hypothesis. We applied the Royle–Nichols model and binomial regression in order to: (1) assess whether abundance of small and medium wildlife species is higher close to conucos and (2) evaluate whether hunters select hunting localities based on accessibility to wildlife resources (closeness to conuco) more than wildlife abundance.
Results
We find mixed evidence supporting the Garden Hunting hypothesis predictions. Abundance of small and medium species was high close to conucos but the pattern was not statistically significant for most of them. Pemón seem to hunt in locations dominated by forest, where species abundance was predicted to be higher, than in close vicinity to conucos. Hunting scope was focused on the most abundant species located close to the conuco ( Cuniculus paca ), but also in less abundant and unavailable species ( Crax alector, Tapirus terrestris and Odocoileus virginianus) .
Conclusions
Our research provided the first attempt of a systematic sampling survey in the Gran Sabana, generating a quantitative dataset that not only describes the current pattern of wildlife abundance, but sets the base-line to monitor temporal and spatial change in this region of highland Amazon. We discuss the applicability of the estimates generated as a baseline as well as, environmental challenges imposed by economic, social and cultural changes such as mining encroachment for wildlife management.
