Aim Unsustainable hunting is leading to widespread defaunation across the tropics. To mitigate against this threat with limited conservation resources, stakeholders must make decisions on where to focus anti‐poaching activities. Identifying priority areas in a robust way allows decision‐makers to target areas of conservation importance, therefore maximizing the impact of conservation interventions. Location Annamite mountains, Vietnam and Laos. Methods We conducted systematic landscape‐scale surveys across five study sites (four protected areas, one unprotected area) using camera‐trapping and leech‐derived environmental DNA. We analysed detections within a Bayesian multispecies occupancy framework to evaluate species responses to environmental and anthropogenic influences. Species responses were then used to predict occurrence to unsampled regions. We used predicted species richness maps and occurrence of endemic species to identify areas of conservation importance for targeted conservation interventions. Results Analyses showed that habitat‐based covariates were uninformative. Our final model therefore incorporated three anthropogenic covariates as well as elevation, which reflects both ecological and anthropogenic factors. Conservation‐priority species tended to found in areas that are more remote now or have been less accessible in the past, and at higher elevations. Predicted species richness was low and broadly similar across the sites, but slightly higher in the more remote site. Occupancy of the three endemic species showed a similar trend. Main conclusion Identifying spatial patterns of biodiversity in heavily defaunated landscapes may require novel methodological and analytical approaches. Our results indicate that to build robust prediction maps it is beneficial to sample over large spatial scales, use multiple detection methods to increase detections for rare species, include anthropogenic covariates that capture different aspects of hunting pressure and analyse data within a Bayesian multispecies framework. Our models further suggest that more remote areas should be prioritized for anti‐poaching efforts to prevent the loss of rare and endemic species.
Habitat degradation and hunting have caused the widespread loss of larger vertebrate species (defaunation) from tropical biodiversity hotspots. However, these defaunation drivers impact vertebrate biodiversity in different ways and, therefore, require different conservation interventions. We conducted landscape-scale camera-trap surveys across six study sites in Southeast Asia to assess how moderate degradation and intensive, indiscriminate hunting differentially impact tropical terrestrial mammals and birds. We found that functional extinction rates were higher in hunted compared to degraded sites. Species found in both sites had lower occupancies in the hunted sites. Canopy closure was the main predictor of occurrence in the degraded sites, while village density primarily influenced occurrence in the hunted sites. Our findings suggest that intensive, indiscriminate hunting may be a more immediate threat than moderate habitat degradation for tropical faunal communities, and that conservation stakeholders should focus as much on overhunting as on habitat conservation to address the defaunation crisis.
Aim: Unsustainable hunting is leading to widespread defaunation across the tropics. To 21 mitigate against this threat with limited conservation resources, stakeholders must 22 make decisions on where to focus anti-poaching activities. Identifying priority areas in a 23 robust way allows decision-makers to target areas of conservation importance, 24 therefore maximizing the impact of conservation interventions. 25 Location: Annamite mountains, Vietnam and Laos.26 2 Methods: We conducted systematic landscape-scale surveys across five study sites (four 27 protected areas, one unprotected area) using camera-trapping and leech-derived 28 environmental DNA. We analyzed detections within a Bayesian multi-species occupancy 29 framework to evaluate species responses to environmental and anthropogenic 30 influences. Species responses were then used to predict occurrence to unsampled 31 regions. We used predicted species richness maps and occurrence of endemic species to 32 identify areas of conservation importance for targeted conservation interventions.33 Results: Analyses showed that habitat-based covariates were uninformative. Our final 34 model therefore incorporated three anthropogenic covariates as well as elevation, which 35 reflects both ecological and anthropogenic factors. Conservation-priority species tended 36to found in areas that are more remote now or have been less accessible in the past, and 37 at higher elevations. Predicted species richness was low and broadly similar across the 38 sites, but slightly higher in the more remote site. Occupancy of the three endemic species 39 showed a similar trend. 40Main conclusion: Identifying spatial patterns of biodiversity in heavily-defaunated 41 landscapes may require novel methodological and analytical approaches. Our results 42 indicate to build robust prediction maps it is beneficial to sample over large spatial 43 scales, use multiple detection methods to increase detections for rare species, include 44 anthropogenic covariates that capture different aspects of hunting pressure, and analyze 45 data within a Bayesian multi-species framework. Our models further suggest that more 46 remote areas should be prioritized for anti-poaching efforts to prevent the loss of rare 47 and endemic species. 48
Crested gibbons, genus Nomascus, are endemic to the Indochinese bioregion and occur only in Vietnam, Laos, Cambodia, and southern China. However, knowledge about the number of species to be recognized and their exact geographical distributions is still limited. To further elucidate the evolutionary history of crested gibbon species and to settle their distribution ranges, we analyzed the complete mitochondrial cytochrome b gene from 79 crested gibbon individuals from known locations. Based on our findings, crested gibbons should be classified into seven species. Within N. concolor, we recognize two subspecies, N. concolor concolor and N. concolor lu. Phylogenetic reconstructions indicate that the northernmost species, N. hainanus, N. nasutus, and N. concolor branched off first, suggesting that the genus originated in the north and successively migrated to the south. The most recent splits within Nomascus occurred between N. leucogenys and N. siki, and between Nomascus sp. and N. gabriellae. Based on our data, the currently postulated distributions of the latter four species have to be revised. Our study shows that molecular methods are a useful tool to elucidate phylogenetic relationships among crested gibbons and to determine species boundaries.
Some animal species are hard to see but easy to hear. Standard visual methods for estimating population density for such species are often ineffective or inefficient, but methods based on passive acoustics show more promise. We develop spatially explicit capture-recapture (SECR) methods for territorial vocalising species, in which humans act as an acoustic detector array. We use SECR and estimated bearing data from a single-occasion acoustic survey of a gibbon population in northeastern Cambodia to estimate the density of calling groups. The properties of the estimator are assessed using a simulation study, in which a variety of survey designs are also investigated. We then present a new form of the SECR likelihood for multi-occasion data which accounts for the stochastic availability of animals. In the context of gibbon surveys this allows model-based estimation of the proportion of groups that produce territorial vocalisations on a given day, thereby enabling the density of groups, instead of the density of calling groups, to be estimated. We illustrate the performance of this new estimator by simulation. We show that it is possible to estimate density reliably from human acoustic detections of visually cryptic species using SECR methods. For gibbon surveys we also show that incorporating observers’ estimates of bearings to detected groups substantially improves estimator performance. Using the new form of the SECR likelihood we demonstrate that estimates of availability, in addition to population density and detection function parameters, can be obtained from multi-occasion data, and that the detection function parameters are not confounded with the availability parameter. This acoustic SECR method provides a means of obtaining reliable density estimates for territorial vocalising species. It is also efficient in terms of data requirements since since it only requires routine survey data. We anticipate that the low-tech field requirements will make this method an attractive option in many situations where populations can be surveyed acoustically by humans.
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