Lack of local genetic representation in one of the regions with the highest bird species richness, the Peruvian Amazonia.

Peru ranks among the three countries with the highest bird species diversity globally and a majority of those species are found in the Peruvian Amazon. However, birds in this area are currently facing serious anthropogenic threats. Genetic and genomic methods are becoming important tools for avian biodiversity monitoring and conservation planning. Comprehensive molecular libraries that are publicly available are key to the effective deployment of these tools. We analyze the information gaps for four molecular markers in the most important genetic sequence databases, Barcode of Life Data Systems (BOLD) and NCBI GenBank, for bird species of the Peruvian Amazonia. We found that 64% of Peruvian Amazonian bird species have gene sequences for COI, 59.5% have CYTB sequences, 16.4% have 12S sequences, and only 0.6% have 18S sequences. However, these numbers decrease drastically to 4.3% for COI sequences when we only consider specimens sampled in Peru. Our data also showed that 43.8% of Peruvian Amazonian endemic species (n = 32) are missing sequences of any screened marker uploaded to GenBank or BOLD. Our results will encourage and guide efforts of the scientific community to complete reference libraries for Peruvian avian species that will be useful for future DNA-based monitoring projects that include birds.

Madagascar Terrestrial Camera Survey Database 2021: A collation of protected forest camera surveys from 2007-2021.

Madagascar is a threatened global biodiversity hotspot and conservation priority, yet we lack broad-scale surveys to assess biodiversity across space and time. To fill this gap, we collated camera trap surveys, capturing species occurrences within Madagascar into a single standardized database. This data set includes nine distinct protected areas of Madagascar and encompasses 13 subprojects, 38 camera arrays, and 1156 sampling units (independent camera site per survey) within two important biodiversity eco-regions: western dry deciduous forest and eastern humid rainforest. Camera surveys were conducted from June 2007 to January 2021. The final data set includes 17 unique families of mammals (Bovidae, Canidae, Cheirogaleidae, Daubentoniidae, Equidae, Eupleridae, Felidae, Hominidae, Indriidae, Lemuridae, Lepilemuridae, Muridae, Nesomyidae, Pteropodidae, Soricidae, Suidae, Tenrecidae) comprising 45 species and 27 unique families of birds (Accipitridae, Acrocephalidae, Alcedinidae, Bernieridae, Brachypteraciidae, Caprimulgidae, Cisticolidae, Columbidae, Coraciidae, Corvidae, Cuculidae, Dicruridae, Mesitornithidae, Monarchidae, Motacillidae, Muscicapidae, Numididae, Phasianidae, Rallidae, Sarothruridae, Strigidae, Sturnidae, Sulidae, Threskiornithidae, Upupidae, Vangidae, Zosteropidae) comprising 58 species. Images were processed and verified by individual project data set creators and camera operation and species tables were then collated. The final product represents the first broad-scale freely available standardized formal faunal database for Madagascar. Data are available through this publication and at DOI: 10.5281/zenodo.5801806. These data will be useful for examining species-level and community-level trends in occurrence across space or time within Madagascar and globally, evaluating native and invasive species dynamics, and will aid in determining species conservation status and planning for at-risk species. There are no copyright restrictions; please cite this paper when using the data for publication.

Environmental and anthropogenic factors synergistically affect space use of jaguars.

Large terrestrial carnivores have undergone some of the largest population declines and range reductions of any species, which is of concern as they can have large effects on ecosystem dynamics and function.1-4 The jaguar (Panthera onca) is the apex predator throughout the majority of the Neotropics; however, its distribution has been reduced by >50% and it survives in increasingly isolated populations.5 Consequently, the range-wide management of the jaguar depends upon maintaining core populations connected through multi-national, transboundary cooperation, which requires understanding the movement ecology and space use of jaguars throughout their range.6-8 Using GPS telemetry data for 111 jaguars from 13 ecoregions within the four biomes that constitute the majority of jaguar habitat, we examined the landscape-level environmental and anthropogenic factors related to jaguar home range size and movement parameters. Home range size decreased with increasing net productivity and forest cover and increased with increasing road density. Speed decreased with increasing forest cover with no sexual differences, while males had more directional movements, but tortuosity in movements was not related to any landscape factors. We demonstrated a synergistic relationship between landscape-scale environmental and anthropogenic factors and jaguars' spatial needs, which has applications to the conservation strategy for the species throughout the Neotropics. Using large-scale collaboration, we overcame limitations from small sample sizes typical in large carnivore research to provide a mechanism to evaluate habitat quality for jaguars and an inferential modeling framework adaptable to the conservation of other large terrestrial carnivores.

Identifying gaps in the photographic record of the vascular plant flora of the Americas.

Field photographs of plant species are crucial for research and conservation, but the lack of a centralized database makes them difficult to locate. We surveyed 25 online databases of field photographs and found that they harboured only about 53% of the approximately 125,000 vascular plant species of the Americas. These results reflect the urgent need for a centralized database that can both integrate and complete the photographic record of the world's flora.

Environmental DNA metabarcoding as a useful tool for evaluating terrestrial mammal diversity in tropical forests.

Innovative techniques, such as environmental DNA (eDNA) metabarcoding, are now promoting broader biodiversity monitoring at unprecedented scales, because of the reduction in time, presumably lower cost, and methodological efficiency. Our goal was to assess the efficiency of established inventory techniques (live-trapping grids, pitfall traps, camera trapping, mist netting) as well as eDNA for detecting Amazonian mammals. For terrestrial small mammals, we used 32 live-trapping grids based on Sherman and Tomahawk traps (total effort of 10,368 trap-nights); in addition to 16 pitfall traps (1,408 trap-nights). For bats, we used mist nets at 8 sites (4,800 net hours). For medium and large mammals, we used 72 camera trap stations (5,208 camera-days). We identified vertebrate and mammal taxa based on eDNA analysis (12S region, with V05 and Mamm01 markers) from water samples, including a total of 11 3-km transects for stagnant water sampling and seven small streams for running water sampling. A total of 106 mammal species were recorded. Building on sample-based rarefaction and extrapolation curves, both trapping grids and pitfall were successful, recording 91.16% and 82.1% of the expected species for these techniques (~22 and ~9 species), and 16.98% and 6.60% of the total recorded mammal species, respectively. Mist nets recorded 83.2% of the expected bat species (~48), and 34.91% of the total recorded species. Camera trapping recorded 99.2% of the predicted large- and medium-sized species (~31), and 33.02% of the total recorded species. eDNA recorded 75.4% of the expected mammal species for this technique (~68), and 47.0% of the total recorded species. eDNA resulted in a useful tool that saves on effort and reduces sampling costs. This study is among the first to show the large potential of eDNA metabarcoding for assessing Amazonian mammal communities, providing, in combination with conventional techniques, a rapid overview of mammal diversity with broad applications to monitoring, management and conservation. By including appropriate genetic markers and updated reference databases, eDNA metabarcoding method can be extended to the whole vertebrate community.

Camera settings and biome influence the accuracy of citizen science approaches to camera trap image classification.

Scientists are increasingly using volunteer efforts of citizen scientists to classify images captured by motion-activated trail cameras. The rising popularity of citizen science reflects its potential to engage the public in conservation science and accelerate processing of the large volume of images generated by trail cameras. While image classification accuracy by citizen scientists can vary across species, the influence of other factors on accuracy is poorly understood. Inaccuracy diminishes the value of citizen science derived data and prompts the need for specific best-practice protocols to decrease error. We compare the accuracy between three programs that use crowdsourced citizen scientists to process images online: Snapshot Serengeti, Wildwatch Kenya, and AmazonCam Tambopata. We hypothesized that habitat type and camera settings would influence accuracy. To evaluate these factors, each photograph was circulated to multiple volunteers. All volunteer classifications were aggregated to a single best answer for each photograph using a plurality algorithm. Subsequently, a subset of these images underwent expert review and were compared to the citizen scientist results. Classification errors were categorized by the nature of the error (e.g., false species or false empty), and reason for the false classification (e.g., misidentification). Our results show that Snapshot Serengeti had the highest accuracy (97.9%), followed by AmazonCam Tambopata (93.5%), then Wildwatch Kenya (83.4%). Error type was influenced by habitat, with false empty images more prevalent in open-grassy habitat (27%) compared to woodlands (10%). For medium to large animal surveys across all habitat types, our results suggest that to significantly improve accuracy in crowdsourced projects, researchers should use a trail camera set up protocol with a burst of three consecutive photographs, a short field of view, and determine camera sensitivity settings based on in situ testing. Accuracy level comparisons such as this study can improve reliability of future citizen science projects, and subsequently encourage the increased use of such data.

Joint species distribution models with species correlations and imperfect detection.

Spatiotemporal patterns in biological communities are typically driven by environmental factors and species interactions. Spatial data from communities are naturally described by stacking models for all species in the community. Two important considerations in such multispecies or joint species distribution models (JSDMs) are measurement errors and correlations between species. Up to now, virtually all JSDMs have included either one or the other, but not both features simultaneously, even though both measurement errors and species correlations may be essential for achieving unbiased inferences about the distribution of communities and species co-occurrence patterns. We developed two presence-absence JSDMs for modeling pairwise species correlations while accommodating imperfect detection: one using a latent variable and the other using a multivariate probit approach. We conducted three simulation studies to assess the performance of our new models and to compare them to earlier latent variable JSDMs that did not consider imperfect detection. We illustrate our models with a large Atlas data set of 62 passerine bird species in Switzerland. Under a wide range of conditions, our new latent variable JSDM with imperfect detection and species correlations yielded estimates with little or no bias for occupancy, occupancy regression coefficients, and the species correlation matrix. In contrast, with the multivariate probit model we saw convergence issues with large data sets (many species and sites) resulting in very long run times and larger errors. A latent variable model that ignores imperfect detection produced correlation estimates that were consistently negatively biased, that is, underestimated. We found that the number of latent variables required to represent the species correlation matrix adequately may be much greater than previously suggested, namely around n/2, where n is community size. The analysis of the Swiss passerine data set exemplifies how not accounting for imperfect detection will lead to negative bias in occupancy estimates and to attenuation in the estimated covariate coefficients in a JSDM. Furthermore, spatial heterogeneity in detection may cause spurious patterns in the estimated species correlation matrix if not accounted for. Our new JSDMs represent an important extension of current approaches to community modeling to the common case where species presence-absence cannot be detected with certainty.

Density trends and demographic signals uncover the long-term impact of transmissible cancer in Tasmanian devils.

1. Monitoring the response of wild mammal populations to threatening processes is fundamental to effective conservation management. This is especially true for infectious diseases, which may have dynamic and therefore unpredictable interactions with their host. 2. We investigate the long-term impact of a transmissible cancer, devil facial tumour disease (DFTD), on the endemic Tasmanian devil. We analyse trends in devil spot-light counts and density across the area impacted by the disease. We investigate the demographic parameters which might be driving these trends, and use spatial capture-recapture models to examine whether DFTD has affected home range size. 3. We found that devils have declined by an average of 77% in areas affected by DFTD, and that there is a congruent trend of ongoing small decline in spotlight counts and density estimates. Despite this, devils have persisted to date within each of nine monitoring sites. One site is showing as yet unexplained small increases in density 8-10 years after the emergence of DFTD. 4. We also found the prevalence of DFTD has not abated despite large declines in density and that diseased sites continue to be dominated by young devils. The long-term impact of the disease has been partially offset by increased fecundity in the form of precocial breeding in 1-year-old females, and more pouch young per female in diseased sites. The lower densities resulting from DFTD did not affect home range size. 5. Synthesis and applications. Transmission of devil facial tumour disease continues despite large declines in devil density over multiple generations. Plasticity in life history traits has ameliorated the impact of devil facial tumour disease, however broad-scale trends in density show ongoing decline. In light of this, devil facial tumour disease and the impact of stochastic events on the reduced densities wrought by the disease, continue to threaten devils. In the absence of methods to manage disease in wild populations, we advocate managing the low population densities resulting from disease rather than disease per se.

Publisher Correction: Sumatran tiger survival threatened by deforestation despite increasing densities in parks.

In the original version of the Article, reference 18 was incorrectly numbered as reference 30, and references 19 to 30 were incorrectly numbered as 18 to 29. These errors have now been corrected in the PDF and HTML versions of the manuscript.

Sumatran tiger survival threatened by deforestation despite increasing densities in parks.

The continuing development of improved capture-recapture (CR) modeling techniques used to study apex predators has also limited robust temporal and cross-site analyses due to different methods employed. We develop an approach to standardize older non-spatial CR and newer spatial CR density estimates and examine trends for critically endangered Sumatran tigers (Panthera tigris sumatrae) using a meta-regression of 17 existing densities and new estimates from our own fieldwork. We find that tiger densities were 47% higher in primary versus degraded forests and, unexpectedly, increased 4.9% per yr from 1996 to 2014, likely indicating a recovery from earlier poaching. However, while tiger numbers may have temporarily risen, the total potential island-wide population declined by 16.6% from 2000 to 2012 due to forest loss and degradation and subpopulations are significantly more fragmented. Thus, despite increasing densities in smaller parks, we conclude that there are only two robust populations left with >30 breeding females, indicating Sumatran tigers still face a high risk of extinction unless deforestation can be controlled.