Protected areas slow declines unevenly across the tetrapod tree of life.

Protected areas (PAs) are the primary strategy for slowing terrestrial biodiversity loss. Although expansion of PA coverage is prioritized under the Convention on Biological Diversity, it remains unknown whether PAs mitigate declines across the tetrapod tree of life and to what extent land cover and climate change modify PA effectiveness1,2. Here we analysed rates of change in abundance of 2,239 terrestrial vertebrate populations across the globe. On average, vertebrate populations declined five times more slowly within PAs (-0.4% per year) than at similar sites lacking protection (-1.8% per year). The mitigating effects of PAs varied both within and across vertebrate classes, with amphibians and birds experiencing the greatest benefits. The benefits of PAs were lower for amphibians in areas with converted land cover and lower for reptiles in areas with rapid climate warming. By contrast, the mitigating impacts of PAs were consistently augmented by effective national governance. This study provides evidence for the effectiveness of PAs as a strategy for slowing tetrapod declines. However, optimizing the growing PA network requires targeted protection of sensitive clades and mitigation of threats beyond PA boundaries. Provided the conditions of targeted protection, adequate governance and well-managed landscapes are met, PAs can serve a critical role in safeguarding tetrapod biodiversity.

Application of a deep learning image classifier for identification of Amazonian fishes.

Given the sharp increase in agricultural and infrastructure development and the paucity of widespread data available to support conservation management decisions, a more rapid and accurate tool for identifying fish fauna in the world's largest freshwater ecosystem, the Amazon, is needed. Current strategies for identification of freshwater fishes require high levels of training and taxonomic expertise for morphological identification or genetic testing for species recognition at a molecular level. To overcome these challenges, we built an image masking model (U-Net) and a convolutional neural net (CNN) to classify Amazonian fish in photographs. Fish used to generate training data were collected and photographed in tributaries in seasonally flooded forests of the upper Morona River valley in Loreto, Peru in 2018 and 2019. Species identifications in the training images (n = 3068) were verified by expert ichthyologists. These images were supplemented with photographs taken of additional Amazonian fish specimens housed in the ichthyological collection of the Smithsonian's National Museum of Natural History. We generated a CNN model that identified 33 genera of fishes with a mean accuracy of 97.9%. Wider availability of accurate freshwater fish image recognition tools, such as the one described here, will enable fishermen, local communities, and citizen scientists to more effectively participate in collecting and sharing data from their territories to inform policy and management decisions that impact them directly.

Dado el aumento del desarrollo agrícola e infraestructura y la escasa información disponible para apoyar la toma de decisiones con respecto al manejo y la conservación de la fauna, es necesario contar con una herramienta más rápida y precisa para la identificación de peces en el ecosistema de agua dulce más grande del mundo, la Amazonía. Las estrategias actuales para la identificación de peces de agua dulce requieren altos niveles de capacitación y experiencia taxonómica para la identificación morfológica o las pruebas genéticas para el reconocimiento de especies a nivel molecular. Para superar estos desafíos, construimos un modelo de enmascaramiento de imágenes (U­Net) y una red neuronal convolucional (CNN) para clasificar los peces amazónicos en las fotografías. Los peces utilizados para generar datos de entrenamiento fueron recolectados y fotografiados en afluentes de bosques inundables de la cuenca alta del río Morona en Loreto, Perú en 2018 y 2019. Las identificaciones de especies en las imágenes de entrenamiento (n = 3.068) fueron verificadas por ictiólogos expertos. Estas imágenes se complementaron con fotografías tomadas de ejemplares adicionales de peces amazónicos alojados en la colección ictiológica del Museo Nacional de Historia Natural del Smithsonian en Washington, DC. Se generó un modelo CNN que identificó 33 géneros de peces con una precisión media del 97,9%. Una mayor disponibilidad de herramientas precisas de reconocimiento de imágenes de peces de agua dulce, como la que se describe aquí, permitirá a los pescadores, las comunidades amazónicas y los "científicos ciudadanos" participar de manera más efectiva en la recopilación y el intercambio de datos de sus territorios para informar las políticas y decisiones de gestión que los afectan directamente.

Ectoparasitism by Chigger Mite Larvae (Acari: Trombiculidae) in a Wintering Population of Catharus ustulatus (Turdidae) in Southeastern Peru.

We document chigger mite (Acari: Trombiculidae) ectoparasitic infestation (prevalence and intensity) on a population of Catharus ustulatus (Turdidae) wintering at a site (PAD A) in southeastern Peru undergoing development for natural gas exploration. We compare prevalence (i.e., the proportion of individuals infested by chigger mites) and intensity (i.e., the average number of larvae and larvae clusters in infested individuals) at forest edge (<100 m) and interior (>100 m) from PAD A because variations in biotic (e.g., vegetation cover) and abiotic (e.g., relative humidity and temperature) factors are expected to influence chigger mite abundance. Chigger mite prevalence was 100%; all C. ustulatus captured were infested regardless of distance. The range of variation in larvae (2-72 larvae/individual) and cluster intensity (1-4 clusters/individual) did not differ between edge and interior ( P > 0.05), despite differences in herbaceous vegetation cover (UM-W = 180, n = 30, 31; P < 0.01). Ectoparasitic prevalence and intensity in long-distance migratory birds might add risks to an already hazardous journey; because ectoparasitic variation and other selective pressures experienced by individuals at each locality not only may be a cause of within-site mortality, but, by affecting the physical condition of birds, may be carried over to subsequent sites and affect reproductive success and survival. Documenting ectoparasitism at any phase of the life cycle of migrants could improve understanding of population declines of migratory birds.

How many species and under what names? Using DNA barcoding and GenBank data for west Central African amphibian conservation.

Development projects in west Central Africa are proceeding at an unprecedented rate, often with little concern for their effects on biodiversity. In an attempt to better understand potential impacts of a road development project on the anuran amphibian community, we conducted a biodiversity assessment employing multiple methodologies (visual encounter transects, auditory surveys, leaf litter plots and pitfall traps) to inventory species prior to construction of a new road within the buffer zone of Moukalaba-Doudou National Park, Gabon. Because of difficulties in morphological identification and taxonomic uncertainty of amphibian species observed in the area, we integrated a DNA barcoding analysis into the project to improve the overall quality and accuracy of the species inventory. Based on morphology alone, 48 species were recognized in the field and voucher specimens of each were collected. We used tissue samples from specimens collected at our field site, material available from amphibians collected in other parts of Gabon and the Republic of Congo to initiate a DNA barcode library for west Central African amphibians. We then compared our sequences with material in GenBank for the genera recorded at the study site to assist in identifications. The resulting COI and 16S barcode library allowed us to update the number of species documented at the study site to 28, thereby providing a more accurate assessment of diversity and distributions. We caution that because sequence data maintained in GenBank are often poorly curated by the original submitters and cannot be amended by third-parties, these data have limited utility for identification purposes. Nevertheless, the use of DNA barcoding is likely to benefit biodiversity inventories and long-term monitoring, particularly for taxa that can be difficult to identify based on morphology alone; likewise, inventory and monitoring programs can contribute invaluable data to the DNA barcode library and the taxonomy of complex groups. Our methods provide an example of how non-taxonomists and parataxonomists working in understudied parts of the world with limited geographic sampling and comparative morphological material can use DNA barcoding and publicly available sequence data (GenBank) to rapidly identify the number of species and assign tentative names to aid in urgent conservation management actions and contribute to taxonomic resolution.

Natural canopy bridges effectively mitigate tropical forest fragmentation for arboreal mammals.

Linear infrastructure development and resulting habitat fragmentation are expanding in Neotropical forests, and arboreal mammals may be disproportionately impacted by these linear habitat clearings. Maintaining canopy connectivity through preservation of connecting branches (i.e. natural canopy bridges) may help mitigate that impact. Using camera traps, we evaluated crossing rates of a pipeline right-of-way in a control area with no bridges and in a test area where 13 bridges were left by the pipeline construction company. Monitoring all canopy crossing points for a year (7,102 canopy camera nights), we confirmed bridge use by 25 mammal species from 12 families. With bridge use beginning immediately after exposure and increasing over time, use rates were over two orders of magnitude higher than on the ground. We also found a positive relationship between a bridge's use rate and the number of species that used it, suggesting well-used bridges benefit multiple species. Data suggest bridge use may be related to a combination of bridge branch connectivity, multiple connections, connectivity to adjacent forest, and foliage cover. Given the high use rate and minimal cost, we recommend all linear infrastructure projects in forests with arboreal mammal populations include canopy bridges.