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How are frogs responding to hurricanes, droughts, and climate change?

Acoustic monitoring can help us understand how the frog community in Puerto Rico responds to different types of disturbances.Read more

Impacts of a large hydroelectric dam on the Madeira River (Brazil) on floodplain avifauna

Hydroelectric dams represent an important threat to seasonally flooded environments in the Amazon basin. We aimed to evaluate how a dam in the Madeira River, one of the largest tributaries of the Amazonas River, affected floodplain avifauna. Bird occurrence was recorded through simultaneous passive acoustic monitoring in early successional vegetation and floodplain forest downstream from the dam and upstream in sites impacted by permanent flooding after dam reservoir filling.

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The Role of Urbanness, Vegetation Structure, and Scale in Shaping Puerto Rico’s Acoustically Active Mangrove Fauna Communities

The mangroves of Puerto Rico occupy a gradient of urbanization that offers a chance to test hypotheses on urban faunal communities. These hypotheses state that urban avifaunal communities have greater representation by generalists and that certain mangrove specialists can utilize urban landscapes. Much of this is said to be driven by food resources, with frugivores and nectarivores benefiting from abundant residential flowers and fruits, while insectivores are driven away by low food resources.

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Climate change is creating a mismatch between protected areas and suitable habitats for frogs and birds in Puerto Rico

Climate change is altering the spatial distribution of many species around the world. In response, we need to identify and protect suitable areas for a large proportion of the fauna so that they persist through time. This exercise must also evaluate the ability of existing protected areas to provide safe havens for species in the context of climate change.

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Bird Occupancy of a Neotropical Forest is Stable but influenced by Forest age

The effects of forest degradation, fragmentation, and climate change occur over long time periods, yet relatively few data are available to evaluate the long-term effects of these disturbances on tropical species occurrence. Here, we quantified changes in occupancy of 50 bird species over 17 years on Barro Colorado Island (BCI), Panama, a model system for the long-term effects of habitat fragmentation.

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Impacts of Drought and Hurricane on tropical bird and frog distributions

During the last few decades, much attention has focused on how global change is affecting the environment and species distributions. Land-use change is still the major cause of species declines worldwide, but changes in species distributions have been documented even in pristine and protected areas. Here, we document the distribution dynamics of 26 species of frogs and birds within a Caribbean protected area between 2015 and 2019.

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Acoustic metrics predict habitat type and vegetation structure in the Amazon

The rapidly developing field of ecoacoustics offers methods that can advance multi-taxa animal surveys at policy-relevant extents. While the field is promising, there remain foundational assumptions that need to be tested across different biomes before the methods can be applied widely. Here we test two of these assumptions in the Amazon: 1) acoustic indices can be used to predict soundscapes of different habitat types, and 2) acoustic indices are related to vegetation structure.

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Identification of bird and frog species using a convolutional neural network

Automated acoustic recorders can collect long-term soundscape data containing species-specific signals in remote environments. Deep learning methods have gained recent attention for automating the process of species identification in soundscape recordings. We present an end-to-end pipeline for training a convolutional neural network (CNN) for multispecies multi-label classification of soundscape recordings, starting from raw, unlabeled audio.

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Multispecies Bioacoustic Classification using transfer learning of deep convolutional
neural networks with pseudo-labeling

In this study, we evaluated deep convolutional neural networks for classifying the calls of 24 birds and amphibian species detected in ambient field recordings. In classifying a test set of manually validated positive and negative template based detections, our proposed model achieves 97.7% sensitivity (true positive rate), 96.4% specificity (true negative rate) and 99.5% Area Under a Curve (AUC). This multi-label multi-species classification methodology and its framework can be easily adopted by other acoustic classification problems. Please email us at contact@rfcx.org for a copy of this article.

How does FSC forest certification affect the acoustically active fauna in Peru?

Despite several efforts to quantify the effectiveness of forest certification in developing sustainable use of forest resources, there is little evidence that certified forests are more effective in conserving fauna than non-certified managed forest. Our findings correspond with the conclusions of other studies that certified forests can maintain levels of fauna biodiversity similar to those of undisturbed primary forest in the Amazon region.

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