bioRxiv Science⌕ Search

bioRxiv · 10.64898/2026.11.12.766214

Beaver Impacts Tool: A Graphical User Interface for Analyzing Ecosystem Impacts of Beaver Dams Using Remote Sensing Data

Abstract

Beavers are being increasingly recognized as driving factors in diverse and resilient riparian ecosystems. Many of their impacts, including changes to water levels and vegetation, can be studied through remote sensing. However, ecologists and conservationists may lack the tools to easily analyze remote sensing data for these purposes. We offer here a Google Earth Engine-backed Streamlit app that allows users to easily upload locations of observed dams or installed beaver dam analogs for analysis. Via a graphical user interface, users then generate a set of dam-absent locations for comparison and receive plots and numerical data indicating how indices associated with vegetation, water, temperature, and evapotranspiration change over time for dam-present and dam-absent locations. Based on the availability of open datasets, our tool provides coverage from 2017 onward. The cloud version of the tool can be accessed via a static URL, or users can run the app locally using code and documentation provided on github. We believe this tool will allow a wider range of ecologists and conservationists to complement their work with the use of remote sensing data, without the need to gain expertise in specific software.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Tyree, Q., Etheredge, J., Kong, Z., Murray, C., Norcross, C., Owens-Rios, W. A., Lindsay, G. W.. 2026-11-13. Beaver Impacts Tool: A Graphical User Interface for Analyzing Ecosystem Impacts of Beaver Dams Using Remote Sensing Data. https://doi.org/10.64898/2026.11.12.766214

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Rapid estimation of insect biodiversity using AI assisted image analysis:a cost-effective tool for monitoring and ecological assessmen

Protection of natural areas and environmentally friendly management of anthropogenic landscapes require reliable tools for monitoring and comparing biodiversity. Bioindicator-based approaches can support large-scale ecological assessment, but insect monitoring remains constrained by the taxonomic expertise required for species identification. Here, we propose an AI-supported index for estimating the biodiversity of flying insects, based on the diversity of visual features of insect bodies. Flying insects were captured using yellow sticky traps across agricultural and natural habitats, seasons, crops, and sites in Israel's Mediterranean region. Traps were scanned at high resolution and uploaded to a dedicated image database. A machine learning model was used to detect and delineate insects, after which engineered visual features representing body size, color, and shape were extracted. Biodiversity was estimated from distances among feature vectors and compared with taxonomic diversity derived from expert identification of a representative validation set. The AI-derived diversity index correlated strongly with expert-based taxonomic diversity, supporting the hypothesis that morphological variation in insect images can provide a proxy for taxonomic diversity. Applying the index to the full dataset revealed a negative relationship between insect abundance and diversity, while diversity also varied across habitats and sampling seasons. Our results demonstrate the potential of AI-based image analysis to provide rapid and cost-effective assessments of insect biodiversity without requiring complete taxonomic identification. This approach may facilitate biodiversity monitoring and support timely ecological assessment and decision-making in sustainable agricultural and landscape management.

ecology↗

Pervasive ethanol in the fruits and floral nectars consumed by tropical frugivores

Dietary ethanol has long been proposed as a selective force shaping the diets and physiology of tropical frugivores and nectarivores, yet this idea has rested on measurements from only a few species and sites. Here, we present the first global survey of ethanol in wild fruits and flowers (591 and 37 species, respectively, across 18 countries) and test ecological and phylogenetic predictors of its variation. We detected ethanol in the ripened fruits of 72% of angiosperm species (211 species, N [≥] 3 per species; 0.021% - 3.9% alcohol by volume (ABV)). Ethanol was also detected in the flowers of 12 species (0.037% - 0.73% ABV). Maximum fruit ethanol varied with temperature, humidity, and phylogenetic relatedness, and it was higher in ripe fruits collected from the forest floor relative to their canopy counterparts. We then extrapolated potential daily ethanol consumption for 10 primate species. Estimated maximum daily ethanol ingestion for primates ranged from negligible to 0.72 g/kg/day on average (equivalent to 5.1 international standard drinks, 10 g ethanol each, for a 70 kg human). Our findings show that ethanol is widespread in plant reproductive tissues and shaped by both phylogeny and environment, supporting the hypothesis that dietary ethanol has been a pervasive selective pressure on fruit- and nectar-feeding animals.

ecology↗

Thermal Similarity Attenuates the Strength of Bergmanns Rule in Birds

Geographic body size variation, classically framed as Bergmann's rule, is a fundamental indicator of temperature-mediated morphological adaptation. However, empirical support for Bergmann's rule in birds remains highly unpredictable across lineages. We hypothesized that this variation is caused by differences in thermal similarity among species within the same genus, which may limit temperature driven changes in body size and be influenced by ecological factors. Using a global dataset comprising 5,715 bird species across 513 genera, we observed that thermal similarity was the strongest predictor of variation in the strength of Bergmann's rule among competing hypotheses. Among genera exhibiting significantly negative body mass temperature relationships, higher thermal similarity was consistently associated with less negative slopes, indicating weaker Bergmannian clines. Subgroup analyses indicated that the positive thermal similarity slope association was supported in dense and semi open habitats and among nonmigratory birds, but was not clearly supported in open habitats or among migratory birds. Our findings provide a novel explanation for variation in the strength of Bergmannian clines among avian lineages, showing that stronger morphological differentiation along thermal gradients is associated with greater thermal contrast. Consequently, our findings provide a basis for testing whether incorporating thermal similarity and ecological context can improve forecasts of avian morphological responses to ongoing climate change.

ecology↗