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• AI for Conservation Office Hours: 2025 Review

Read about the advice provided by AI specialists in AI Conservation Office Hours 2025 earlier this year and reflect on how this helped projects so far.

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• AI for Conservation Office Hours: 2025 Review

Read about the advice provided by AI specialists in AI Conservation Office Hours 2025 earlier this year and reflect on how this helped projects so far.

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• Opportunity to participate in study on what evidence you trust in conservation

This is a chance to participate in a short survey about the preferences that conservation practitioners have for evidence. There's a chance to win one of three £20 Mastercard gift cards.

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• IUCN Red list R client.

Everything you need on the IUCN Red list is now accessible from R, outputted as tibble to facilitate data query, analysis, and visualization.

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• Population genetics with eDNA

Using SNP markers with an Amphibian species, we were able to identify a total of 17,617 nuclear single nuclear polymorphisms shared across individual, pond eDNA (4 populations) and tank eDNA samples (where tadpoles of the four ponds were housed), enabling us to detect genetic structuring across sampling locations (previously demenstrated with microsatellites and tissue samples), consistent with individual-based estimates. Collecting only the matrix (here water) allows describing the existing population structure...that could be a nice progress for conservation biology...

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• MyProgress: Advancing GIS and R programming skills.

A fascinating journey of unleashing my potentials in spatial analysis using ArcGIS Pro and R programming.

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• IUCN Red list R client.

Everything you need on the IUCN Red list is now accessible from R, outputted as tibble to facilitate data query, analysis, and visualization.

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• BoutScout – Beyond AI for Images, Detecting Avian Behaviour with Sensors

In this case, you’ll explore how the BoutScout project is improving avian behavioural research through deep learning—without relying on images or video. By combining dataloggers, open-source hardware, and a powerful BiLSTM deep learning model trained on temperature data, the team has reduced the time needed to analyse weeks or even months of incubation behaviour to just seconds. This has enabled the discovery of new patterns in how tropical birds incubate their eggs across different elevations and climates. With tools soon to be released on PyPI, including a no-code platform for behavioural analysis, this work offers a fresh, scalable approach for conservationists and researchers working on breeding data at the tropics.

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• Nature Tech for Biodiversity Sector Map launched!

Conservation International is proud to announce the launch of the Nature Tech for Biodiversity Sector Map, developed in partnership with the Nature Tech Collective!