A horizon scan of biological conservation issues for 2025.

We discuss the outcomes of our 16th horizon scan of issues that are novel or represent a considerable step-change and have the potential to substantially affect conservation of biological diversity in the coming decade. From an initial 96 topics, our international panel of 32 scientists and practitioners prioritised 15 issues. Technological advances are prominent, including metal and non-metal organic frameworks, deriving rare earth elements from macroalgae, synthetic gene drives in plants, and low-emission cement.

A horizon scan of global biological conservation issues for 2024.

We present the results of our 15th horizon scan of novel issues that could influence biological conservation in the future. From an initial list of 96 issues, our international panel of scientists and practitioners identified 15 that we consider important for societies worldwide to track and potentially respond to. Issues are novel within conservation or represent a substantial positive or negative step-change with global or regional extents.

Social vulnerability of the people exposed to wildfires in U.S. West Coast states.

Understanding of the vulnerability of populations exposed to wildfires is limited. We used an index from the U.S.

Ecological inferences about marine mammals from passive acoustic data.

Monitoring on the basis of sound recordings, or passive acoustic monitoring, can complement or serve as an alternative to real-time visual or aural monitoring of marine mammals and other animals by human observers. Passive acoustic data can support the estimation of common, individual-level ecological metrics, such as presence, detection-weighted occupancy, abundance and density, population viability and structure, and behaviour. Passive acoustic data also can support estimation of some community-level metrics, such as species richness and composition.

Silbido profundo: An open source package for the use of deep learning to detect odontocete whistles.

This work presents an open-source matlab software package for exploiting recent advances in extracting tonal signals from large acoustic data sets. A whistle extraction algorithm published by Li, Liu, Palmer, Fleishman, Gillespie, Nosal, Shiu, Klinck, Cholewiak, Helble, and Roch [(2020). Proceedings of the International Joint Conference on Neural Networks, July 19-24, Glasgow, Scotland, p.