Multinational evaluation of genetic diversity indicators for the Kunming-Montreal Global Biodiversity Framework.

Under the recently adopted Kunming-Montreal Global Biodiversity Framework, 196 Parties committed to reporting the status of genetic diversity for all species. To facilitate reporting, three genetic diversity indicators were developed, two of which focus on processes contributing to genetic diversity conservation: maintaining genetically distinct populations and ensuring populations are large enough to maintain genetic diversity. The major advantage of these indicators is that they can be estimated with or without DNA-based data.

Monitoring of species' genetic diversity in Europe varies greatly and overlooks potential climate change impacts.

Genetic monitoring of populations currently attracts interest in the context of the Convention on Biological Diversity but needs long-term planning and investments. However, genetic diversity has been largely neglected in biodiversity monitoring, and when addressed, it is treated separately, detached from other conservation issues, such as habitat alteration due to climate change. We report an accounting of efforts to monitor population genetic diversity in Europe (genetic monitoring effort, GME), the evaluation of which can help guide future capacity building and collaboration towards areas most in need of expanded monitoring.

Learning from the mistakes of others: How female elk (Cervus elaphus) adjust behaviour with age to avoid hunters.

In animal behaviour, there is a dichotomy between innate behaviours (e.g., temperament or personality traits) versus those behaviours shaped by learning.

Dispersal Ecology Informs Design of Large-Scale Wildlife Corridors.

Landscape connectivity describes how the movement of animals relates to landscape structure. The way in which movement among populations is affected by environmental conditions is important for predicting the effects of habitat fragmentation, and for defining conservation corridors. One approach has been to map resistance surfaces to characterize how environmental variables affect animal movement, and to use these surfaces to model connectivity.

Applications of step-selection functions in ecology and conservation.

Recent progress in positioning technology facilitates the collection of massive amounts of sequential spatial data on animals. This has led to new opportunities and challenges when investigating animal movement behaviour and habitat selection. Tools like Step Selection Functions (SSFs) are relatively new powerful models for studying resource selection by animals moving through the landscape.

Habitat selection during ungulate dispersal and exploratory movement at broad and fine scale with implications for conservation management.

Background: Dispersal has a critical influence on demography and gene flow and as such maintaining connectivity between populations is an essential element of modern conservation. Advances in satellite radiotelemetry are providing new opportunities to document dispersal, which previously has been difficult to study. This type of data also can be used as an empirical basis for defining landscapes in terms of resistance surfaces, enabling habitat corridors to be identified.