Accelerating climate change and habitat loss make it imperative that plans to conserve biodiversity consider species' ability to adapt to changing environments. However, in biomes where biodiversity is highest, the evolutionary mechanisms responsible for generating adaptative variation and, ultimately, new species are frequently poorly understood. African rainforests represent one such biome, as decadal debates continue concerning the mechanisms generating African rainforest biodiversity. These debates hinge on the relative importance of geographic isolation versus divergent natural selection across environmental gradients. Hindering progress is a lack of robust tests of these competing hypotheses. Because African rainforests are severely at‐risk due to climate change and other anthropogenic activities, addressing this long‐standing debate is critical for making informed conservation decisions. We use demographic inference and allele frequency‐environment relationships to investigate mechanisms of diversification in an African rainforest skink,
Preserving biodiversity under rapidly changing climate conditions is challenging. One approach for estimating impacts and their magnitude is to model current relationships between genomic and environmental data and then to forecast those relationships under future climate scenarios. In this way, understanding future genomic and environmental relationships can help guide management decisions, such as where to establish new protected areas where populations might be buffered from high temperatures or major changes in rainfall. However, climate warming is only one of many anthropogenic threats one must consider in rapidly developing parts of the world. In Central Africa, deforestation, mining, and infrastructure development are accelerating population declines of rainforest species. Here we investigate multiple anthropogenic threats in a Central African rainforest songbird, the little greenbul (
- Award ID(s):
- 1933351
- NSF-PAR ID:
- 10366694
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Evolutionary Applications
- Volume:
- 14
- Issue:
- 5
- ISSN:
- 1752-4571
- Format(s):
- Medium: X Size: p. 1239-1247
- Size(s):
- ["p. 1239-1247"]
- Sponsoring Org:
- National Science Foundation
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