Ecological genomics of adaptation to unpredictability in experimental rotifer populations.

Elucidating the genetic basis of phenotypic variation in response to different environments is key to understanding how populations evolve. Facultatively sexual rotifers can develop adaptive responses to fluctuating environments. In a previous evolution experiment, diapause-related traits changed rapidly in response to two selective regimes (predictable vs unpredictable) in laboratory populations of the rotifer Brachionus plicatilis.

Genomic signatures of local adaptation to the degree of environmental predictability in rotifers.

Environmental fluctuations are ubiquitous and thus essential for the study of adaptation. Despite this, genome evolution in response to environmental fluctuations -and more specifically to the degree of environmental predictability- is still unknown. Saline lakes in the Mediterranean region are remarkably diverse in their ecological conditions, which can lead to divergent local adaptation patterns in the inhabiting aquatic organisms.

Adaptation in response to environmental unpredictability.

Understanding how organisms adaptively respond to environmental fluctuations is a fundamental question in evolutionary biology. The Mediterranean region typically exhibits levels of environmental unpredictability that vary greatly in habitats over small geographical scales. In cyclically parthenogenetic rotifers, clonal proliferation occurs along with occasional bouts of sex.

Quantifying unpredictability: A multiple-model approach based on satellite imagery data from Mediterranean ponds.

Fluctuations in environmental parameters are increasingly being recognized as essential features of any habitat. The quantification of whether environmental fluctuations are prevalently predictable or unpredictable is remarkably relevant to understanding the evolutionary responses of organisms. However, when characterizing the relevant features of natural habitats, ecologists typically face two problems: (1) gathering long-term data and (2) handling the hard-won data.