Working Group
Evolutionary and ecological immunology is a multi-disciplinary topic in evolutionary biology. Considerable empirical attention has been paid to identifying the costs of mounting an immune response, determining whether immunity is sexually dimorphic, and elucidating how immunity is related to the expression of sexually selected traits across a variety of taxa. There is, however, little consensus on whether current hypotheses and predictions are supported. It is unclear if general patterns exist within and differ across taxa. Our NESCent working group intends to address these issues in three ways: (1) perform taxonomically-broad, phylogenetic meta-analyses to assess the support for hypotheses and predictions and to identify alternative explanations and new hypothese; (2) modify existing life history models to derive quantitative predictions about the relationship between immune function and key life history traits; (3) construct an open-access, updatable online database to facilitate further analyses relevant to evolutionary immunology.
Advancing knowledge of evolutionary and ecological immunology
| PI(s): | Clint Kelly (Iowa State University (Ames,IA)) Michael Jennions (Australian National University) |
| Start Date: | 1-May-2013 |
| End Date: | 15-Nov-2014 |
| Keywords: | behavior, sexual selection, life histories, meta-analysis, database |
Evolutionary and ecological immunology is a multi-disciplinary topic in evolutionary biology. Considerable empirical attention has been paid to identifying the costs of mounting an immune response, determining whether immunity is sexually dimorphic, and elucidating how immunity is related to the expression of sexually selected traits across a variety of taxa. There is, however, little consensus on whether current hypotheses and predictions are supported. It is unclear if general patterns exist within and differ across taxa. Our NESCent working group intends to address these issues in three ways: (1) perform taxonomically-broad, phylogenetic meta-analyses to assess the support for hypotheses and predictions and to identify alternative explanations and new hypothese; (2) modify existing life history models to derive quantitative predictions about the relationship between immune function and key life history traits; (3) construct an open-access, updatable online database to facilitate further analyses relevant to evolutionary immunology.
