TY - JOUR
T1 - A framework for incorporating evolutionary genomics into biodiversity conservation and management
AU - Hoffmann, Ary
AU - Griffin, Philippa
AU - Dillon, Shannon
AU - Catullo, Renee
AU - Rane, Rahul
AU - Byrne, Margaret
AU - Jordan, Rebecca
AU - Oakeshott, John
AU - and three others, null
PY - 2015
Y1 - 2015
N2 - Evolutionary adaptation drives biodiversity. So far, however, evolutionary thinking has had limited impact on plans to counter the effects of climate change on biodiversity and associated ecosystem services. This is despite habitat fragmentation diminishing the ability of populations to mount evolutionary responses, via reductions in population size, reductions in gene flow and reductions in the heterogeneity of environments that populations occupy. Research on evolutionary adaptation to other challenges has benefitted enormously in recent years from genomic tools, but these have so far only been applied to the climate change issue in a piecemeal manner. Here, we explore how new genomic knowledge might be combined with evolutionary thinking in a decision framework aimed at reducing the long-term impacts of climate change on biodiversity and ecosystem services. This framework highlights the need to rethink local conservation and management efforts in biodiversity conservation. We take a dynamic view of biodiversity based on the recognition of continuously evolving lineages, and we highlight when and where new genomic approaches are justified. In general, and despite challenges in developing genomic tools for non-model organisms, genomics can help management decide when resources should be redirected to increasing gene flow and hybridisation across climate zones and facilitating in situ evolutionary change in large heterogeneous areas. It can also help inform when conservation priorities need to shift from maintaining genetically distinct populations and species to supporting processes of evolutionary change. We illustrate our argument with particular reference to Australia's biodiversity.
AB - Evolutionary adaptation drives biodiversity. So far, however, evolutionary thinking has had limited impact on plans to counter the effects of climate change on biodiversity and associated ecosystem services. This is despite habitat fragmentation diminishing the ability of populations to mount evolutionary responses, via reductions in population size, reductions in gene flow and reductions in the heterogeneity of environments that populations occupy. Research on evolutionary adaptation to other challenges has benefitted enormously in recent years from genomic tools, but these have so far only been applied to the climate change issue in a piecemeal manner. Here, we explore how new genomic knowledge might be combined with evolutionary thinking in a decision framework aimed at reducing the long-term impacts of climate change on biodiversity and ecosystem services. This framework highlights the need to rethink local conservation and management efforts in biodiversity conservation. We take a dynamic view of biodiversity based on the recognition of continuously evolving lineages, and we highlight when and where new genomic approaches are justified. In general, and despite challenges in developing genomic tools for non-model organisms, genomics can help management decide when resources should be redirected to increasing gene flow and hybridisation across climate zones and facilitating in situ evolutionary change in large heterogeneous areas. It can also help inform when conservation priorities need to shift from maintaining genetically distinct populations and species to supporting processes of evolutionary change. We illustrate our argument with particular reference to Australia's biodiversity.
KW - biodiversity conservation
KW - genomics
UR - http://handle.uws.edu.au:8081/1959.7/uws:36349
UR - http://climatechangeresponses.biomedcentral.com/articles/10.1186/s40665-014-0009-x
U2 - 10.1186/s40665-014-0009-x
DO - 10.1186/s40665-014-0009-x
M3 - Article
SN - 2053-7565
VL - 2
JO - Climate Change Responses
JF - Climate Change Responses
IS - 1
ER -