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Integration of Population Genetic Structure and Plant Response to Climate Change: Sustaining Genetic Resources Through Evaluation of Projected Threats

Authored By: B. A. Richardson, M. V. Warwell, M. Kim, N. B. Klopfenstein, G. I. McDonald

To assess threats or predict responses to disturbances, or both, it is essential to recognize and characterize the population structures of forest species in relation to changing environments. Appropriate management of these genetic resources in the future will require: (1) understanding the existing genetic diversity/variation and population structure of forest trees, (2) understanding climatic change and its potential impacts on forest species and populations, and (3) development and use of new tools to identify populations at risk and geographic areas that will provide suitable habitat in the future. Forest trees exist within distinct geographic populations created by climatic shifts, evolutionary processes, the availability of suitable habitats, and other environmental factors. These processes have occurred over millennia and continue to shape the biogeography and genetic structure of these species. Forest trees in Western North America are being defined on the basis of molecular markers and quantitative traits. For example, studies of whitebark pine (Pinus albicaulis) and western white pine (P. monticola) demonstrate the existence of several distinct populations that likely developed via the long-term processes described above. These studies and others have shown that distinct populations exist within western conifer species and further indicate that the biogeographies of forest species are quite dynamic over time and space. Here, we present a case study using genetic data from whitebark pine and western white pine coupled with landscape-based, plant-climate modeling. Suitable contemporary habitat is accurately predicted for both species based on presence/absence of field observations. General circulation models were used to predict areas of suitable habitat for both species under the current climate and the projected climate around the year 2030. These models predict that both species will respond differently to projected climate change. Suitable habitat, (i.e., climate space) for whitebark pine is predicted to decline dramatically by the year ca. 2030. Populations in the lower latitudes (below 45ยบ N) and those persisting at the low elevation limits show the greatest threat to extinction from climate change. Predictions also indicate that suitable habitat for western white pine will be reduced in some southern latitudes, whereas the suitable habitat will be increased in the northern latitudes of its distribution. For whitebark and western white pine, both molecular markers and quantitative traits frequently reveal congruent genetic structure for species conservation. The combination of genetic studies with climate modeling can provide base-line tools that will enable managers to focus genetic conservation efforts on populations at highest risk while restoring areas that have the lowest risk for predicted climatic extirpation. The ability to define forest populations and predict landscape-level effects of climate change is critical for sustaining future forest health.


Subsections found in Integration of Population Genetic Structure and Plant Response to Climate Change: Sustaining Genetic Resources Through Evaluation of Projected Threats
  • Introduction : Climate change and associated glacial/interglacial cycles have had a profound impact on the biogeography of plant communities.
  • Material and Methods : This section reviews Population Genetic Analyses and Plant-Climate Modeling.
  • Results : Population genetics and plant-climate modeling results are summarized for both the whitebark and western white pine.
  • Discussion : This section discusses the study findings regarding Whitebark Pine and Western White Pine, and reviews Model Refinements and Uncertainties.
  • Summary : Case studies were presented for whitebark pine and western white pine using plant-climate modeling of current and future climate predictions and genetic studies.

Encyclopedia ID: p3565



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