DOI: 10.1111/ele.12376
Scopus记录号: 2-s2.0-84916893470
论文题名: Ecological genomics meets community-level modelling of biodiversity: Mapping the genomic landscape of current and future environmental adaptation
作者: Fitzpatrick M.C. ; Keller S.R.
刊名: Ecology Letters
ISSN: 1461023X
EISSN: 1461-0248
出版年: 2015
卷: 18, 期: 1 起始页码: 1
结束页码: 16
语种: 英语
英文关键词: Biodiversity
; Climate change
; Generalised dissimilarity modelling
; Gradient forests
; Intraspecific variation
; Landscape genetics
; Local adaptation
; Populus balsamifera
; Single-nucleotide polymorphism
; Species distribution modelling
Scopus关键词: Populus balsamifera
; transcription factor CLOCK
; vegetable protein
; adaptation
; biodiversity
; biological model
; climate change
; genetic variability
; genetics
; genomics
; Populus
; procedures
; single nucleotide polymorphism
; spatial analysis
; statistical model
; Adaptation, Physiological
; Biodiversity
; Climate Change
; CLOCK Proteins
; Genetic Variation
; Genomics
; Models, Biological
; Models, Statistical
; Plant Proteins
; Polymorphism, Single Nucleotide
; Populus
; Spatial Analysis
英文摘要: Local adaptation is a central feature of most species occupying spatially heterogeneous environments, and may factor critically in responses to environmental change. However, most efforts to model the response of species to climate change ignore intraspecific variation due to local adaptation. Here, we present a new perspective on spatial modelling of organism-environment relationships that combines genomic data and community-level modelling to develop scenarios regarding the geographic distribution of genomic variation in response to environmental change. Rather than modelling species within communities, we use these techniques to model large numbers of loci across genomes. Using balsam poplar (Populus balsamifera) as a case study, we demonstrate how our framework can accommodate nonlinear responses of loci to environmental gradients. We identify a threshold response to temperature in the circadian clock gene GIGANTEA-5 (GI5), suggesting that this gene has experienced strong local adaptation to temperature. We also demonstrate how these methods can map ecological adaptation from genomic data, including the identification of predicted differences in the genetic composition of populations under current and future climates. Community-level modelling of genomic variation represents an important advance in landscape genomics and spatial modelling of biodiversity that moves beyond species-level assessments of climate change vulnerability. © 2014 John Wiley & Sons Ltd/CNRS. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/107892
Appears in Collections: 气候减缓与适应
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作者单位: Appalachian Lab, University of Maryland Center for Environmental Science, Frostburg, MD, United States; Department of Plant Biology, University of Vermont, Burlington, VT, United States
Recommended Citation:
Fitzpatrick M.C.,Keller S.R.. Ecological genomics meets community-level modelling of biodiversity: Mapping the genomic landscape of current and future environmental adaptation[J]. Ecology Letters,2015-01-01,18(1)