scholarly journals Using connectivity to identify climatic drivers of local adaptation

2017 ◽  
Author(s):  
Stewart L. Macdonald ◽  
John Llewelyn ◽  
Ben L. Phillips
Keyword(s):  
Gene Flow ◽  
Local Adaptation ◽  
Environmental Variables ◽  
Evolutionary Biology ◽  
Landscape Connectivity ◽  
Environmental Drivers ◽  
Lizard Species ◽  
Trait Variation ◽  
Vast Number ◽  
Climatic Drivers

AbstractThis preprint has been reviewed and recommended by Peer Community In Evolutionary Biology (http://dx.doi.org/10.24072/pci.evolbiol.100034). Despite being able to conclusively demonstrate local adaptation, we are still often unable to objectively determine the climatic drivers of local adaptation. Given the rapid rate of global change, understanding the climatic drivers of local adaptation is vital. Not only will this tell us which climate axes matter most to population fitness, but such knowledge is critical to inform management strategies such as translocation and targeted gene flow. While simple assessments of geographic trait variation are useful, geographic variation (and its associations with environment) may represent plastic, rather than evolved, differences. Additionally, the vast number of trait–environment combinations makes it difficult to determine which aspects of the environment populations adapt to. Here we argue that by incorporating a measure of landscape connectivity as a proxy for gene flow, we can differentiate between trait–environment relationships underpinned by genetic differences versus those that reflect phenotypic plasticity. By doing so, we can rapidly shorten the list of trait–environment combinations that may be of adaptive significance. We demonstrate how this reasoning can be applied using data on geographic trait variation in a lizard species from Australia's Wet Tropics rainforest. Our analysis reveals an overwhelming signal of local adaptation for the traits and environmental variables we investigated. Our analysis also allows us to rank environmental variables by the degree to which they appear to be driving local adaptation. Although encouraging, methodological issues remain: we point to these issue in the hope that the community can rapidly hone the methods we sketch here. The promise is a rapid and general approach to identifying the environmental drivers of local adaptation.

scholarly journals Genomic assessment of local adaptation in dwarf birch to inform assisted gene flow

2019 ◽  
Author(s):  
James S. Borrell ◽  
Jasmin Zohren ◽  
Richard A. Nichols ◽  
Richard J. A. Buggs
Keyword(s):  
Climate Change ◽  
Gene Flow ◽  
Local Adaptation ◽  
Environmental Variables ◽  
Allele Frequencies ◽  
Species Range ◽  
Conservation Action ◽  
Mean Temperature ◽  
Diurnal Range ◽  
Dwarf Birch

AbstractWhen populations of a rare species are small, isolated and declining under climate change, some populations may become locally maladapted. Detecting this maladaptation may allow effective rapid conservation interventions, even if based on incomplete knowledge. Population maladaptation may be estimated by finding genome-environment associations (GEA) between allele frequencies and environmental variables across a local species range, and identifying populations whose allele frequencies do not fit with these trends. We can then design assisted gene flow strategies for maladapted populations, to adjust their allele frequencies, entailing lower levels of intervention than with undirected conservation action. Here, we investigate this strategy in Scottish populations of the montane plant dwarf birch (Betula nana). In genome-wide single nucleotide polymorphism (SNP) data we found 267 significant associations between SNP loci and environmental variables. We ranked populations by maladaptation estimated using allele frequency deviation from the general trends at these loci; this gave a different prioritization for conservation action than the Shapely Index, which seeks to preserve rare neutral variation. Populations estimated to be maladapted in their allele frequencies at loci associated with annual mean temperature were found to have reduced catkin production. Using an environmental niche modelling (ENM) approach, we found annual mean temperature (35%), and mean diurnal range (15%), to be important predictors of the dwarf birch distribution. Intriguingly, there was a significant correlation between the number of loci associated with each environmental variable in the GEA, and the importance of that variable in the ENM. Together, these results suggest that the same environmental variables determine both adaptive genetic variation and species range in Scottish dwarf birch. We suggest an assisted gene flow strategy that aims to maximize the local adaptation of dwarf birch populations under climate change by matching allele frequencies to current and future environments.

scholarly journals Genomic and common garden approaches yield complementary results for quantifying environmental drivers of local adaptation in rubber rabbitbrush, a foundational Great Basin shrub

2021 ◽  
Author(s):  
Trevor M Faske ◽  
Alison C Agneray ◽  
Joshua P Jahner ◽  
Lana M Sheta ◽  
Elizabeth A Leger ◽  
...  
Keyword(s):  
Local Adaptation ◽  
Great Basin ◽  
Phenotypic Variation ◽  
Environmental Variables ◽  
Genomic Structure ◽  
Common Garden ◽  
Environmental Drivers ◽  
Slope Aspect ◽  
Phenotypic Data ◽  
Precipitation Seasonality

The spatial structure of genomic and phenotypic variation across populations reflects historical and demographic processes as well as evolution via natural selection. Characterizing such variation can provide an important perspective for understanding the evolutionary consequences of changing climate and for guiding ecological restoration. While evidence for local adaptation has been traditionally evaluated using phenotypic data, modern methods for generating and analyzing landscape genomic data can directly quantify local adaptation by associating allelic variation with environmental variation. Here, we analyze both genomic and phenotypic variation of rubber rabbitbrush (Ericameria nauseosa), a foundational shrub species of western North America. To quantify landscape genomic structure and provide perspective on patterns of local adaptation, we generated reduced representation sequencing data for 17 wild populations (222 individuals; 38,615 loci) spanning a range of environmental conditions. Population genetic analyses illustrated pronounced landscape genomic structure jointly shaped by geography and environment. Genetic-environment association (GEA) analyses using both redundancy analysis (RDA) and a machine-learning approach (Gradient Forest) indicated environmental variables (precipitation seasonality, slope, aspect, elevation, and annual precipitation) influenced spatial genomic structure, and were correlated with allele frequency shifts indicative of local adaptation at a consistent set of genomic regions. We compared our GEA based inference of local adaptation with phenotypic data collected by growing seeds from each population in a greenhouse common garden. Population differentiation in seed weight, emergence, and seedling traits was associated with environmental variables (e.g., precipitation seasonality) that were also implicated in GEA analyses, suggesting complementary conclusions about the drivers of local adaptation across different methods and data sources. Our results provide a baseline understanding of spatial genomic structure for E. nauseosa across the western Great Basin and illustrate the utility of GEA analyses for detecting the environmental causes and genetic signatures of local adaptation in a widely distributed plant species of restoration significance.

scholarly journals Transcriptome Expression of Biomineralization Genes in Littoraria flava Gastropod in Brazilian Rocky Shore Reveals Evidence of Local Adaptation

2021 ◽  
Vol 13 (4) ◽  
Author(s):  
Camilla A Santos ◽  
Gabriel G Sonoda ◽  
Thainá Cortez ◽  
Luiz L Coutinho ◽  
Sónia C S Andrade
Keyword(s):  
Local Adaptation ◽  
Differentially Expressed Genes ◽  
Evolutionary Biology ◽  
Rocky Shore ◽  
Expression Patterns ◽  
Purifying Selection ◽  
Marine Species ◽  
Differentially Expressed ◽  
Planktonic Larva ◽  
Structure Changes

Abstract Understanding how selection shapes population differentiation and local adaptation in marine species remains one of the greatest challenges in the field of evolutionary biology. The selection of genes in response to environment-specific factors and microenvironmental variation often results in chaotic genetic patchiness, which is commonly observed in rocky shore organisms. To identify these genes, the expression profile of the marine gastropod Littoraria flava collected from four Southeast Brazilian locations in ten rocky shore sites was analyzed. In this first L. flava transcriptome, 250,641 unigenes were generated, and 24% returned hits after functional annotation. Independent paired comparisons between 1) transects, 2) sites within transects, and 3) sites from different transects were performed for differential expression, detecting 8,622 unique differentially expressed genes. Araçá (AR) and São João (SJ) transect comparisons showed the most divergent gene products. For local adaptation, fitness-related differentially expressed genes were chosen for selection tests. Nine and 24 genes under adaptative and purifying selection, respectively, were most related to biomineralization in AR and chaperones in SJ. The biomineralization-genes perlucin and gigasin-6 were positively selected exclusively in the site toward the open ocean in AR, with sequence variants leading to pronounced protein structure changes. Despite an intense gene flow among L. flava populations due to its planktonic larva, gene expression patterns within transects may be the result of selective pressures. Our findings represent the first step in understanding how microenvironmental genetic variation is maintained in rocky shore populations and the mechanisms underlying local adaptation in marine species.

Gene flow favours local adaptation under habitat choice in ciliate microcosms

2017 ◽  
Vol 1 (9) ◽  
pp. 1407-1410 ◽  
Author(s):  
Staffan Jacob ◽  
Delphine Legrand ◽  
Alexis S. Chaine ◽  
Dries Bonte ◽  
Nicolas Schtickzelle ◽  
...  
Keyword(s):  
Gene Flow ◽  
Local Adaptation ◽  
Habitat Choice

Gene Flow, Spatial Structure, Local Adaptation, and Assisted Migration in Trees

2012 ◽  
pp. 71-116 ◽  
Author(s):  
Konstantin V. Krutovsky ◽  
Jaroslaw Burczyk ◽  
Igor Chybicki ◽  
Reiner Finkeldey ◽  
Tanja Pyhäjärvi ◽  
...  
Keyword(s):  
Gene Flow ◽  
Spatial Structure ◽  
Local Adaptation ◽  
Assisted Migration

Landscape Connectivity

2019 ◽  
pp. 206-238
Author(s):  
Kimberly A. With
Keyword(s):  
Invasive Species ◽  
Gene Flow ◽  
Landscape Pattern ◽  
Landscape Structure ◽  
Pattern Analysis ◽  
Landscape Connectivity ◽  
Ecological Processes ◽  
Independent Variable ◽  
Ecological Flows

Landscape connectivity is essential for maintaining ecological flows across landscapes. Processes as diverse as dispersal; gene flow; the flow of water, materials and nutrients; the spread of invasive species, diseases, or pests; or the spread of disturbances like fire, are all potentially influenced by the connectivity of different land covers and land uses. Landscape connectivity can be defined structurally as well as functionally. Landscape connectivity may therefore be treated as either an independent variable, in terms of studying how landscape connectivity influences ecological flows, or as a dependent variable in which landscape connectivity emerges as a consequence of how species or ecological flows interact with landscape structure. This chapter thus explores the different scales and ways in which connectivity can be measured and studied, providing a bridge between the previous chapter on landscape pattern analysis and the chapters that follow on the effects of landscape pattern on ecological processes.

scholarly journals Fine-scale landscape genetics unveiling contemporary asymmetric movement of red panda (Ailurus fulgens) in Kangchenjunga landscape, India

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Supriyo Dalui ◽  
Hiren Khatri ◽  
Sujeet Kumar Singh ◽  
Shambadeb Basu ◽  
Avijit Ghosh ◽  
...  
Keyword(s):  
Gene Flow ◽  
Landscape Connectivity ◽  
Anthropogenic Activities ◽  
Clustering Algorithms ◽  
Area Network ◽  
Fine Scale ◽  
Contemporary Gene Flow ◽  
Red Panda ◽  
Population Structuring ◽  
Ailurus Fulgens

Abstract Wildlife management in rapid changing landscapes requires critical planning through cross cutting networks, and understanding of landscape features, often affected by the anthropogenic activities. The present study demonstrates fine-scale spatial patterns of genetic variation and contemporary gene flow of red panda (Ailurus fulgens) populations with respect to landscape connectivity in Kangchenjunga Landscape (KL), India. The study found about 1,309.54 km2 area suitable for red panda in KL—India, of which 62.21% area fell under the Protected Area network. We identified 24 unique individuals from 234 feces collected at nine microsatellite loci. The spatially explicit and non-explicit Bayesian clustering algorithms evident to exhibit population structuring and supported red panda populations to exist in meta-population frame work. In concurrence to the habitat suitability and landscape connectivity models, gene flow results supported a contemporary asymmetric movement of red panda by connecting KL—India in a crescent arc. We demonstrate the structural-operational connectivity of corridors in KL—India that facilitated red panda movement in the past. We also seek for cooperation in Nepal, Bhutan and China to aid in preparing for a comprehensive monitoring plan for the long-term conservation and management of red panda in trans-boundary landscapes.

Local adaptation along a sharp rainfall gradient occurs in a native Patagonian grass, Festuca pallescens, regardless of extensive gene flow

2020 ◽  
Vol 171 ◽  
pp. 103933
Author(s):  
Aldana S. López ◽  
Dardo R. López ◽  
Gonzalo Caballé ◽  
Guillermo L. Siffredi ◽  
Paula Marchelli
Keyword(s):  
Gene Flow ◽  
Local Adaptation ◽  
Rainfall Gradient ◽  
Festuca Pallescens

scholarly journals The limits to parapatric speciation 3: evolution of strong reproductive isolation in presence of gene flow despite limited ecological differentiation

2020 ◽  
Vol 375 (1806) ◽  
pp. 20190532 ◽  
Author(s):  
Alexandre Blanckaert ◽  
Claudia Bank ◽  
Joachim Hermisson
Keyword(s):  
Gene Flow ◽  
Reproductive Isolation ◽  
Local Adaptation ◽  
Theme Issue ◽  
Genetic Barrier ◽  
Incipient Species ◽  
Postzygotic Reproductive Isolation ◽  
Minimal Configuration ◽  
Parapatric Speciation ◽  
Two Populations

Gene flow tends to impede the accumulation of genetic divergence. Here, we determine the limits for the evolution of postzygotic reproductive isolation in a model of two populations that are connected by gene flow. We consider two selective mechanisms for the creation and maintenance of a genetic barrier: local adaptation leads to divergence among incipient species due to selection against migrants, and Dobzhansky–Muller incompatibilities (DMIs) reinforce the genetic barrier through selection against hybrids. In particular, we are interested in the maximum strength of the barrier under a limited amount of local adaptation, a challenge that many incipient species may initially face. We first confirm that with classical two-locus DMIs, the maximum amount of local adaptation is indeed a limit to the strength of a genetic barrier. However, with three or more loci and cryptic epistasis, this limit holds no longer. In particular, we identify a minimal configuration of three epistatically interacting mutations that is sufficient to confer strong reproductive isolation. This article is part of the theme issue ‘Towards the completion of speciation: the evolution of reproductive isolation beyond the first barriers’.

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