Assessing uncertainty in genomic offset forecasts from landscape genomic models (and implications for restoration and assisted migration) DOI Creative Commons
Susanne Lachmuth, Thibaut Capblancq, Stephen R. Keller

et al.

Frontiers in Ecology and Evolution, Journal Year: 2023, Volume and Issue: 11

Published: June 19, 2023

Introduction Ecological genomic models are increasingly used to guide climate-conscious restoration and conservation practices in the light of accelerating environmental change. Genomic offsets that quantify disruption existing genotype–environment associations under change a promising model-based tool inform such measures. With recent advances, potential applications offset predictions include but not restricted to: (1) assessing situ climate risks, (2) mapping future habitat suitability while accounting for local adaptations, or (3) selecting donor populations recipient areas maximize diversity minimize maladaptation environments assisted migration planning. As any approach, it is crucial understand how arbitrary decisions made during modeling process affect induce uncertainty. Methods Here, we present sensitivity analysis various components influence forecasts offset-based metrics, using red spruce ( Picea rubens ), cool-temperate tree species endemic eastern North America, as case study. We assess effects marker set, climatic predictor scenario, “not-to-exceed” threshold evaluate uncertainty varies across space. Results Climate scenario induced by far largest our forecasts; however, choice set was also important regions Southern Central Appalachians high relevance efforts. While much effort often expended identifying candidate loci, found minor importance. The maximum limit transfers between locations programs has mostly affected magnitude rather than geographic variation predictions. Discussion Overall, model suggest risks entire distributional range strongly underscore help ameliorate these risks. In regard, well along US Canadian east coast seem best candidates both relocation.

Language: Английский

Genetic load: genomic estimates and applications in non-model animals DOI
Giorgio Bertorelle, Francesca Raffini, Mirte Bosse

et al.

Nature Reviews Genetics, Journal Year: 2022, Volume and Issue: 23(8), P. 492 - 503

Published: Feb. 8, 2022

Language: Английский

Citations

187
The evolutionary genomics of species’ responses to climate change DOI
Jonás A. Aguirre‐Liguori, Santiago Ramírez‐Barahona, Brandon S. Gaut

et al.

Nature Ecology & Evolution, Journal Year: 2021, Volume and Issue: 5(10), P. 1350 - 1360

Published: Aug. 9, 2021

Language: Английский

Citations

135
Prospects and limitations of genomic offset in conservation management DOI Creative Commons
Christian Rellstab, Benjamin Dauphin, Moisés Expósito‐Alonso

et al.

Evolutionary Applications, Journal Year: 2021, Volume and Issue: 14(5), P. 1202 - 1212

Published: Feb. 10, 2021

In nature conservation, there is keen interest in predicting how populations will respond to environmental changes such as climate change. These predictions can help determine whether a population be self-sustaining under future alterations of its habitat or it may require human intervention protection, restoration, assisted migration. An increasingly popular approach this respect the concept genomic offset, which combines and data from different time points and/or locations assess degree possible maladaptation new conditions. Here, we argue that offset holds great potential, but an exploration risks limitations needed use for recommendations conservation After briefly describing concept, list important issues consider (e.g., statistical frameworks, genetic structure, migration, independent evidence) when using developing these methods further. We conclude area development still lacks some features should used combination with other approaches inform measures.

Language: Английский

Citations

127
Space‐for‐time substitutions in climate change ecology and evolution DOI Creative Commons
Rebecca S. L. Lovell, Sinéad Collins, Simon H. Martin

et al.

Biological reviews/Biological reviews of the Cambridge Philosophical Society, Journal Year: 2023, Volume and Issue: 98(6), P. 2243 - 2270

Published: Aug. 9, 2023

ABSTRACT In an epoch of rapid environmental change, understanding and predicting how biodiversity will respond to a changing climate is urgent challenge. Since we seldom have sufficient long‐term biological data use the past anticipate future, spatial climate–biotic relationships are often used as proxy for biotic responses change over time. These ‘space‐for‐time substitutions’ (SFTS) become near ubiquitous in global biology, but with different subfields largely developing methods isolation. We review climate‐focussed SFTS four ecology evolution, each focussed on type variable – population phenotypes, genotypes, species' distributions, ecological communities. then examine similarities differences between terms methods, limitations opportunities. While wide range applications, two main approaches applied across subfields: situ gradient transplant experiments. find that share common relating ( i ) causality identified ii transferability these relationships, i.e. whether observed space equivalent those occurring Moreover, despite widespread application research, key assumptions remain untested. highlight opportunities enhance robustness by addressing limitations, particular emphasis where could be shared subfields.

Language: Английский

Citations

74
Natural hybridization reduces vulnerability to climate change DOI Creative Commons
Chris J. Brauer, Jonathan Sandoval‐Castillo, Katie Gates

et al.

Nature Climate Change, Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 30, 2023

Abstract Under climate change, species unable to track their niche via range shifts are largely reliant on genetic variation adapt and persist. Genomic vulnerability predictions used identify populations that lack the necessary variation, particularly at climate-relevant genes. However, hybridization as a source of novel adaptive is typically ignored in genomic studies. We estimated environmental models for closely related rainbowfish ( Melanotaenia spp.) across an elevational gradient Australian Wet Tropics. Hybrid between widespread generalist several narrow endemic exhibited reduced projected climates compared pure endemics. Overlaps introgressed regions were consistent with signal introgression. Our findings highlight often-underappreciated conservation value hybrid indicate introgression may contribute evolutionary rescue ranges.

Language: Английский

Citations

73
Genomics for monitoring and understanding species responses to global climate change DOI Creative Commons
Louis Bernatchez, Anne‐Laure Ferchaud, C.S. Berger

et al.

Nature Reviews Genetics, Journal Year: 2023, Volume and Issue: 25(3), P. 165 - 183

Published: Oct. 20, 2023

All life forms across the globe are experiencing drastic changes in environmental conditions as a result of global climate change. These happening rapidly, incur substantial socioeconomic costs, pose threats to biodiversity and diminish species' potential adapt future environments. Understanding monitoring how organisms respond human-driven change is therefore major priority for conservation rapidly changing environment. Recent developments genomic, transcriptomic epigenomic technologies enabling unprecedented insights into evolutionary processes molecular bases adaptation. This Review summarizes methods that apply integrate omics tools experimentally investigate, monitor predict species communities wild cope with change, which by genetically adapting new conditions, through range shifts or phenotypic plasticity. We identify advantages limitations each method discuss research avenues would improve our understanding responses highlighting need holistic, multi-omics approaches ecosystem during Species can shifting their these responses.

Language: Английский

Citations

66
Neutral and adaptive genetic diversity in plants: An overview DOI Creative Commons
Mi Yoon Chung, Juha Merilä, Jialiang Li

et al.

Frontiers in Ecology and Evolution, Journal Year: 2023, Volume and Issue: 11

Published: Feb. 16, 2023

Genetic diversity is a prerequisite for evolutionary change in all kinds of organisms. It generally acknowledged that populations lacking genetic variation are unable to evolve response new environmental conditions (e.g., climate change) and thus may face an increased risk extinction. Although the importance incorporating into design conservation measures now well understood, less attention has been paid distinction between neutral (NGV) adaptive (AGV) variation. In this review, we first focus on utility NGV by examining ways quantify it, reviewing applications infer ecological processes, exploring its designing plant species. Against background, then summarize identify estimate AGV discuss potential use conservation. After comparing considering their pros cons context, conclude there urgent need better understanding role adaptation. To date, however, only few studies non-model species aimed at deciphering genomic basis complex trait Therefore, researchers practitioners should keep utilizing develop relevant strategies rare endangered until more estimates available.

Language: Английский

Citations

48
The paradox of adaptive trait clines with nonclinal patterns in the underlying genes DOI Creative Commons
Katie E. Lotterhos

Proceedings of the National Academy of Sciences, Journal Year: 2023, Volume and Issue: 120(12)

Published: March 14, 2023

Multivariate climate change presents an urgent need to understand how species adapt complex environments. Population genetic theory predicts that loci under selection will form monotonic allele frequency clines with their selective environment, which has led the wide use of genotype–environment associations (GEAs). This study used a set simulations elucidate conditions are more or less likely evolve as multiple quantitative traits multivariate Phenotypic evolved nonmonotonic (i.e., nonclinal) patterns in frequencies promoted unique combinations mutations achieve optimum different parts landscape. Such resulted from interactions among landscape, demography, pleiotropy, and architecture. GEA methods failed accurately infer basis adaptation range scenarios due first principles (clinal did not evolve) statistical issues but were detected overcorrection for structure). Despite limitations GEAs, this shows back-transformation ordination can predict individual genotype environmental data regardless whether inference GEAs was accurate. In addition, frameworks introduced be by empiricists quantify importance clinal alleles adaptation. research highlights trait prediction lead accurate underlying display patterns.

Language: Английский

Citations

47
How useful is genomic data for predicting maladaptation to future climate? DOI Creative Commons
Brandon M. Lind, Rafael Candido‐Ribeiro, Pooja Singh

et al.

Global Change Biology, Journal Year: 2024, Volume and Issue: 30(4)

Published: April 1, 2024

Abstract Methods using genomic information to forecast potential population maladaptation climate change or new environments are becoming increasingly common, yet the lack of model validation poses serious hurdles toward their incorporation into management and policy. Here, we compare estimates derived from two methods—Gradient Forests (GF offset ) risk non‐adaptedness (RONA)—using exome capture pool‐seq data 35 39 populations across three conifer taxa: Douglas‐fir varieties jack pine. We evaluate sensitivity these algorithms source input loci (markers selected genotype–environment associations [GEA] those at random). validate methods against 2‐ 52‐year growth mortality measured in independent transplant experiments. Overall, find that both often better predict performance than climatic geographic distances. also GF RONA models surprisingly not improved GEA candidates. Even with promising results, variation projections future climates makes it difficult identify most maladapted either method. Our work advances understanding applicability approaches, discuss recommendations for use.

Language: Английский

Citations

26
Interpretation issues with “genomic vulnerability” arise from conceptual issues in local adaptation and maladaptation DOI Creative Commons
Katie E. Lotterhos

Evolution Letters, Journal Year: 2024, Volume and Issue: 8(3), P. 331 - 339

Published: Feb. 8, 2024

Abstract As climate change causes the environment to shift away from local optimum that populations have adapted to, fitness declines are predicted occur. Recently, methods known as genomic offsets (GOs) become a popular tool predict population responses landscape data. Populations with high GO been interpreted “genomic vulnerability” change. GOs often implicitly offset, or in of an individual new compared reference. However, there several different types offset can be calculated, and appropriate choice depends on management goals. This study uses hypothetical empirical data explore situations which may not correlated each other GO. The examples reveal even when common garden experiment, this does necessarily validate their ability environmental Conceptual also used show how large arise under positive thus cannot vulnerability. These issues resolved robust validation experiments evaluate GOs.

Language: Английский

Citations

19