ArticleMolecular ecology resources2025
The accuracy of predicting maladaptation to new environments with genomic data.
Article in Molecular ecology resources, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
27 citing papers in PubMed.
- The utility of herbarium collections for genetic monitoring.Bioscience · 2026Review
- Putatively Adaptive and Genome-Wide Genetic Variation Often Rank Populations as Similarly Distinctive.Molecular ecology · 2026Article
- Genomic Offsets Predict Survival With Low Accuracy in a Marine Common Garden.Molecular ecology · 2026Article
- How Robust Are Genomic Offset Predictions to Methodological Choices? Insights From Perennial Ryegrass.Molecular ecology · 2026Article
- Using herbarium collections to study genetic responses to global change.The New phytologist · 2026Review
- Landscape Genomic Tools Can Inform Future Rootstock and Farmland Selection for an Agricultural Tree Nut From Its Wild Relatives.Molecular ecology · 2026Article
- Whole genome sequencing reveals interbay population structure of Saccharina latissima (sugar kelp) in western Iceland.BMC ecology and evolution · 2026Article
- Landscape Genomic Analyses ofEvolutionary applications · 2026Article
- Applying Both Landscape Genomic and Ecological Niche Model Predictions to Inform Conservation Strategies of a California Foundational Oak Species.Molecular ecology · 2026Article
- Contrasting Patterns of Local Adaptation and Adaptive Potential Under Climate Change for Old-Growth and Planted Stands of Norway Spruce (Evolutionary applications · 2026Article
- A Mosaic of Future Maladaptation Predicted for the Widespread TreeEvolutionary applications · 2026Article
- The genetic architecture and spatiotemporal dynamics of adaptation across human-modified landscapes.The New phytologist · 2026Review
- Editorial 2026.Molecular ecology resources · 2026Article
- Integrating Genomic and Climate Data to Design Representative Seed Production Areas: A Pragmatic Workflow for Climate-Adjusted Provenancing.Ecology and evolution · 2026Article
- Adaptive Potential and Genomic Vulnerability of Keystone Forest Tree Species to Climate Change: A Case Study in Scots Pine.Evolutionary applications · 2025Article
- Genomic Basis and Climate Change Vulnerability of Migration Timing in Atlantic Salmon (Evolutionary applications · 2025Article
- Applying Genomic Offsets to Breeding Programmes: Bridging Evolutionary Insights With Practical Applications.Evolutionary applications · 2025Article
- Genomic Vulnerability of a Sentinel Mammal Under Climate Change.Molecular ecology · 2025Article
- Genomic Signatures of Climate-Driven (Mal)Adaptation in an Iconic Conifer, the English Yew (Evolutionary applications · 2025Article
- Application of Genomic Offsets to Inform Freshwater Fisheries Management Under Climate Change.Evolutionary applications · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Rapid environmental change poses unprecedented challenges to species persistence. To understand the extent that continued change could have, genomic offset methods have been used to forecast maladaptation of natural populations to future environmental change. However, while their use has become increasingly common, little is known regarding their predictive performance across a wide array of realistic and challenging scenarios. Here, we evaluate the performance of currently available offset methods (gradientForest, the Risk-Of-Non-Adaptedness, redundancy analysis with and without structure correction and LFMM2) using an extensive set of simulated data sets that vary demography, adaptive architecture and the number and spatial patterns of adaptive environments. For each data set, we train models using either all, adaptive or neutral marker sets and evaluate performance using in silico common gardens by correlating known fitness with projected offset. Using over 4,849,600 of such evaluations, we find that (1) method performance is largely due to the degree of local adaptation across the metapopulation (LA), (2) adaptive marker sets provide minimal performance advantages, (3) performance within the species range is variable across gardens and declines when offset models are trained using additional non-adaptive environments and (4) despite (1) performance declines more rapidly in globally novel climates (i.e. a climate without an analogue within the species range) for metapopulations with greater LA than lesser LA. We discuss the implications of these results for management, assisted gene flow and assisted migration.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.