Forecasting climate change response in an alpine specialist songbird reveals the importance of considering novel climate

DeSaix, Matthew G.; George, T. Luke; Seglund, Amy E.; Spellman, Garth M.; Zavaleta, Erika S.; Ruegg, Kristen

doi:10.1111/ddi.13628

Cited by 10 publications

(9 citation statements)

References 128 publications

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“…We observed performance declines below the analogous z E =3.13 Climate Novelty scenario, indicating offset predictions will likely be inaccurate in many real-world climate change predictions. These issues are also germane to measures derived from offset values (Gougherty et al, 2021; Lachmuth, Capblancq, Keller, et al, 2023; Lachmuth, Capblancq, Prakash, et al, 2023), which currently do not consider the degree of climate novelty in the prediction (but see DeSaix et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

The limits of predicting maladaptation to future environments with genomic data

Lind,

Lotterhos

2024

Preprint

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Anthropogenically driven changes in land use and climate patterns pose unprecedented challenges to species persistence. To understand the extent of these impacts, 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 four offset methods (Gradient Forests, the Risk-Of-Non-Adaptedness, redundancy analysis, and LFMM2) using an extensive set of simulated datasets that vary demography, adaptive architecture, and the number and spatial patterns of adaptive environments. For each dataset, 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 4,850,000 of such evaluations, we find that 1) method performance is largely due to the degree of local adaptation across the metapopulation (LAΔSA), 2) adaptive marker sets provide minimal performance advantages, 3) within-landscape performance 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 novel climates for metapopulations with higher LAΔSA than lower LAΔSA. We discuss the implications of these results for management, assisted gene flow, and assisted migration.

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Section: Discussionmentioning

confidence: 99%

The limits of predicting maladaptation to future environments with genomic data

Lind,

Lotterhos

2024

Preprint

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“…Higher genomic offset indicates that populations will need to change allele frequencies more to maintain current gene–environment relationships in future conditions. Though some caution should be used when evaluating genomic offset metrics due to the assumptions of the model (for a thorough discussion of assumptions and limitations, see Ahrens et al., 2023; Capblancq et al., 2020; DeSaix et al., 2022; Rellstab, 2021), here we use genomic offset to identify which AUs may be the most at risk of climate‐related vulnerability. Using the adaptive loci found with LFMM and RDA as our response, we ran gradient forest (Ellis et al., 2012) and used the reduced environmental variable set as predictors to generate a model of allele frequency turnover across the breeding range.…”

Section: Methodsmentioning

confidence: 99%

Genomics‐informed conservation units reveal spatial variation in climate vulnerability in a migratory bird

Miller,

Bossu,

Saracco

et al. 2023

Molecular Ecology

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Identifying genetic conservation units (CUs) in threatened species is critical for the preservation of adaptive capacity and evolutionary potential in the face of climate change. However, delineating CUs in highly mobile species remains a challenge due to high rates of gene flow and genetic signatures of isolation by distance. Even when CUs are delineated in highly mobile species, the CUs often lack key biological information about what populations have the most conservation need to guide management decisions. Here we implement a framework for CU identification in the Canada Warbler (Cardellina canadensis), a migratory bird species of conservation concern, and then integrate demographic modelling and genomic offset to guide conservation decisions. We find that patterns of whole genome genetic variation in this highly mobile species are primarily driven by putative adaptive variation. Identification of CUs across the breeding range revealed that Canada Warblers fall into two evolutionarily significant units (ESU), and three putative adaptive units (AUs) in the South, East, and Northwest. Quantification of genomic offset, a metric of genetic changes necessary to maintain current gene–environment relationships, revealed significant spatial variation in climate vulnerability, with the Northwestern AU being identified as the most vulnerable to future climate change. Alternatively, quantification of past population trends within each AU revealed the steepest population declines have occurred within the Eastern AU. Overall, we illustrate that genomics‐informed CUs provide a strong foundation for identifying current and future regional threats that can be used to inform management strategies for a highly mobile species in a rapidly changing world.

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“…Ecologically vulnerable populations and genomically vulnerable populations may not coincide geographically, as in DeSaix et al. (2022) and Tournebize et al. (2022), illustrating the need for both genomic and ecological vulnerability assessments.…”

Section: Approaches That Integrate Wgr and Enmmentioning

confidence: 97%

“…Analysing contemporary and ancient DNA for comparison (Rellstab et al, 2021) We strongly recommend active cross-talk between WGR genomicists and ENM ecologists to foster collaboration. (Figures 3 and 4; see also Hodel et al, 2018;Chen et al, 2022;and DeSaix et al, 2022). Figure 3 shows an example of prospective workflows (based on Gheyas et al, 2021 andVallejo-Trujillo et al, 2022) which unify WGR and ENM to cope with future threats.…”

Section: Potential Limitations and Solutionsmentioning

confidence: 99%

The integration of whole‐genome resequencing and ecological niche modelling to conserve profiles of local adaptation

Jeon,

Shin,

Mularo

et al. 2024

Diversity and Distributions

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BackgroundEcological and genomic attributes of populations can provide two orthologous perspectives on the biological profiles associated with local adaptation. The ability of organisms to track suitable habitats (ecological adaptability) and of populations to shift allele frequencies (adaptive potential) are prerequisite for population sustainability.AimsMany contemporary populations are threatened by habitat loss (ecological vulnerability) and a lack of adaptive potential (evolutionary vulnerability). Technical advances provide new opportunities to address these challenges in biological conservation: Future habitat shifts can be predicted by ecological niche modelling and adaptive genetic diversity can be discerned using genome sequence data. Together, these two approaches illuminate the local adaptation profile and help identify the environmental and genomic conditions that should maximize evolutionary fitness.Materials and MethodsHere, we reviewed the primary literature to identify key studies that utilize both whole‐genome resequencing (WGR) and ecological niche modelling (ENM) in an effort to envisage future research directions that may benefit conservation efforts.ResultsWe identified ways to integrate different approaches, such as ENM‐informed adaptive genomics and adaptive genomics‐informed ENMs, that can be used to delineate and conserve local adaptation profiles.DiscussionIntegrative approaches can identify adaptive characteristics, vulnerable populations subject to environmental changes, and the patterns of local adaptation from geographic and genomic analyses. We discuss future research directions, limitations and their potential solutions with suggestions for collaborative workflows.ConclusionThe integration of WGR and ENM is promising with their continuous advancement. An integrative approach can be used to evaluate eco‐evolutionary attributes, at both organismal and molecular levels, that can be used to help conserve local adaptation profiles.

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Forecasting climate change response in an alpine specialist songbird reveals the importance of considering novel climate

Cited by 10 publications

References 128 publications

The limits of predicting maladaptation to future environments with genomic data

The limits of predicting maladaptation to future environments with genomic data

Genomics‐informed conservation units reveal spatial variation in climate vulnerability in a migratory bird

The integration of whole‐genome resequencing and ecological niche modelling to conserve profiles of local adaptation

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