The DOI matches its Crossref record.
Climate-adjusted provenancing: a strategy for climate-resilient ecological restoration
Open accessAbstract
IntroductionInvestments in ecological restoration are estimated at $US 2 trillion per annum worldwide and are increasing rapidly (Cunningham 2008, Williams et al. 2014). These investments are occurring in an environment of accelerated climate change that is projected to continue into the next century, yet they currently take little account of such change. This has significant implications for the long-term success of restoration plantings across millions of hectares, with germplasm used in current restoration efforts potentially poorly-adapted to future climates. New approaches that optimize the climate-resilience of these restoration efforts are thus essential (Breed et al. 2013; Williams et al. 2014; Havens et al. 2015).A promising, but as yet untapped, opportunity for enhancing the climate-resilience of restoration investments rests in the exploitation of natural genetic variability of plant species. The capacity of plants to adapt to environmental change through plasticity, selection or gene flow is only beginning to be explored (Nicotra et al. 2010, Hoffman and Sgro 2011, Aitken and Whitlock 2013, Alberto et al. 2013). Informed strategies for sourcing germplasm that capitalize on inherent genetic diversity and adaptive capacity offer significant promise for improving the success of extensive plantings to restore landscapes that are eroded, salinized, desertified, highly fragmented or degraded through introduced competitors, herbivores or diseases.Here we describe a new strategy for sourcing germplasm for ecological restoration to promote adaptation in a changing climate. We argue that a ‘climate-adjusted’ provenancing strategy (Fig. 1a) should combine genetic diversity and adaptability, targeting projected climate change directions whilst allowing for uncertainty in such projections as well as unforeseen selective agents. We introduce climate-adjusted provenancing in the context of historical approaches to provenancing, and highlight emerging research to test this strategy.Provenancing strategiesEarly ecological restoration typically focused on restoring ecological functions such as soil stability, using whatever plants were available to achieve these outcomes (including exotics, with many adverse outcomes). In recent decades, attention has turned to strategic sourcing of native germplasm for restoration plantings to achieve biodiversity conservation and other outcomes. Accordingly, an increasing awareness of the role of genetic provenance in plant performance has led to a strong theoretical and practical focus on maintaining local genetic-environmental relationships (McKay et al. 2005, Broadhurst et al. 2008). This strategy, typically known as ‘local’ provenancing (Fig. 1b), is based on evidence that in a static environment, local populations are best adapted to local conditions (Broadhurst et al. 2008).More recently, arguments have been made to move away from a strict focus on local provenancing, towards the use of multiple or targeted provenancing strategies that address risks of inbreeding associated with collections from small and/or fragmented local populations, and begin to consider adaptation potential in relation to changing environments (Broadhurst et al., 2008; Breed et al., 2013). In particular, Broadhurst et al. (2008) proposed a shift to ‘composite’ provenancing (Fig. 1c), which aims to mimic natural patterns of gene flow by mixing seed from healthy local provenances combined with progressively smaller amounts of seed from more distant sites. Breed et al. (2013) further emphasized the importance of adaptability in their proposal for ‘admixture’ provenancing (Fig. 1d). This aims to build evolutionary resilience into plantings by mixing a wide variety of provenances from sources across a species range, without regard to the location of the planting site. They argued that such an approach is most appropriate when changes in conditions are expected but there are few data to indicate likely responses. Provenancing in a changing climate It is now a near-certainty that local climates are changing around the globe (IPCC 2013). As the climate changes, local genetic adaptations will be increasingly weakened in situ, and a static view of genetic-environmental relationships will no longer be relevant. Instead, capturing advantages of local adaptations will need to account for spatial shifts in climate, and maximizing adaptation potential will be crucial (Aitken & Whitlock 2013, Thomas et al. 2014).Our climate-adjusted provenancing strategy thus proposes a targeted approach to enhancing the climate-resilience of restoration plantings, with seed sourcing biased toward the direction of predicted climatic change (Fig. 1a), but not exclusive to it. Germplasm pools would incorporate a mix of genotypes from a climatic gradient, biased towards environments more likely to be encountered in the future, but would also include local genotypes. Other principles articulated by Broadhurst et al. (2008) regarding ro
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Conservation and the Genomics of Populations
Allendorf, F. W., Funk, W. C., Aitken, S. N., Byrne, M., Luikart, G., & Antunes, A. (2022) · doi:10.1093/oso/9780198856566.001.0001 · Cited by 207
Self-citationForecasting trait responses in novel environments to aid seed provenancing under climate change
Putra, A. R., Yen, J. D. L., & Fournier‐Level, A. (2023) · Molecular Ecology Resources · doi:10.1111/1755-0998.13728 · Cited by 7
Metadata
- Authors
- Prober, S. M., Byrne, M., McLean, E. H., Steane, D. A., Potts, B. M., Vaillancourt, R. E., & Stock, W. D.
- Venue
- Frontiers in Ecology and Evolution
- Publisher
- Frontiers Media SA
- Published
- 2015-06-23
- Volume
- 3
- ISSN
- 2296-701X (ISSN-L)
- OpenAlex
- W1486942185
- Cited by
- 392
- References
- 0
- FWCI
- 19.94
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Climate-adjusted provenancing: a strategy for climate-resilient ecological restoration. https://app.cochat.ai/papers/10.3389/fevo.2015.00065
- The paper
- Prober, S. M., Byrne, M., McLean, E. H., Steane, D. A., Potts, B. M., Vaillancourt, R. E., & Stock, W. D. (2015). Climate-adjusted provenancing: a strategy for climate-resilient ecological restoration. Frontiers in Ecology and Evolution. https://doi.org/10.3389/fevo.2015.00065
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.