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Draghi JA, McGlothlin JW, Kindsvater HK. Demographic feedbacks during evolutionary rescue can slow or speed adaptive evolution. Proc Biol Sci 2024; 291:20231553. [PMID: 38351805 PMCID: PMC10865011 DOI: 10.1098/rspb.2023.1553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 01/16/2024] [Indexed: 02/16/2024] Open
Abstract
Populations declining toward extinction can persist via genetic adaptation in a process called evolutionary rescue. Predicting evolutionary rescue has applications ranging from conservation biology to medicine, but requires understanding and integrating the multiple effects of a stressful environmental change on population processes. Here we derive a simple expression for how generation time, a key determinant of the rate of evolution, varies with population size during evolutionary rescue. Change in generation time is quantitatively predicted by comparing how intraspecific competition and the source of maladaptation each affect the rates of births and deaths in the population. Depending on the difference between two parameters quantifying these effects, the model predicts that populations may experience substantial changes in their rate of adaptation in both positive and negative directions, or adapt consistently despite severe stress. These predictions were then tested by comparison to the results of individual-based simulations of evolutionary rescue, which validated that the tolerable rate of environmental change varied considerably as described by analytical results. We discuss how these results inform efforts to understand wildlife disease and adaptation to climate change, evolution in managed populations and treatment resistance in pathogens.
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Affiliation(s)
- Jeremy A. Draghi
- Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24060, USA
| | - Joel W. McGlothlin
- Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24060, USA
| | - Holly K. Kindsvater
- Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA 24060, USA
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Longcamp A, Draghi J. Evolutionary rescue via niche construction: Infrequent construction can prevent post-invasion extinction. Theor Popul Biol 2023; 153:37-49. [PMID: 37328113 DOI: 10.1016/j.tpb.2023.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 06/06/2023] [Accepted: 06/07/2023] [Indexed: 06/18/2023]
Abstract
A population experiencing habitat loss can avoid extinction by undergoing genetic adaptation-a process known as evolutionary rescue. Here we analytically approximate the probability of evolutionary rescue via a niche-constructing mutation that allows carriers to convert a novel, unfavorable reproductive habitat to a favorable state at a cost to their fecundity. We analyze competition between mutants and non-niche-constructing wild types, who ultimately require the constructed habitats to reproduce. We find that over-exploitation of the constructed habitats by wild types can generate damped oscillations in population size shortly after mutant invasion, thereby decreasing the probability of rescue. Such post-invasion extinction is less probable when construction is infrequent, habitat loss is common, the reproductive environment is large, or the population's carrying capacity is small. Under these conditions, wild types are less likely to encounter the constructed habitats and, consequently, mutants are more likely to fix. These results suggest that, without a mechanism that deters wild type inheritance of the constructed habitats, a population undergoing rescue via niche construction may remain prone to short-timescale extinction despite successful mutant invasion.
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Affiliation(s)
- Alexander Longcamp
- Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061, United States of America.
| | - Jeremy Draghi
- Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061, United States of America
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Torres E, García-Fernández A, Iñigo D, Lara-Romero C, Morente-López J, Prieto-Benítez S, Rubio Teso ML, Iriondo JM. Facilitated Adaptation as A Conservation Tool in the Present Climate Change Context: A Methodological Guide. PLANTS (BASEL, SWITZERLAND) 2023; 12:1258. [PMID: 36986946 PMCID: PMC10053585 DOI: 10.3390/plants12061258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 03/04/2023] [Accepted: 03/07/2023] [Indexed: 06/18/2023]
Abstract
Climate change poses a novel threat to biodiversity that urgently requires the development of adequate conservation strategies. Living organisms respond to environmental change by migrating to locations where their ecological niche is preserved or by adapting to the new environment. While the first response has been used to develop, discuss and implement the strategy of assisted migration, facilitated adaptation is only beginning to be considered as a potential approach. Here, we present a review of the conceptual framework for facilitated adaptation, integrating advances and methodologies from different disciplines. Briefly, facilitated adaptation involves a population reinforcement that introduces beneficial alleles to enable the evolutionary adaptation of a focal population to pressing environmental conditions. To this purpose, we propose two methodological approaches. The first one (called pre-existing adaptation approach) is based on using pre-adapted genotypes existing in the focal population, in other populations, or even in closely related species. The second approach (called de novo adaptation approach) aims to generate new pre-adapted genotypes from the diversity present in the species through artificial selection. For each approach, we present a stage-by-stage procedure, with some techniques that can be used for its implementation. The associated risks and difficulties of each approach are also discussed.
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Affiliation(s)
- Elena Torres
- Departamento de Biotecnología-Biología Vegetal, Universidad Politécnica de Madrid, 28040 Madrid, Spain
| | - Alfredo García-Fernández
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
| | - Diana Iñigo
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
| | - Carlos Lara-Romero
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
| | - Javier Morente-López
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
- Grupo de Investigación de Ecología y Evolución en Islas, Instituto de Productos Naturales y Agrobiología (IPNA-CSIC), 38206 Tenerife, Spain
| | - Samuel Prieto-Benítez
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
- Ecotoxicology of Air Pollution, Environmental Department, CIEMAT, 28040 Madrid, Spain
| | - María Luisa Rubio Teso
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
| | - José M. Iriondo
- Grupo de Ecología Evolutiva (ECOEVO), Área de Biodiversidad y Conservación, Departamento de Biología, Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
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Tomasini M, Peischl S. The role of spatial structure in multi-deme models of evolutionary rescue. J Evol Biol 2022; 35:986-1001. [PMID: 35704340 DOI: 10.1111/jeb.14018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 04/07/2022] [Accepted: 04/13/2022] [Indexed: 11/30/2022]
Abstract
Genetic variation and population sizes are critical factors for successful adaptation to novel environmental conditions. Gene flow between sub-populations is a potent mechanism to provide such variation and can hence facilitate adaptation, for instance by increasing genetic variation or via the introduction of beneficial variants. On the other hand, if gene flow between different habitats is too strong, locally beneficial alleles may not be able to establish permanently. In the context of evolutionary rescue, intermediate levels of gene flow are therefore often optimal for maximizing a species chance for survival in metapopulations without spatial structure. To which extent and under which conditions gene flow facilitates or hinders evolutionary rescue in spatially structured populations remains unresolved. We address this question by studying the differences between evolutionary rescue in the island model and in the stepping stone model in a gradually deteriorating habitat. We show that evolutionary rescue is modulated by the rate of gene flow between different habitats, which in turn depends strongly on the spatial structure and the pattern of environmental deterioration. We use these insights to show that in many cases spatially structured models can be translated into a simpler island model using an appropriately scaled effective migration rate.
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Affiliation(s)
- Matteo Tomasini
- Interfaculty Bioinformatics Unit, University of Bern, Bern, Switzerland.,Computational and Molecular Population Genetics Laboratory, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland.,Swiss Institute for Bioinformatics, Lausanne, Switzerland
| | - Stephan Peischl
- Interfaculty Bioinformatics Unit, University of Bern, Bern, Switzerland.,Swiss Institute for Bioinformatics, Lausanne, Switzerland
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Tanaka MM, Wahl LM. Surviving environmental change: when increasing population size can increase extinction risk. Proc Biol Sci 2022; 289:20220439. [PMID: 35642362 PMCID: PMC9156903 DOI: 10.1098/rspb.2022.0439] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Populations threatened by an abrupt environmental change-due to rapid climate change, pathogens or invasive competitors-may survive if they possess or generate genetic combinations adapted to the novel, challenging condition. If these genotypes are initially rare or non-existent, the emergence of lineages that allow a declining population to survive is known as 'evolutionary rescue'. By contrast, the genotypes required for survival could, by chance, be common before the environmental change. Here, considering both of these possibilities, we find that the risk of extinction can be lower in very small or very large populations, but peaks at intermediate population sizes. This pattern occurs when the survival genotype has a small deleterious effect before the environmental change. Since mildly deleterious mutations constitute a large fraction of empirically measured fitness effects, we suggest that this unexpected result-an intermediate size that puts a population at a greater risk of extinction-may not be unusual in the face of environmental change.
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Affiliation(s)
- Mark M. Tanaka
- University of New South Wales, Sydney, NSW 2052, Australia
| | - Lindi M. Wahl
- Western University, London, Ontario, Canada, N6A 5B7
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