Title (eng)
Dealing With the Complexity of Effective Population Size in Conservation Practice
Author
Abstract (eng)
Effective population size (Ne) is one of the most important parameters in evolutionary biology, as it is linked to the long-term survival capability of species. Therefore, Ne greatly interests conservation geneticists, but it is also very relevant to policymakers, managers, and conservation practitioners. Molecular methods to estimate Ne rely on various assumptions, including no immigration, panmixia, random sampling, absence of spatial genetic structure, and/or mutation-drift equilibrium. Species are, however, often characterized by fragmented populations under changing environmental conditions and anthropogenic pressure. Therefore, the estimation methods' assumptions are seldom addressed and rarely met, possibly leading to biased and inaccurate Ne estimates. To address the challenges associated with estimating Ne for conservation purposes, the COST Action 18134, Genomic Biodiversity Knowledge for Resilient Ecosystems (G-BiKE), organized an international workshop that met in August 2022 in Bra?ov, Romania. The overarching goal was to operationalize the current knowledge of Ne estimation methods for conservation practitioners and decision-makers. We set out to identify datasets to evaluate the sensitivity of Ne estimation methods to violations of underlying assumptions and to develop data analysis strategies that addressed pressing issues in biodiversity monitoring and conservation. Referring to a comprehensive body of scientific work on Ne, this meeting report is not intended to be exhaustive but rather to present approaches, workshop findings, and a collection of papers that serve as fruits of those efforts. We aimed to provide insights and opportunities to help bridge the gap between scientific research and conservation practice.
Keywords (eng)
Linkage DisequilibriumOverlapping GenerationsNatural-PopulationsDemographic HistorySingle-SampleN-EInferenceProgramSoftwareGenetics
Type (eng)
Language
[eng]
Persistent identifier
Is in series
Title (eng)
Evolutionary Applications
Volume
17
Issue
12
ISSN
1752-4571
Issued
2024
Number of pages
17
Publication
Wiley
Version type (eng)
Date issued
2024
Access rights (eng)
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Rights statement (eng)
© 2024 The Author(s)
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