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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

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Dealing With the Complexity of Effective Population Size in Conservation Practice.

Ancuta Fedorca^1,2, Joachim Mergeay^3,4, Adejoke O Akinyele⁵

¹Department of Wildlife National Institute for Research and Development in Forestry 'Marin Dracea' Brașov Romania.

Evolutionary Applications

|December 16, 2024

Summary

Estimating effective population size (Ne) is crucial for species survival. This study addresses challenges in Ne estimation for conservation by evaluating methods and developing strategies to improve accuracy for biodiversity monitoring.

Keywords:

Kunming‐Montreal global biodiversity framework Ne biodiversity monitoring bridging science‐to‐application gap effective number of breeders genetic diversity genetic indicators species conservation and management

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Area of Science:

Evolutionary biology
Conservation genetics
Genomics

Background:

Effective population size (Ne) is vital for species' long-term survival and conservation.
Molecular Ne estimation methods often rely on assumptions rarely met in fragmented populations facing environmental changes.
Violations of these assumptions can lead to biased and inaccurate Ne estimates, hindering conservation efforts.

Purpose of the Study:

To operationalize Ne estimation knowledge for conservation practitioners and policymakers.
To evaluate the sensitivity of Ne estimation methods to assumption violations using real-world datasets.
To develop data analysis strategies for biodiversity monitoring and conservation.

Main Methods:

International workshop (COST Action G-BiKE) focused on Ne estimation challenges.
Identification and evaluation of datasets to test Ne estimation method sensitivity.
Development of data analysis strategies for conservation applications.

Main Results:

The workshop identified key challenges in applying Ne estimation methods in conservation.
Strategies were explored to mitigate biases caused by violated assumptions in Ne estimation.
The report synthesizes approaches and findings to bridge the gap between research and practice.

Conclusions:

Accurate Ne estimation is critical for effective species conservation and biodiversity management.
Addressing assumption violations in Ne estimation methods is essential for reliable conservation outcomes.
This work provides practical insights for applying genomic data in conservation decision-making.