Abstract

A major challenge in conservation biology is the need to broadly prioritize conservation efforts when demographic data are limited. One method to address this challenge is to use population genetic data to define groups of populations linked by migration and then use demographic information from monitored populations to draw inferences about the status of unmonitored populations within those groups. We applied this method to anadromous alewife (Alosa pseudoharengus) and blueback herring (Alosa aestivalis), species for which long-term demographic data are limited. Recent decades have seen dramatic declines in these species, which are an important ecological component of coastal ecosystems and once represented an important fishery resource. Results show that most populations comprise genetically distinguishable units, which are nested geographically within genetically distinct clusters or stocks. We identified three distinct stocks in alewife and four stocks in blueback herring. Analysis of available time series data for spawning adult abundance and body size indicate declines across the US ranges of both species, with the most severe declines having occurred for populations belonging to the Southern New England and the Mid-Atlantic Stocks. While all alewife and blueback herring populations deserve conservation attention, those belonging to these genetic stocks warrant the highest conservation prioritization.

Highlights

  • The inherent value of integrating genetic and demographic data in the design of conservation and recovery plans has been recognized for some time, in the context of evaluating extinction risk in small, isolated populations (Lande 1988; Jamieson and Allendorf 2012)

  • Genetic analysis Data conformance to model assumptions Evidence for null alleles resulted in the exclusion of loci for both alewife (Aa082, Ap037, Ap047, Ap070) and blueback herring (Aa081, Ap058) prior to further analyses

  • Our results show that the majority of rivers examined comprise genetically distinguishable groups (Tables 2 and 3)

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Summary

Introduction

The inherent value of integrating genetic and demographic data in the design of conservation and recovery plans has been recognized for some time, in the context of evaluating extinction risk in small, isolated populations (Lande 1988; Jamieson and Allendorf 2012). A somewhat different perspective that has received less attention is the combination of genetic and demographic information to define management units and prioritize populations within those units for conservation action (Wood and Gross 2008). The complementarity of genetic and demographic data may be especially useful when demographic data are limited, yet broad conservation prioritization is required In this circumstance, population genetic data can be used to define demographically linked groups of populations (e.g., clusters or stocks), and demographic information from a subset of populations can be used to draw inferences about the status of other populations within those groups. This approach allows both monitored and unmonitored populations to be included in conservation prioritizations, which is critical for the management of species for which long-term demographic data are limited to just a few populations

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