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Frankham R.,Macquarie University | Frankham R.,College Street | Ballou J.D.,Smithsonian Conservation Biology Institute | Eldridge M.D.B.,College Street | And 4 more authors.
Conservation Biology | Year: 2011

Fragmentation of animal and plant populations typically leads to genetic erosion and increased probability of extirpation. Although these effects can usually be reversed by re-establishing gene flow between population fragments, managers sometimes fail to do so due to fears of outbreeding depression (OD). Rapid development of OD is due primarily to adaptive differentiation from selection or fixation of chromosomal variants. Fixed chromosomal variants can be detected empirically. We used an extended form of the breeders' equation to predict the probability of OD due to adaptive differentiation between recently isolated population fragments as a function of intensity of selection, genetic diversity, effective population sizes, and generations of isolation. Empirical data indicated that populations in similar environments had not developed OD even after thousands of generations of isolation. To predict the probability of OD, we developed a decision tree that was based on the four variables from the breeders' equation, taxonomic status, and gene flow within the last 500 years. The predicted probability of OD in crosses between two populations is elevated when the populations have at least one of the following characteristics: are distinct species, have fixed chromosomal differences, exchanged no genes in the last 500 years, or inhabit different environments. Conversely, the predicted probability of OD in crosses between two populations of the same species is low for populations with the same karyotype, isolated for <500 years, and that occupy similar environments. In the former case, we recommend crossing be avoided or tried on a limited, experimental basis. In the latter case, crossing can be carried out with low probability of OD. We used crosses with known results to test the decision tree and found that it correctly identified cases where OD occurred. Current concerns about OD in recently fragmented populations are almost certainly excessive. ©2011 Society for Conservation Biology. Source


Carroll C.,Klamath Center for Conservation Research | Fredrickson R.J.,1310 Lower Lincoln Hills Drive | Lacy R.C.,Chicago Zoological Society
Conservation Biology | Year: 2014

Restoring connectivity between fragmented populations is an important tool for alleviating genetic threats to endangered species. Yet recovery plans typically lack quantitative criteria for ensuring such population connectivity. We demonstrate how models that integrate habitat, genetic, and demographic data can be used to develop connectivity criteria for the endangered Mexican wolf (Canis lupus baileyi), which is currently being restored to the wild from a captive population descended from 7 founders. We used population viability analysis that incorporated pedigree data to evaluate the relation between connectivity and persistence for a restored Mexican wolf metapopulation of 3 populations of equal size. Decreasing dispersal rates greatly increased extinction risk for small populations (<150-200), especially as dispersal rates dropped below 0.5 genetically effective migrants per generation. We compared observed migration rates in the Northern Rocky Mountains (NRM) wolf metapopulation to 2 habitat-based effective distance metrics, least-cost and resistance distance. We then used effective distance between potential primary core populations in a restored Mexican wolf metapopulation to evaluate potential dispersal rates. Although potential connectivity was lower in the Mexican wolf versus the NRM wolf metapopulation, a connectivity rate of >0.5 genetically effective migrants per generation may be achievable via natural dispersal under current landscape conditions. When sufficient data are available, these methods allow planners to move beyond general aspirational connectivity goals or rules of thumb to develop objective and measurable connectivity criteria that more effectively support species recovery. The shift from simple connectivity rules of thumb to species-specific analyses parallels the previous shift from general minimum-viable-population thresholds to detailed viability modeling in endangered species recovery planning. © 2013 Society for Conservation Biology. Source


Ivy J.A.,San Diego Zoo Global | Lacy R.C.,Chicago Zoological Society
Journal of Heredity | Year: 2012

Captive breeding programs aim to maintain populations that are demographically self-sustaining and genetically healthy. It has been well documented that the best way for managed breeding programs to retain gene diversity (GD) and limit inbreeding is to select breeding pairs that minimize a population's average kinship. We used a series of computer simulations to test 4 methods of minimizing average kinship across a variety of scenarios with varying generation lengths, mortality rates, reproductive rates, and rates of breeding pair success. "Static MK Selection" and "Dynamic MK Selection" are 2 methods for iteratively selecting genetically underrepresented individuals for breeding, whereas "Ranked MK Selection" and "Simultaneous MK Selection" are 2 methods for concurrently selecting the group of breeding individuals that produce offspring with the lowest average kinship. For populations with discrete generations (24 tested scenarios), we found that the Simultaneous and Ranked MK Selection methods were generally the best, nearly equivalent methods for selecting breeding pairs that retained GD and limited inbreeding. For populations with overlapping generations (198 tested scenarios), we found that Dynamic MK Selection was the most robust method for selecting breeding pairs. We used these results to provide guidelines for identifying which method of minimizing average kinship was most appropriate for various breeding program scenarios. © The American Genetic Association. 2012. All rights reserved. Source


Hedrick P.W.,Arizona State University | Lacy R.C.,Chicago Zoological Society
Journal of Heredity | Year: 2015

Genetic relatedness between individuals is an important measure in many areas of biology. However, some relatedness measures for use with molecular (allele) data assume that the individuals themselves are not inbred. Here, we present a new measure of relatedness based on the different modes of identity-by-descent for alleles that has an upper bound of 1 even when the individuals being compared are themselves inbred. This new measure is compared to several other measures of relatedness using several simple examples and pedigree data from the wolf population in Isle Royale National Park. Source


Lacy R.C.,Chicago Zoological Society | Ballou J.D.,Smithsonian Conservation Biology Institute | Pollak J.P.,Cornell University
Methods in Ecology and Evolution | Year: 2012

1.The concepts and algorithms for demographic and genetic analysis of pedigreed populations have been evolving rapidly in recent years. 2.The PMx software brings together into one integrated package a number of tools for pedigree analysis, including methods for dealing with missing, uncertain and probabilistic data not previously available in distributed software. 3.PMx provides tools for optimal demographic and genetic management of populations of wildlife species, rare domestic breeds, and other populations for which the primary goal is to conserve genetic diversity, and it is being implemented as the primary pedigree management tool for the breeding programmes of zoo associations around the world. 4.PMx can be used to characterize the demography and genetics of any captive or wild population for which pedigree and life-history data are available. © 2011 The Authors. Methods in Ecology and Evolution © 2011 British Ecological Society. Source

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