Section: Zoology
Topic: Ecology, Sustainability science, Genetics/Genomics

Improving species conservation plans under IUCN’s One Plan Approach using quantitative genetic methods

10.24072/pcjournal.163 - Peer Community Journal, Volume 2 (2022), article no. e50.

Get full text PDF Peer reviewed and recommended by PCI

Human activities are resulting in altered environmental conditions that are impacting the demography and evolution of species globally. If we wish to prevent anthropogenic extinction and extirpation, we need to improve our ability to restore wild populations. Ex situ populations can be an important tool for species conservation. However, it is difficult to prevent deviations from an optimal breeding design and altered environments in captivity seem likely to lead to evolutionary or plasticity-induced phenotypic change that could make reintroduction more difficult. Quantitative genetic analysis can help disentangle the causes of phenotypic change in ex situ populations. Consequently, quantitative genetics can improve the management of these populations and the success of in situ population management actions that they support. In this review we outline methods that could be used to improve the management of in situ and ex situ populations in a One Plan Approach. We discuss how quantitative genetic models can help measure genetic variation, phenotypic plasticity, and social effects on phenotypes. Finally, we discuss how phenotypic change can be predicted using measurements of additive genetic variance and selection. While previous work has highlighted the value of ex situ populations for the field of quantitative genetics, we argue that quantitative genetics can, in turn, offer opportunities to improve management and consequently conservation of populations of species at risk. We show that quantitative genetic analyses are a tool that could be incorporated into and improve ex situ management practices.

Published online:
DOI: 10.24072/pcjournal.163
Type: Research article
Sauve, Drew 1; Hudecki, Jane 2; Steiner, Jessica 2; Wheeler, Hazel 2; Lynch, Colleen 3; Chabot, Amy A. 4

1 Department of Biology, Queen's University, Kingston, Ontario K7L 3N6, Canada
2 Wildlife Preservation Canada, 5420 Highway 6 North, Guelph, Ontario N1H 6J2, Canada
3 Riverbanks Zoo and Garden, 500 Wildlife Parkway, Columbia, South Carolina, USA
4 African Lion Safari, 1386 Cooper Road, Cambridge, Ontario N1R 5S2, Canada
License: CC-BY 4.0
Copyrights: The authors retain unrestricted copyrights and publishing rights
     author = {Sauve, Drew and Hudecki, Jane and Steiner, Jessica and Wheeler, Hazel and Lynch, Colleen and Chabot, Amy A.},
     title = {Improving species conservation plans under {IUCN{\textquoteright}s} {One} {Plan} {Approach} using quantitative genetic methods},
     journal = {Peer Community Journal},
     eid = {e50},
     publisher = {Peer Community In},
     volume = {2},
     year = {2022},
     doi = {10.24072/pcjournal.163},
     url = {}
AU  - Sauve, Drew
AU  - Hudecki, Jane
AU  - Steiner, Jessica
AU  - Wheeler, Hazel
AU  - Lynch, Colleen
AU  - Chabot, Amy A.
TI  - Improving species conservation plans under IUCN’s One Plan Approach using quantitative genetic methods
JO  - Peer Community Journal
PY  - 2022
VL  - 2
PB  - Peer Community In
UR  -
DO  - 10.24072/pcjournal.163
ID  - 10_24072_pcjournal_163
ER  - 
%0 Journal Article
%A Sauve, Drew
%A Hudecki, Jane
%A Steiner, Jessica
%A Wheeler, Hazel
%A Lynch, Colleen
%A Chabot, Amy A.
%T Improving species conservation plans under IUCN’s One Plan Approach using quantitative genetic methods
%J Peer Community Journal
%D 2022
%V 2
%I Peer Community In
%R 10.24072/pcjournal.163
%F 10_24072_pcjournal_163
Sauve, Drew; Hudecki, Jane; Steiner, Jessica; Wheeler, Hazel; Lynch, Colleen; Chabot, Amy A. Improving species conservation plans under IUCN’s One Plan Approach using quantitative genetic methods. Peer Community Journal, Volume 2 (2022), article  no. e50. doi : 10.24072/pcjournal.163.

PCI peer reviews and recommendation, and links to data, scripts, code and supplementary information: 10.24072/pci.zool.100015

Conflict of interest of the recommender and peer reviewers:
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.

[1] Aase, K.; Jensen, H.; Muff, S. Genomic estimation of quantitative genetic parameters in wild admixed populations, Methods in Ecology and Evolution, Volume 13 (2022) no. 5, pp. 1014-1026 | DOI

[2] Arnold, S. J.; Wade, M. J. On the Measurement of Natural and Sexual Selection: Applications, Evolution, Volume 38 (1984) no. 4 | DOI

[3] Arnold, S. J.; Wade, M. J. On the Measurement of Natural and Sexual Selection: Theory, Evolution, Volume 38 (1984) no. 4 | DOI

[4] Allegue, H.; Araya‐Ajoy, Y. G.; Dingemanse, N. J.; Dochtermann, N. A.; Garamszegi, L. Z.; Nakagawa, S.; Réale, D.; Schielzeth, H.; Westneat, D. F. Statistical Quantification of Individual Differences (SQuID): an educational and statistical tool for understanding multilevel phenotypic data in linear mixed models, Methods in Ecology and Evolution, Volume 8 (2017) no. 2, pp. 257-267 | DOI

[5] Ballou, J.; Lacy, R.; Pollak, J. PMx: Software for demographic and genetic analysis and management of pedigreed populations (Version Chicago Zoological Society, Brookfield, Illinois, USA, 2020 (

[6] Baskett, M. L.; Burgess, S. C.; Waples, R. S. Assessing strategies to minimize unintended fitness consequences of aquaculture on wild populations, Evolutionary Applications, Volume 6 (2013) no. 7, pp. 1090-1108 | DOI

[7] Blumstein, D. T.; Mari, M.; Daniel, J. C.; Ardron, J. G.; Griffin, A. S.; Evans, C. S. Olfactory predator recognition: wallabies may have to learn to be wary, Animal Conservation, Volume 5 (2006) no. 2, pp. 87-93 | DOI

[8] Bonamour, S.; Chevin, L.-M.; Charmantier, A.; Teplitsky, C. Phenotypic plasticity in response to climate change: the importance of cue variation, Philosophical Transactions of the Royal Society B: Biological Sciences, Volume 374 (2019) no. 1768 | DOI

[9] Bonnet, T.; Morrissey, M. B.; Kruuk, L. E. B. Estimation of Genetic Variance in Fitness, and Inference of Adaptation, When Fitness Follows a Log-Normal Distribution, Journal of Heredity, Volume 110 (2019) no. 4, pp. 383-395 | DOI

[10] Bonnet, T.; Morrissey, M. B.; Morris, A.; Morris, S.; Clutton-Brock, T. H.; Pemberton, J. M.; Kruuk, L. E. B. The role of selection and evolution in changing parturition date in a red deer population, PLOS Biology, Volume 17 (2019) no. 11 | DOI

[11] Bonnet, T.; Wandeler, P.; Camenisch, G.; Postma, E. Bigger Is Fitter? Quantitative Genetic Decomposition of Selection Reveals an Adaptive Evolutionary Decline of Body Mass in a Wild Rodent Population, PLOS Biology, Volume 15 (2017) no. 1 | DOI

[12] Byers, O.; Lees, C.; Wilcken, J.; Schwitzer, C. The One Plan Approach: The philosophy and implementation of CBSG's approach to integrated species conservation planning, World association of Zoos and Aquariums Magazine, Volume 14 (2013), pp. 2-5

[13] Chargé, R.; Sorci, G.; Saint Jalme, M.; Lesobre, L.; Hingrat, Y.; Lacroix, F.; Teplitsky, C. Does recognized genetic management in supportive breeding prevent genetic changes in life‐history traits?, Evolutionary Applications, Volume 7 (2014) no. 5, pp. 521-532 | DOI

[14] Charmantier, A.; Garant, D. D.; Kruuk, L. E. B. Quantitative genetics in the wild, Oxford University Press, Oxford, 2014

[15] Charmantier, A.; Réale, D. How do misassigned paternities affect the estimation of heritability in the wild?, Molecular Ecology, Volume 14 (2005) no. 9, pp. 2839-2850 | DOI

[16] Che-Castaldo, J. P.; Grow, S. A.; Faust, L. J. Evaluating the Contribution of North American Zoos and Aquariums to Endangered Species Recovery, Scientific Reports, Volume 8 (2018) no. 1 | DOI

[17] Chevin, L.-M.; Lande, R. When do adaptive plasticity and genetic evolution prevent extinction of a density-regulated population?, Evolution, Volume 64 (2010) no. 4, pp. 1143-1150 | DOI

[18] Courtney Jones, S. K.; Munn, A. J.; Byrne, P. G. Effect of captivity on morphology: negligible changes in external morphology mask significant changes in internal morphology, Royal Society Open Science, Volume 5 (2018) no. 5 | DOI

[19] Cox, J.; Lima, S. Naiveté and an aquatic–terrestrial dichotomy in the effects of introduced predators, Trends in Ecology & Evolution, Volume 21 (2006) no. 12, pp. 674-680 | DOI

[20] Dingemanse, N. J.; Dochtermann, N. A. Quantifying individual variation in behaviour: mixed-effect modelling approaches, Journal of Animal Ecology, Volume 82 (2013) no. 1, pp. 39-54 | DOI

[21] English, S.; Fawcett, T. W.; Higginson, A. D.; Trimmer, P. C.; Uller, T. Adaptive Use of Information during Growth Can Explain Long-Term Effects of Early Life Experiences, The American Naturalist, Volume 187 (2016) no. 5, pp. 620-632 | DOI

[22] Firth, J. A.; Hadfield, J. D.; Santure, A. W.; Slate, J.; Sheldon, B. C. The influence of nonrandom extra-pair paternity on heritability estimates derived from wild pedigrees, Evolution, Volume 69 (2015) no. 5, pp. 1336-1344 | DOI

[23] Fischer, C. P.; Romero, L. M. Chronic captivity stress in wild animals is highly species-specific, Conservation Physiology, Volume 7 (2020) no. 1 | DOI

[24] Fischer, J.; Lindenmayer, D. An assessment of the published results of animal relocations, Biological Conservation, Volume 96 (2000) no. 1, pp. 1-11 | DOI

[25] Fisher, D. N.; Haines, J. A.; Boutin, S.; Dantzer, B.; Lane, J. E.; Coltman, D. W.; McAdam, A. G. Indirect effects on fitness between individuals that have never met via an extended phenotype, Ecology Letters, Volume 22 (2019) no. 4, pp. 697-706 | DOI

[26] Fisher, D. N.; McAdam, A. G. Indirect genetic effects clarify how traits can evolve even when fitness does not, Evolution Letters, Volume 3 (2019) no. 1, pp. 4-14 | DOI

[27] Fisher, D. N.; Wilson, A. J.; Boutin, S.; Dantzer, B.; Lane, J. E.; Coltman, D. W.; Gorrell, J. C.; McAdam, A. G. Social effects of territorial neighbours on the timing of spring breeding in North American red squirrels, Journal of Evolutionary Biology, Volume 32 (2019) no. 6, pp. 559-571 | DOI

[28] Fisher, R. A. The genetical theory of natural selection (1st ed.), Clarendon Press, Oxford, 1930

[29] Frankham, R. Genetic adaptation to captivity in species conservation programs, Molecular Ecology, Volume 17 (2008) no. 1, pp. 325-333 | DOI

[30] Gaynor, R. C.; Gorjanc, G.; Hickey, J. M. AlphaSimR: an R package for breeding program simulations, G3 Genes|Genomes|Genetics, Volume 11 (2021) no. 2 | DOI

[31] Gervais, L.; Perrier, C.; Bernard, M.; Merlet, J.; Pemberton, J. M.; Pujol, B.; Quéméré, E. RAD‐sequencing for estimating genomic relatedness matrix‐based heritability in the wild: A case study in roe deer, Molecular Ecology Resources, Volume 19 (2019) no. 5, pp. 1205-1217 | DOI

[32] Gienapp, P.; Fior, S.; Guillaume, F.; Lasky, J. R.; Sork, V. L.; Csilléry, K. Genomic Quantitative Genetics to Study Evolution in the Wild, Trends in Ecology & Evolution, Volume 32 (2017) no. 12, pp. 897-908 | DOI

[33] Griffin, A. S.; Blumstein, D. T.; Evans, C. S. Training Captive-Bred or Translocated Animals to Avoid Predators, Conservation Biology, Volume 14 (2000) no. 5, pp. 1317-1326 | DOI

[34] Hadfield, J. D. MCMC Methods for Multi-Response Generalized Linear Mixed Models: The MCMCglmm R Package, Journal of Statistical Software, Volume 33 (2010) no. 2 | DOI

[35] Hadfield, J. D.; Wilson, A. J.; Garant, D.; Sheldon, B. C.; Kruuk, L. E. B. The Misuse of BLUP in Ecology and Evolution, The American Naturalist, Volume 175 (2010) no. 1, pp. 116-125 | DOI

[36] Harbers, H.; Neaux, D.; Ortiz, K.; Blanc, B.; Laurens, F.; Baly, I.; Callou, C.; Schafberg, R.; Haruda, A.; Lecompte, F.; Casabianca, F.; Studer, J.; Renaud, S.; Cornette, R.; Locatelli, Y.; Vigne, J.-D.; Herrel, A.; Cucchi, T. The mark of captivity: plastic responses in the ankle bone of a wild ungulate (Sus scrofa), Royal Society Open Science, Volume 7 (2020) no. 3 | DOI

[37] Henderson, C. R. Estimation of genetic parameters, Biometrics, Volume 6 (1950), pp. 186-187

[38] Hendry, A. P. Eco-evolutionary Dynamics (1st ed.), Princeton University Press, Princeton, 2016

[39] Houslay, T. M.; Wilson, A. J. Avoiding the misuse of BLUP in behavioural ecology, Behavioral Ecology, Volume 28 (2017) no. 4, pp. 948-952 | DOI

[40] Janeiro, M. J.; Coltman, D. W.; Festa-Bianchet, M.; Pelletier, F.; Morrissey, M. B. Towards robust evolutionary inference with integral projection models, Journal of Evolutionary Biology, Volume 30 (2017) no. 2, pp. 270-288 | DOI

[41] Jolly, C. J.; Phillips, B. L. Rapid evolution in predator‐free conservation havens and its effects on endangered species recovery, Conservation Biology, Volume 35 (2021) no. 1, pp. 383-385 | DOI

[42] Kruuk, L. E. B. Estimating genetic parameters in natural populations using the ‘animal model’, Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, Volume 359 (2004) no. 1446, pp. 873-890 | DOI

[43] Lacy, R. C. Extending Pedigree Analysis for Uncertain Parentage and Diverse Breeding Systems, Journal of Heredity, Volume 103 (2012) no. 2, pp. 197-205 | DOI

[44] Lacy, R. C.; Malo, A. F.; Alaks, G. Maintenance of genetic variation in quantitative traits of a woodland rodent during generations of captive breeding, Conservation Genetics, Volume 19 (2018) no. 4, pp. 789-802 | DOI

[45] Lacy, R.; Pollak, J. P. Vortex: A stochastic simulation of the extinction process. Version 10.5.5., Chicago Zoological Society, Brookfield, Illinois, USA, 2021

[46] Lande, R.; Arnold, S. J. The Measurement of Selection on Correlated Characters, Evolution, Volume 37 (1983) no. 6 | DOI

[47] Laskowski, K. L.; Wolf, M.; Bierbach, D. The making of winners (and losers): how early dominance interactions determine adult social structure in a clonal fish, Proceedings of the Royal Society B: Biological Sciences, Volume 283 (2016) no. 1830 | DOI

[48] Lees, C.; Rutschmann, A.; Santure, A.; Beggs, J. Science-based, stakeholder-inclusive and participatory conservation planning helps reverse the decline of threatened species, Biological Conservation, Volume 260 (2021) | DOI

[49] Lynch, M.; Walsh, B. Genetics and analysis of quantitative traits, Sinauer Associates, Sunderland, MA

[50] Martin, J. G. A.; Nussey, D. H.; Wilson, A. J.; Réale, D. Measuring individual differences in reaction norms in field and experimental studies: a power analysis of random regression models, Methods in Ecology and Evolution, Volume 2 (2011) no. 4, pp. 362-374 | DOI

[51] Meuwissen, T. H. E.; Sonesson, A. K.; Gebregiwergis, G.; Woolliams, J. A. Management of Genetic Diversity in the Era of Genomics, Frontiers in Genetics, Volume 11 (2020) | DOI

[52] McDougall, P. T.; Réale, D.; Sol, D.; Reader, S. M. Wildlife conservation and animal temperament: causes and consequences of evolutionary change for captive, reintroduced, and wild populations, Animal Conservation, Volume 9 (2006) no. 1, pp. 39-48 | DOI

[53] Mittell, E. A.; Nakagawa, S.; Hadfield, J. D. Are molecular markers useful predictors of adaptive potential?, Ecology Letters, Volume 18 (2015) no. 8, pp. 772-778 | DOI

[54] Moiron, M.; Araya-Ajoy, Y. G.; Teplitsky, C.; Bouwhuis, S.; Charmantier, A. Understanding the Social Dynamics of Breeding Phenology: Indirect Genetic Effects and Assortative Mating in a Long-Distance Migrant, The American Naturalist, Volume 196 (2020) no. 5, pp. 566-576 | DOI

[55] Monaghan, P. Early growth conditions, phenotypic development and environmental change, Philosophical Transactions of the Royal Society B: Biological Sciences, Volume 363 (2008) no. 1497, pp. 1635-1645 | DOI

[56] Monk, C. T.; Bekkevold, D.; Klefoth, T.; Pagel, T.; Palmer, M.; Arlinghaus, R. The battle between harvest and natural selection creates small and shy fish, Proceedings of the National Academy of Sciences, Volume 118 (2021) no. 9 | DOI

[57] Montgomery, M. E.; Ballou, J. D.; Nurthen, R. K.; England, P. R.; Briscoe, D. A.; Frankham, R. Minimizing kinship in captive breeding programs, Zoo Biology, Volume 16 (1997) no. 5, pp. 377-389 | DOI

[58] Morales-González, E.; Fernández, J.; Pong-Wong, R.; Toro, M. Á.; Villanueva, B. Changes in Allele Frequencies When Different Genomic Coancestry Matrices Are Used for Maintaining Genetic Diversity, Genes, Volume 12 (2021) no. 5 | DOI

[59] Morrissey, M. B.; Wilson, A. J. pedantics: an r package for pedigree-based genetic simulation and pedigree manipulation, characterization and viewing, Molecular Ecology Resources, Volume 10 (2010) no. 4, pp. 711-719 | DOI

[60] Moseby, K. E.; Cameron, A.; Crisp, H. A. Can predator avoidance training improve reintroduction outcomes for the greater bilby in arid Australia?, Animal Behaviour, Volume 83 (2013) no. 4, pp. 1011-1021 | DOI

[61] Muff, S.; Niskanen, A. K.; Saatoglu, D.; Keller, L. F.; Jensen, H. Animal models with group-specific additive genetic variances: extending genetic group models, Genetics Selection Evolution, Volume 51 (2019) no. 1 | DOI

[62] Munch, K. L.; Noble, D. W. A.; Budd, L.; Row, A.; Wapstra, E.; While, G. M. Maternal presence facilitates plasticity in offspring behavior: insights into the evolution of parental care, Behavioral Ecology, Volume 29 (2018) no. 6, pp. 1298-1306 | DOI

[63] Nussey, D. H.; Wilson, A. J.; Brommer, J. E. The evolutionary ecology of individual phenotypic plasticity in wild populations, Journal of Evolutionary Biology, Volume 20 (2007) no. 3, pp. 831-844 | DOI

[64] O'Regan, H. J.; Kitchener, A. C. The effects of captivity on the morphology of captive, domesticated and feral mammals, Mammal Review, Volume 35 (2005) no. 3-4, pp. 215-230 | DOI

[65] Parmesan, C. Ecological and Evolutionary Responses to Recent Climate Change, Annual Review of Ecology, Evolution, and Systematics, Volume 37 (2006) no. 1, pp. 637-669 | DOI

[66] Pelletier, F.; Réale, D.; Watters, J.; Boakes, E. H.; Garant, D. Value of captive populations for quantitative genetics research, Trends in Ecology & Evolution, Volume 24 (2009) no. 5, pp. 263-270 | DOI

[67] Pigeon, G.; Festa-Bianchet, M.; Coltman, D. W.; Pelletier, F. Intense selective hunting leads to artificial evolution in horn size, Evolutionary Applications, Volume 9 (2016) no. 4, pp. 521-530 | DOI

[68] Ponzi, E.; Keller, L. F.; Bonnet, T.; Muff, S. Heritability, selection, and the response to selection in the presence of phenotypic measurement error: Effects, cures, and the role of repeated measurements, Evolution, Volume 72 (2018) no. 10, pp. 1992-2004 | DOI

[69] Postma, E. Implications of the difference between true and predicted breeding values for the study of natural selection and micro-evolution, Journal of Evolutionary Biology, Volume 19 (2006) no. 2, pp. 309-320 | DOI

[70] Power, M. L.; Oftedal, O. T.; Tardif, S. D. Does the milk of callitrichid monkeys differ from that of larger anthropoids?, American Journal of Primatology, Volume 56 (2002) no. 2, pp. 117-127 | DOI

[71] Power, M. L.; Verona, C. E.; Ruiz-Miranda, C.; Oftedal, O. T. The composition of milk from free-living common marmosets (Callithrix jacchus) in Brazil, American Journal of Primatology, Volume 70 (2008) no. 1, pp. 78-83 | DOI

[72] Price, G. R. Selection and Covariance, Nature, Volume 227 (1970) no. 5257, pp. 520-521 | DOI

[73] Princée, F. P. G. Exploring studbooks for wildlife management and conservation, Springer International Publishing, East Rudham, Norfolk, UK, 2016

[74] Queller, D. C. Fundamental Theorems of Evolution, The American Naturalist, Volume 189 (2017) no. 4, pp. 345-353 | DOI

[75] Ralls, K.; Ballou, J. D.; Rideout, B. A.; Frankham, R. Genetic management of chondrodystrophy in California condors, Animal Conservation, Volume 3 (2000) no. 2, pp. 145-153 | DOI

[76] Reading, R. P.; Miller, B.; Shepherdson, D. The Value of Enrichment to Reintroduction Success, Zoo Biology, Volume 32 (2013) no. 3, pp. 332-341 | DOI

[77] Reed, D. H.; Frankham, R. How closely correlated are molecular and quantitative measures of genetic variation? A meta-analysis, Evolution, Volume 55 (2001) no. 6, pp. 1095-1103 | DOI

[78] Reid, J. M.; Arcese, P.; Nietlisbach, P.; Wolak, M. E.; Muff, S.; Dickel, L.; Keller, L. F. Immigration counter‐acts local micro‐evolution of a major fitness component: Migration‐selection balance in free‐living song sparrows, Evolution Letters, Volume 5 (2021) no. 1, pp. 48-60 | DOI

[79] Rendel, J. M.; Robertson, A. Estimation of genetic gain in milk yield by selection in a closed herd of dairy cattle, Journal of Genetics, Volume 50 (1950) no. 1, pp. 1-8 | DOI

[80] Saura, M.; Pérez-Figueroa, A.; Fernández, J.; Toro, M. A.; Caballero, A. Preserving population allele frequencies in ex situ conservation programs, Conservation Biology, Volume 22 (2008) no. 5, pp. 1277-1287 | DOI

[81] Schulte‐Hostedde, A. I.; Mastromonaco, G. F. Integrating evolution in the management of captive zoo populations, Evolutionary Applications, Volume 8 (2015) no. 5, pp. 413-422 | DOI

[82] Soorae, P.; (ed) Global conservation translocation perspectives: 2021. Case studies from around the globe, IUCN SSC Conservation Translocation Specialist Group, Environment Agency - Abu Dhabi and Calgary Zoo, Canada., 2021

[83] Sultan, S. E. Organism and Environment, Oxford University Press, Oxford, 2015

[84] Sundström, L. F.; Lõhmus, M.; Devlin, R. H. Gene-environment interactions influence feeding and anti-predator behavior in wild and transgenic coho salmon, Ecological Applications, Volume 26 (2016) no. 1, pp. 67-76 | DOI

[85] Tardif, S. D.; Power, M. L.; Ross, C. N.; Rutherford, J. N. Body mass growth in common marmosets: Toward a model of pediatric obesity, American Journal of Physical Anthropology, Volume 150 (2013) no. 1, pp. 21-28 | DOI

[86] Tavecchia, G.; Viedma, C.; Martínez-Abraín, A.; Bartolomé, M.-A.; Gómez, J. A.; Oro, D. Maximizing re-introduction success: Assessing the immediate cost of release in a threatened waterfowl, Biological Conservation, Volume 142 (2009) no. 12, pp. 3005-3012 | DOI

[87] Thomson, C. E.; Winney, I. S.; Salles, O. C.; Pujol, B. A guide to using a multiple-matrix animal model to disentangle genetic and nongenetic causes of phenotypic variance, PLOS ONE, Volume 13 (2018) no. 10 | DOI

[88] United Nations Environment Program Convention on Biological Diversity X/2.Strategic Plan for Biodiversity 2011-2020, 2010 (

[89] Vedder, O.; Bouwhuis, S.; Sheldon, B. C. Quantitative Assessment of the Importance of Phenotypic Plasticity in Adaptation to Climate Change in Wild Bird Populations, PLoS Biology, Volume 11 (2013) no. 7 | DOI

[90] de Villemereuil, P.; Schielzeth, H.; Nakagawa, S.; Morrissey, M. General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models, Genetics, Volume 204 (2016) no. 3, pp. 1281-1294 | DOI

[91] Wade, M. J.; Goodnight, C. J. Perspective: the theories of fisher and wright in the context of metapopulations: when nature does many small experiments, Evolution, Volume 52 (1998) no. 6, pp. 1537-1553 | DOI

[92] Walsh, B.; Lynch, M. Evolution and Selection of Quantitative Traits, Oxford University Press., Oxford, New York, 2018

[93] West-Eberhard, M. J. Developmental plasticity and evolution, Oxford University Press, Oxford, 2003

[94] Williams, S. E.; Hoffman, E. A. Minimizing genetic adaptation in captive breeding programs: A review, Biological Conservation, Volume 142 (2009) no. 11, pp. 2388-2400 | DOI

[95] Willoughby, J. R.; Fernandez, N. B.; Lamb, M. C.; Ivy, J. A.; Lacy, R. C.; DeWoody, J. A. The impacts of inbreeding, drift and selection on genetic diversity in captive breeding populations, Molecular Ecology, Volume 24 (2015) no. 1, pp. 98-110 | DOI

[96] Wilson, A. J.; Réale, D.; Clements, M. N.; Morrissey, M. M.; Postma, E.; Walling, C. A.; Kruuk, L. E. B.; Nussey, D. H. An ecologist’s guide to the animal model, Journal of Animal Ecology, Volume 79 (2010) no. 1, pp. 13-26 | DOI

[97] Wolak, M. E. Nadiv: An R package to create relatedness matrices for estimating non-additive genetic variances in animal models, Methods in Ecology and Evolution, Volume 3 (2012) no. 5, pp. 792-796 | DOI

[98] Wolak, M. E.; Keller, L. F. Dominance genetic variance and inbreeding in natural populations In: In Quantitative genetics in the wild, Oxford University Press, Oxford, pp. 104-127

[99] Wolak, M. E.; Reid, J. M. Accounting for genetic differences among unknown parents in microevolutionary studies: how to include genetic groups in quantitative genetic animal models, Journal of Animal Ecology, Volume 86 (2017) no. 1, pp. 7-20 | DOI

Cited by Sources: