Genetically defining populations is of limited use for evaluating and managing human impacts on gene flow
Adam J. Stow A C and William E. Magnusson B
+ Author Affiliations
- Author Affiliations
A Department of Biological Sciences, Macquarie University, NSW 2109, Australia.
B Coordenação da Biodiversidade, Instituto Nacional de Pesquisas da Amazonia, CP 478, 69011-970 Manaus AM, Brazil.
C Corresponding author. Email: adam.stow@mq.edu.au
Wildlife Research 39(4) 290-294 https://doi.org/10.1071/WR11150
Submitted: 15 August 2011 Accepted: 2 March 2012 Published: 8 May 2012
Abstract
Partitioning genetic variation into panmictic units is one of the most commonly used techniques in genetic studies of wild organisms. For conservation, the rationale is to identify units for management, most often referred to as populations. Describing these populations provides a measure of genetic differentiation, but they are only management units in relation to specific objectives. In situ conservation activities are mostly constrained to landscape (or ‘seascape’) units. With continuing habitat fragmentation, maintaining gene flow and genetic variation is an underlying objective for many conservation activities. Spatially explicit genetic approaches can describe how gene flow varies across a landscape, but the popular approach of identifying populations has limited and specific application. The statistical tests and sampling procedures used seldom allow for the spatial extent of genetic panmixia to be precisely defined. Gene flow, genetic variation and genetic detection of individual movements can be estimated without reference to populations. Furthermore, the term ‘population’ is used inconsistently in the literature and is often poorly defined. Formulating appropriate questions for management requires that the unit of study is clearly described, and often this could be organisms inhabiting defined areas of the landscape. Resources for conservation management are limited, so geneticists working on gene flow in wild organisms need to frame questions relevant to specific management needs and carefully consider the language and approaches employed.
References
Allendorf, F. W., England, P. R., Luikart, G., Ritchie, P. A., and Ryman, N. (2008). Genetic effects of harvest on wild animal populations. Trends in Ecology & Evolution 23, 327–337.| Genetic effects of harvest on wild animal populations.Crossref | GoogleScholarGoogle Scholar |
Bergl, R. A., and Vigilant, L. (2006). Genetic analysis reveals population structure and recent migration within the highly fragmented range of the Cross River gorilla (Gorilla gorilla diehli). Molecular Ecology 16, 501–516.
| Genetic analysis reveals population structure and recent migration within the highly fragmented range of the Cross River gorilla (Gorilla gorilla diehli).Crossref | GoogleScholarGoogle Scholar |
Bowcock, A. M., Ruíz-Linares, A., Tomfohrde, J., Minch, E., Kidd, J. R., and Cavalli-Sforza, L. L. (1994). High resolution human evolutionary trees with polymorphic microsatellites. Nature 368, 455–457.
| High resolution human evolutionary trees with polymorphic microsatellites.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaK2c7otFShsA%3D%3D&md5=8015008fac4e7ceece1f1f15a4b7c2beCAS |
Carr, D., Bowman, J., Kyle, C. J., Tully, S. M., Koen, E. L., Robitaille, F., and Wilson, P. J. (2007). Rapid homogenisation of multiple sources: genetic structure of recolonising populations of fishers. Wildlife Management 71, 1853–1861.
| Rapid homogenisation of multiple sources: genetic structure of recolonising populations of fishers.Crossref | GoogleScholarGoogle Scholar |
Cullingham, C. I., Pond, B. A., Kyle, S. C., Rees, E. E., Rosatte, R. C., and White, B. N. (2008). Combining direct and indirect genetic methods to estimate dispersal for informing wildlife disease management decisions. Molecular Ecology 17, 4874–4886.
| Combining direct and indirect genetic methods to estimate dispersal for informing wildlife disease management decisions.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD1M%2FmvFWhtQ%3D%3D&md5=d8b51993a695c8089c58037b814df204CAS |
Cushman, S. A., and Landguth, E. L. (2010a). Scale dependent inference in landscapegenetics. Landscape Ecology 25, 967–979.
| Scale dependent inference in landscapegenetics.Crossref | GoogleScholarGoogle Scholar |
Cushman, S. A., and Landguth, E. L. (2010b). Spurious correlations and inferences in landscape genetics. Molecular Ecology 19, 3592–3602.
| Spurious correlations and inferences in landscape genetics.Crossref | GoogleScholarGoogle Scholar |
Diniz-Filho, J. A. F., and De Campos Telles, M. P. (2002). Spatial autocorrelation analysis and the identification of operational units for conservation in continuous populations. Conservation Biology 16, 924–935.
| Spatial autocorrelation analysis and the identification of operational units for conservation in continuous populations.Crossref | GoogleScholarGoogle Scholar |
Dyer, R. J., Nason, J. D., and Garrick, R. C. (2010). Landscape modelling of geneflow: improved power using conditional genetic distance derived from the topology of population networks. Molecular Ecology 19, 3746–3759.
| Landscape modelling of geneflow: improved power using conditional genetic distance derived from the topology of population networks.Crossref | GoogleScholarGoogle Scholar |
Foley, J. A., DeFries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter, S. R., Chapin, F. S., Coe, M. T., Daily, G. C., Gibbs, H. K., Helkowski, J. H., Holloway, T., Howard, E. A., Kucharik, C. J., Monfreda, C., Patz, J. A., Prentice, I. C., Ramankutty, N., and Snyder, P. K. (2005). Global consequences of land use. Science 309, 570–574.
| Global consequences of land use.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2MXmsFChtrs%3D&md5=b0d43545fdeffbb2e0619a8499013cc4CAS |
Frankham, R. (2010). Where are we in conservation genetics and where do we need to go? Conservation Genetics 11, 661–663.
| Where are we in conservation genetics and where do we need to go?Crossref | GoogleScholarGoogle Scholar |
Frankham, R., Ballou, J. D., and Briscoe, D. A. (2010). ‘Introduction to Conservation Genetics.’ 2nd edn. (Cambridge University Press: Cambridge, UK.)
Frankham, R., Ballou, J. D., Eldridge, M. D. B., Lacy, R. C., Ralls, K., Dudash, M. R., and Fenester, C. B. (2011). Predicting the probability of outbreeding depression. Conservation Biology 25, 465–475.
| Predicting the probability of outbreeding depression.Crossref | GoogleScholarGoogle Scholar |
Guillot, G., Leblois, R., Coulon, A., and Frantz, A. C. (2009). Statistical methods in spatial genetics. Molecular Ecology 18, 4734–4756.
| Statistical methods in spatial genetics.Crossref | GoogleScholarGoogle Scholar |
Jaquiéry, J., Broquet, T., Hirzel, A. H., Yearsley, J., and Perrin, N. (2011). Inferring landscape effects on dispersal from genetic distances: how far can we go? Molecular Ecology 20, 692–705.
| Inferring landscape effects on dispersal from genetic distances: how far can we go?Crossref | GoogleScholarGoogle Scholar |
Jombart, T., Dufour, A. B., and Pontier, D. (2008). Revealing cryptic spatial patterns in genetic variability by a new multivariate method. Heredity 101, 92–103.
| Revealing cryptic spatial patterns in genetic variability by a new multivariate method.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXnt1eis7g%3D&md5=f9d5262d4cfb89a217deccd8c726c27fCAS |
Jones, M. E., Paetkau, D., Geffen, E., and Moritz, C. (2004). Genetic diversity and population structure of Tasmanian devils, the largest marsupial carnivore. Molecular Ecology 13, 2197–2209.
| Genetic diversity and population structure of Tasmanian devils, the largest marsupial carnivore.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXmsl2rtbk%3D&md5=19875c28d676aa4b81b2bd7df08a254cCAS |
Lachish, S., Miller, K. J., Storfer, A., Goldizen, A. W., and Jones, M. E. (2011). Evidence that disease-induced population decline changes genetic structure and alters dispersal patterns in the Tasmanian devil. Heredity 106, 172–182.
| Evidence that disease-induced population decline changes genetic structure and alters dispersal patterns in the Tasmanian devil.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC3M%2Fislehtg%3D%3D&md5=06ad4b3c139160cbc5f106b76a12851aCAS |
Laikre, L. (2010). Genetic diversity is overlooked in international policy implementation. Conservation Genetics 11, 349–354.
| Genetic diversity is overlooked in international policy implementation.Crossref | GoogleScholarGoogle Scholar |
Landguth, E. L., Cushman, S. A., Schwartz, M. K., McKelvey, K. S., Murphy, M., and Luikart, G. (2010). Quantifying the lag time to detect barriers in landscape genetics. Molecular Ecology 19, 4179–4191.
| Quantifying the lag time to detect barriers in landscape genetics.Crossref | GoogleScholarGoogle Scholar |
Lowe, W. H., and Allendorf, F. W. (2010). What can genetics tell us about population connectivity? Molecular Ecology 19, 3038–3051.
| What can genetics tell us about population connectivity?Crossref | GoogleScholarGoogle Scholar |
Manel, S., Gaggiotti, O. E., and Waples, R. S. (2005). Assignment methods: matching biological questions with appropriate techniques. Trends in Ecology & Evolution 20, 136–142.
| Assignment methods: matching biological questions with appropriate techniques.Crossref | GoogleScholarGoogle Scholar |
Moritz, C. (2002). Strategies to protect biological diversity and the evolutionary processes that sustain it. Systematic Biology 51, 238–254.
| Strategies to protect biological diversity and the evolutionary processes that sustain it.Crossref | GoogleScholarGoogle Scholar |
Moyle, L. C., Stinchcombe, J. R., Hudgens, B. R., and Morris, W. F. (2003). Conservation genetics in the recovery of endangered animal species: a review of US endangered species recovery plans (1977–1998). Animal Biodiversity and Conservation 26, 85–95.
Murphy, M. A., Evans, J. S., Cushman, S., and Storfer, A. (2008). Representing genetic variation as continuous surfaces: an approach for identifying spatial dependency in landscape genetic studies. Ecography 31, 685–697.
| Representing genetic variation as continuous surfaces: an approach for identifying spatial dependency in landscape genetic studies.Crossref | GoogleScholarGoogle Scholar |
Pritchard, J. K., Stephens, M., and Donnelly, P. (2000). Inference of population structure using multilocus genotype data. Genetics 155, 945–959.
| 1:STN:280:DC%2BD3cvislKrtA%3D%3D&md5=97b0a0ccf9f60fe6bcc1047c2001a240CAS |
Pullin, A. S., and Stewart, G. B. (2006). Guidelines for systematic review in conservation and environmental management. Conservation Biology 20, 1647–1656.
| Guidelines for systematic review in conservation and environmental management.Crossref | GoogleScholarGoogle Scholar |
Sarre, S. D., and Georges, A. (2009). Genetics in conservation and wildlife management: a revolution since Caughley. Wildlife Research 36, 70–80.
| Genetics in conservation and wildlife management: a revolution since Caughley.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXnsVWhuw%3D%3D&md5=8c3b355e5d70f038d1600c9352d6a814CAS |
Schwartz, M. K., and McKelvey, K. S. (2009). Why sampling scheme matters: the effect of sampling scheme on landscape genetic results. Conservation Genetics 10, 441–452.
| Why sampling scheme matters: the effect of sampling scheme on landscape genetic results.Crossref | GoogleScholarGoogle Scholar |
Simmons, J. M., Sunnucks, P., Taylor, A. C., and van der Ree, R. (2010). Beyond roadkill, radiotracking, recapture and FST – a review of some genetic methods to improve understanding of the influence of roads on wildlife. Ecology and Society 15, 9.
Storfer, A., Murphy, M. A., Spear, S. F., Holderegger, R., and Waits, L. P. (2010). Landscape genetics: where are we now? Molecular Ecology 19, 3496–3514.
| Landscape genetics: where are we now?Crossref | GoogleScholarGoogle Scholar |
Stow, A. J., and Sunnucks, P. (2004). High mate and site fidelity in Cunningham’s skinks (Egernia cunninghami) in natural and fragmented habitat. Molecular Ecology 13, 419–430.
| High mate and site fidelity in Cunningham’s skinks (Egernia cunninghami) in natural and fragmented habitat.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD2c%2FitFCrtQ%3D%3D&md5=4db49f711c16de173928da07d22f7b57CAS |
Sunnucks, P. (2010). Towards modelling persistence of woodland birds: the role of genetics. Emu 1, 19–39.
Sunnucks, P., and Taylor, A. (2008). The application of genetic markers to landscape management. In ‘Landscape Management and Visualisation: Spatial Models for Natural Resource Management and Planning’. (Eds C. Pettit, W. Cartwright, I. Bishop, K. Lowell, D. Pullar and D. Duncan.) pp. 211–234. (Springer: Berlin.)
Sutherland, W. J., Pullin, A. S., Dolman, P. M., and Knight, T. M. (2004). The need for evidence-based conservation. Trends in Ecology & Evolution 19, 305–308.
| The need for evidence-based conservation.Crossref | GoogleScholarGoogle Scholar |
Taylor, B. L., and Dizon, A. E. (1999). First policy then science: why a management unit based soley on genetic criteria cannot work. Molecular Ecology 8, S11–S16.
| First policy then science: why a management unit based soley on genetic criteria cannot work.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3c7mvVWqsQ%3D%3D&md5=44b08930e72dffe55fae91ff6647604dCAS |
Waples, R. S., and Gaggiotti, O. (2006). What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity. Molecular Ecology 15, 1419–1439.
| What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28XlsVCjur4%3D&md5=2c6e24dd2772d1774a862f23b5ee64d4CAS |
Weeks, A. R., Sgro, C. M., Young, A. G., Frankham, R., Mitchell, N. J., Miller, K. A., Byrne, M., Coates, D. G., Eldridge, M. D. B., Sunnucks, P., Breed, M. F., James, E. A., and Hoffmann, A. A. (2011). Assessing the benefits and risks of translocations in changing environments: a genetic perspective. Evolutionary Applications 4, 709–725.
| Assessing the benefits and risks of translocations in changing environments: a genetic perspective.Crossref | GoogleScholarGoogle Scholar |
Wells, J. V., and Richmond, M. E. (1995). Populations, metapopulations, and species populations: what are they and who should care? Wildlife Society Bulletin 23, 458–462.
