301
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RASIC GORDANA, KEYGHOBADI NUSHA. From broadscale patterns to fine-scale processes: habitat structure influences genetic differentiation in the pitcher plant midge across multiple spatial scales. Mol Ecol 2011; 21:223-36. [DOI: 10.1111/j.1365-294x.2011.05280.x] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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302
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Microevolution of sympatry: landscape genetics of hedgehogs Erinaceus europaeus and E. roumanicus in Central Europe. Heredity (Edinb) 2011; 108:248-55. [PMID: 21863052 DOI: 10.1038/hdy.2011.67] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
We used the mitochondrial control region and nuclear microsatellites to assess the distribution patterns, population structure, demography and landscape genetics for the hedgehogs Erinaceus europaeus and Erinaceus roumanicus in a transect of the mid-European zone of sympatry. E. roumanicus was less frequent and restricted to regions with lower altitudes. Demographic analyses suggested recent population growth in this species. A comparison of patterns in the spatial variability of mitochondrial and nuclear DNA indicated less sex-biased dispersal and higher levels of gene flow in E. roumanicus. No evidence of recent hybridisation or introgression was detected. We interpreted these results by comparing with phylogeographic and palaeontological studies as well as with the occurrence of hybridisation in the Russian contact zone. We propose that Central Europe was colonised by E. roumanicus by the beginning of the Neolithic period and that there was a subsequent reinforcement stage as well as the formation of a zone of sympatry after the complete reproductive isolation of both species.
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303
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KANNO YOICHIRO, VOKOUN JASONC, LETCHER BENJAMINH. Fine-scale population structure and riverscape genetics of brook trout (Salvelinus fontinalis) distributed continuously along headwater channel networks. Mol Ecol 2011; 20:3711-29. [DOI: 10.1111/j.1365-294x.2011.05210.x] [Citation(s) in RCA: 97] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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304
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Lander T, Bebber D, Choy C, Harris S, Boshier D. The Circe Principle Explains How Resource-Rich Land Can Waylay Pollinators in Fragmented Landscapes. Curr Biol 2011; 21:1302-7. [DOI: 10.1016/j.cub.2011.06.045] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2010] [Revised: 04/15/2011] [Accepted: 06/17/2011] [Indexed: 11/26/2022]
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305
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Coastal pollution limits pelagic larval dispersal. Nat Commun 2011; 2:226. [PMID: 21407192 DOI: 10.1038/ncomms1238] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2010] [Accepted: 02/09/2011] [Indexed: 11/08/2022] Open
Abstract
The ecological impact of large coastal human populations on marine ecosystems remains relatively unknown. Here, we examine the population structure of Patiria miniata, the bat star, and correlate genetic distances with a model based on flow rates and proximity to P. miniata populations for the four major stormwater runoff and wastewater effluent sources of the Southern California Bight. We show that overall genetic connectivity is high (F(ST)~0.005); however, multivariate analyses show that genetic structure is highly correlated with anthropogenic inputs. The best models included both stormwater and wastewater variables and explained between 26.55 and 93.69% of the observed structure. Additionally, regressions between allelic richness and distance to sources show that populations near anthropogenic pollution have reduced genetic diversity. Our results indicate that anthropogenic runoff and effluent are acting as barriers to larval dispersal, effectively isolating a high gene flow species that is virtually free of direct human impact.
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306
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Marko PB, Hart MW. The complex analytical landscape of gene flow inference. Trends Ecol Evol 2011; 26:448-56. [PMID: 21722987 DOI: 10.1016/j.tree.2011.05.007] [Citation(s) in RCA: 117] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2011] [Revised: 04/29/2011] [Accepted: 05/17/2011] [Indexed: 11/25/2022]
Abstract
Gene flow estimation is essential for characterizing local adaptation, speciation potential and connectivity among threatened populations. New model-based population genetic methods can resolve complex demographic histories, but many studies in fields such as landscape genetics continue to rely on simple rules of thumb focused on gene flow to explain patterns of spatial differentiation. Here, we show how methods that use gene genealogies can reveal cryptic demographic histories and provide better estimates of gene flow with other parameters that contribute to genetic variation across landscapes and seascapes. We advocate for the expanded use and development of methods that consider spatial differentiation as the product of multiple forces interacting over time, and caution against a routine reliance on post-hoc gene flow interpretations.
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Affiliation(s)
- Peter B Marko
- Department of Biological Sciences, Clemson University, Clemson, SC 29634, USA.
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307
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Kirk H, Freeland JR. Applications and implications of neutral versus non-neutral markers in molecular ecology. Int J Mol Sci 2011; 12:3966-88. [PMID: 21747718 PMCID: PMC3131602 DOI: 10.3390/ijms12063966] [Citation(s) in RCA: 109] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2011] [Revised: 06/06/2011] [Accepted: 06/07/2011] [Indexed: 11/17/2022] Open
Abstract
The field of molecular ecology has expanded enormously in the past two decades, largely because of the growing ease with which neutral molecular genetic data can be obtained from virtually any taxonomic group. However, there is also a growing awareness that neutral molecular data can provide only partial insight into parameters such as genetic diversity, local adaptation, evolutionary potential, effective population size, and taxonomic designations. Here we review some of the applications of neutral versus adaptive markers in molecular ecology, discuss some of the advantages that can be obtained by supplementing studies of molecular ecology with data from non-neutral molecular markers, and summarize new methods that are enabling researchers to generate data from genes that are under selection.
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Affiliation(s)
- Heather Kirk
- Department of Biology, Trent University, Peterborough, Ontario K9J 7B8, Canada; E-Mail:
| | - Joanna R. Freeland
- Department of Biology, Trent University, Peterborough, Ontario K9J 7B8, Canada; E-Mail:
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308
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WANG IANJ. Choosing appropriate genetic markers and analytical methods for testing landscape genetic hypotheses. Mol Ecol 2011. [DOI: 10.1111/j.1365-294x.2011.05123.x] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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309
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Chan LM, Brown JL, Yoder AD. Integrating statistical genetic and geospatial methods brings new power to phylogeography. Mol Phylogenet Evol 2011; 59:523-37. [DOI: 10.1016/j.ympev.2011.01.020] [Citation(s) in RCA: 156] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2010] [Revised: 01/31/2011] [Accepted: 01/31/2011] [Indexed: 01/29/2023]
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310
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Crispo E, Moore JS, Lee-Yaw JA, Gray SM, Haller BC. Broken barriers: human-induced changes to gene flow and introgression in animals: an examination of the ways in which humans increase genetic exchange among populations and species and the consequences for biodiversity. Bioessays 2011; 33:508-18. [PMID: 21523794 DOI: 10.1002/bies.201000154] [Citation(s) in RCA: 141] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
We identify two processes by which humans increase genetic exchange among groups of individuals: by affecting the distribution of groups and dispersal patterns across a landscape, and by affecting interbreeding among sympatric or parapatric groups. Each of these processes might then have two different effects on biodiversity: changes in the number of taxa through merging or splitting of groups, and the extinction/extirpation of taxa through effects on fitness. We review the various ways in which humans are affecting genetic exchange, and highlight the difficulties in predicting the impacts on biodiversity. Gene flow and hybridization are crucially important evolutionary forces influencing biodiversity. Humans alter natural patterns of genetic exchange in myriad ways, and these anthropogenic effects are likely to influence the genetic integrity of populations and species. We argue that taking a gene-centric view towards conservation will help resolve issues pertaining to conservation and management. Editor's suggested further reading in BioEssays A systemic view of biodiversity and its conservation: Processes, interrelationships, and human culture Abstract.
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Affiliation(s)
- Erika Crispo
- Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada.
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311
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Zhang YX, He CZ, Dudgeon D, Zhang ZY, Wang GM. Mountain Ridge and Sea: Geographic-Barrier Effects on Genetic Diversity and Differentiation of the Hong Kong Newt (Paramesotriton hongkongensis) Revealed by AFLP. ANN ZOOL FENN 2011. [DOI: 10.5735/086.048.0204] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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312
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BALKENHOL NIKO, LANDGUTH ERINL. Simulation modelling in landscape genetics: on the need to go further. Mol Ecol 2011; 20:667-70. [DOI: 10.1111/j.1365-294x.2010.04967.x] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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313
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SHORT BULL RA, CUSHMAN SA, MACE R, CHILTON T, KENDALL KC, LANDGUTH EL, SCHWARTZ M, MCKELVEY K, ALLENDORF FREDW, LUIKART G. Why replication is important in landscape genetics: American black bear in the Rocky Mountains. Mol Ecol 2011; 20:1092-107. [DOI: 10.1111/j.1365-294x.2010.04944.x] [Citation(s) in RCA: 147] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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314
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315
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Jaquiéry J, Broquet T, Hirzel AH, Yearsley J, Perrin N. Inferring landscape effects on dispersal from genetic distances: how far can we go? Mol Ecol 2010; 20:692-705. [PMID: 21175906 DOI: 10.1111/j.1365-294x.2010.04966.x] [Citation(s) in RCA: 88] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Functional connectivity affects demography and gene dynamics in fragmented populations. Besides species-specific dispersal ability, the connectivity between local populations is affected by the landscape elements encountered during dispersal. Documenting these effects is thus a central issue for the conservation and management of fragmented populations. In this study, we compare the power and accuracy of three methods (partial correlations, regressions and Approximate Bayesian Computations) that use genetic distances to infer the effect of landscape upon dispersal. We use stochastic individual-based simulations of fragmented populations surrounded by landscape elements that differ in their permeability to dispersal. The power and accuracy of all three methods are good when there is a strong contrast between the permeability of different landscape elements. The power and accuracy can be further improved by restricting analyses to adjacent pairs of populations. Landscape elements that strongly impede dispersal are the easiest to identify. However, power and accuracy decrease drastically when landscape complexity increases and the contrast between the permeability of landscape elements decreases. We provide guidelines for future studies and underline the needs to evaluate or develop approaches that are more powerful.
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Affiliation(s)
- J Jaquiéry
- Department of Ecology and Evolution, University of Lausanne, CH-1015 Lausanne, Switzerland.
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316
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Holderegger R, Buehler D, Gugerli F, Manel S. Landscape genetics of plants. TRENDS IN PLANT SCIENCE 2010; 15:675-683. [PMID: 20940103 DOI: 10.1016/j.tplants.2010.09.002] [Citation(s) in RCA: 66] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2010] [Revised: 08/31/2010] [Accepted: 09/08/2010] [Indexed: 05/30/2023]
Abstract
Landscape genetics is the amalgamation of landscape ecology and population genetics to help with understanding microevolutionary processes such as gene flow and adaptation. In this review, we examine why landscape genetics of plants lags behind that of animals, both in number of studies and consideration of landscape elements. The classical landscape distance/resistance approach to study gene flow is challenging in plants, whereas boundary detection and the assessment of contemporary gene flow are more feasible. By contrast, the new field of landscape genetics of adaptive genetic variation, establishing the relationship between adaptive genomic regions and environmental factors in natural populations, is prominent in plant studies. Landscape genetics is ideally suited to study processes such as migration and adaptation under global change.
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Affiliation(s)
- Rolf Holderegger
- WSL Swiss Federal Research Institute, Zürcherstrasse 111, CH-8903 Birmensdorf, Switzerland.
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317
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Landguth EL, Cushman SA, Schwartz MK, McKelvey KS, Murphy M, Luikart G. Quantifying the lag time to detect barriers in landscape genetics. Mol Ecol 2010; 19:4179-91. [PMID: 20819159 DOI: 10.1111/j.1365-294x.2010.04808.x] [Citation(s) in RCA: 265] [Impact Index Per Article: 18.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Understanding how spatial genetic patterns respond to landscape change is crucial for advancing the emerging field of landscape genetics. We quantified the number of generations for new landscape barrier signatures to become detectable and for old signatures to disappear after barrier removal. We used spatially explicit, individual-based simulations to examine the ability of an individual-based statistic [Mantel's r using the proportion of shared alleles' statistic (Dps)] and population-based statistic (FST ) to detect barriers. We simulated a range of movement strategies including nearest neighbour dispersal, long-distance dispersal and panmixia. The lag time for the signal of a new barrier to become established is short using Mantel's r (1-15 generations). FST required approximately 200 generations to reach 50% of its equilibrium maximum, although G'ST performed much like Mantel's r. In strong contrast, FST and Mantel's r perform similarly following the removal of a barrier formerly dividing a population. Also, given neighbour mating and very short-distance dispersal strategies, historical discontinuities from more than 100 generations ago might still be detectable with either method. This suggests that historical events and landscapes could have long-term effects that confound inferences about the impacts of current landscape features on gene flow for species with very little long-distance dispersal. Nonetheless, populations of organisms with relatively large dispersal distances will lose the signal of a former barrier within less than 15 generations, suggesting that individual-based landscape genetic approaches can improve our ability to measure effects of existing landscape features on genetic structure and connectivity.
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Affiliation(s)
- E L Landguth
- University of Montana, Mathematics Building, Missoula, MT, 59812, USAUSDA Forest Service, Rocky Mountain Research Station, 800 E Beckwith Ave., Missoula, MT 59801, USAColorado State University, Biology Department, Fort Collins, CO 80523-1878 USAFlathead Lake Biological Station, Division of Biological Sciences, University of Montana, Polson, MT 59860, USACentro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto (CIBIO-UP), Campus Agrário de Vairão, 4485-661 Vairão, Portugal
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318
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ANDERSON COREYDEVIN, EPPERSON BRYANK, FORTIN MARIEJOSÉE, HOLDEREGGER ROLF, JAMES PATRICKMA, ROSENBERG MICHAELS, SCRIBNER KIMT, SPEAR STEPHEN. Considering spatial and temporal scale in landscape-genetic studies of gene flow. Mol Ecol 2010; 19:3565-75. [DOI: 10.1111/j.1365-294x.2010.04757.x] [Citation(s) in RCA: 308] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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319
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Sork VL, Waits L. Contributions of landscape genetics - approaches, insights, and future potential. Mol Ecol 2010; 19:3489-95. [PMID: 20723050 DOI: 10.1111/j.1365-294x.2010.04786.x] [Citation(s) in RCA: 99] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- Victoria L Sork
- Department of Ecology and Evolutionary Biology and Institute of the Environment, University of California Los Angeles, Los Angeles, CA 90095-1606, USA.
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320
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Spear SF, Balkenhol N, Fortin MJ, McRae BH, Scribner K. Use of resistance surfaces for landscape genetic studies: considerations for parameterization and analysis. Mol Ecol 2010; 19:3576-91. [PMID: 20723064 DOI: 10.1111/j.1365-294x.2010.04657.x] [Citation(s) in RCA: 323] [Impact Index Per Article: 23.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Measures of genetic structure among individuals or populations collected at different spatial locations across a landscape are commonly used as surrogate measures of functional (i.e. demographic or genetic) connectivity. In order to understand how landscape characteristics influence functional connectivity, resistance surfaces are typically created in a raster GIS environment. These resistance surfaces represent hypothesized relationships between landscape features and gene flow, and are based on underlying biological functions such as relative abundance or movement probabilities in different land cover types. The biggest challenge for calculating resistance surfaces is assignment of resistance values to different landscape features. Here, we first identify study objectives that are consistent with the use of resistance surfaces and critically review the various approaches that have been used to parameterize resistance surfaces and select optimal models in landscape genetics. We then discuss the biological assumptions and considerations that influence analyses using resistance surfaces, such as the relationship between gene flow and dispersal, how habitat suitability may influence animal movement, and how resistance surfaces can be translated into estimates of functional landscape connectivity. Finally, we outline novel approaches for creating optimal resistance surfaces using either simulation or computational methods, as well as alternatives to resistance surfaces (e.g. network and buffered paths). These approaches have the potential to improve landscape genetic analyses, but they also create new challenges. We conclude that no single way of using resistance surfaces is appropriate for every situation. We suggest that researchers carefully consider objectives, important biological assumptions and available parameterization and validation techniques when planning landscape genetic studies.
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Affiliation(s)
- Stephen F Spear
- Project Orianne: The Indigo Snake Initiative, Clayton, GA 30525, USA.
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321
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EPPERSON BRYANK, MCRAE BRADH, SCRIBNER KIM, CUSHMAN SAMUELA, ROSENBERG MICHAELS, FORTIN MARIEJOSÉE, JAMES PATRICKMA, MURPHY MELANIE, MANEL STÉPHANIE, LEGENDRE PIERRE, DALE MARKRT. Utility of computer simulations in landscape genetics. Mol Ecol 2010; 19:3549-64. [DOI: 10.1111/j.1365-294x.2010.04678.x] [Citation(s) in RCA: 151] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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322
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Epperson BK. Spatial correlations at different spatial scales are themselves highly correlated in isolation by distance processes. Mol Ecol Resour 2010; 10:845-53. [PMID: 21565095 DOI: 10.1111/j.1755-0998.2010.02886.x] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Although many properties of spatial autocorrelation statistics are well characterized, virtually nothing is known about possible correlations among values at different spatial scales, which ultimately would influence how inferences about spatial genetics are made at multiple spatial scales. This article reports the results of stochastic space-time simulations of isolation by distance processes, having a very wide range of amounts of dispersal for plants or animals, and analyses of the correlations among Moran's I-statistics for different mutually exclusive distance classes. In general, the stochastic correlations are extremely large (>0.90); however, the correlations bear a complex relationship with level of dispersal, spatial scale and spatial lag between distance classes. The correlations are so large that any existing or conceived statistical method that employs more than one distance class (or spatial scale) should not ignore them. This result also suggests that gains in statistical power via increasing sample size are limited, and that increasing numbers of assayed loci generally should be preferred. To the extent that sampling error for real data sets can be treated as white noise, it should be possible to account for stochastic correlations in formulating more precise statistical methods. Further, while the current results are for isolation by distance processes, they provide some guidance for some more complex stochastic space-time processes of landscape genetics. Moreover, the results hold for several popular measures other than Moran's I. In addition, in the results, the signal to noise ratios strongly decreased with distance, which also has several implications for optimal statistical methods using correlations at multiple spatial scales.
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323
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Segelbacher G, Cushman SA, Epperson BK, Fortin MJ, Francois O, Hardy OJ, Holderegger R, Taberlet P, Waits LP, Manel S. Applications of landscape genetics in conservation biology: concepts and challenges. CONSERV GENET 2010. [DOI: 10.1007/s10592-009-0044-5] [Citation(s) in RCA: 165] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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