Contrasting support for alternative models of genomic variation based on microhabitat preference: species‐specific effects of climate change in alpine sedges

Deterministic processes may uniquely affect codistributed species’ phylogeographic patterns such that discordant genetic variation among taxa is predicted. Yet, explicitly testing expectations of genomic discordance in a statistical framework remains challenging. Here, we construct spatially and tem...

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Published in:Molecular Ecology
Main Authors: Massatti, Rob, Knowles, L. Lacey
Format: Article in Journal/Newspaper
Language:unknown
Published: Elsevier 2016
Subjects:
glaciation
Pleistocene
Rocky Mountains
Cyperaceae
Carex
Ecology and Evolutionary Biology
Science
Arctic
Online Access:https://hdl.handle.net/2027.42/134290
https://doi.org/10.1111/mec.13735
id ftumdeepblue:oai:deepblue.lib.umich.edu:2027.42/134290
record_format openpolar
institution Open Polar
collection University of Michigan: Deep Blue
op_collection_id ftumdeepblue
language unknown
topic glaciation
Pleistocene
Rocky Mountains
Cyperaceae
Carex
Ecology and Evolutionary Biology
Science
spellingShingle glaciation
Pleistocene
Rocky Mountains
Cyperaceae
Carex
Ecology and Evolutionary Biology
Science
Massatti, Rob
Knowles, L. Lacey
Contrasting support for alternative models of genomic variation based on microhabitat preference: species‐specific effects of climate change in alpine sedges
topic_facet glaciation
Pleistocene
Rocky Mountains
Cyperaceae
Carex
Ecology and Evolutionary Biology
Science
description Deterministic processes may uniquely affect codistributed species’ phylogeographic patterns such that discordant genetic variation among taxa is predicted. Yet, explicitly testing expectations of genomic discordance in a statistical framework remains challenging. Here, we construct spatially and temporally dynamic models to investigate the hypothesized effect of microhabitat preferences on the permeability of glaciated regions to gene flow in two closely related montane species. Utilizing environmental niche models from the Last Glacial Maximum and the present to inform demographic models of changes in habitat suitability over time, we evaluate the relative probabilities of two alternative models using approximate Bayesian computation (ABC) in which glaciated regions are either (i) permeable or (ii) a barrier to gene flow. Results based on the fit of the empirical data to data sets simulated using a spatially explicit coalescent under alternative models indicate that genomic data are consistent with predictions about the hypothesized role of microhabitat in generating discordant patterns of genetic variation among the taxa. Specifically, a model in which glaciated areas acted as a barrier was much more probable based on patterns of genomic variation in Carex nova, a wet‐adapted species. However, in the dry‐adapted Carex chalciolepis, the permeable model was more probable, although the difference in the support of the models was small. This work highlights how statistical inferences can be used to distinguish deterministic processes that are expected to result in discordant genomic patterns among species, including species‐specific responses to climate change. Peer Reviewed http://deepblue.lib.umich.edu/bitstream/2027.42/134290/1/mec13735.pdf http://deepblue.lib.umich.edu/bitstream/2027.42/134290/2/mec13735_am.pdf http://deepblue.lib.umich.edu/bitstream/2027.42/134290/3/mec13735-sup-0001-SupInfo.pdf
format Article in Journal/Newspaper
author Massatti, Rob
Knowles, L. Lacey
author_facet Massatti, Rob
Knowles, L. Lacey
author_sort Massatti, Rob
title Contrasting support for alternative models of genomic variation based on microhabitat preference: species‐specific effects of climate change in alpine sedges
title_short Contrasting support for alternative models of genomic variation based on microhabitat preference: species‐specific effects of climate change in alpine sedges
title_full Contrasting support for alternative models of genomic variation based on microhabitat preference: species‐specific effects of climate change in alpine sedges
title_fullStr Contrasting support for alternative models of genomic variation based on microhabitat preference: species‐specific effects of climate change in alpine sedges
title_full_unstemmed Contrasting support for alternative models of genomic variation based on microhabitat preference: species‐specific effects of climate change in alpine sedges
title_sort contrasting support for alternative models of genomic variation based on microhabitat preference: species‐specific effects of climate change in alpine sedges
publisher Elsevier
publishDate 2016
url https://hdl.handle.net/2027.42/134290
https://doi.org/10.1111/mec.13735
genre Arctic
genre_facet Arctic
op_relation Massatti, Rob; Knowles, L. Lacey (2016). "Contrasting support for alternative models of genomic variation based on microhabitat preference: species‐specific effects of climate change in alpine sedges." Molecular Ecology 25(16): 3974-3986.
0962-1083
1365-294X
https://hdl.handle.net/2027.42/134290
doi:10.1111/mec.13735
Molecular Ecology
O’Meara BC, Jackson ND, Morales‐Garcia AE, Carstens BC ( 2015 ) Phylogeographic inference using approximate likelihoods. bioRxiv. doi:10.1101/025353.
Morgan K, O’Loughlin SM, Chen B et al. ( 2011 ) Comparative phylogeography reveals a shared impact of Pleistocene environmental change in shaping genetic diversity within nine Anopheles mosquito species across the Indo‐Burma biodiversity hotspot. Molecular Ecology, 20, 4533 – 4549.
Neuenschwander S, Largiader CR, Ray N et al. ( 2008 ) Colonization history of the Swiss Rhine basin by the bullhead ( Cottus gobio ): inference under a Bayesian spatially explicit framework. Molecular Ecology, 17, 757 – 772.
Nielsen R, Beaumont MA ( 2009 ) Statistical inferences in phylogeography. Molecular Ecology, 18, 1034 – 1047.
Oaks JR, Sukumaran J, Esselstyn JA et al. ( 2013 ) Evidence for climate‐driven diversification? A caution for interpreting ABC inferences of simultaneous historical events. Evolution, 67, 991 – 1010.
Papadopoulou A, Knowles LL ( 2015a ) Genomic tests of the species‐pump hypothesis: recent island connectivity cycles drive population divergence but not speciation in Caribbean crickets across the Virgin Islands. Evolution, 69, 1501 – 1517.
Papadopoulou A, Knowles LL ( 2015b ) Species‐specific responses to island connectivity cycles: refined models for testing phylogenetic concordance across a Mediterranean Pleistocene Aggregate Island Complex. Molecular Ecology, 24, 4252 – 4268.
Papadopoulou A, Knowles LL ( 2016 ) Refined hypotheses based on taxon‐specific traits in comparative phylogeography. Proceedings of the National Academy of Sciences of the USA, in press.
Pelletier TA, Carstens BC ( 2014 ) Model choice in phylogeography using a large set of models. Molecular Ecology, 23, 3028 – 3043.
Peterson BK, Weber JN, Kay EH, Fisher HS, Hoekstra HE ( 2012 ) Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non‐model species. PLoS One, 7, e37135.
Phillips SJ, Anderson RP, Schapire RE ( 2006 ) Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231 – 259.
Pritchard JK, Seielstad MT, Perez‐Lezaun A, Feldman MW ( 1999 ) Population growth of human Y chromosomes: a study of Y chromosome microsatellites. Molecular Biology and Evolution, 16, 1791 – 1798.
R Core Team ( 2014 ) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
Ray N, Currat M, Foll M, Excoffier L ( 2010 ) splatche 2: a spatially explicit simulation framework for complex demography, genetic admixture and recombination. Bioinformatics, 26, 2993 – 2994.
Shirk AJ, Cushman SA, Landguth EL ( 2012 ) Simulating pattern‐process relationships to validate landscape genetic models. International Journal of Ecology, 2012, 539109.
Slatkin M ( 1993 ) Isolation by distance in equilibrium and non‐equilibrium populations. Evolution, 47, 264 – 279.
Wachter GA, Papadopoulou A, Muster C et al. ( 2016 ) Glacial refugia, recolonisation patterns, and diversification forces in Alpine‐endemic Megabunus harvestmen. Molecular Ecology, 25, 2904 – 2919.
Wegmann D, Currat M, Excoffier L ( 2006 ) Molecular diversity after a range expansion in heterogeneous environments. Genetics, 174, 2009 – 2020.
Wegmann D, Leuenberger C, Neuenschwander S, Excoffier L ( 2010 ) ABCtoolbox: a versatile toolkit for approximate Bayesian computations. BMC Bioinformatics, 11, 7.
Weir BS, Cockerham CC ( 1984 ) Estimating F‐statistics for the analysis of population structure. Evolution, 38, 1358 – 1370.
Westergaard KB, Alsos IG, Popp M et al. ( 2011 ) Glacial survival may matter after all: nunatak signatures in the rare European populations of two west‐arctic species. Molecular Ecology, 20, 376 – 393.
Alexander JM, Diez JM, Levine JM ( 2016 ) Novel competitors shape species’ responses to climate change. Nature, 525, 515 – 518.
Avise JC, Walker D, Johns GC ( 1998 ) Speciation durations and Pleistocene effects on vertebrate phylogeography. Proceedings of the Royal Society B: Biological Sciences, 265, 1707 – 1712.
Beaumont MA, Zhang WY, Balding DJ ( 2002 ) Approximate Bayesian computation in population genetics. Genetics, 162, 2025 – 2035.
Bertorelle G, Benazzo A, Mona S ( 2010 ) ABC as a flexible framework to estimate demography over space and time: some cons, many pros. Molecular Ecology, 19, 2609 – 2625.
Boulesteix A‐L, Strimmer K ( 2007 ) Partial least squares: a versatile tool for the analysis of high‐dimensional genomic data. Briefings in Bioinformatics, 8, 32 – 44.
Box GEP, Cox DR ( 1964 ) An analysis of transformations. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 26, 211 – 252.
Braconnot P, Otto‐Bliesner B, Harrison S et al. ( 2007 ) Results of PMIP2 coupled simulations of the Mid‐Holocene and Last Glacial Maximum‐Part 1: experiments and large‐scale features. Climate of the Past, 3, 261 – 277.
Brown JL, Knowles LL ( 2012 ) Spatially explicit models of dynamic histories: examination of the genetic consequences of Pleistocene glaciation and recent climate change on the American Pika. Molecular Ecology, 21, 3757 – 3775.
Bruggeman DJ, Wiegand T, Fernandez N ( 2010 ) The relative effects of habitat loss and fragmentation on population genetic variation in the red‐cockaded woodpecker ( Picoides borealis ). Molecular Ecology, 19, 3679 – 3691.
Carstens BC, Knowles LL ( 2007 ) Estimating species phylogeny from gene‐tree probabilities despite incomplete lineage sorting: an example from Melanoplus grasshoppers. Systematic Biology, 56, 400 – 411.
Catchen JM, Amores A, Hohenlohe P, Cresko W, Postlethwait JH ( 2011 ) Stacks: building and genotyping loci de novo from short‐read sequences. G3 Genes, Genomes, Genetics, 1, 171 – 182.
Catchen J, Hohenlohe P, Bassham S, Amores A, Cresko WA ( 2013 ) Stacks: an analysis tool set for population genomics. Molecular Ecology, 22, 3124 – 3140.
Cook SR, Gelman A, Rubin DB ( 2006 ) Validation of software for Bayesian models using posterior quantiles. Journal of Computational and Graphical Statistics, 15, 675 – 692.
Csillery K, Blum MGB, Gaggiotti OE, Francois O ( 2010 ) Approximate Bayesian computation (ABC) in practice. Trends in Ecology & Evolution, 25, 410 – 418.
Currat M, Excoffier L ( 2004 ) Modern humans did not admix with Neanderthals during their range expansion into Europe. PLoS Biology, 2, 2264 – 2274.
Currat M, Ray N, Excoffier L ( 2004 ) SPLATCHE: a program to simulate genetic diversity taking into account environmental heterogeneity. Molecular Ecology Notes, 4, 139 – 142.
Ehlers J, Gibbard PL (eds.) ( 2004 ) Quaternary Glaciations – Extent and Chronology II: North America. Elsevier, London, UK.
Epperson BK, McRae BH, Scribner K et al. ( 2010 ) Utility of computer simulations in landscape genetics. Molecular Ecology, 19, 3549 – 3564.
Excoffier L, Lischer HEL ( 2010 ) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resources, 10, 564 – 567.
Excoffier L, Novembre J, Schneider S ( 2000 ) SIMCOAL: a general coalescent program for the simulation of molecular data in interconnected populations with arbitrary demography. Journal of Heredity, 91, 506 – 509.
Excoffier L, Dupanloup I, Huerta‐Sanchez E et al. ( 2013 ) Robust demographic inference from genomic and SNP data. PLoS Genetics, 9, e1003905.
Grummer JA, Calderón‐Espinosa ML, Nieto‐Montes de Oca A et al. ( 2015 ) Estimating the temporal and spatial extent of gene flow among sympatric lizard populations (genus Sceloporus ) in the southern Mexican highlands. Molecular Ecology, 24, 1523 – 1542.
He Q, Edwards DL, Knowles LL ( 2013 ) Integrative testing of how environments from the past to the present shape genetic structure across landscapes. Evolution, 67, 3386 – 3402.
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container_title Molecular Ecology
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spelling ftumdeepblue:oai:deepblue.lib.umich.edu:2027.42/134290 2023-08-20T04:03:11+02:00 Contrasting support for alternative models of genomic variation based on microhabitat preference: species‐specific effects of climate change in alpine sedges Massatti, Rob Knowles, L. Lacey 2016-08 application/pdf https://hdl.handle.net/2027.42/134290 https://doi.org/10.1111/mec.13735 unknown Elsevier Wiley Periodicals, Inc. Massatti, Rob; Knowles, L. Lacey (2016). "Contrasting support for alternative models of genomic variation based on microhabitat preference: species‐specific effects of climate change in alpine sedges." Molecular Ecology 25(16): 3974-3986. 0962-1083 1365-294X https://hdl.handle.net/2027.42/134290 doi:10.1111/mec.13735 Molecular Ecology O’Meara BC, Jackson ND, Morales‐Garcia AE, Carstens BC ( 2015 ) Phylogeographic inference using approximate likelihoods. bioRxiv. doi:10.1101/025353. Morgan K, O’Loughlin SM, Chen B et al. ( 2011 ) Comparative phylogeography reveals a shared impact of Pleistocene environmental change in shaping genetic diversity within nine Anopheles mosquito species across the Indo‐Burma biodiversity hotspot. Molecular Ecology, 20, 4533 – 4549. Neuenschwander S, Largiader CR, Ray N et al. ( 2008 ) Colonization history of the Swiss Rhine basin by the bullhead ( Cottus gobio ): inference under a Bayesian spatially explicit framework. Molecular Ecology, 17, 757 – 772. Nielsen R, Beaumont MA ( 2009 ) Statistical inferences in phylogeography. Molecular Ecology, 18, 1034 – 1047. Oaks JR, Sukumaran J, Esselstyn JA et al. ( 2013 ) Evidence for climate‐driven diversification? A caution for interpreting ABC inferences of simultaneous historical events. Evolution, 67, 991 – 1010. Papadopoulou A, Knowles LL ( 2015a ) Genomic tests of the species‐pump hypothesis: recent island connectivity cycles drive population divergence but not speciation in Caribbean crickets across the Virgin Islands. Evolution, 69, 1501 – 1517. Papadopoulou A, Knowles LL ( 2015b ) Species‐specific responses to island connectivity cycles: refined models for testing phylogenetic concordance across a Mediterranean Pleistocene Aggregate Island Complex. Molecular Ecology, 24, 4252 – 4268. Papadopoulou A, Knowles LL ( 2016 ) Refined hypotheses based on taxon‐specific traits in comparative phylogeography. Proceedings of the National Academy of Sciences of the USA, in press. Pelletier TA, Carstens BC ( 2014 ) Model choice in phylogeography using a large set of models. Molecular Ecology, 23, 3028 – 3043. Peterson BK, Weber JN, Kay EH, Fisher HS, Hoekstra HE ( 2012 ) Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non‐model species. PLoS One, 7, e37135. Phillips SJ, Anderson RP, Schapire RE ( 2006 ) Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231 – 259. Pritchard JK, Seielstad MT, Perez‐Lezaun A, Feldman MW ( 1999 ) Population growth of human Y chromosomes: a study of Y chromosome microsatellites. Molecular Biology and Evolution, 16, 1791 – 1798. R Core Team ( 2014 ) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Ray N, Currat M, Foll M, Excoffier L ( 2010 ) splatche 2: a spatially explicit simulation framework for complex demography, genetic admixture and recombination. Bioinformatics, 26, 2993 – 2994. Shirk AJ, Cushman SA, Landguth EL ( 2012 ) Simulating pattern‐process relationships to validate landscape genetic models. International Journal of Ecology, 2012, 539109. Slatkin M ( 1993 ) Isolation by distance in equilibrium and non‐equilibrium populations. Evolution, 47, 264 – 279. Wachter GA, Papadopoulou A, Muster C et al. ( 2016 ) Glacial refugia, recolonisation patterns, and diversification forces in Alpine‐endemic Megabunus harvestmen. Molecular Ecology, 25, 2904 – 2919. Wegmann D, Currat M, Excoffier L ( 2006 ) Molecular diversity after a range expansion in heterogeneous environments. Genetics, 174, 2009 – 2020. Wegmann D, Leuenberger C, Neuenschwander S, Excoffier L ( 2010 ) ABCtoolbox: a versatile toolkit for approximate Bayesian computations. BMC Bioinformatics, 11, 7. Weir BS, Cockerham CC ( 1984 ) Estimating F‐statistics for the analysis of population structure. Evolution, 38, 1358 – 1370. Westergaard KB, Alsos IG, Popp M et al. ( 2011 ) Glacial survival may matter after all: nunatak signatures in the rare European populations of two west‐arctic species. Molecular Ecology, 20, 376 – 393. Alexander JM, Diez JM, Levine JM ( 2016 ) Novel competitors shape species’ responses to climate change. Nature, 525, 515 – 518. Avise JC, Walker D, Johns GC ( 1998 ) Speciation durations and Pleistocene effects on vertebrate phylogeography. Proceedings of the Royal Society B: Biological Sciences, 265, 1707 – 1712. Beaumont MA, Zhang WY, Balding DJ ( 2002 ) Approximate Bayesian computation in population genetics. Genetics, 162, 2025 – 2035. Bertorelle G, Benazzo A, Mona S ( 2010 ) ABC as a flexible framework to estimate demography over space and time: some cons, many pros. Molecular Ecology, 19, 2609 – 2625. Boulesteix A‐L, Strimmer K ( 2007 ) Partial least squares: a versatile tool for the analysis of high‐dimensional genomic data. Briefings in Bioinformatics, 8, 32 – 44. Box GEP, Cox DR ( 1964 ) An analysis of transformations. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 26, 211 – 252. Braconnot P, Otto‐Bliesner B, Harrison S et al. ( 2007 ) Results of PMIP2 coupled simulations of the Mid‐Holocene and Last Glacial Maximum‐Part 1: experiments and large‐scale features. Climate of the Past, 3, 261 – 277. Brown JL, Knowles LL ( 2012 ) Spatially explicit models of dynamic histories: examination of the genetic consequences of Pleistocene glaciation and recent climate change on the American Pika. Molecular Ecology, 21, 3757 – 3775. Bruggeman DJ, Wiegand T, Fernandez N ( 2010 ) The relative effects of habitat loss and fragmentation on population genetic variation in the red‐cockaded woodpecker ( Picoides borealis ). Molecular Ecology, 19, 3679 – 3691. Carstens BC, Knowles LL ( 2007 ) Estimating species phylogeny from gene‐tree probabilities despite incomplete lineage sorting: an example from Melanoplus grasshoppers. Systematic Biology, 56, 400 – 411. Catchen JM, Amores A, Hohenlohe P, Cresko W, Postlethwait JH ( 2011 ) Stacks: building and genotyping loci de novo from short‐read sequences. G3 Genes, Genomes, Genetics, 1, 171 – 182. Catchen J, Hohenlohe P, Bassham S, Amores A, Cresko WA ( 2013 ) Stacks: an analysis tool set for population genomics. Molecular Ecology, 22, 3124 – 3140. Cook SR, Gelman A, Rubin DB ( 2006 ) Validation of software for Bayesian models using posterior quantiles. Journal of Computational and Graphical Statistics, 15, 675 – 692. Csillery K, Blum MGB, Gaggiotti OE, Francois O ( 2010 ) Approximate Bayesian computation (ABC) in practice. Trends in Ecology & Evolution, 25, 410 – 418. Currat M, Excoffier L ( 2004 ) Modern humans did not admix with Neanderthals during their range expansion into Europe. PLoS Biology, 2, 2264 – 2274. Currat M, Ray N, Excoffier L ( 2004 ) SPLATCHE: a program to simulate genetic diversity taking into account environmental heterogeneity. Molecular Ecology Notes, 4, 139 – 142. Ehlers J, Gibbard PL (eds.) ( 2004 ) Quaternary Glaciations – Extent and Chronology II: North America. Elsevier, London, UK. Epperson BK, McRae BH, Scribner K et al. ( 2010 ) Utility of computer simulations in landscape genetics. Molecular Ecology, 19, 3549 – 3564. Excoffier L, Lischer HEL ( 2010 ) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resources, 10, 564 – 567. Excoffier L, Novembre J, Schneider S ( 2000 ) SIMCOAL: a general coalescent program for the simulation of molecular data in interconnected populations with arbitrary demography. Journal of Heredity, 91, 506 – 509. Excoffier L, Dupanloup I, Huerta‐Sanchez E et al. ( 2013 ) Robust demographic inference from genomic and SNP data. PLoS Genetics, 9, e1003905. Grummer JA, Calderón‐Espinosa ML, Nieto‐Montes de Oca A et al. ( 2015 ) Estimating the temporal and spatial extent of gene flow among sympatric lizard populations (genus Sceloporus ) in the southern Mexican highlands. Molecular Ecology, 24, 1523 – 1542. He Q, Edwards DL, Knowles LL ( 2013 ) Integrative testing of how environments from the past to the present shape genetic structure across landscapes. Evolution, 67, 3386 – 3402. IndexNoFollow glaciation Pleistocene Rocky Mountains Cyperaceae Carex Ecology and Evolutionary Biology Science Article 2016 ftumdeepblue https://doi.org/10.1111/mec.1373510.1101/02535310.1093/sysbio/syu046 2023-07-31T21:21:03Z Deterministic processes may uniquely affect codistributed species’ phylogeographic patterns such that discordant genetic variation among taxa is predicted. Yet, explicitly testing expectations of genomic discordance in a statistical framework remains challenging. Here, we construct spatially and temporally dynamic models to investigate the hypothesized effect of microhabitat preferences on the permeability of glaciated regions to gene flow in two closely related montane species. Utilizing environmental niche models from the Last Glacial Maximum and the present to inform demographic models of changes in habitat suitability over time, we evaluate the relative probabilities of two alternative models using approximate Bayesian computation (ABC) in which glaciated regions are either (i) permeable or (ii) a barrier to gene flow. Results based on the fit of the empirical data to data sets simulated using a spatially explicit coalescent under alternative models indicate that genomic data are consistent with predictions about the hypothesized role of microhabitat in generating discordant patterns of genetic variation among the taxa. Specifically, a model in which glaciated areas acted as a barrier was much more probable based on patterns of genomic variation in Carex nova, a wet‐adapted species. However, in the dry‐adapted Carex chalciolepis, the permeable model was more probable, although the difference in the support of the models was small. This work highlights how statistical inferences can be used to distinguish deterministic processes that are expected to result in discordant genomic patterns among species, including species‐specific responses to climate change. Peer Reviewed http://deepblue.lib.umich.edu/bitstream/2027.42/134290/1/mec13735.pdf http://deepblue.lib.umich.edu/bitstream/2027.42/134290/2/mec13735_am.pdf http://deepblue.lib.umich.edu/bitstream/2027.42/134290/3/mec13735-sup-0001-SupInfo.pdf Article in Journal/Newspaper Arctic University of Michigan: Deep Blue Molecular Ecology 25 16 3974 3986

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