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Schrey AW, Ragsdale AK, McCoy ED, Mushinsky HR. Repeated Habitat Disturbances by Fire Decrease Local Effective Population Size. J Hered 2016; 107:336-41. [PMID: 26976940 DOI: 10.1093/jhered/esw016] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2015] [Accepted: 03/09/2016] [Indexed: 01/12/2023] Open
Abstract
Effective population size is a fundamental parameter in population genetics, and factors that alter effective population size will shape the genetic characteristics of populations. Habitat disturbance may have a large effect on genetic characteristics of populations by influencing immigration and gene flow, particularly in fragmented habitats. We used the Florida Sand Skink (Plestiodon reynoldsi) to investigate the effect of fire-based habitat disturbances on the effective population size in the highly threatened, severely fragmented, and fire dependent Florida scrub habitat. We screened 7 microsatellite loci in 604 individuals collected from 12 locations at Archbold Biological Station. Archbold Biological Station has an active fire management plan and detailed records of fires dating to 1967. Our objective was to determine how the timing, number, and intervals between fires affect effective population size, focusing on multiple fires in the same location. Effective population size was higher in areas that had not been burned for more than 10 years and decreased with number of fires and shorter time between fires. A similar pattern was observed in abundance: increasing abundance with time-since-fire and decreasing abundance with number of fires. The ratio of effective population size to census size was higher at sites with more recent fires and tended to decrease with time-since-last-fire. These results suggest that habitat disturbances, such as fire, may have a large effect in the genetic characteristics of local populations and that Florida Sand Skinks are well adapted to the natural fire dynamics required to maintain Florida scrub.
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Affiliation(s)
- Aaron W Schrey
- From the Department of Biology, Armstrong State University, Science Center, 11935 Abercorn Street, Savannah, GA 31419 (Schrey and Ragsdale); and Department of Integrative Biology, University of South Florida, Tampa, FL (Schrey, McCoy, and Mushinsky).
| | - Alexandria K Ragsdale
- From the Department of Biology, Armstrong State University, Science Center, 11935 Abercorn Street, Savannah, GA 31419 (Schrey and Ragsdale); and Department of Integrative Biology, University of South Florida, Tampa, FL (Schrey, McCoy, and Mushinsky)
| | - Earl D McCoy
- From the Department of Biology, Armstrong State University, Science Center, 11935 Abercorn Street, Savannah, GA 31419 (Schrey and Ragsdale); and Department of Integrative Biology, University of South Florida, Tampa, FL (Schrey, McCoy, and Mushinsky)
| | - Henry R Mushinsky
- From the Department of Biology, Armstrong State University, Science Center, 11935 Abercorn Street, Savannah, GA 31419 (Schrey and Ragsdale); and Department of Integrative Biology, University of South Florida, Tampa, FL (Schrey, McCoy, and Mushinsky)
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9
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Ozerov M, Jürgenstein T, Aykanat T, Vasemägi A. Use of sibling relationship reconstruction to complement traditional monitoring in fisheries management and conservation of brown trout. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2015; 29:1164-1175. [PMID: 25773302 DOI: 10.1111/cobi.12480] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2014] [Accepted: 12/20/2014] [Indexed: 06/04/2023]
Abstract
Declining trends in the abundance of many fish urgently call for more efficient and informative monitoring methods that would provide necessary demographic data for the evaluation of existing conservation, restoration, and management actions. We investigated how genetic sibship reconstruction from young-of-the-year brown trout (Salmo trutta L.) juveniles provides valuable, complementary demographic information that allowed us to disentangle the effects of habitat quality and number of breeders on juvenile density. We studied restored (n = 15) and control (n = 15) spawning and nursery habitats in 16 brown trout rivers and streams over 2 consecutive years to evaluate the effectiveness of habitat restoration activities. Similar juvenile densities both in restored and control spawning and nursery grounds were observed. Similarly, no differences in the effective number of breeders, Nb(SA) , were detected between habitats, indicating that brown trout readily used recently restored spawning grounds. Only a weak relationship between the Nb(SA) and juvenile density was observed, suggesting that multiple factors affect juvenile abundance. In some areas, very low estimates of Nb(SA) were found at sites with high juvenile density, indicating that a small number of breeders can produce a high number of progeny in favorable conditions. In other sites, high Nb(SA) estimates were associated with low juvenile density, suggesting low habitat quality or lack of suitable spawning substrate in relation to available breeders. Based on these results, we recommend the incorporation of genetic sibship reconstruction to ongoing and future fish evaluation and monitoring programs to gain novel insights into local demographic and evolutionary processes relevant for fisheries management, habitat restoration, and conservation.
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Affiliation(s)
- Mikhail Ozerov
- Division of Genetics and Physiology, Department of Biology, University of Turku, 20014, Turku, Finland
| | - Tauno Jürgenstein
- Department of Aquaculture, Institute of Veterinary Medicine and Animal Science, Estonian University of Life Sciences, 51014, Tartu, Estonia
| | - Tutku Aykanat
- Division of Genetics and Physiology, Department of Biology, University of Turku, 20014, Turku, Finland
| | - Anti Vasemägi
- Division of Genetics and Physiology, Department of Biology, University of Turku, 20014, Turku, Finland
- Department of Aquaculture, Institute of Veterinary Medicine and Animal Science, Estonian University of Life Sciences, 51014, Tartu, Estonia
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11
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DeFaveri J, Merilä J. Temporal stability of genetic variability and differentiation in the three-spined stickleback (Gasterosteus aculeatus). PLoS One 2015; 10:e0123891. [PMID: 25853707 PMCID: PMC4390281 DOI: 10.1371/journal.pone.0123891] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2014] [Accepted: 03/02/2015] [Indexed: 11/19/2022] Open
Abstract
Temporal variation in allele frequencies, whether caused by deterministic or stochastic forces, can inform us about interesting demographic and evolutionary phenomena occurring in wild populations. In spite of the continued surge of interest in the genetics of three-spined stickleback (Gasterosteus aculeatus) populations, little attention has been paid towards the temporal stability of allele frequency distributions, and whether there are consistent differences in effective size (Ne) of local populations. We investigated temporal stability of genetic variability and differentiation in 15 microsatellite loci within and among eight collection sites of varying habitat type, surveyed twice over a six-year time period. In addition, Nes were estimated with the expectation that they would be lowest in isolated ponds, intermediate in larger lakes and largest in open marine sites. In spite of the marked differences in genetic variability and differentiation among the study sites, the temporal differences in allele frequencies, as well as measures of genetic diversity and differentiation, were negligible. Accordingly, the Ne estimates were temporally stable, but tended to be lower in ponds than in lake or marine habitats. Hence, we conclude that allele frequencies in putatively neutral markers in three-spined sticklebacks seem to be temporally stable - at least over periods of few generations - across a wide range of habitat types differing markedly in levels of genetic variability, effective population size and gene flow.
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Affiliation(s)
- Jacquelin DeFaveri
- Ecological Genetics Research Unit, Department of Biosciences, University of Helsinki, Helsinki, Finland
| | - Juha Merilä
- Ecological Genetics Research Unit, Department of Biosciences, University of Helsinki, Helsinki, Finland
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12
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O'Leary SJ, Feldheim KA, Fields AT, Natanson LJ, Wintner S, Hussey N, Shivji MS, Chapman DD. Genetic Diversity of White Sharks, Carcharodon carcharias, in the Northwest Atlantic and Southern Africa. J Hered 2015; 106:258-65. [PMID: 25762777 DOI: 10.1093/jhered/esv001] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2014] [Accepted: 01/16/2015] [Indexed: 11/12/2022] Open
Abstract
The white shark, Carcharodon carcharias, is both one of the largest apex predators in the world and among the most heavily protected marine fish. Population genetic diversity is in part shaped by recent demographic history and can thus provide information complementary to more traditional population assessments, which are difficult to obtain for white sharks and have at times been controversial. Here, we use the mitochondrial control region and 14 nuclear-encoded microsatellite loci to assess white shark genetic diversity in 2 regions: the Northwest Atlantic (NWA, N = 35) and southern Africa (SA, N = 131). We find that these 2 regions harbor genetically distinct white shark populations (Φ ST = 0.10, P < 0.00001; microsatellite F ST = 0.1057, P < 0.021). M-ratios were low and indicative of a genetic bottleneck in the NWA (M-ratio = 0.71, P < 0.004) but not SA (M-ratio = 0.85, P = 0.39). This is consistent with other evidence showing a steep population decline occurring in the mid to late 20th century in the NWA, whereas the SA population appears to have been relatively stable. Estimates of effective population size ranged from 22.6 to 66.3 (NWA) and 188 to 1998.3 (SA) and evidence of inbreeding was found (primarily in NWA). Overall, our findings indicate that white population dynamics within NWA and SA are determined more by intrinsic reproduction than immigration and there is genetic evidence of a population decline in the NWA, further justifying the strong domestic protective measures that have been taken for this species in this region. Our study also highlights how assessment of genetic diversity can complement other sources of information to better understand the status of threatened marine fish populations.
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Affiliation(s)
- Shannon J O'Leary
- From the School of Marine and Atmospheric Science, Stony Brook University, Stony Brook, NY 11394 (O'Leary, Fields, and Chapman); the Pritzker Laboratory for Molecular Systematics and Evolution, The Field Museum, Chicago, IL 60605 (Feldheim); the National Marine Fisheries Service, Apex Predators Program, Narragansett, RI 02882 (Natanson); the KwaZulu-Natal Sharks Board and Biomedical Resource Unit, University of KwaZulu-Natal, Durban 4000, South Africa (Wintner); the Great Lakes Institute for Environmental Research University of Windsor, Windsor, Ontario N9B3P4, Canada (Hussey); the Save our Seas Shark Center and Guy Harvey Research Institute, Nova Southeastern University, FL 33004 (Shivji); and the Institute of Ocean Conservation Science, Stony Brook, NY 11794 (Chapman). shannon.O'
| | - Kevin A Feldheim
- From the School of Marine and Atmospheric Science, Stony Brook University, Stony Brook, NY 11394 (O'Leary, Fields, and Chapman); the Pritzker Laboratory for Molecular Systematics and Evolution, The Field Museum, Chicago, IL 60605 (Feldheim); the National Marine Fisheries Service, Apex Predators Program, Narragansett, RI 02882 (Natanson); the KwaZulu-Natal Sharks Board and Biomedical Resource Unit, University of KwaZulu-Natal, Durban 4000, South Africa (Wintner); the Great Lakes Institute for Environmental Research University of Windsor, Windsor, Ontario N9B3P4, Canada (Hussey); the Save our Seas Shark Center and Guy Harvey Research Institute, Nova Southeastern University, FL 33004 (Shivji); and the Institute of Ocean Conservation Science, Stony Brook, NY 11794 (Chapman)
| | - Andrew T Fields
- From the School of Marine and Atmospheric Science, Stony Brook University, Stony Brook, NY 11394 (O'Leary, Fields, and Chapman); the Pritzker Laboratory for Molecular Systematics and Evolution, The Field Museum, Chicago, IL 60605 (Feldheim); the National Marine Fisheries Service, Apex Predators Program, Narragansett, RI 02882 (Natanson); the KwaZulu-Natal Sharks Board and Biomedical Resource Unit, University of KwaZulu-Natal, Durban 4000, South Africa (Wintner); the Great Lakes Institute for Environmental Research University of Windsor, Windsor, Ontario N9B3P4, Canada (Hussey); the Save our Seas Shark Center and Guy Harvey Research Institute, Nova Southeastern University, FL 33004 (Shivji); and the Institute of Ocean Conservation Science, Stony Brook, NY 11794 (Chapman)
| | - Lisa J Natanson
- From the School of Marine and Atmospheric Science, Stony Brook University, Stony Brook, NY 11394 (O'Leary, Fields, and Chapman); the Pritzker Laboratory for Molecular Systematics and Evolution, The Field Museum, Chicago, IL 60605 (Feldheim); the National Marine Fisheries Service, Apex Predators Program, Narragansett, RI 02882 (Natanson); the KwaZulu-Natal Sharks Board and Biomedical Resource Unit, University of KwaZulu-Natal, Durban 4000, South Africa (Wintner); the Great Lakes Institute for Environmental Research University of Windsor, Windsor, Ontario N9B3P4, Canada (Hussey); the Save our Seas Shark Center and Guy Harvey Research Institute, Nova Southeastern University, FL 33004 (Shivji); and the Institute of Ocean Conservation Science, Stony Brook, NY 11794 (Chapman)
| | - Sabine Wintner
- From the School of Marine and Atmospheric Science, Stony Brook University, Stony Brook, NY 11394 (O'Leary, Fields, and Chapman); the Pritzker Laboratory for Molecular Systematics and Evolution, The Field Museum, Chicago, IL 60605 (Feldheim); the National Marine Fisheries Service, Apex Predators Program, Narragansett, RI 02882 (Natanson); the KwaZulu-Natal Sharks Board and Biomedical Resource Unit, University of KwaZulu-Natal, Durban 4000, South Africa (Wintner); the Great Lakes Institute for Environmental Research University of Windsor, Windsor, Ontario N9B3P4, Canada (Hussey); the Save our Seas Shark Center and Guy Harvey Research Institute, Nova Southeastern University, FL 33004 (Shivji); and the Institute of Ocean Conservation Science, Stony Brook, NY 11794 (Chapman)
| | - Nigel Hussey
- From the School of Marine and Atmospheric Science, Stony Brook University, Stony Brook, NY 11394 (O'Leary, Fields, and Chapman); the Pritzker Laboratory for Molecular Systematics and Evolution, The Field Museum, Chicago, IL 60605 (Feldheim); the National Marine Fisheries Service, Apex Predators Program, Narragansett, RI 02882 (Natanson); the KwaZulu-Natal Sharks Board and Biomedical Resource Unit, University of KwaZulu-Natal, Durban 4000, South Africa (Wintner); the Great Lakes Institute for Environmental Research University of Windsor, Windsor, Ontario N9B3P4, Canada (Hussey); the Save our Seas Shark Center and Guy Harvey Research Institute, Nova Southeastern University, FL 33004 (Shivji); and the Institute of Ocean Conservation Science, Stony Brook, NY 11794 (Chapman)
| | - Mahmood S Shivji
- From the School of Marine and Atmospheric Science, Stony Brook University, Stony Brook, NY 11394 (O'Leary, Fields, and Chapman); the Pritzker Laboratory for Molecular Systematics and Evolution, The Field Museum, Chicago, IL 60605 (Feldheim); the National Marine Fisheries Service, Apex Predators Program, Narragansett, RI 02882 (Natanson); the KwaZulu-Natal Sharks Board and Biomedical Resource Unit, University of KwaZulu-Natal, Durban 4000, South Africa (Wintner); the Great Lakes Institute for Environmental Research University of Windsor, Windsor, Ontario N9B3P4, Canada (Hussey); the Save our Seas Shark Center and Guy Harvey Research Institute, Nova Southeastern University, FL 33004 (Shivji); and the Institute of Ocean Conservation Science, Stony Brook, NY 11794 (Chapman)
| | - Demian D Chapman
- From the School of Marine and Atmospheric Science, Stony Brook University, Stony Brook, NY 11394 (O'Leary, Fields, and Chapman); the Pritzker Laboratory for Molecular Systematics and Evolution, The Field Museum, Chicago, IL 60605 (Feldheim); the National Marine Fisheries Service, Apex Predators Program, Narragansett, RI 02882 (Natanson); the KwaZulu-Natal Sharks Board and Biomedical Resource Unit, University of KwaZulu-Natal, Durban 4000, South Africa (Wintner); the Great Lakes Institute for Environmental Research University of Windsor, Windsor, Ontario N9B3P4, Canada (Hussey); the Save our Seas Shark Center and Guy Harvey Research Institute, Nova Southeastern University, FL 33004 (Shivji); and the Institute of Ocean Conservation Science, Stony Brook, NY 11794 (Chapman)
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13
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Putman AI, Carbone I. Challenges in analysis and interpretation of microsatellite data for population genetic studies. Ecol Evol 2014; 4:4399-428. [PMID: 25540699 PMCID: PMC4267876 DOI: 10.1002/ece3.1305] [Citation(s) in RCA: 237] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2014] [Revised: 10/02/2014] [Accepted: 10/03/2014] [Indexed: 12/14/2022] Open
Abstract
Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (F ST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.
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Affiliation(s)
- Alexander I Putman
- Department of Plant Pathology, North Carolina State University Raleigh, North Carolina, 27695-7616
| | - Ignazio Carbone
- Department of Plant Pathology, North Carolina State University Raleigh, North Carolina, 27695-7616
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14
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Perrier C, Normandeau É, Dionne M, Richard A, Bernatchez L. Alternative reproductive tactics increase effective population size and decrease inbreeding in wild Atlantic salmon. Evol Appl 2014; 7:1094-106. [PMID: 25553070 PMCID: PMC4231598 DOI: 10.1111/eva.12172] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2014] [Accepted: 05/06/2014] [Indexed: 01/07/2023] Open
Abstract
While nonanadromous males (stream-resident and/or mature male parr) contribute to reproduction in anadromous salmonids, little is known about their impacts on key population genetic parameters. Here, we evaluated the contribution of Atlantic salmon mature male parr to the effective number of breeders (Nb) using both demographic (variance in reproductive success) and genetic (linkage disequilibrium) methods, the number of alleles, and the relatedness among breeders. We used a recently published pedigree reconstruction of a wild anadromous Atlantic salmon population in which 2548 fry born in 2010 were assigned parentage to 144 anadromous female and 101 anadromous females that returned to the river to spawn in 2009 and to 462 mature male parr. Demographic and genetic methods revealed that mature male parr increased population Nb by 1.79 and 1.85 times, respectively. Moreover, mature male parr boosted the number of alleles found among progenies. Finally, mature male parr were in average less related to anadromous females than were anadromous males, likely because of asynchronous sexual maturation between mature male parr and anadromous fish of a given cohort. By increasing Nb and allelic richness, and by decreasing inbreeding, the reproductive contribution of mature male parr has important evolutionary and conservation implications for declining Atlantic salmon populations.
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Affiliation(s)
- Charles Perrier
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval Québec, Canada
| | - Éric Normandeau
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval Québec, Canada
| | - Mélanie Dionne
- Direction de la faune aquatique, Ministère du Développement durable, de l'Environnement, de la Faune et des Parcs du Québec Québec, Canada
| | - Antoine Richard
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval Québec, Canada
| | - Louis Bernatchez
- Département de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval Québec, Canada
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