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Clubley CH, Silva TAM, Wood LE, Firth LB, Bilton DT, O'Dea E, Knights AM. Multi-generational dispersal and dynamic patch occupancy reveals spatial and temporal stability of seascapes. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 952:175762. [PMID: 39197777 DOI: 10.1016/j.scitotenv.2024.175762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 07/30/2024] [Accepted: 08/22/2024] [Indexed: 09/01/2024]
Abstract
The success of non-native species (NNS) invasions depends on patterns of dispersal and connectivity, which underpin genetic diversity, population establishment and growth. In the marine environment, both global environmental change and increasing anthropogenic activity can alter hydrodynamic patterns, leading to significant inter-annual variability in dispersal pathways. Despite this, multi-generational dispersal is rarely explicitly considered in attempts to understand NNS spread or in the design of management interventions. Here, we present a novel approach to quantifying species spread that considers range expansion and network formation across time using the non-native Pacific oyster, Magallana gigas (Thunberg 1793), as a model. We combined biophysical modelling, dynamic patch occupancy models, consideration of environmental factors, and graph network theory to model multi-generational dispersal in northwest Europe over 13 generations. Results revealed that M. gigas has a capacity for rapid range expansion through the creation of an ecological network of dispersal pathways that remains stable through time. Maximum network size was achieved in four generations, after which connectivity patterns remained temporally stable. Multi-generational connectivity could therefore be divided into two periods: network growth (2000-2003) and network stability (2004-2012). Our study is the first to examine how dispersal trajectories affect the temporal stability of ecological networks across biogeographic scales, and provides an approach for the assignment of site-based prioritisation of non-native species management at different stages of the invasion timeline. More broadly, the framework we present can be applied to other fields (e.g. Marine Protected Area design, management of threatened species and species range expansion due to climate change) as a means of characterising and defining ecological network structure, functioning and stability.
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Affiliation(s)
- Charlotte H Clubley
- School of Biological and Marine Sciences, University of Plymouth, Plymouth PL4 8AA, United Kingdom; Aarhus University, Department of Ecoscience, Frederiksborgvej 399, PO Box 358, 4000 Roskilde, Denmark.
| | - Tiago A M Silva
- Lowestoft Laboratory, Centre for Environment, Fisheries and Aquaculture Science, NR33 0HT Lowestoft, United Kingdom
| | - Louisa E Wood
- Centre for Blue Governance, Department of Economics and Finance, University of Portsmouth, Portsmouth, Hampshire PO1 3DE, United Kingdom; Department of Biology, University of Fribourg, Chemin du Musée 15, CH-1700 Fribourg, Switzerland
| | - Louise B Firth
- School of Biological and Marine Sciences, University of Plymouth, Plymouth PL4 8AA, United Kingdom; School of Biological, Earth and Environmental Sciences, University College Cork, North Mall, Cork, Ireland
| | - David T Bilton
- School of Biological and Marine Sciences, University of Plymouth, Plymouth PL4 8AA, United Kingdom; Department of Zoology, University of Johannesburg, PO Box 524, Auckland Park, Johannesburg 2006, South Africa
| | - Enda O'Dea
- Met Éireann, 65/67 Glasnevin Hill, Dublin 9 D09 Y921, Ireland; Met Office, FitzRoy Road, Exeter, Devon EX1 3PB, United Kingdom
| | - Antony M Knights
- School of Biological and Marine Sciences, University of Plymouth, Plymouth PL4 8AA, United Kingdom; School of Biological, Earth and Environmental Sciences, University College Cork, North Mall, Cork, Ireland
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2
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Milligan BG, Rohde AT. Why More Biologists Must Embrace Quantitative Modeling. Integr Comp Biol 2024; 64:975-986. [PMID: 38740442 DOI: 10.1093/icb/icae038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 04/26/2024] [Accepted: 05/01/2024] [Indexed: 05/16/2024] Open
Abstract
Biology as a field has transformed since the time of its foundation from an organized enterprise cataloging the diversity of the natural world to a quantitatively rigorous science seeking to answer complex questions about the functions of organisms and their interactions with each other and their environments. As the mathematical rigor of biological analyses has improved, quantitative models have been developed to describe multi-mechanistic systems and to test complex hypotheses. However, applications of quantitative models have been uneven across fields, and many biologists lack the foundational training necessary to apply them in their research or to interpret their results to inform biological problem-solving efforts. This gap in scientific training has created a false dichotomy of "biologists" and "modelers" that only exacerbates the barriers to working biologists seeking additional training in quantitative modeling. Here, we make the argument that all biologists are modelers and are capable of using sophisticated quantitative modeling in their work. We highlight four benefits of conducting biological research within the framework of quantitative models, identify the potential producers and consumers of information produced by such models, and make recommendations for strategies to overcome barriers to their widespread implementation. Improved understanding of quantitative modeling could guide the producers of biological information to better apply biological measurements through analyses that evaluate mechanisms, and allow consumers of biological information to better judge the quality and applications of the information they receive. As our explanations of biological phenomena increase in complexity, so too must we embrace modeling as a foundational skill.
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Affiliation(s)
- Brook G Milligan
- Department of Biology, New Mexico State University, Las Cruces, NM 88001, USA
| | - Ashley T Rohde
- Department of Biology, New Mexico State University, Las Cruces, NM 88001, USA
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3
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Trumbo DR, Hardy BM, Crockett HJ, Muths E, Forester BR, Cheek RG, Zimmerman SJ, Corey-Rivas S, Bailey LL, Funk WC. Conservation genomics of an endangered montane amphibian reveals low population structure, low genomic diversity and selection pressure from disease. Mol Ecol 2023; 32:6777-6795. [PMID: 37864490 DOI: 10.1111/mec.17175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 10/07/2023] [Accepted: 10/11/2023] [Indexed: 10/23/2023]
Abstract
Wildlife diseases are a major global threat to biodiversity. Boreal toads (Anaxyrus [Bufo] boreas) are a state-endangered species in the southern Rocky Mountains of Colorado and New Mexico, and a species of concern in Wyoming, largely due to lethal skin infections caused by the amphibian chytrid fungus Batrachochytrium dendrobatidis (Bd). We performed conservation and landscape genomic analyses using single nucleotide polymorphisms from double-digest, restriction site-associated DNA sequencing in combination with the development of the first boreal toad (and first North American toad) reference genome to investigate population structure, genomic diversity, landscape connectivity and adaptive divergence. Genomic diversity (π = 0.00034-0.00040) and effective population sizes (Ne = 8.9-38.4) were low, likely due to post-Pleistocene founder effects and Bd-related population crashes over the last three decades. Population structure was also low, likely due to formerly high connectivity among a higher density of geographically proximate populations. Boreal toad gene flow was facilitated by low precipitation, cold minimum temperatures, less tree canopy, low heat load and less urbanization. We found >8X more putatively adaptive loci related to Bd intensity than to all other environmental factors combined, and evidence for genes under selection related to immune response, heart development and regulation and skin function. These data suggest boreal toads in habitats with Bd have experienced stronger selection pressure from disease than from other, broad-scale environmental variations. These findings can be used by managers to conserve and recover the species through actions including reintroduction and supplementation of populations that have declined due to Bd.
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Affiliation(s)
- D R Trumbo
- Department of Biology, Colorado State University, Fort Collins, Colorado, USA
| | - B M Hardy
- Department of Biology, Colorado State University, Fort Collins, Colorado, USA
- Department of Fish, Wildlife and Conservation Biology, Colorado State University, Fort Collins, Colorado, USA
- Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, USA
| | - H J Crockett
- Colorado Parks and Wildlife, Fort Collins, Colorado, USA
| | - E Muths
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado, USA
| | - B R Forester
- Department of Biology, Colorado State University, Fort Collins, Colorado, USA
| | - R G Cheek
- Department of Biology, Colorado State University, Fort Collins, Colorado, USA
- Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, USA
| | - S J Zimmerman
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado, USA
| | - S Corey-Rivas
- Department of Biology, New Mexico Highlands University, Las Vegas, New Mexico, USA
| | - L L Bailey
- Department of Fish, Wildlife and Conservation Biology, Colorado State University, Fort Collins, Colorado, USA
- Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, USA
| | - W C Funk
- Department of Biology, Colorado State University, Fort Collins, Colorado, USA
- Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, USA
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Fencing Can Alter Gene Flow of Asian Elephant Populations within Protected Areas. CONSERVATION 2022. [DOI: 10.3390/conservation2040046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
The Asian elephant is mostly confined to mountainous ranges and therefore risks population fragmentation if hard protected area (PA) boundaries near steep slopes prevent movement. We tested whether elephant gene flow is (i) controlled by slope and (ii) affected by the interplay between barriers and slope. We used 176 unique genotypes obtained non-invasively from fresh elephant dung to assess individual-by-individual genetic distance across the Western Ghats of India, a biodiversity hotspot. To assess landscape distance, 36 resistance models were produced by transforming a slope raster. Core areas and corridors were calculated from the raster that provided the best correlation between the genetic and distance matrices. The influence of the closure of PAs on gene flow was examined for one region, the Nilgiri Biosphere Reserve. The best resistance raster obtained by transforming the slope occupancy model was better than Euclidean distance for explaining genetic distance, indicating that slope partially controls gene flow. Fencing elephant PAs on hilly terrain reduces core areas and disrupts corridors. Consequently, hard PA boundaries abutting slopes can fragment elephant populations, but this can be ameliorated by protecting the adjacent flatter terrain.
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Fletcher RJ, Sefair JA, Kortessis N, Jaffe R, Holt RD, Robertson EP, Duncan SI, Marx AJ, Austin JD. Extending isolation by resistance to predict genetic connectivity. Methods Ecol Evol 2022. [DOI: 10.1111/2041-210x.13975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Robert J. Fletcher
- Department of Wildlife Ecology and Conservation University of Florida Gainesville Florida USA
| | - Jorge A. Sefair
- School of Computing, Informatics, and Decision Systems Engineering Arizona State University Tempe Arizona USA
| | | | | | - Robert D. Holt
- Department of Biology University of Florida Gainesville Florida USA
| | - Ellen P. Robertson
- Department of Wildlife Ecology and Conservation University of Florida Gainesville Florida USA
| | - Sarah I. Duncan
- Department of Wildlife Ecology and Conservation University of Florida Gainesville Florida USA
- Department of Biology Eckerd College St. Petersburg Florida USA
| | - Andrew J. Marx
- Department of Wildlife Ecology and Conservation University of Florida Gainesville Florida USA
| | - James D. Austin
- Department of Wildlife Ecology and Conservation University of Florida Gainesville Florida USA
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Zimmerman SJ, Aldridge CL, Hooten MB, Oyler-McCance SJ. Scale-dependent influence of the sagebrush community on genetic connectivity of the sagebrush obligate Gunnison sage-grouse. Mol Ecol 2022; 31:3267-3285. [PMID: 35501946 PMCID: PMC9325045 DOI: 10.1111/mec.16470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 03/23/2022] [Accepted: 04/01/2022] [Indexed: 11/30/2022]
Abstract
Habitat fragmentation and degradation impacts an organism's ability to navigate the landscape, ultimately resulting in decreased gene flow and increased extinction risk. Understanding how landscape composition impacts gene flow (i.e., connectivity) and interacts with scale is essential to conservation decision‐making. We used a landscape genetics approach implementing a recently developed statistical model based on the generalized Wishart probability distribution to identify the primary landscape features affecting gene flow and estimate the degree to which each component influences connectivity for Gunnison sage‐grouse (Centrocercus minimus). We were interested in two spatial scales: among distinct populations rangewide and among leks (i.e., breeding grounds) within the largest population, Gunnison Basin. Populations and leks are nested within a landscape fragmented by rough terrain and anthropogenic features, although requisite sagebrush habitat is more contiguous within populations. Our best fit models for each scale confirm the importance of sagebrush habitat in connectivity, although the important sagebrush characteristics differ. For Gunnison Basin, taller shrubs and higher quality nesting habitat were the primary drivers of connectivity, while more sagebrush cover and less conifer cover facilitated connectivity rangewide. Our findings support previous assumptions that Gunnison sage‐grouse range contraction is largely the result of habitat loss and degradation. Importantly, we report direct estimates of resistance for landscape components that can be used to create resistance surfaces for prioritization of specific locations for conservation or management (i.e., habitat preservation, restoration, or development) or as we demonstrated, can be combined with simulation techniques to predict impacts to connectivity from potential management actions.
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Affiliation(s)
- Shawna J Zimmerman
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado, USA
| | - Cameron L Aldridge
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado, USA
| | - Mevin B Hooten
- Department of Statistics and Data Sciences, The University of Texas at Austin, Austin, Texas, USA
| | - Sara J Oyler-McCance
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado, USA
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7
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Bibliometric Analysis of Global Research on Ecological Networks in Nature Conservation from 1990 to 2020. SUSTAINABILITY 2022. [DOI: 10.3390/su14094925] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
As a nature-based solution to land-use sustainability, ecological networks (ENs) have received substantial attention from researchers, planners, and decision-makers worldwide. To portray the global research on ENs in nature conservation during the period of 1990–2020, 1371 papers in 53 subject categories were reviewed with bibliometric methods and CiteSpace. The results showed a successive growth of publications at an annually averaged rate of 18.9% during the past three decades. Co-citation analysis indicated that the most popular topic was connectivity, on which the studies concentrated on quantifying connectivity, identifying priority areas, and integrating conservation planning. A recent hotspot is to study the landscape fragmentation effects on natural habitats or biodiversity under land-use changes in urbanized areas. Multidisciplinary approaches have been increasingly used to tackle more complex interplays among economic, social, ecological, and cultural factors, with the aim of alleviating ecological service losses attributed to human activities. Spatiotemporal dynamics and participatory design of ENs at different scales have become an emerging trend. In order to address increasing pressures on biodiversity or landscape connectivity brought about by land use and climate change, it is suggested to develop more research on the evaluation and management of the resilience of ENs.
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Kittlein MJ, Mora MS, Mapelli FJ, Austrich A, Gaggiotti OE. Deep learning and satellite imagery predict genetic diversity and differentiation. Methods Ecol Evol 2021. [DOI: 10.1111/2041-210x.13775] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Marcelo J. Kittlein
- Departamento de Biología Instituto de Investigaciones Marinas y Costeras (IIMyC) Facultad de Ciencias Exáctas y Naturales Universidad Nacional de Mar del Plata Consejo Nacional de Investigaciones Científica y Técnicas (CONICET) Mar del Plata Argentina
| | - Matías S. Mora
- Departamento de Biología Instituto de Investigaciones Marinas y Costeras (IIMyC) Facultad de Ciencias Exáctas y Naturales Universidad Nacional de Mar del Plata Consejo Nacional de Investigaciones Científica y Técnicas (CONICET) Mar del Plata Argentina
| | - Fernando J. Mapelli
- Grupo de Genética y Ecología en Conservación y Biodiversidad (GECOBI) División Mastozoología Museo Argentino de Ciencias Naturales ‘Bernardino Rivadavia’ (CONICET) Ciudad de Buenos Aires Argentina
| | - Ailín Austrich
- Departamento de Biología Instituto de Investigaciones Marinas y Costeras (IIMyC) Facultad de Ciencias Exáctas y Naturales Universidad Nacional de Mar del Plata Consejo Nacional de Investigaciones Científica y Técnicas (CONICET) Mar del Plata Argentina
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9
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Exploratory dispersal movements by young tigers in Thailand’s Western Forest Complex: the challenges of securing a territory. MAMMAL RES 2021. [DOI: 10.1007/s13364-021-00602-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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10
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Lasky JR, Hooten MB, Adler PB. What processes must we understand to forecast regional-scale population dynamics? Proc Biol Sci 2020; 287:20202219. [PMID: 33290672 PMCID: PMC7739927 DOI: 10.1098/rspb.2020.2219] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 11/12/2020] [Indexed: 12/14/2022] Open
Abstract
An urgent challenge facing biologists is predicting the regional-scale population dynamics of species facing environmental change. Biologists suggest that we must move beyond predictions based on phenomenological models and instead base predictions on underlying processes. For example, population biologists, evolutionary biologists, community ecologists and ecophysiologists all argue that the respective processes they study are essential. Must our models include processes from all of these fields? We argue that answering this critical question is ultimately an empirical exercise requiring a substantial amount of data that have not been integrated for any system to date. To motivate and facilitate the necessary data collection and integration, we first review the potential importance of each mechanism for skilful prediction. We then develop a conceptual framework based on reaction norms, and propose a hierarchical Bayesian statistical framework to integrate processes affecting reaction norms at different scales. The ambitious research programme we advocate is rapidly becoming feasible due to novel collaborations, datasets and analytical tools.
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Affiliation(s)
- Jesse R. Lasky
- Department of Biology, Pennsylvania State University, University Park, PA, USA
| | - Mevin B. Hooten
- U.S. Geological Survey, Colorado Cooperative Fish and Wildlife Research Unit, Colorado State University, Fort Collins, CO, USA
- Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, USA
- Department of Statistics, Colorado State University, Fort Collins, CO, USA
| | - Peter B. Adler
- Department of Wildland Resources and the Ecology Center, Utah State University, Logan, UT, USA
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11
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Peterman WE, Pope NS. The use and misuse of regression models in landscape genetic analyses. Mol Ecol 2020; 30:37-47. [PMID: 33128830 DOI: 10.1111/mec.15716] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 08/21/2020] [Accepted: 10/22/2020] [Indexed: 12/27/2022]
Abstract
The field of landscape genetics has been rapidly evolving, adopting and adapting analytical frameworks to address research questions. Current studies are increasingly using regression-based frameworks to infer the individual contributions of landscape and habitat variables on genetic differentiation. This paper outlines appropriate and inappropriate uses of multiple regression for these purposes, and demonstrates through simulation the limitations of different analytical frameworks for making correct inference. Of particular concern are recent studies seeking to explain genetic differences by fitting regression models with effective distance variables calculated independently on separate landscape resistance surfaces. When moving across the landscape, organisms cannot respond independently and uniquely to habitat and landscape features. Analyses seeking to understand how landscape features affect gene flow should model a single conductance or resistance surface as a parameterized function of relevant spatial covariates, and estimate the values of these parameters by linking a single set of resistance distances to observed genetic dissimilarity via a loss function. While this loss function may involve a regression-like step, the associated nuisance parameters are not interpretable in terms of organismal movement and should not be conflated with what is actually of interest: the mapping between spatial covariates and conductance/resistance. The growth and evolution of landscape genetics as a field has been rapid and exciting. It is the goal of this paper to highlight past missteps and demonstrate limitations of current approaches to ensure that future use of regression models will appropriately consider the process being modeled, which will provide clarity to model interpretation.
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Affiliation(s)
- William E Peterman
- School of Environment and Natural Resources, The Ohio State University, Columbus, OH, USA
| | - Nathaniel S Pope
- Department of Entomology, The Pennsylvania State University, University Park, PA, USA
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Covarrubias S, González C, Gutiérrez‐Rodríguez C. Effects of natural and anthropogenic features on functional connectivity of anurans: a review of landscape genetics studies in temperate, subtropical and tropical species. J Zool (1987) 2020. [DOI: 10.1111/jzo.12851] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- S. Covarrubias
- Instituto de Investigaciones sobre los Recursos Naturales Universidad Michoacana de San Nicolás de Hidalgo Morelia Michoacán México
| | - C. González
- Instituto de Investigaciones sobre los Recursos Naturales Universidad Michoacana de San Nicolás de Hidalgo Morelia Michoacán México
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13
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White SL, Hanks EM, Wagner T. A novel quantitative framework for riverscape genetics. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2020; 30:e02147. [PMID: 32338800 DOI: 10.1002/eap.2147] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 03/08/2020] [Accepted: 03/30/2020] [Indexed: 06/11/2023]
Abstract
Riverscape genetics, which applies concepts in landscape genetics to riverine ecosystems, lack appropriate quantitative methods that address the spatial autocorrelation structure of linear stream networks and account for bidirectional geneflow. To address these challenges, we present a general framework for the design and analysis of riverscape genetic studies. Our framework starts with the estimation of pairwise genetic distance at sample sites and the development of a spatially structured ecological network (SSEN) on which riverscape covariates are measured. We then introduce the novel bidirectional geneflow in riverscapes (BGR) model that uses principles of isolation-by-resistance to quantify the effects of environmental covariates on genetic connectivity, with spatial covariance defined using simultaneous autoregressive models on the SSEN and the generalized Wishart distribution to model pairwise distance matrices arising through a random walk model of geneflow. We highlight the utility of this framework in an analysis of riverscape genetics for brook trout (Salvelinus fontinalis) in north central Pennsylvania, USA. Using the fixation index (FST ) as the measure of genetic distance, we estimated the effects of 12 riverscape covariates on geneflow by evaluating the relative support of eight competing BGR models. We then compared the performance of the top-ranked BGR model to results obtained from comparable analyses using multiple regression on distance matrices (MRM) and the program STRUCTURE. We found that the BGR model had more power to detect covariate effects, particularly for variables that were only partial barriers to geneflow and/or uncommon in the riverscape, making it more informative for assessing patterns of population connectivity and identifying threats to species conservation. This case study highlights the utility of our modeling framework over other quantitative methods in riverscape genetics, particularly the ability to rigorously test hypotheses about factors that influence geneflow and probabilistically estimate the effect of riverscape covariates, including stream flow direction. This framework is flexible across taxa and riverine networks, is easily executable, and provides intuitive results that can be used to investigate the likely outcomes of current and future management scenarios.
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Affiliation(s)
- Shannon L White
- Pennsylvania Cooperative Fish and Wildlife Research Unit, Pennsylvania State University, University Park, Pennsylvania, 16802, USA
- Department of Ecosystem Science and Management, Pennsylvania State University, University Park, Pennsylvania, 16802, USA
| | - Ephraim M Hanks
- Department of Statistics, Pennsylvania State University, University Park, Pennsylvania, 16802, USA
| | - Tyler Wagner
- U.S. Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit, Pennsylvania State University, University Park, Pennsylvania, 16802, USA
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