Disease Risk in Temperate Amphibian Populations Is Higher at Closed-Canopy Sites
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{"title"=>"Disease Risk in Temperate Amphibian Populations Is Higher at Closed-Canopy Sites", "type"=>"journal", "authors"=>[{"first_name"=>"C. Guilherme", "last_name"=>"Becker", "scopus_author_id"=>"23090520500"}, {"first_name"=>"David", "last_name"=>"Rodriguez", "scopus_author_id"=>"56984124400"}, {"first_name"=>"Ana V.", "last_name"=>"Longo", "scopus_author_id"=>"22953960000"}, {"first_name"=>"Amanda L.", "last_name"=>"Talaba", "scopus_author_id"=>"23480604200"}, {"first_name"=>"Kelly R.", "last_name"=>"Zamudio", "scopus_author_id"=>"6603683897"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84868283434", "doi"=>"10.1371/journal.pone.0048205", "pui"=>"365972089", "pmid"=>"23118953", "scopus"=>"2-s2.0-84868283434", "issn"=>"19326203", "isbn"=>"1932-6203"}, "id"=>"f7843360-cef7-3bc6-9357-bd3bb46188bb", "abstract"=>"Habitat loss and chytridiomycosis (a disease caused by the chytrid fungus Batrachochytrium dendrobatidis - Bd) are major drivers of amphibian declines worldwide. Habitat loss regulates host-pathogen interactions by altering biotic and abiotic factors directly linked to both host and pathogen fitness. Therefore, studies investigating the links between natural vegetation and chytridiomycosis require integrative approaches to control for the multitude of possible interactions of biological and environmental variables in spatial epidemiology. In this study, we quantified Bd infection dynamics across a gradient of natural vegetation and microclimates, looking for causal associations between vegetation cover, multiple microclimatic variables, and pathogen prevalence and infection intensity. To minimize the effects of host diversity in our analyses, we sampled amphibian populations in the Adirondack Mountains of New York State, a region with relatively high single-host dominance. We sampled permanent ponds for anurans, focusing on populations of the habitat generalist frog Lithobates clamitans, and recorded various biotic and abiotic factors that potentially affect host-pathogen interactions: natural vegetation, canopy density, water temperature, and host population and community attributes. We screened for important explanatory variables of Bd infections and used path analyses to statistically test for the strength of cascading effects linking vegetation cover, microclimate, and Bd parameters. We found that canopy density, natural vegetation, and daily average water temperature were the best predictors of Bd. High canopy density resulted in lower water temperature, which in turn predicted higher Bd prevalence and infection intensity. Our results confirm that microclimatic shifts arising from changes in natural vegetation play an important role in Bd spatial epidemiology, with areas of closed canopy favoring Bd. Given increasing rates of anthropogenic habitat modification and the resulting declines in temperate and tropical frogs, understanding how vegetation cover and disease interact is critical for predicting Bd spread and developing appropriate management tools for wild populations.", "link"=>"http://www.mendeley.com/research/disease-risk-temperate-amphibian-populations-higher-closedcanopy-sites", "reader_count"=>82, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>4, "Researcher"=>15, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>16, "Student > Postgraduate"=>5, "Student > Master"=>16, "Other"=>4, "Student > Bachelor"=>12, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>4, "Researcher"=>15, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>16, "Student > Postgraduate"=>5, "Student > Master"=>16, "Other"=>4, "Student > Bachelor"=>12, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>3, "Environmental Science"=>14, "Biochemistry, Genetics and Molecular Biology"=>5, "Agricultural and Biological Sciences"=>54, "Veterinary Science and Veterinary Medicine"=>1, "Social Sciences"=>2, "Earth and Planetary Sciences"=>1, "Economics, Econometrics and Finance"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Social Sciences"=>{"Social Sciences"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>54}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>5}, "Unspecified"=>{"Unspecified"=>3}, "Environmental Science"=>{"Environmental Science"=>14}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Argentina"=>1, "United States"=>10, "Brazil"=>2, "Mexico"=>1, "Australia"=>1}, "group_count"=>9}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/294340"], "description"=>"<div><p>Habitat loss and chytridiomycosis (a disease caused by the chytrid fungus <em>Batrachochytrium dendrobatidis</em> - <em>Bd</em>) are major drivers of amphibian declines worldwide. Habitat loss regulates host-pathogen interactions by altering biotic and abiotic factors directly linked to both host and pathogen fitness. Therefore, studies investigating the links between natural vegetation and chytridiomycosis require integrative approaches to control for the multitude of possible interactions of biological and environmental variables in spatial epidemiology. In this study, we quantified <em>Bd</em> infection dynamics across a gradient of natural vegetation and microclimates, looking for causal associations between vegetation cover, multiple microclimatic variables, and pathogen prevalence and infection intensity. To minimize the effects of host diversity in our analyses, we sampled amphibian populations in the Adirondack Mountains of New York State, a region with relatively high single-host dominance. We sampled permanent ponds for anurans, focusing on populations of the habitat generalist frog <em>Lithobates clamitans</em>, and recorded various biotic and abiotic factors that potentially affect host-pathogen interactions: natural vegetation, canopy density, water temperature, and host population and community attributes. We screened for important explanatory variables of <em>Bd</em> infections and used path analyses to statistically test for the strength of cascading effects linking vegetation cover, microclimate, and <em>Bd</em> parameters. We found that canopy density, natural vegetation, and daily average water temperature were the best predictors of <em>Bd</em>. High canopy density resulted in lower water temperature, which in turn predicted higher <em>Bd</em> prevalence and infection intensity. Our results confirm that microclimatic shifts arising from changes in natural vegetation play an important role in <em>Bd</em> spatial epidemiology, with areas of closed canopy favoring <em>Bd</em>. Given increasing rates of anthropogenic habitat modification and the resulting declines in temperate and tropical frogs, understanding how vegetation cover and disease interact is critical for predicting <em>Bd</em> spread and developing appropriate management tools for wild populations.</p> </div>", "links"=>[], "tags"=>["temperate", "amphibian", "populations", "higher", "closed-canopy", "sites"], "article_id"=>117960, "categories"=>["Microbiology", "Cancer", "Biotechnology", "Cell Biology"], "users"=>["C. Guilherme Becker", "David Rodriguez", "Ana V. Longo", "Amanda L. Talaba", "Kelly R. Zamudio"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0048205"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Disease_Risk_in_Temperate_Amphibian_Populations_Is_Higher_at_Closed_Canopy_Sites__/117960", "title"=>"Disease Risk in Temperate Amphibian Populations Is Higher at Closed-Canopy Sites", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-10-31 02:12:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/550599"], "description"=>"<p>(A) <i>Bd</i> prevalence; (B) <i>Bd</i> infection intensity.</p>", "links"=>[], "tags"=>["canopy", "populations", "adirondack"], "article_id"=>221087, "categories"=>["Microbiology", "Biotechnology", "Infectious Diseases", "Plant Biology"], "users"=>["C. Guilherme Becker", "David Rodriguez", "Ana V. Longo", "Amanda L. Talaba", "Kelly R. Zamudio"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0048205.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effect_of_canopy_density_on_Bd_across_populations_of_L_clamitans_from_the_Adirondack_region_New_York_USA_/221087", "title"=>"Effect of canopy density on <i>Bd</i> across populations of <i>L. clamitans</i> from the Adirondack region, New York, USA.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-10-31 00:18:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/550712"], "description"=>"<p>The relative strength of each effect is indicated by line width. Linear regressions are shown for each relationship. Numbers are standardized path coefficients (*P<0.05). Diagram shows models for <i>Bd</i> prevalence and infection intensity combined.</p>", "links"=>[], "tags"=>["analyses", "unidirectional", "causal", "canopy"], "article_id"=>221204, "categories"=>["Microbiology", "Biotechnology", "Infectious Diseases", "Plant Biology"], "users"=>["C. Guilherme Becker", "David Rodriguez", "Ana V. Longo", "Amanda L. Talaba", "Kelly R. Zamudio"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0048205.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Path_analyses_indicating_a_unidirectional_causal_relationship_between_natural_vegetation_canopy_density_water_temperature_and_Bd_/221204", "title"=>"Path analyses indicating a unidirectional causal relationship between natural vegetation, canopy density, water temperature, and <i>Bd</i>.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-10-31 00:20:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/550848"], "description"=>"<p>(A) <i>Bd</i> prevalence; (B) <i>Bd</i> infection intensity. The relative strength of each effect is indicated by line width. Grey lines stand for non-significant effects. Numbers are standardized path coefficients (*P<0.05).</p>", "links"=>[], "tags"=>["indirect", "canopy"], "article_id"=>221340, "categories"=>["Microbiology", "Biotechnology", "Infectious Diseases", "Plant Biology"], "users"=>["C. Guilherme Becker", "David Rodriguez", "Ana V. Longo", "Amanda L. Talaba", "Kelly R. Zamudio"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0048205.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Alternative_path_models_including_both_direct_and_indirect_effects_of_canopy_density_on_Bd_/221340", "title"=>"Alternative path models, including both direct and indirect effects of canopy density on <i>Bd</i>.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-10-31 00:22:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/550987"], "description"=>"<p>Whole-model tests: prevalence: (F = 7.418, n = 10, r<sup>2</sup> = 0.481, P = 0.026); infection intensity: (F = 38.376, n = 10, r<sup>2</sup> = 0.950, P<0.001). Std. coeff. stands for standard coefficient. Final models chosen based on Akaike Information Criterion (AICc).</p>", "links"=>[], "tags"=>["autoregressive", "models", "canopy", "prevalence", "amphibian", "populations", "adirondack"], "article_id"=>221477, "categories"=>["Microbiology", "Biotechnology", "Infectious Diseases", "Plant Biology"], "users"=>["C. Guilherme Becker", "David Rodriguez", "Ana V. Longo", "Amanda L. Talaba", "Kelly R. Zamudio"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0048205.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Conditional_autoregressive_models_CAR_simultaneously_testing_the_effects_of_natural_vegetation_canopy_density_and_water_temperature_on_Bd_prevalence_and_infection_intensity_in_amphibian_populations_from_the_Adirondack_region_New_York_USA_/221477", "title"=>"Conditional autoregressive models (CAR) simultaneously testing the effects of natural vegetation, canopy density, and water temperature on <i>Bd</i> prevalence and infection intensity in amphibian populations from the Adirondack region, New York, USA.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-10-31 00:24:37"}
  • {"files"=>["https://ndownloader.figshare.com/files/551025"], "description"=>"<p>Best explanatory variables predicting <i>Bd</i> prevalence (%) and infection intensity (average g.e. log) across ten sites in the southern Adirondack region, New York, USA [Habitat loss (%), canopy density (%), and average water temperature (°C)].</p>", "links"=>[], "tags"=>["explanatory", "variables", "predicting", "prevalence", "sites", "adirondack", "usa", "canopy"], "article_id"=>221509, "categories"=>["Microbiology", "Biotechnology", "Infectious Diseases", "Plant Biology"], "users"=>["C. Guilherme Becker", "David Rodriguez", "Ana V. Longo", "Amanda L. Talaba", "Kelly R. Zamudio"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0048205.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Best_explanatory_variables_predicting_Bd_prevalence_and_infection_intensity_average_g_e_log_across_ten_sites_in_the_southern_Adirondack_region_New_York_USA_Habitat_loss_canopy_density_and_average_water_temperature_C_/221509", "title"=>"Best explanatory variables predicting <i>Bd</i> prevalence (%) and infection intensity (average g.e. log) across ten sites in the southern Adirondack region, New York, USA [Habitat loss (%), canopy density (%), and average water temperature (°C)].", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-10-31 00:25:09"}

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Relative Metric

{"start_date"=>"2012-01-01T00:00:00Z", "end_date"=>"2012-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[322, 550, 671, 773, 864, 955, 1048, 1135, 1223, 1308, 1387, 1465, 1534, 1602, 1673, 1744, 1813, 1885, 1955, 2026, 2093, 2160, 2228, 2290, 2349]}, {"subject_area"=>"/Biology and life sciences/Organisms", "average_usage"=>[331, 557, 677, 777, 868, 960, 1050, 1136, 1223, 1307, 1390, 1466, 1536, 1603, 1673, 1741, 1814, 1889, 1954, 2028, 2096, 2164, 2233, 2305, 2362]}, {"subject_area"=>"/Earth sciences", "average_usage"=>[368, 548, 649, 749, 833, 915, 993, 1071, 1153, 1240, 1315, 1388, 1456, 1520, 1597, 1673, 1747, 1826, 1892, 1975, 2036, 2101, 2178, 2256, 2319]}, {"subject_area"=>"/Ecology and environmental sciences", "average_usage"=>[348, 541, 638, 730, 827, 907, 993, 1074, 1152, 1232, 1310, 1379, 1442, 1507, 1576, 1648, 1715, 1786, 1854, 1926, 1991, 2059, 2125, 2181, 2249]}, {"subject_area"=>"/Ecology and environmental sciences/Habitats", "average_usage"=>[355, 533, 627, 707, 778, 856, 928, 1005, 1080, 1162, 1245, 1303, 1378, 1445, 1504, 1573, 1659, 1717, 1797, 1846, 1928, 1994, 2063, 2137, 2206]}, {"subject_area"=>"/Medicine and health sciences/Pathology and laboratory medicine", "average_usage"=>[321, 553, 683, 785, 880, 973, 1072, 1162, 1249, 1336, 1425, 1504, 1574, 1642, 1711, 1785, 1852, 1923, 1987, 2050, 2129, 2192, 2259, 2325, 2393]}]}
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