Summer Hot Snaps and Winter Conditions: Modelling White Syndrome Outbreaks on Great Barrier Reef Corals
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{"title"=>"Summer hot snaps and winter conditions: Modelling white syndrome outbreaks on great barrier reef corals", "type"=>"journal", "authors"=>[{"first_name"=>"Scott F.", "last_name"=>"Heron", "scopus_author_id"=>"7004098794"}, {"first_name"=>"Bette L.", "last_name"=>"Willis", "scopus_author_id"=>"7101749421"}, {"first_name"=>"William J.", "last_name"=>"Skirving", "scopus_author_id"=>"6601967743"}, {"first_name"=>"C.", "last_name"=>"Mark Eakin", "scopus_author_id"=>"36704834200"}, {"first_name"=>"Cathie A.", "last_name"=>"Page", "scopus_author_id"=>"13205167500"}, {"first_name"=>"Ian R.", "last_name"=>"Miller", "scopus_author_id"=>"7202080756"}], "year"=>2010, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"20808912", "sgr"=>"77957887793", "scopus"=>"2-s2.0-77957887793", "isbn"=>"1932-6203", "doi"=>"10.1371/journal.pone.0012210", "pui"=>"359754160", "issn"=>"19326203"}, "id"=>"eeab0f6f-a691-3ae8-99f8-665496c036e1", "abstract"=>"<p>Coral reefs are under increasing pressure in a changing climate, one such threat being more frequent and destructive outbreaks of coral diseases. Thermal stress from rising temperatures has been implicated as a causal factor in disease outbreaks observed on the Great Barrier Reef, Australia, and elsewhere in the world. Here, we examine seasonal effects of satellite-derived temperature on the abundance of coral diseases known as white syndromes on the Great Barrier Reef, considering both warm stress during summer and deviations from mean temperatures during the preceding winter. We found a high correlation (r<sup>2</sup> = 0.953) between summer warm thermal anomalies (Hot Snap) and disease abundance during outbreak events. Inclusion of thermal conditions during the preceding winter revealed that a significant reduction in disease outbreaks occurred following especially cold winters (Cold Snap), potentially related to a reduction in pathogen loading. Furthermore, mild winters (i.e., neither excessively cool nor warm) frequently preceded disease outbreaks. In contrast, disease outbreaks did not typically occur following warm winters, potentially because of increased disease resistance of the coral host. Understanding the balance between the effects of warm and cold winters on disease outbreak will be important in a warming climate. Combining the influence of winter and summer thermal effects resulted in an algorithm that yields both a Seasonal Outlook of disease risk at the conclusion of winter and near real-time monitoring of Outbreak Risk during summer. This satellite-derived system can provide coral reef managers with an assessment of risk three-to-six months in advance of the summer season that can then be refined using near-real-time summer observations. This system can enhance the capacity of managers to prepare for and respond to possible disease outbreaks and focus research efforts to increase understanding of environmental impacts on coral disease in this era of rapidly changing climate.</p>", "link"=>"http://www.mendeley.com/research/summer-hot-snaps-winter-conditions-modelling-white-syndrome-outbreaks-great-barrier-reef-corals", "reader_count"=>83, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>5, "Student > Doctoral Student"=>2, "Researcher"=>26, "Student > Ph. D. Student"=>13, "Student > Postgraduate"=>5, "Other"=>7, "Student > Master"=>14, "Student > Bachelor"=>6, "Lecturer"=>1, "Professor"=>4}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>5, "Student > Doctoral Student"=>2, "Researcher"=>26, "Student > Ph. D. Student"=>13, "Student > Postgraduate"=>5, "Other"=>7, "Student > Master"=>14, "Student > Bachelor"=>6, "Lecturer"=>1, "Professor"=>4}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>1, "Environmental Science"=>22, "Biochemistry, Genetics and Molecular Biology"=>1, "Mathematics"=>1, "Agricultural and Biological Sciences"=>43, "Medicine and Dentistry"=>1, "Chemistry"=>1, "Decision Sciences"=>1, "Earth and Planetary Sciences"=>11}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Chemistry"=>{"Chemistry"=>1}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>11}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>43}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>1}, "Environmental Science"=>{"Environmental Science"=>22}}, "reader_count_by_country"=>{"Venezuela"=>1, "Hong Kong"=>1, "Fiji Islands"=>1, "United States"=>3, "Brazil"=>2, "Mexico"=>1, "Malaysia"=>1, "Australia"=>2}, "group_count"=>6}

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  • {"files"=>["https://ndownloader.figshare.com/files/415970"], "description"=>"<div><p>Coral reefs are under increasing pressure in a changing climate, one such threat being more frequent and destructive outbreaks of coral diseases. Thermal stress from rising temperatures has been implicated as a causal factor in disease outbreaks observed on the Great Barrier Reef, Australia, and elsewhere in the world. Here, we examine seasonal effects of satellite-derived temperature on the abundance of coral diseases known as white syndromes on the Great Barrier Reef, considering both warm stress during summer and deviations from mean temperatures during the preceding winter. We found a high correlation (r<sup>2</sup> = 0.953) between summer warm thermal anomalies (Hot Snap) and disease abundance during outbreak events. Inclusion of thermal conditions during the preceding winter revealed that a significant reduction in disease outbreaks occurred following especially cold winters (Cold Snap), potentially related to a reduction in pathogen loading. Furthermore, mild winters (i.e., neither excessively cool nor warm) frequently preceded disease outbreaks. In contrast, disease outbreaks did not typically occur following warm winters, potentially because of increased disease resistance of the coral host. Understanding the balance between the effects of warm and cold winters on disease outbreak will be important in a warming climate. Combining the influence of winter and summer thermal effects resulted in an algorithm that yields both a Seasonal Outlook of disease risk at the conclusion of winter and near real-time monitoring of Outbreak Risk during summer. This satellite-derived system can provide coral reef managers with an assessment of risk three-to-six months in advance of the summer season that can then be refined using near-real-time summer observations. This system can enhance the capacity of managers to prepare for and respond to possible disease outbreaks and focus research efforts to increase understanding of environmental impacts on coral disease in this era of rapidly changing climate.</p></div>", "links"=>[], "tags"=>["snaps", "outbreaks", "reef", "corals"], "article_id"=>142128, "categories"=>["Ecology", "Marine Biology"], "users"=>["Scott F. Heron", "Bette L. Willis", "William J. Skirving", "C. Mark Eakin", "Cathie A. Page", "Ian R. Miller"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012210"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Summer_Hot_Snaps_and_Winter_Conditions_Modelling_White_Syndrome_Outbreaks_on_Great_Barrier_Reef_Corals/142128", "title"=>"Summer Hot Snaps and Winter Conditions: Modelling White Syndrome Outbreaks on Great Barrier Reef Corals", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-17 00:35:28"}
  • {"files"=>["https://ndownloader.figshare.com/files/834596"], "description"=>"<p>Surveys undertaken as part of the AIMS LTMP and RAP programs. Red symbols indicate locations that experienced a WS outbreak observed during AIMS surveys. Survey sectors indicated for CL = Cooktown-Lizard, CA = Cairns, WH = Whitsunday, SW = Swains and CB = Capricorn-Bunker.</p>", "links"=>[], "tags"=>["reef", "locations", "surveyed"], "article_id"=>504969, "categories"=>["Ecology", "Marine Biology"], "users"=>["Scott F. Heron", "Bette L. Willis", "William J. Skirving", "C. Mark Eakin", "Cathie A. Page", "Ian R. Miller"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012210.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Map_of_the_Great_Barrier_Reef_showing_reef_locations_surveyed_for_white_syndrome_abundance_/504969", "title"=>"Map of the Great Barrier Reef showing reef locations surveyed for white syndrome abundance.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-17 01:22:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/834784"], "description"=>"<p>Shown for Slate Reef (149°55′E, 19°40′S). The Hot Snap metric accumulates when temperature exceeds the summer-mean (solid red line) plus one summer-standard-deviation (dashed red line). The Winter Condition metric accumulates anomalies with respect to the winter mean (solid-blue line) that are within the three winter months and/or below the winter-mean plus one winter-standard-deviation (dashed blue line). The Cold Snap metric accumulates when temperature drops below the winter-mean less one winter-standard-deviation (dashed blue line).</p>", "links"=>[], "tags"=>["metrics"], "article_id"=>505154, "categories"=>["Ecology", "Marine Biology"], "users"=>["Scott F. Heron", "Bette L. Willis", "William J. Skirving", "C. Mark Eakin", "Cathie A. Page", "Ian R. Miller"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012210.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Temperature_metrics_for_a_sample_temperature_time_series_/505154", "title"=>"Temperature metrics for a sample temperature time-series.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-17 01:25:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/834907"], "description"=>"<p>Outbreak threshold determined by the iterative analysis (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012210#s2\" target=\"_blank\">Methods</a>). Open blue squares correspond to disease observations interpreted as non-outbreak abundances, with the yearly-maximum non-outbreak events, all within one standard deviation of their mean, marked by blue triangles. The blue line shows the mean of non-outbreak yearly maxima (38.7 WS cases per 1500 m<sup>2</sup>); the red line is the outbreak threshold, one standard deviation (10.9 WS cases per 1500 m<sup>2</sup>) above the mean.</p>", "links"=>[], "tags"=>["abundance", "plotted", "outbreak", "events"], "article_id"=>505273, "categories"=>["Ecology", "Marine Biology"], "users"=>["Scott F. Heron", "Bette L. Willis", "William J. Skirving", "C. Mark Eakin", "Cathie A. Page", "Ian R. Miller"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012210.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_White_syndrome_abundance_plotted_against_survey_years_showing_outbreak_events_red_triangle_/505273", "title"=>"White syndrome abundance plotted against survey years, showing outbreak events (red triangle).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-17 01:27:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/834999"], "description"=>"<p>The symbol shape and colour indicate whether <i>Acropora</i> spp. coral cover was low: <30% (open orange circle), or high: ≥30% (violet square). Dashed lines indicate the outbreak threshold (50 WS cases per 1500 m<sup>2</sup>). WS counts plotted against (a) <i>Acropora</i> spp. cover; (b) Hot Snap; (c) WSSTA; (d) Cold Snap; and (e) Winter Condition.</p>", "links"=>[], "tags"=>["counts", "coral", "km"], "article_id"=>505368, "categories"=>["Ecology", "Marine Biology"], "users"=>["Scott F. Heron", "Bette L. Willis", "William J. Skirving", "C. Mark Eakin", "Cathie A. Page", "Ian R. Miller"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012210.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Variation_in_white_syndrome_disease_counts_with_coral_cover_and_4_km_satellite_metrics_/505368", "title"=>"Variation in white syndrome disease counts with coral cover and 4 km satellite metrics.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-17 01:29:28"}
  • {"files"=>["https://ndownloader.figshare.com/files/835089"], "description"=>"<p>(a) 4 km summer-stress monitoring metrics; (b) 4 km post-winter seasonal forecast metrics; (c) 50 km summer-stress monitoring metrics; and (d) 50 km post-winter seasonal forecast metrics. Coral cover of <i>Acropora</i> spp. is indicated by open orange circles (<30%); and violet squares (≥30%).</p>", "links"=>[], "tags"=>["counts", "plotted"], "article_id"=>505460, "categories"=>["Ecology", "Marine Biology"], "users"=>["Scott F. Heron", "Bette L. Willis", "William J. Skirving", "C. Mark Eakin", "Cathie A. Page", "Ian R. Miller"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012210.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Observed_disease_counts_plotted_against_satellite_metrics_/505460", "title"=>"Observed disease counts plotted against satellite metrics.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-17 01:31:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/835274"], "description"=>"<p>(a) Winter Condition for winter 2001; (b) Cold Snap for winter 2001; (c) Seasonal Outlook – Cold Snap spatially filtered by preceding mild-Winter Condition, overlaid with survey data [circle: <i>Acropora</i> cover <30%, square: <i>Acropora</i> cover ≥30%; white: disease <50 counts, yellow: 50≤ disease <100 counts, orange: 100≤ disease <200 counts, red: disease ≥200 counts]. Survey sectors indicated per <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012210#pone-0012210-g001\" target=\"_blank\">Fig. 1</a>; (d) Hot Snap for summer 2001-02; (e) Near real-time Outbreak Risk – Hot Snap spatially filtered by preceding mild-Winter Condition and/or Cold Snap event, overlaid with survey data [as for (c)]. The grey box encloses the final risk assessment products.</p>", "links"=>[], "tags"=>["metrics", "assessments"], "article_id"=>505646, "categories"=>["Ecology", "Marine Biology"], "users"=>["Scott F. Heron", "Bette L. Willis", "William J. Skirving", "C. Mark Eakin", "Cathie A. Page", "Ian R. Miller"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012210.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Maps_of_metrics_and_risk_assessments_for_2001_02_/505646", "title"=>"Maps of metrics and risk assessments for 2001-02.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-17 01:34:06"}

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