Predicting Grizzly Bear Density in Western North America
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{"title"=>"Predicting grizzly bear density in western North America", "type"=>"journal", "authors"=>[{"first_name"=>"Garth", "last_name"=>"Mowat", "scopus_author_id"=>"7003939936"}, {"first_name"=>"Douglas C.", "last_name"=>"Heard", "scopus_author_id"=>"7006700659"}, {"first_name"=>"Carl J.", "last_name"=>"Schwarz", "scopus_author_id"=>"7101995199"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84893198798", "issn"=>"19326203", "scopus"=>"2-s2.0-84893198798", "pmid"=>"24367552", "pui"=>"372231429", "isbn"=>"1932-6203 (Electronic) 1932-6203 (Linking)", "doi"=>"10.1371/journal.pone.0082757"}, "id"=>"0ed0886c-597c-3823-a589-621322c22fe3", "abstract"=>"Conservation of grizzly bears (Ursus arctos) is often controversial and the disagreement often is focused on the estimates of density used to calculate allowable kill. Many recent estimates of grizzly bear density are now available but field-based estimates will never be available for more than a small portion of hunted populations. Current methods of predicting density in areas of management interest are subjective and untested. Objective methods have been proposed, but these statistical models are so dependent on results from individual study areas that the models do not generalize well. We built regression models to relate grizzly bear density to ultimate measures of ecosystem productivity and mortality for interior and coastal ecosystems in North America. We used 90 measures of grizzly bear density in interior ecosystems, of which 14 were currently known to be unoccupied by grizzly bears. In coastal areas, we used 17 measures of density including 2 unoccupied areas. Our best model for coastal areas included a negative relationship with tree cover and positive relationships with the proportion of salmon in the diet and topographic ruggedness, which was correlated with precipitation. Our best interior model included 3 variables that indexed terrestrial productivity, 1 describing vegetation cover, 2 indices of human use of the landscape and, an index of topographic ruggedness. We used our models to predict current population sizes across Canada and present these as alternatives to current population estimates. Our models predict fewer grizzly bears in British Columbia but more bears in Canada than in the latest status review. These predictions can be used to assess population status, set limits for total human-caused mortality, and for conservation planning, but because our predictions are static, they cannot be used to assess population trend.", "link"=>"http://www.mendeley.com/research/predicting-grizzly-bear-density-western-north-america", "reader_count"=>57, "reader_count_by_academic_status"=>{"Unspecified"=>5, "Student > Doctoral Student"=>1, "Researcher"=>10, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>2, "Other"=>5, "Student > Master"=>10, "Student > Bachelor"=>9, "Professor"=>3}, "reader_count_by_user_role"=>{"Unspecified"=>5, "Student > Doctoral Student"=>1, "Researcher"=>10, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>2, "Other"=>5, "Student > Master"=>10, "Student > Bachelor"=>9, "Professor"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>8, "Environmental Science"=>20, "Nursing and Health Professions"=>3, "Agricultural and Biological Sciences"=>25, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>25}, "Computer Science"=>{"Computer Science"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>3}, "Unspecified"=>{"Unspecified"=>8}, "Environmental Science"=>{"Environmental Science"=>20}}, "reader_count_by_country"=>{"Canada"=>1, "United States"=>1, "United Kingdom"=>2, "Australia"=>1, "Portugal"=>1}, "group_count"=>7}

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  • {"files"=>["https://ndownloader.figshare.com/files/1321619"], "description"=>"<p><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757.s001\" target=\"_blank\">Appendix S1</a> for detailed description of GIS derived variables.<sup></sup> We digitized the study area boundary for each study area and calculated the average for each index using a GIS. See Table S1 in </p><p> =  the proportion of the study with pixels rated as >50% herb/shrub.<sup>1</sup> This is the sum of all pixels with >the stated percentage of described cover. For example, herb50</p><p><sup>2</sup> This is the mean human and livestock (sheep and cattle) density (summed) for the area within 10 or 50 km of the study area boundary.</p>", "links"=>[], "tags"=>["hypothesized", "grizzly", "ecosystems", "america", "variables", "derived"], "article_id"=>881531, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0082757.t001", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Factors_hypothesized_to_limit_grizzly_bear_density_in_interior_ecosystems_in_North_America_and_the_variables_we_derived_to_index_these_factors_/881531", "title"=>"Factors hypothesized to limit grizzly bear density in interior ecosystems in North America and the variables we derived to index these factors.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-12-18 03:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1321618"], "description"=>"<p><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757.s001\" target=\"_blank\">Appendix S1</a> for detailed description of GIS derived variables.<sup></sup> See Table S1 in </p><p><sup>1</sup> The kill rate in unoccupied areas was zero, but we used the mean rate of 3.7 for occupied areas during analysis so that these areas did not bias the distribution for this variable.</p>", "links"=>[], "tags"=>["grizzly"], "article_id"=>881530, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0082757.t002", "stats"=>{"downloads"=>11, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Descriptive_statistics_for_data_used_to_build_models_to_predict_grizzly_bear_density_in_interior_North_America_/881530", "title"=>"Descriptive statistics for data used to build models to predict grizzly bear density in interior North America.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-12-18 03:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1321613"], "description"=>"<p>Current population estimates were taken from government sources in British Columbia and the US and predicted population sizes were derived using our top coastal or interior model.</p>a<p><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-Hamilton2\" target=\"_blank\">[92]</a>.</p>b<p><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-Apps2\" target=\"_blank\">[68]</a>.</p>c<p><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-Proctor2\" target=\"_blank\">[93]</a>.</p>d<p>C. Servheen, USFWS, Montana, pers. com.</p>e<p><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-Kendall1\" target=\"_blank\">[64]</a>.</p>f<p><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-Servheen1\" target=\"_blank\">[67]</a>.</p>", "links"=>[], "tags"=>["grizzly", "densities", "sizes", "areas", "america", "occupied", "considered"], "article_id"=>881525, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0082757.t007", "stats"=>{"downloads"=>7, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Extrapolated_grizzly_bear_densities_and_population_sizes_for_a_selection_of_areas_in_western_North_America_that_are_currently_unoccupied_occupied_at_low_densities_or_are_considered_threatened_/881525", "title"=>"Extrapolated grizzly bear densities and population sizes for a selection of areas in western North America that are currently unoccupied, occupied at low densities, or are considered threatened.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-12-18 03:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1321612"], "description"=>"<p>These criteria can be used to confirm residency, to identify suspect predictions, evaluate a predicted level of harvest, or help decide what level of harvest to allow.</p>", "links"=>[], "tags"=>["predictions"], "article_id"=>881524, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0082757.t008", "stats"=>{"downloads"=>11, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Criteria_used_to_evaluate_individual_model_predictions_that_were_independent_of_the_model_process_/881524", "title"=>"Criteria used to evaluate individual model predictions that were independent of the model process.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-12-18 03:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1321609"], "description"=>"<p>These are 76 sites from across interior North America where salmon is a minor component of the diet. We compare this relationship between 2 variables, tree cover (a–b) and herb-shrub cover (c–d). We also present 2 levels of summary within each study area for each variable. For example, tree>10% means that we summed the pixels where tree cover was >10% and calculated the proportion of the study area where this occurred. Black bears appear to be absent from areas where grizzlies are present and trees cover < about 20% of the study area. The proportion of the study with >25% tree cover appears to best describe this process.</p>", "links"=>[], "tags"=>["vegetation", "grizzly"], "article_id"=>881521, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0082757.g003", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_relationship_between_vegetation_cover_and_grizzly_bear_density_/881521", "title"=>"The relationship between vegetation cover and grizzly bear density.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-12-18 03:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1321607"], "description"=>"<p>Areas currently unoccupied are filled with hatching. The presence of black bears throughout the study area is denoted by a black outline, partial presence of black bears by a gray outline and a hatched gray or no outline means black bears did not occur on the study area. Areas without salmon are not colour filled, those with abundant salmon are filled in red, and those where salmon were present but not abundant in rose. The black bear distribution in North America is shown in tan <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-Laliberte1\" target=\"_blank\">[91]</a>.</p>", "links"=>[], "tags"=>["grizzly"], "article_id"=>881519, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0082757.g001", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Estimates_of_grizzly_bear_density_in_North_America_/881519", "title"=>"Estimates of grizzly bear density in North America.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-12-18 03:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1321608"], "description"=>"<p>Study areas where grizzly bears were allopatric are denoted by squares and where black and brown bears were sympatric by diamonds. Open symbols denote coastal study areas where salmon was a major component of the diet; filled symbols show study areas where salmon were few. Unoccupied areas and one coastal area where brown bears were allopatric and at very high density (856) are not shown.</p>", "links"=>[], "tags"=>["grizzly"], "article_id"=>881520, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0082757.g002", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_relationship_between_grizzly_bear_density_and_mean_annual_precipitation_/881520", "title"=>"The relationship between grizzly bear density and mean annual precipitation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-12-18 03:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1321620", "https://ndownloader.figshare.com/files/1321621", "https://ndownloader.figshare.com/files/1321622", "https://ndownloader.figshare.com/files/1321623"], "description"=>"<div><p>Conservation of grizzly bears (<i>Ursus arctos</i>) is often controversial and the disagreement often is focused on the estimates of density used to calculate allowable kill. Many recent estimates of grizzly bear density are now available but field-based estimates will never be available for more than a small portion of hunted populations. Current methods of predicting density in areas of management interest are subjective and untested. Objective methods have been proposed, but these statistical models are so dependent on results from individual study areas that the models do not generalize well. We built regression models to relate grizzly bear density to ultimate measures of ecosystem productivity and mortality for interior and coastal ecosystems in North America. We used 90 measures of grizzly bear density in interior ecosystems, of which 14 were currently known to be unoccupied by grizzly bears. In coastal areas, we used 17 measures of density including 2 unoccupied areas. Our best model for coastal areas included a negative relationship with tree cover and positive relationships with the proportion of salmon in the diet and topographic ruggedness, which was correlated with precipitation. Our best interior model included 3 variables that indexed terrestrial productivity, 1 describing vegetation cover, 2 indices of human use of the landscape and, an index of topographic ruggedness. We used our models to predict current population sizes across Canada and present these as alternatives to current population estimates. Our models predict fewer grizzly bears in British Columbia but more bears in Canada than in the latest status review. These predictions can be used to assess population status, set limits for total human-caused mortality, and for conservation planning, but because our predictions are static, they cannot be used to assess population trend.</p></div>", "links"=>[], "tags"=>["grizzly"], "article_id"=>881532, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0082757.s001", "https://dx.doi.org/10.1371/journal.pone.0082757.s002", "https://dx.doi.org/10.1371/journal.pone.0082757.s003", "https://dx.doi.org/10.1371/journal.pone.0082757.s004"], "stats"=>{"downloads"=>17, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicting_Grizzly_Bear_Density_in_Western_North_America_/881532", "title"=>"Predicting Grizzly Bear Density in Western North America", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-12-18 03:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1321617"], "description"=>"<p><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757.s001\" target=\"_blank\">Appendix S1</a> for detailed description of GIS derived variables.<sup></sup> We separated areas where black bears were absent, because there were large difference in density between these areas. See Table S1 in </p>", "links"=>[], "tags"=>["grizzly"], "article_id"=>881529, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0082757.t003", "stats"=>{"downloads"=>4, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Descriptive_statistics_for_data_used_to_predict_grizzly_bear_density_in_coastal_North_America_/881529", "title"=>"Descriptive statistics for data used to predict grizzly bear density in coastal North America.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-12-18 03:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1321615"], "description"=>"<p><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone-0082757-t004\" target=\"_blank\">Table 4</a> for definition of variables; salmon  =  salmon in diet.<sup></sup> The two top-ranked models were excluded from this list, because they contained four and three uninformative variables. See </p>", "links"=>[], "tags"=>["10", "areas", "grizzly", "bears", "sympatric", "america", "relating", "variables", "hypothesized", "functionally"], "article_id"=>881527, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0082757.t005", "stats"=>{"downloads"=>7, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_top_10_model_selection_results_for_study_areas_where_grizzly_and_black_bears_were_sympatric_in_coastal_North_America_n_8202_8202_17_relating_grizzly_density_to_variables_that_were_hypothesized_to_be_functionally_related_to_density_/881527", "title"=>"The top 10 model selection results for study areas where grizzly and black bears were sympatric in coastal North America (n = 17) relating grizzly density to variables that were hypothesized to be functionally related to density.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-12-18 03:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1321616"], "description"=>"<p> =  precipitation, NDVI = normalized differential vegetation index, AET =  actual evapotranspiration, H50 =  herbaceous and shrub cover >50%, T25 =  tree cover >25%, Meat  =  terrestrial meat in diet, SP = presence of salmon in diet, LHum =  log human density, Live  =  livestock density, Harv  =  human-caused mortality, Rug  =  ruggedness.<sup></sup> The top-ranked model was excluded from this list, because it contained 2 uninformative variables. Variables are: Prcp</p>", "links"=>[], "tags"=>["10", "areas", "america", "relating", "grizzly", "variables", "hypothesized", "functionally"], "article_id"=>881528, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0082757.t004", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_top_10_model_selection_results_for_study_areas_in_interior_North_America_n_8202_8202_90_relating_grizzly_density_to_variables_that_were_hypothesized_to_be_functionally_related_to_density_/881528", "title"=>"The top 10 model selection results for study areas in interior North America (n = 90) relating grizzly density to variables that were hypothesized to be functionally related to density.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-12-18 03:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1321614"], "description"=>"<p>–5 WMUs), and territorial guide territory boundaries which were roughly similar to WMUs in size.<sup></sup> We predicted density for small portions of each province using ecological unit mapping (ecoregions-the largest units used), provincial wildlife management units (WMUs), provincial grizzly bear population units (GBPUs, groups of 1</p><p><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-FestaBianchet1\" target=\"_blank\">[94]</a> with corrections for portions of the National Parks that were not included.<sup>a</sup></p>b<p><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-Hamilton2\" target=\"_blank\">[92]</a>.</p>c<p><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-McLoughlin1\" target=\"_blank\">[9]</a>.</p>", "links"=>[], "tags"=>["numbers", "grizzly", "bears", "canada", "parks", "developed"], "article_id"=>881526, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0082757.t006", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_summary_of_predicted_numbers_of_grizzly_bears_in_Canada_and_in_National_Parks_by_province_based_on_the_coastal_and_interior_models_developed_in_this_paper_/881526", "title"=>"A summary of predicted numbers of grizzly bears in Canada and in National Parks by province, based on the coastal and interior models developed in this paper.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-12-18 03:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1321611"], "description"=>"<p>Data included 15 inventoried study areas and 2 unoccupied areas across the interior of western North America. Error bars are 95% confidence limits for observed data derived from the survey results or, estimated subjectively based on survey methods (see Methods for detailed description).</p>", "links"=>[], "tags"=>["grizzly"], "article_id"=>881523, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0082757.g005", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Observed_versus_predicted_values_of_grizzly_bear_density_bears_1000_km_2_using_the_best_fit_coastal_model_described_in_Table_5_/881523", "title"=>"Observed versus predicted values of grizzly bear density (bears/1000 km<sup>2</sup>) using the best fit coastal model described in Table 5.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-12-18 03:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1321610"], "description"=>"<p>Data included 76 inventoried study areas and 14 unoccupied areas across the interior of western North America. Error bars are 95% confidence limits for observed data derived from the survey results or estimated subjectively, based on survey methods (see Methods for detailed description). The cases with the largest residuals often had the greatest error and were hence weighted lower in the regression.</p>", "links"=>[], "tags"=>["grizzly"], "article_id"=>881522, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Garth Mowat", "Douglas C. Heard", "Carl J. Schwarz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0082757.g004", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Observed_versus_predicted_values_of_grizzly_bear_density_bears_1000_km_2_using_the_best_fit_interior_model_described_in_Table_4_/881522", "title"=>"Observed versus predicted values of grizzly bear density (bears/1000 km<sup>2</sup>) using the best fit interior model described in Table 4.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-12-18 03:44:49"}

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Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[269, 466, 588, 697, 800, 896, 988, 1076, 1165, 1254, 1340, 1417]}, {"subject_area"=>"/Biology and life sciences/Nutrition", "average_usage"=>[264, 463, 602, 708, 816, 908, 1015, 1103, 1200, 1297, 1389, 1476, 1538]}, {"subject_area"=>"/Biology and life sciences/Population biology", "average_usage"=>[269, 448, 558, 658, 744, 830, 914, 995, 1068, 1139, 1214, 1284, 1349]}, {"subject_area"=>"/Ecology and environmental sciences", "average_usage"=>[284, 475, 603, 722, 826, 928, 1026, 1129, 1225, 1310, 1390, 1468, 1549]}, {"subject_area"=>"/Ecology and environmental sciences/Ecology", "average_usage"=>[298, 487, 610, 722, 827, 929, 1029, 1125, 1217, 1306, 1388, 1464, 1535]}, {"subject_area"=>"/Medicine and health sciences/Nutrition", "average_usage"=>[273, 476, 611, 714, 821, 911, 1005, 1103, 1201, 1287, 1388, 1478, 1557]}, {"subject_area"=>"/People and places", "average_usage"=>[270, 456, 573, 676, 773, 867, 955, 1037, 1120, 1205, 1286, 1363, 1436]}, {"subject_area"=>"/People and places/Demography", "average_usage"=>[253, 440, 552, 650, 735, 820, 902, 976, 1042, 1112, 1192, 1271, 1337]}]}
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