Predicting Climate Change Impacts on the Amount and Duration of Autumn Colors in a New England Forest
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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/982808"], "description"=>"<p>The amount of autumn color (0–100) is calculated as <i>i</i><sub>n</sub>(100−<i>j</i><sub>n</sub>) on day <i>n</i>, where the percentage of red leaves <i>i</i><sub>n</sub> is multiplied by the percentage of leaves retained (100−<i>j</i><sub>n</sub>). Individual years (1993–2010) are shown by dotted lines, and their average by the thick curve.</p>", "links"=>[], "tags"=>["autumn", "colors", "deciduous", "broadleaf"], "article_id"=>648858, "categories"=>["Information And Computing Sciences", "Plant Biology"], "users"=>["Marco Archetti", "Andrew D. Richardson", "John O'Keefe", "Nicolas Delpierre"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0057373.g001", "stats"=>{"downloads"=>0, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_amount_of_autumn_colors_over_time_for_eight_deciduous_broadleaf_species_that_turn_red_in_autumn_/648858", "title"=>"The amount of autumn colors over time for eight deciduous broadleaf species that turn red in autumn.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-09 12:28:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/982827"], "description"=>"<p>Each point (<i>x</i>,<i>y</i>) in each plot represents a time window spanning the <i>y</i> weeks (vertical axis) before day <i>x</i> (horizontal axis). The color at each point (<i>x</i>,<i>y</i>) represents the correlation between the average air temperature for the time window (<i>x</i>,<i>y</i>) and the measure of autumn leaf phenology for that plot: onset of autumn colors (<i>c</i><sub>i</sub>), time of leaf fall (<i>f</i><sub>i</sub>), duration of autumn colors (<i>d</i><sub>i</sub>) and total amount of color (<i>A</i>). Values of <i>R</i> are shown by colors ranging from orange-red (minimum, negative) to blue-purple (maximum, positive); absolute values of <i>R</i>>0.468 (the critical value of the Pearson product-moment correlation coefficient; <i>p</i> = 0.05; <i>d.f.</i> = 16) are inside the bold lines. Here, both leaf fall and the display of red leaves were shifted significantly later in years with warmer autumn temperatures. Dates of the full display of autumn colors (<i>c</i><sub>75</sub>, <i>c</i><sub>90</sub>) were positively correlated with temperatures from spring through (especially) autumn, while warmer spring temperatures are correlated with earlier onset of color (<i>c</i><sub>10</sub>). Both the duration of autumn colors (<i>d</i><sub>x</sub>) and the total amount of autumn color (<i>A</i>) tended to increase in years with warmer temperatures.</p>", "links"=>[], "tags"=>["interannual", "autumn", "phenology"], "article_id"=>648871, "categories"=>["Information And Computing Sciences", "Plant Biology"], "users"=>["Marco Archetti", "Andrew D. Richardson", "John O'Keefe", "Nicolas Delpierre"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0057373.g003", "stats"=>{"downloads"=>1, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Correlation_between_interannual_variation_in_temperature_and_interannual_variation_in_autumn_color_phenology_in_red_maple_Acer_rubrum_/648871", "title"=>"Correlation between interannual variation in temperature and interannual variation in autumn color phenology in red maple, <i>Acer rubrum</i>.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-09 12:30:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/982843", "https://ndownloader.figshare.com/files/982866", "https://ndownloader.figshare.com/files/982881", "https://ndownloader.figshare.com/files/982882"], "description"=>"<div><p>Climate change affects the phenology of many species. As temperature and precipitation are thought to control autumn color change in temperate deciduous trees, it is possible that climate change might also affect the phenology of autumn colors. Using long-term data for eight tree species in a New England hardwood forest, we show that the timing and cumulative amount of autumn color are correlated with variation in temperature and precipitation at specific times of the year. A phenological model driven by accumulated cold degree-days and photoperiod reproduces most of the interspecific and interannual variability in the timing of autumn colors. We use this process-oriented model to predict changes in the phenology of autumn colors to 2099, showing that, while responses vary among species, climate change under standard IPCC projections will lead to an overall increase in the amount of autumn colors for most species.</p> </div>", "links"=>[], "tags"=>["predicting", "impacts", "duration", "autumn", "colors", "england", "forest"], "article_id"=>648885, "categories"=>["Information And Computing Sciences", "Plant Biology"], "users"=>["Marco Archetti", "Andrew D. Richardson", "John O'Keefe", "Nicolas Delpierre"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0057373.s001", "https://dx.doi.org/10.1371/journal.pone.0057373.s002", "https://dx.doi.org/10.1371/journal.pone.0057373.s003", "https://dx.doi.org/10.1371/journal.pone.0057373.s004"], "stats"=>{"downloads"=>17, "page_views"=>25, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Predicting_Climate_Change_Impacts_on_the_Amount_and_Duration_of_Autumn_Colors_in_a_New_England_Forest__/648885", "title"=>"Predicting Climate Change Impacts on the Amount and Duration of Autumn Colors in a New England Forest", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-03-09 12:34:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/982839"], "description"=>"<p>For each species, the process-oriented (CDD/P) model, calibrated to 18 years of field data, was run forward using statistically downscaled climate projections from the GFDL CM2 model (IPCC A1fi and B1 scenarios; only A1fi scenario results shown in panels a through c). Projected rates of change (as plotted on the y-axis) were then calculated as the slope of the linear regression line between each phenological variable and year, over the period 2010–2099. Thus, for panels a through c, units are days per year, whereas for d, units are amount of color/year. ACRU: <i>Acer rubrum</i>; ACSA: <i>Acer saccharum</i>; FRAM: <i>Fraxinus americana</i>; NYSY: <i>Nyssa sylvatica</i>; PRSE: <i>Prunus serotina</i>; QUAL: <i>Quercus alba</i>; QURU: <i>Quercus rubra</i>: QUVE: <i>Quercus velutina</i>.</p>", "links"=>[], "tags"=>["rates", "coloration", "dates", "thresholds", "duration", "days", "autumn", "colors"], "article_id"=>648881, "categories"=>["Information And Computing Sciences", "Plant Biology"], "users"=>["Marco Archetti", "Andrew D. Richardson", "John O'Keefe", "Nicolas Delpierre"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0057373.g005", "stats"=>{"downloads"=>0, "page_views"=>17, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Projected_rates_of_change_in_the_timing_of_leaf_coloration_and_leaf_fall_5a_and_5b_dates_at_which_thresholds_of_10_25_50_75_and_90_were_reached_leaf_color_duration_5c_number_of_days_between_different_leaf_color_duration_thresholds_and_90_leaf_fall_and_to/648881", "title"=>"Projected rates of change in the timing of leaf coloration and leaf fall (5a and 5b; dates at which thresholds of 10%, 25%, 50%, 75% and 90% were reached), leaf color duration (5c; number of days between different leaf color duration thresholds and 90% leaf fall), and total amount of autumn colors (5d).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-09 12:31:51"}
  • {"files"=>["https://ndownloader.figshare.com/files/982837"], "description"=>"<p>Comparison of goodness-of-fit (in terms of RMSE) of empirical (MLR) and process-oriented (CDD/P) models for leaf coloration (left) and leaf fall (right), in a leave-one-out cross-validation analysis. The MLR model is shown to be less robust, as its RMSE is higher (to the right of the 1∶1 line) in a majority of cases.</p>", "links"=>[], "tags"=>["empirical", "process-oriented"], "article_id"=>648879, "categories"=>["Information And Computing Sciences", "Plant Biology"], "users"=>["Marco Archetti", "Andrew D. Richardson", "John O'Keefe", "Nicolas Delpierre"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0057373.g004", "stats"=>{"downloads"=>10, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_the_empirical_and_process_oriented_models_/648879", "title"=>"Comparison of the empirical and process-oriented models.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-09 12:31:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/982815"], "description"=>"<p><b>2a:</b> timing of leaf coloration stages (c<sub>10</sub> = 10% of leaves colored … c<sub>90</sub> = 90% of leaves coloured) for <i>Quercus alba</i>, white oak. <b>2b:</b> timing of 50% leaf fall for four species (ACRU  =  <i>Acer rubrum</i>; FRAM  =  <i>Fraxinus americana</i>, PRSE  =  <i>Prunus serotina</i>; QURU  =  <i>Quercus rubra</i>).</p>", "links"=>[], "tags"=>["variability", "autumn", "senescence"], "article_id"=>648861, "categories"=>["Information And Computing Sciences", "Plant Biology"], "users"=>["Marco Archetti", "Andrew D. Richardson", "John O'Keefe", "Nicolas Delpierre"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0057373.g002", "stats"=>{"downloads"=>0, "page_views"=>23, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Interannual_variability_of_autumn_senescence_stages_/648861", "title"=>"Interannual variability of autumn senescence stages.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-09 12:29:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1006612"], "description"=>"<p>AICc  =  Akaike's Information Criterion, corrected for small samples (△AIC  =  AICc(MLR) – AICc(CDD/P)); ME  =  model efficiency; P  =  number of fit parameters. ACRU: <i>Acer rubrum</i>; ACSA: <i>Acer saccharum</i>; FRAM: <i>Fraxins americana</i>; NYSY: <i>Nyssa sylvatica</i>; PRSE: <i>Prunus serotina</i>; QUAL: <i>Quercus alba</i>; QURU: <i>Quercus rubra</i>: QUVE: <i>Quercus velutina</i>.</p>", "links"=>[], "tags"=>["process-oriented", "calculated", "trajectory", "coloration"], "article_id"=>667236, "categories"=>["Information And Computing Sciences", "Plant Biology"], "users"=>["Marco Archetti", "Andrew D. Richardson", "John O'Keefe", "Nicolas Delpierre"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0057373.t001", "stats"=>{"downloads"=>3, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Empirical_MLR_and_process_oriented_CDD_P_model_fit_statistics_calculated_across_the_entire_trajectory_of_leaf_coloration_c_10_8230_c_90_and_leaf_fall_f_10_8230_f_90_for_all_eight_study_species_/667236", "title"=>"Empirical (MLR) and process-oriented (CDD/P) model fit statistics, calculated across the entire trajectory of leaf coloration (<i>c</i><sub>10</sub> … <i>c</i><sub>90</sub>) and leaf fall (<i>f</i><sub>10</sub> … <i>f</i><sub>90</sub>) for all eight study species.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-08 02:00:36"}

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Relative Metric

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