Drought Tolerance in Wild Plant Populations: The Case of Common Beans (Phaseolus vulgaris L.)
Publication Date
May 03, 2013
Journal
PLOS ONE
Authors
Andrés J. Cortés, Fredy A. Monserrate, Julián Ramírez Villegas, Santiago Madriñán, et al
Volume
8
Issue
5
Pages
e62898
DOI
https://dx.plos.org/10.1371/journal.pone.0062898
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0062898
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/23658783
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3643911
Europe PMC
http://europepmc.org/abstract/MED/23658783
Web of Science
000321202100046
Scopus
84877051303
Mendeley
http://www.mendeley.com/research/drought-tolerance-wild-plant-populations-case-common-beans-phaseolus-vulgaris-l
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Mendeley | Further Information

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Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1052810", "https://ndownloader.figshare.com/files/1052813"], "description"=>"<div><p>Reliable estimations of drought tolerance in wild plant populations have proved to be challenging and more accessible alternatives are desirable. With that in mind, an ecological diversity study was conducted based on the geographical origin of 104 wild common bean accessions to estimate drought tolerance in their natural habitats. Our wild population sample covered a range of mesic to very dry habitats from Mexico to Argentina. Two potential evapotranspiration models that considered the effects of temperature and radiation were coupled with the precipitation regimes of the last fifty years for each collection site based on geographical information system analysis. We found that wild accessions were distributed among different precipitation regimes following a latitudinal gradient and that habitat ecological diversity of the collection sites was associated with natural sub-populations. We also detected a broader geographic distribution of wild beans across ecologies compared to cultivated common beans in a reference collection of 297 cultivars. Habitat drought stress index based on the Thornthwaite potential evapotranspiration model was equivalent to the Hamon estimator. Both ecological drought stress indexes would be useful together with population structure for the genealogical analysis of gene families in common bean, for genome-wide genetic-environmental associations, and for postulating the evolutionary history and diversification processes that have occurred for the species. Finally, we propose that wild common bean should be taken into account to exploit variation for drought tolerance in cultivated common bean which is generally considered susceptible as a crop to drought stress.</p></div>", "links"=>[], "tags"=>["Agroecology", "Ecosystems agroecology", "crops", "Crop management", "ecology", "Plant ecology", "Plant-environment interactions", "Plant science", "Botany", "plants", "geography", "Cartography", "gis", "drought", "beans"], "article_id"=>697182, "categories"=>["Medicine", "Biological Sciences", "Sociology", "Earth and Environmental Sciences"], "users"=>["Andrés J. Cortés", "Fredy A. Monserrate", "Julián Ramírez-Villegas", "Santiago Madriñán", "Matthew W. Blair"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0062898.s001", "https://dx.doi.org/10.1371/journal.pone.0062898.s002"], "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Drought_Tolerance_in_Wild_Plant_Populations_The_Case_of_Common_Beans_Phaseolus_vulgaris_L_/697182", "title"=>"Drought Tolerance in Wild Plant Populations: The Case of Common Beans (<i>Phaseolus vulgaris</i> L.)", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-05-03 01:59:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/1052807"], "description"=>"<p>Bold: significant values: <0.05 for r or <−0.5 and >0.5 for ρ.</p><p>DI<sub>T</sub>: Normalized Annual Thornthwaite Drought Index.</p><p>DI<sub>H</sub>: Normalized Annual Hamon Drought Index.</p><p>DI <sub>max N</sub>: Normalized Maximum Month Drought Index (Thornthwaite (T) or Hamon (H)).</p><p>F#i: Two main components using all bioclimatic variables (i = T), only precipitation variables (i = P), or only drought-related variables (i = S) (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062898#pone-0062898-t001\" target=\"_blank\">table 1</a>).</p><p>Original Control Bioclimatic Variables: P12: Annual Precipitation, P14: Precipitation of Driest Period, P1: Annual Mean Temperature, P9: Mean Temperature of Driest Quarter.</p>", "links"=>[], "tags"=>["Agroecology", "Ecosystems agroecology", "crops", "Crop management", "ecology", "Plant ecology", "Plant-environment interactions", "Plant science", "Botany", "plants", "geography", "Cartography", "gis", "coefficients", "climatic", "components", "drought", "severity"], "article_id"=>697179, "categories"=>["Medicine", "Biological Sciences", "Sociology", "Earth and Environmental Sciences"], "users"=>["Andrés J. Cortés", "Fredy A. Monserrate", "Julián Ramírez-Villegas", "Santiago Madriñán", "Matthew W. Blair"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062898.t003", "stats"=>{"downloads"=>2, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Pearson_8217_s_correlation_coefficients_r_8211_above_the_diagonal_and_Spearman_s_rank_correlation_coefficients_961_8211_below_the_diagonal_among_some_representative_climatic_variables_components_and_drought_severity_estimators_/697179", "title"=>"Pearson’s correlation coefficients (r – above the diagonal) and Spearman's rank correlation coefficients (ρ – below the diagonal) among some representative climatic variables, components and drought severity estimators.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-05-03 01:59:39"}
  • {"files"=>["https://ndownloader.figshare.com/files/1052806"], "description"=>"+<p>Three categories (F1–F3) are used to analyze the 19 bioclimatic variables. Three main components and the percentage of explained variance are indicated for each category.</p>*<p>Variables used in the third analysis (selected because of being strictly drought-related variables).</p><p>- Bold numbers: Variables with significant contribution in the definition of the respective component and pertinent for drought stress estimation.</p><p>- Bold and italic numbers: Variables with significant contribution in the definition of the respective component but not conceptually pertinent for drought stress estimation.</p>", "links"=>[], "tags"=>["Agroecology", "Ecosystems agroecology", "crops", "Crop management", "ecology", "Plant ecology", "Plant-environment interactions", "Plant science", "Botany", "plants", "geography", "Cartography", "gis", "bioclimatic", "pca"], "article_id"=>697178, "categories"=>["Medicine", "Biological Sciences", "Sociology", "Earth and Environmental Sciences"], "users"=>["Andrés J. Cortés", "Fredy A. Monserrate", "Julián Ramírez-Villegas", "Santiago Madriñán", "Matthew W. Blair"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062898.t001", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Contribution_of_each_bioclimatic_variable_to_the_PCA_analysis_/697178", "title"=>"Contribution (%) of each bioclimatic variable to the PCA analysis.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-05-03 01:59:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/1052800"], "description"=>"<p>A dispersion diagram between the estimated drought index using the potential evapo-transpiration (PET) of Thornthwaite and the estimated drought index using the PET of Hamon is presented in B. Populations definition as in Blair <i>et al. </i><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062898#pone.0062898-Blair2\" target=\"_blank\">[26]</a> and Broughton et al. <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062898#pone.0062898-Broughton1\" target=\"_blank\">[27]</a>.</p>", "links"=>[], "tags"=>["Agroecology", "Ecosystems agroecology", "crops", "Crop management", "ecology", "Plant ecology", "Plant-environment interactions", "Plant science", "Botany", "plants", "geography", "Cartography", "gis", "cultivated", "accessions", "precipitation", "driest", "geographic"], "article_id"=>697172, "categories"=>["Medicine", "Biological Sciences", "Sociology", "Earth and Environmental Sciences"], "users"=>["Andrés J. Cortés", "Fredy A. Monserrate", "Julián Ramírez-Villegas", "Santiago Madriñán", "Matthew W. Blair"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062898.g001", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Geographic_distribution_of_wild_104_accessions_and_cultivated_297_accessions_common_bean_accessions_A_and_precipitation_during_the_driest_period_along_the_geographic_range_of_wild_common_bean_B_/697172", "title"=>"Geographic distribution of wild (104 accessions) and cultivated (297 accessions) common bean accessions (A), and precipitation during the driest period along the geographic range of wild common bean (B).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-05-03 01:59:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/1052808"], "description"=>"<p>Variable abbreviations: P1–P19: main variables as defined in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062898#pone-0062898-t001\" target=\"_blank\">table 1</a>, DIT: Annual Mean Drought Index (Thornthwaite), DIT, Max: Maximum Drought Index (Thornthwaite), DIH: Annual Mean Drought Index (Hamon), DIH, Max: Maximum Drought Index (Hamon), F1P, F2P: Main two factors for bioclimatic precipitation variables (P12–P19), F1S, F2S: Main two factors for drought-related variables.</p><p>Kruskal-Wallis tests were applied in all cases except for DI (Drought Index) estimations, where an ANOVA followed by a Tukey’s-b post-hoc test was used. A, B and C are different ranks. Populations with more than one letter could not be assigned to a single rank. Mean for each variable for each population: A>B>C.</p><p>Bold variables: Drought-related variables. Selected variables for further analysis based on their conceptual power to describe drought tolerance.</p>", "links"=>[], "tags"=>["Agroecology", "Ecosystems agroecology", "crops", "Crop management", "ecology", "Plant ecology", "Plant-environment interactions", "Plant science", "Botany", "plants", "geography", "Cartography", "gis", "comparisons", "bioclimatic", "drought", "severity", "estimator"], "article_id"=>697180, "categories"=>["Medicine", "Biological Sciences", "Sociology", "Earth and Environmental Sciences"], "users"=>["Andrés J. Cortés", "Fredy A. Monserrate", "Julián Ramírez-Villegas", "Santiago Madriñán", "Matthew W. Blair"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062898.t002", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Pairwise_comparisons_of_significant_variation_for_each_bioclimatic_variable_component_and_drought_severity_estimator_in_relation_with_population_structure_p_value_lt_0_001_/697180", "title"=>"Pairwise comparisons of significant variation for each bioclimatic variable, component and drought severity estimator in relation with population structure (p-value<0,001).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-05-03 01:59:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/1052803"], "description"=>"<p>Arrows indicate the increase in the estimated drought stress for each component. Wild populations: M: Mesoamerican, G: Guatemala, C: Colombia, E: Ecuador-North Peru and A: Andean. Numbers in E, F and G are percentage of explained variation by each component.</p>", "links"=>[], "tags"=>["Agroecology", "Ecosystems agroecology", "crops", "Crop management", "ecology", "Plant ecology", "Plant-environment interactions", "Plant science", "Botany", "plants", "geography", "Cartography", "gis", "precipitation", "driest", "wettest", "thornthwaite", "drought", "hamon", "components", "pca", "bioclimatic", "variables", "drought-related"], "article_id"=>697175, "categories"=>["Medicine", "Biological Sciences", "Sociology", "Earth and Environmental Sciences"], "users"=>["Andrés J. Cortés", "Fredy A. Monserrate", "Julián Ramírez-Villegas", "Santiago Madriñán", "Matthew W. Blair"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062898.g003", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Scatter_plots_for_A_mean_annual_precipitation_P12_and_precipitation_of_the_driest_period_P14_B_mean_annual_precipitation_P12_and_precipitation_of_the_wettest_period_P13_C_mean_and_maximum_Thornthwaite_Drought_Index_DI_D_mean_and_maximum_Hamon_DI_E_two_ma/697175", "title"=>"Scatter plots for: A.mean annual precipitation (P12) and precipitation of the driest period (P14), B. mean annual precipitation (P12) and precipitation of the wettest period (P13), C. mean and maximum Thornthwaite Drought Index (DI), D. mean and maximum Hamon DI, E. two main components of the PCA for all bioclimatic variables (P1–P19– table 1), F. two main components of the PCA for precipitation related bioclimatic variables (P12–P19– table 1), and G. two main components of the PCA for drought-related bioclimatic variables (table 1).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-05-03 01:59:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/1052802"], "description"=>"<p>Temporal variation of precipitation (bars), maximum temperature (red squares) and minimum temperature (blue squares) in different representative regions: A. Mexico (−102° latitude, 20° longitude), B. Guatemala (−90°, 14°), C. Colombia (−74°, 4°), D. Ecuador-North Peru (−80°, −4°) and E. Argentina (−65°, −24°).</p>", "links"=>[], "tags"=>["Agroecology", "Ecosystems agroecology", "crops", "Crop management", "ecology", "Plant ecology", "Plant-environment interactions", "Plant science", "Botany", "plants", "geography", "Cartography", "gis", "precipitation", "mexico", "guatemala", "colombia", "ecuador-north", "peru", "argentina"], "article_id"=>697174, "categories"=>["Medicine", "Biological Sciences", "Sociology", "Earth and Environmental Sciences"], "users"=>["Andrés J. Cortés", "Fredy A. Monserrate", "Julián Ramírez-Villegas", "Santiago Madriñán", "Matthew W. Blair"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062898.g002", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Temporal_variation_of_precipitation_bars_maximum_temperature_red_squares_and_minimum_temperature_blue_squares_in_different_representative_regions_A_Mexico_8722_102_176_latitude_20_176_longitude_B_Guatemala_8722_90_176_14_176_C_Colombia_8722_74_176_4_176_/697174", "title"=>"Temporal variation of precipitation (bars), maximum temperature (red squares) and minimum temperature (blue squares) in different representative regions: A. Mexico (−102° latitude, 20° longitude), B. Guatemala (−90°, 14°), C. Colombia (−74°, 4°), D. Ecuador-North Peru (−80°, −4°) and E. Argentina (−65°, −24°).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-05-03 01:59:34"}

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Relative Metric

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