Strong Discrepancies between Local Temperature Mapping and Interpolated Climatic Grids in Tropical Mountainous Agricultural Landscapes
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{"title"=>"Strong discrepancies between local temperature mapping and interpolated climatic grids in tropical mountainous agricultural landscapes", "type"=>"journal", "authors"=>[{"first_name"=>"Emile", "last_name"=>"Faye", "scopus_author_id"=>"56069580100"}, {"first_name"=>"Mario", "last_name"=>"Herrera", "scopus_author_id"=>"55498738400"}, {"first_name"=>"Lucio", "last_name"=>"Bellomo", "scopus_author_id"=>"35241733900"}, {"first_name"=>"Jean François", "last_name"=>"Silvain", "scopus_author_id"=>"56505650900"}, {"first_name"=>"Olivier", "last_name"=>"Dangles", "scopus_author_id"=>"35329441800"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"isbn"=>"1932-6203", "sgr"=>"84930216870", "pui"=>"373796847", "pmid"=>"25141212", "issn"=>"19326203", "scopus"=>"2-s2.0-84930216870", "doi"=>"10.1371/journal.pone.0105541"}, "id"=>"153169fb-cb1a-385f-bf68-4cb6bdae7f18", "abstract"=>"Bridging the gap between the predictions of coarse-scale climate models and the fine-scale climatic reality of species is a key issue of climate change biology research. While it is now well known that most organisms do not experience the climatic conditions recorded at weather stations, there is little information on the discrepancies between microclimates and global interpolated temperatures used in species distribution models, and their consequences for organisms’ performance. To address this issue, we examined the fine-scale spatiotemporal heterogeneity in air, crop canopy and soil temperatures of agricultural landscapes in the Ecuadorian Andes and compared them to predictions of global interpolated climatic grids. Temperature time-series were measured in air, canopy and soil for 108 localities at three altitudes and analysed using Fourier transform. Discrepancies between local temperatures vs. global interpolated grids and their implications for pest performance were then mapped and analysed using GIS statistical toolbox. Our results showed that global interpolated predictions over-estimate by 77.5±10% and under-estimate by 82.1±12% local minimum and maximum air temperatures recorded in the studied grid. Additional modifications of local air temperatures were due to the thermal buffering of plant canopies (from −2.7°K during daytime to 1.3°K during night-time) and soils (from −4.9°K during daytime to 6.7°K during night-time) with a significant effect of crop phenology on the buffer effect. This discrepancies between interpolated and local temperatures strongly affected predictions of the performance of an ectothermic crop pest as interpolated temperatures predicted pest growth rates 2.3–4.3 times lower than those predicted by local temperatures. This study provides quantitative information on the limitation of coarse-scale climate data to capture the reality of the climatic environment experienced by living organisms. In highly heterogeneous region such as tropical mountains, caution should therefore be taken when using global models to infer local-scale biological processes.", "link"=>"http://www.mendeley.com/research/strong-discrepancies-between-local-temperature-mapping-interpolated-climatic-grids-tropical-mountain", "reader_count"=>36, "reader_count_by_academic_status"=>{"Student > Doctoral Student"=>2, "Researcher"=>10, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>1, "Student > Master"=>6, "Student > Bachelor"=>7, "Professor"=>3}, "reader_count_by_user_role"=>{"Student > Doctoral Student"=>2, "Researcher"=>10, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>1, "Student > Master"=>6, "Student > Bachelor"=>7, "Professor"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Environmental Science"=>8, "Agricultural and Biological Sciences"=>20, "Arts and Humanities"=>1, "Social Sciences"=>2, "Earth and Planetary Sciences"=>2}, "reader_count_by_subdiscipline"=>{"Social Sciences"=>{"Social Sciences"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>20}, "Unspecified"=>{"Unspecified"=>3}, "Environmental Science"=>{"Environmental Science"=>8}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "reader_count_by_country"=>{"Finland"=>1, "Brazil"=>1, "Spain"=>2}, "group_count"=>1}

Scopus | Further Information

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/1644824", "https://ndownloader.figshare.com/files/1644825", "https://ndownloader.figshare.com/files/1644826", "https://ndownloader.figshare.com/files/1644827", "https://ndownloader.figshare.com/files/1644828", "https://ndownloader.figshare.com/files/1644829", "https://ndownloader.figshare.com/files/1644830", "https://ndownloader.figshare.com/files/1644831", "https://ndownloader.figshare.com/files/1644832", "https://ndownloader.figshare.com/files/1644833", "https://ndownloader.figshare.com/files/1644834"], "description"=>"<div><p>Bridging the gap between the predictions of coarse-scale climate models and the fine-scale climatic reality of species is a key issue of climate change biology research. While it is now well known that most organisms do not experience the climatic conditions recorded at weather stations, there is little information on the discrepancies between microclimates and global interpolated temperatures used in species distribution models, and their consequences for organisms’ performance. To address this issue, we examined the fine-scale spatiotemporal heterogeneity in air, crop canopy and soil temperatures of agricultural landscapes in the Ecuadorian Andes and compared them to predictions of global interpolated climatic grids. Temperature time-series were measured in air, canopy and soil for 108 localities at three altitudes and analysed using Fourier transform. Discrepancies between local temperatures vs. global interpolated grids and their implications for pest performance were then mapped and analysed using GIS statistical toolbox. Our results showed that global interpolated predictions over-estimate by 77.5±10% and under-estimate by 82.1±12% local minimum and maximum air temperatures recorded in the studied grid. Additional modifications of local air temperatures were due to the thermal buffering of plant canopies (from −2.7°K during daytime to 1.3°K during night-time) and soils (from −4.9°K during daytime to 6.7°K during night-time) with a significant effect of crop phenology on the buffer effect. This discrepancies between interpolated and local temperatures strongly affected predictions of the performance of an ectothermic crop pest as interpolated temperatures predicted pest growth rates 2.3–4.3 times lower than those predicted by local temperatures. This study provides quantitative information on the limitation of coarse-scale climate data to capture the reality of the climatic environment experienced by living organisms. In highly heterogeneous region such as tropical mountains, caution should therefore be taken when using global models to infer local-scale biological processes.</p></div>", "links"=>[], "tags"=>["gis", "air temperatures", "ectothermic crop pest", "grid", "Tropical Mountainous Agricultural Landscapes Bridging", "Interpolated Climatic Grids", "Local Temperature Mapping", "prediction", "climate change biology research", "species distribution models", "performance", "organism"], "article_id"=>1147220, "categories"=>["Biological Sciences"], "users"=>["Emile Faye", "Mario Herrera", "Lucio Bellomo", "Jean-François Silvain", "Olivier Dangles"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0105541.s001", "https://dx.doi.org/10.1371/journal.pone.0105541.s002", "https://dx.doi.org/10.1371/journal.pone.0105541.s003", "https://dx.doi.org/10.1371/journal.pone.0105541.s004", "https://dx.doi.org/10.1371/journal.pone.0105541.s005", "https://dx.doi.org/10.1371/journal.pone.0105541.s006", "https://dx.doi.org/10.1371/journal.pone.0105541.s007", "https://dx.doi.org/10.1371/journal.pone.0105541.s008", "https://dx.doi.org/10.1371/journal.pone.0105541.s009", "https://dx.doi.org/10.1371/journal.pone.0105541.s010", "https://dx.doi.org/10.1371/journal.pone.0105541.s011"], "stats"=>{"downloads"=>29, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Strong_Discrepancies_between_Local_Temperature_Mapping_and_Interpolated_Climatic_Grids_in_Tropical_Mountainous_Agricultural_Landscapes_/1147220", "title"=>"Strong Discrepancies between Local Temperature Mapping and Interpolated Climatic Grids in Tropical Mountainous Agricultural Landscapes", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-08-20 04:17:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1644806"], "description"=>"<p><b>Bold*</b> indicates significant results (P<0.05).</p>", "links"=>[], "tags"=>["gis", "air temperatures", "ectothermic crop pest", "grid", "Tropical Mountainous Agricultural Landscapes Bridging", "Interpolated Climatic Grids", "Local Temperature Mapping", "prediction", "climate change biology research", "species distribution models", "performance", "organism"], "article_id"=>1147203, "categories"=>["Biological Sciences"], "users"=>["Emile Faye", "Mario Herrera", "Lucio Bellomo", "Jean-François Silvain", "Olivier Dangles"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105541.t001", "stats"=>{"downloads"=>3, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Results_of_the_two_way_ANOVA_with_a_Bonferroni_correction_on_the_effects_of_habitat_elevation_LAI_and_elevation_215_LAI_terms_on_daytime_and_nigh_time_DFT_amplitudes_and_thermal_time_lag_on_inside_canopy_and_soil_temperature_time_series_/1147203", "title"=>"Results of the two-way ANOVA with a Bonferroni correction on the effects of habitat, elevation, LAI and elevation × LAI terms on daytime and nigh-time DFT amplitudes and thermal time lag on inside-canopy and soil temperature time series.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-08-20 04:17:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1644789"], "description"=>"<p>Blue colours indicate <i>Δ Air <sub>L </sub></i><b><i>−</i></b><i> Air <sub>WC</sub></i> <0, i.e. area where local air temperatures are cooler than those gave by WorldClim. Red colours indicate <i>Δ Air <sub>L </sub></i><b><i>−</i></b><i> Air <sub>WC</sub></i> >0, i.e. area where air local temperatures are warmer than the ones gave by the WorldClim. White colours <i>Δ Air <sub>L </sub></i><b><i>−</i></b><i> Air <sub>WC</sub></i> = 0 indicate areas where air WorldClim temperatures equate air local temperatures (±1°C). The extent and position of each square is equal to the spatial resolution of the WorldClim database: 30-arc sec that is the equivalent of 0.86 km<sup>2</sup> for the study area. Temperatures in storages were obtained from <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105541#pone.0105541-CrespoPerez1\" target=\"_blank\">[26]</a>.</p>", "links"=>[], "tags"=>["gis", "air temperatures", "ectothermic crop pest", "grid", "Tropical Mountainous Agricultural Landscapes Bridging", "Interpolated Climatic Grids", "Local Temperature Mapping", "prediction", "climate change biology research", "species distribution models", "performance", "organism"], "article_id"=>1147188, "categories"=>["Biological Sciences"], "users"=>["Emile Faye", "Mario Herrera", "Lucio Bellomo", "Jean-François Silvain", "Olivier Dangles"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105541.g002", "stats"=>{"downloads"=>2, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Maps_showing_the_differences_between_local_air_temperatures_and_the_WorldClim_interpolated_minimum_A_and_maximum_B_Air_L_8722_Air_WC_/1147188", "title"=>"Maps showing the differences between local air temperatures and the WorldClim interpolated minimum (A) and maximum (B) <i>(Δ Air <sub>L</sub> − Air <sub>WC</sub></i>).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-20 04:17:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1644805"], "description"=>"<p>Grey (shaded) bands in the background represent the WorldClim minimum and maximum temperature range.</p>", "links"=>[], "tags"=>["gis", "air temperatures", "ectothermic crop pest", "grid", "Tropical Mountainous Agricultural Landscapes Bridging", "Interpolated Climatic Grids", "Local Temperature Mapping", "prediction", "climate change biology research", "species distribution models", "performance", "organism"], "article_id"=>1147202, "categories"=>["Biological Sciences"], "users"=>["Emile Faye", "Mario Herrera", "Lucio Bellomo", "Jean-François Silvain", "Olivier Dangles"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105541.g006", "stats"=>{"downloads"=>4, "page_views"=>122, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Superimposed_plot_of_the_temperature_dependent_growth_rate_curve_of_the_potato_moth_Phthorimaea_operculella_dashed_line_and_the_frequency_distribution_of_area_of_average_minimum_blue_maximum_red_and_mean_striped_temperatures_for_canopy_and_soil_layers_at/1147202", "title"=>"Superimposed plot of the temperature-dependent growth rate curve of the potato moth Phthorimaea operculella (dashed line) and the frequency distribution (% of area) of average minimum (blue), maximum (red) and mean (striped) temperatures for canopy and soil layers at the three studied elevations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-20 04:17:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1644800"], "description"=>"<p>(A, C) show the daytime temperature excursion with respect to air, whereas (B, D) are the equivalent results for night-time temperatures. The 95% interval of confidence is given between brackets. Blue colours show colder temperatures than air. Red colours show warmer temperatures than air.</p>", "links"=>[], "tags"=>["gis", "air temperatures", "ectothermic crop pest", "grid", "Tropical Mountainous Agricultural Landscapes Bridging", "Interpolated Climatic Grids", "Local Temperature Mapping", "prediction", "climate change biology research", "species distribution models", "performance", "organism"], "article_id"=>1147197, "categories"=>["Biological Sciences"], "users"=>["Emile Faye", "Mario Herrera", "Lucio Bellomo", "Jean-François Silvain", "Olivier Dangles"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105541.g004", "stats"=>{"downloads"=>0, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mean_thermal_buffering_from_Fourier_transforms_at_the_daily_frequency_for_canopy_A_B_and_soil_temperatures_C_D_as_a_function_of_elevation_and_leaf_area_index_/1147197", "title"=>"Mean thermal buffering from Fourier transforms at the daily frequency for canopy (A, B) and soil temperatures (C, D) as a function of elevation and leaf area index.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-20 04:17:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1644802"], "description"=>"<p>The z-axis (log+1 transformed) is expressed in minutes (A) and in hours (B).</p>", "links"=>[], "tags"=>["gis", "air temperatures", "ectothermic crop pest", "grid", "Tropical Mountainous Agricultural Landscapes Bridging", "Interpolated Climatic Grids", "Local Temperature Mapping", "prediction", "climate change biology research", "species distribution models", "performance", "organism"], "article_id"=>1147199, "categories"=>["Biological Sciences"], "users"=>["Emile Faye", "Mario Herrera", "Lucio Bellomo", "Jean-François Silvain", "Olivier Dangles"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0105541.g005", "stats"=>{"downloads"=>0, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Thermal_time_lag_from_Fourier_transforms_at_the_daily_frequency_for_canopy_A_and_soil_temperatures_B_as_a_function_of_elevation_and_leaf_area_index_/1147199", "title"=>"Thermal time lag from Fourier transforms at the daily frequency for canopy (A) and soil temperatures (B) as a function of elevation and leaf area index.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-20 04:17:19"}

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Relative Metric

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