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Inflorescence and fruit traits of 88 Asteraceae species
<p>This data set includes information on inflorescence and fruit tratis on 88 different Asteraceae species. This information was collected after studying material from two herbaria: the Asteraceae collection of the Swedish Natural History Museum Herbarium (S), and the Herbarium of the University of Coimbra (COI). We collected for each species its sexual system, head diameter (dcap), receptacle area (area), number of flowers per head (nflw), density of flowers per head (densflw), size of outermost fruits (mean.size.outer), size of innermost fruits (mean.size.inner) and the fruit size difference between both (FSD) measured as the magnitude of the difference among the size of the outer and inner fruits.</p> <p>This data set is the main data set used in article published in bioRxiv.org: (bioRxiv 356147; doi: DOI: 10.1101/356147, which has been peer-reviewed and recommended by:<em> Peer Community in Evolutionary Biology</em> (DOI: 10.24072/pci.ecology.1000069):</p> <p>Torices R, Afonso A, Anderberg AA, Gómez JM, and Méndez M. (2019). Architectural traits constrain the evolution of unisexual flowers and sexual segregation within inflorescences: an interspecific approach. bioRxiv 236646, ver 3 peer-reviewed and recommended by PCI Evol Biol. DOI: 10.1101/356147.</p>
Functional traits of tree species in old-growth and selectively logged forest
<b>Description: </b><p>Traits matrix for tree species in selectively logged forest at SAFE and in old-growth forest in Danum Valley and Maliau Basin. Sampled during the BALI project traits campaign</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/55"><b>Biodiversity and land-use impacts on tropical ecosystem function (BALI): Quantifying functional trait distributions across the disturbance gradient</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC (Standard grant, NE/K016253/1)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (Research licence JKM/MBS.1000-2.2(385))</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3247631">here</a></p><p><b>Files: </b>This dataset consists of 3 files: Both_tree_functional_traits.xlsx, CSP_protocol_Chlorophyll_and_Carotenoids.pdf, CSP_protocol_Phenols_Tannins_Analysis.pdf</p><p><b>Both_tree_functional_traits.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Tree_functional_traits</b> (described in worksheet Tree_functional_traits)</p><p>Description: Traits matrix for tree species at SAFE and in Danum Valley, Maliau Basin sampled during the BALI project traits campaign</p><p>Number of fields: 84</p><p>Number of data rows: 717</p><p>Fields: </p><ul><li><b>location</b>: Location (Field type: Categorical)</li><li><b>forest_type</b>: Forest type: OG: old-growth plots, Maliau and Danum; SL: selectively logged plots at SAFE (Field type: Categorical)</li><li><b>forestplots_name</b>: Plot name coherent with forestplots database (Field type: ID)</li><li><b>plot_name_trait_campaign</b>: Plot name used during the BALI trait campaign (Field type: ID)</li><li><b>sample_code</b>: Sample code referencing: plot-'T'(ree) ID-branch type (Field type: ID)</li><li><b>branch_type</b>: Binary classification of branch sampled depending on their position in the tree crown. BS: sun branch; BSH: shade branch (Field type: ID)</li><li><b>sampling_date</b>: Date of sampling (Field type: Date)</li><li><b>tree_id</b>: Reference for tree tag label (Field type: ID)</li><li><b>species</b>: Tree species (Field type: Taxa)</li><li><b>height.m</b>: Height of tree individual (Field type: Numeric trait)</li><li><b>total_K_mg.g</b>: Foliar potassium content in mg per g dry weight (Field type: Numeric trait)</li><li><b>total_Ca_mg.g</b>: Foliar calcium content in mg per g dry weight (Field type: Numeric trait)</li><li><b>total_Mg_mg.g</b>: Foliar magnesium content in mg per g dry weight (Field type: Numeric trait)</li><li><b>total_P_mg.g</b>: Foliar phosporus content in mg per g dry weight (Field type: Numeric trait)</li><li><b>N_perc</b>: Foliar nitrogen concentration (Field type: Numeric trait)</li><li><b>15N_per_mil</b>: Foliar 15N isotope concentration (Field type: Numeric trait)</li><li><b>C_perc</b>: Foliar carbon concentration (Field type: Numeric trait)</li><li><b>13C_per_mil</b>: Foliar 13C isotope concentration, expressed relative to Vienna Pee Dee Belemnite (VPDB) as δ13C in units of per mil [‰] (Field type: Numeric trait)</li><li><b>CN</b>: Foliar carbon nitrogen ratio (Field type: Numeric trait)</li><li><b>DR_mean</b>: Mean dark respiration measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric trait)</li><li><b>DR_sd</b>: Standard deviation of dark respiration measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric)</li><li><b>DR_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>Asat_cons_mean</b>: Mean light-saturated net photosynthesis measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch. Data cleaning very conservative: subset of values only with conductance higher 0.04, Ci between 150 - 300, and PS higher than 1, leading to fewer data points. (Field type: Numeric trait)</li><li><b>Asat_cons_sd</b>: Standard deviation of light-saturated net photosynthesis measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric)</li><li><b>Asat_cons_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>Amax_cons_mean</b>: Mean maximum photosynthetic capacity measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch. Data cleaning very conservative: subset of values only with conductance higher 0.04, Ci between 150 - 300, and PS higher than 1, leading to fewer data points. (Field type: Numeric trait)</li><li><b>Amax_cons_sd</b>: Standard deviation of maximum photosynthetic capacity measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric)</li><li><b>Amax_cons_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>Asat_mean</b>: Mean light-saturated net photosynthesis measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric trait)</li><li><b>Asat_sd</b>: Standard deviation of light-saturated net photosynthesis measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric)</li><li><b>Asat_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>Amax_mean</b>: Mean maximum photosynthetic capacity measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric trait)</li><li><b>Amax_sd</b>: Standard deviation of maximum photosynthetic capacity measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric)</li><li><b>Amax_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>LA_cm2_mean</b>: Mean leaf area (LA) calculated from fresh leaves collected from branches, scanned immediately. (Field type: Numeric trait)</li><li><b>LA_cm2_sd</b>: Standard deviation of leaf area (Field type: Numeric)</li><li><b>LA_cm2_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>leaf_thickness_mm_mean</b>: Mean thickness of leaf (Field type: Numeric trait)</li><li><b>fresh_weight_g_mean</b>: Mean leaf fresh weight (Field type: Numeric trait)</li><li><b>dry_weight_g_mean</b>: Mean leaf oven-dried weight (Field type: Numeric trait)</li><li><b>dry_weight_mg_mean</b>: Mean leaf oven-dried weight (Field type: Numeric trait)</li><li><b>LDMC_mg.g_mean</b>: Leaf dry-matter content (LDMC) is the oven-dry mass (mg) of a leaf, divided by its water-saturated fresh mass (g) mg g–1 (Field type: Numeric trait)</li><li><b>leaf_thickness_mm_sd</b>: Standard deviation of leaf thickness (Field type: Numeric)</li><li><b>fresh_weight_g_sd</b>: Standard deviation of fresh leaf weight (Field type: Numeric)</li><li><b>dry_weight_g_sd</b>: Standard deviation of dry leaf weight (Field type: Numeric)</li><li><b>dry_weight_mg_sd</b>: Standard deviation of dry leaf weight (Field type: Numeric)</li><li><b>LDMC_mg.g_sd</b>: Standard deviation of leaf dry matter content (Field type: Numeric)</li><li><b>leaf_thickness_mm_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>fresh_weight_g_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>dry_weight_g_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>dry_weight_mg_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>LDMC_mg.g_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>branch_height_m</b>: Height from where branch sample was taken (Field type: Numeric trait)</li><li><b>chla_mg.g</b>: Foliar chlorophyll a content (Field type: Numeric trait)</li><li><b>chlb_mg.g</b>: Foliar chlorophyll b content (Field type: Numeric trait)</li><li><b>carot_mg.g</b>: Foliar carotenoids content (Field type: Numeric trait)</li><li><b>Fp_N_mm_mean</b>: Mean force to punch leaf, dividing the observed force (N) required to puncture the leaf lamina by the circumference of the instrument's rod (Field type: Numeric trait)</li><li><b>Fp_N_mm_sd</b>: Standard deviation for force to punch (Field type: Numeric trait)</li><li><b>Fp_N_mm_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Numeric trait)</li><li><b>specific_Fp_mean</b>: Mean specific force to punch (Fp divided by lamina thickness) (Field type: Numeric trait)</li><li><b>specific_Fp_sd</b>: Standard deviation for force to punch (Field type: Numeric trait)</li><li><b>specific_Fp_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Numeric trait)</li><li><b>WD_B</b>: Branch wood density from branch segment with bark (Field type: Numeric trait)</li><li><b>WD_NB</b>: Branch wood density from branch segment without bark (bark removed prior measurement) (Field type: Numeric trait)</li><li><b>hemicellulose_perc</b>: Foliar hemicellulose concentration (Field type: Numeric trait)</li><li><b>cellulose_perc</b>: Foliar cellulose concentration (Field type: Numeric trait)</li><li><b>lignin_recalcitrants_perc</b>: Foliar lignin and recalcitrants concentration (Field type: Numeric trait)</li><li><b>Total_tannin_mg.g</b>: Total foliar tannin concentration (Field type: Numeric trait)</li><li><b>Total_phenol_mg.g</b>: Total foliar phenol concentration (Field type: Numeric trait)</li><li><b>SLA_mm2.mg_mean</b>: Specific leaf area (SLA) determined as the one-sided area of a fresh leaf, divided by its oven-dry mass. (Field type: Numeric trait)</li><li><b>total_K_mg.mm2</b>: Foliar potassium content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>total_Ca_mg.mm2</b>: Foliar calcium content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>total_Mg_mg.mm2</b>: Foliar magnesium content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>total_P_mg.mm2</b>: Foliar phosporus content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>chla_mg.mm2</b>: Foliar chlorophyll a content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>chlb_mg.mm2</b>: Foliar chlorophyll b content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>carot_mg.mm2</b>: Foliar carotenoids content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>tannin_mg.mm2</b>: Foliar tannin content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>phenol_mg_mm2</b>: Foliar phenol content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>N_mg.mm2</b>: Foliar nitrogen content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>C_mg.mm2</b>: Foliar carbon content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>hemicellulose_mg.mm2</b>: Foliar hemicellulose content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>cellulose_mg.mm2</b>: Foliar cellulose content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>lignin_recalcitrants_mg.mm2</b>: Foliar lignin and recalcitrants content expressed on leaf area basis (Field type: Numeric trait)</li></ul></li></ol><p><b>CSP_protocol_Chlorophyll_and_Carotenoids.pdf</b></p><p>Description: Methodology of chlorophyll and carotenoids analysis, Carnegie Spectranomics protocol: https://drive.google.com/file/d/0B58dyv8L3FpMdGw0QWtiZElHQzQ/view</p><p><b>CSP_protocol_Phenols_Tannins_Analysis.pdf</b></p><p>Description: Methodology of phenols and tannins analysis, Carnegie Spectranomics protocol: https://drive.google.com/file/d/0B58dyv8L3FpMcTBHblQwRHdyRE0/view</p><p><b>Date range: </b>2014-05-01 to 2018-09-01</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div>Plantae<br> - Tracheophyta<br> -  - Liliopsida<br> -  -  - Poales<br> -  -  -  - Poaceae<br> -  -  -  -  - <i>Dinochloa</i><br> -  -  -  -  -  - <i>Dinochloa trichogona</i><br> -  -  -  -  - <i>Imperata</i><br> -  -  -  -  -  - <i>Imperata cylindrica</i><br> -  -  -  -  - <i>Paspalum</i><br> -  -  -  -  -  - <i>Paspalum virgatum</i><br> -  -  - Zingiberales<br> -  -  -  - Marantaceae<br> -  -  -  -  - <i>Phrynium</i><br> -  -  -  -  -  - <i>Phrynium pubinerve</i><br> -  -  -  - Zingiberaceae<br> -  -  -  -  - <i>Etlingera</i><br> -  - Magnoliopsida<br> -  -  - Asterales<br> -  -  -  - Asteraceae<br> -  -  -  -  - <i>Mikania</i><br> -  -  -  -  -  - <i>Mikania micrantha</i><br> -  -  - Celastrales<br> -  -  -  - Celastraceae<br> -  -  -  -  - <i>Lophopetalum</i><br> -  -  -  -  -  - <i>Lophopetalum beccarianum</i><br> -  -  -  -  -  - <i>Lophopetalum glabrum</i><br> -  -  -  -  -  - <i>Lophopetalum javanicum</i><br> -  -  - Cornales<br> -  -  -  - Cornaceae<br> -  -  -  -  - <i>Alangium</i><br> -  -  -  -  -  - <i>Alangium javanicum</i><br> -  -  -  - Nyssaceae<br> -  -  -  -  - <i>Mastixia</i><br> -  -  -  -  -  - <i>Mastixia trichotoma</i><br> -  -  - Ericales<br> -  -  -  - Ebenaceae<br> -  -  -  -  - <i>Diospyros</i><br> -  -  -  -  -  - <i>Diospyros andamanica</i><br> -  -  -  -  -  - <i>Diospyros curranii</i><br> -  -  -  -  -  - <i>Diospyros daemona</i><br> -  -  -  -  -  - <i>Diospyros dictyoneura</i><br> -  -  -  -  -  - <i>Diospyros macrophylla</i><br> -  -  -  -  -  - <i>Diospyros muricata</i><br> -  -  -  -  -  - <i>Diospyros pilosanthera</i><br> -  -  -  -  -  - <i>Diospyros toposia</i><br> -  -  -  -  -  - <i>Diospyros tuberculata</i><br> -  -  -  - Lecythidaceae<br> -  -  -  -  - <i>Barringtonia</i><br> -  -  -  -  -  - <i>Barringtonia lanceolata</i><br> -  -  -  -  -  - <i>Barringtonia macrostachya</i><br> -  -  -  -  -  - <i>Barringtonia sarcostachys</i><br> -  -  -  -  - <i>Planchonia</i><br> -  -  -  -  -  - <i>Planchonia brevistipitata</i><br> -  -  -  - Pentaphylacaceae<br> -  -  -  -  - <i>Adinandra</i><br> -  -  -  -  -  - <i>Adinandra dumosa</i><br> -  -  -  - Primulaceae<br> -  -  -  -  - <i>Ardisia</i><br> -  -  -  -  -  - <i>Ardisia macrophylla</i><br> -  -  -  -  - <i>Maesa</i><br> -  -  -  -  -  - <i>Maesa macrothyrsa</i><br> -  -  -  - Sapotaceae<br> -  -  -  -  - <i>Madhuca</i><br> -  -  -  -  -  - <i>Madhuca dubardii</i><br> -  -  -  -  -  - <i>Madhuca korthalsii</i><br> -  -  -  -  - <i>Palaquium</i><br> -  -  -  -  -  - <i>Palaquium dasyphyllum</i><br> -  -  -  -  -  - <i>Palaquium obovatum</i><br> -  -  -  -  -  - <i>Palaquium sericeum</i><br> -  -  -  -  - <i>Payena</i><br> -  -  -  -  -  - <i>Payena acuminata</i><br> -  -  -  - Symplocaceae<br> -  -  -  -  - <i>Symplocos</i><br> -  -  -  -  -  - <i>Symplocos fasciculata</i><br> -  -  -  - Theaceae<br> -  -  -  -  - <i>Pyrenaria</i><br> -  -  -  -  -  - <i>Pyrenaria tawauensis</i><br> -  -  - Fabales<br> -  -  -  - Fabaceae<br> -  -  -  -  - <i>Archidendron</i><br> -  -  -  -  -  - <i>Archidendron clypearia</i><br> -  -  -  -  - <i>Crudia</i><br> -  -  -  -  -  - <i>Crudia reticulata</i><br> -  -  -  -  -  - <i>Crudia tenuipes</i><br> -  -  -  -  - <i>Cynometra</i><br> -  -  -  -  -  - <i>Cynometra mirabilis</i><br> -  -  -  -  - <i>Dialium</i><br> -  -  -  -  -  - <i>Dialium indum</i><br> -  -  -  -  -  - <i>Dialium kunstleri</i><br> -  -  -  -  - <i>Fordia</i><br> -  -  -  -  -  - <i>Fordia brachybotrys</i><br> -  -  -  -  -  - <i>Fordia splendidissima</i><br> -  -  -  -  - <i>Sindora</i><br> -  -  -  -  - <i>Spatholobus</i><br> -  -  -  -  -  - <i>Spatholobus macropterus</i><br> -  -  -  - Polygalaceae<br> -  -  -  -  - <i>Xanthophyllum</i><br> -  -  -  -  -  - <i>Xanthophyllum flavescens</i><br> -  -  - Fagales<br> -  -  -  - Fagaceae<br> -  -  -  -  - <i>Castanopsis</i><br> -  -  -  -  -  - <i>Castanopsis hypophoenicea</i><br> -  -  -  -  - <i>Lithocarpus</i><br> -  -  -  -  -  - <i>Lithocarpus blumeanus</i><br> -  -  -  -  -  - <i>Lithocarpus conocarpus</i><br> -  -  -  -  -  - <i>Lithocarpus echinifer</i><br> -  -  -  -  -  - <i>Lithocarpus gracilis</i><br> -  -  -  -  -  - <i>Lithocarpus leptogyne</i><br> -  -  -  -  -  - <i>Lithocarpus sundaicus</i><br> -  -  -  -  - <i>Quercus</i><br> -  -  -  -  -  - <i>Quercus argentata</i><br> -  -  -  -  -  - <i>Quercus lowii</i><br> -  -  -  -  -  - <i>Quercus merrillii</i><br> -  -  -  -  - <i>Trigonobalanus</i><br> -  -  -  -  -  - <i>Trigonobalanus verticillata</i><br> -  -  - Gentianales<br> -  -  -  - Apocynaceae<br> -  -  -  -  - <i>Alstonia</i><br> -  -  -  -  -  - <i>Alstonia angustiloba</i><br> -  -  -  - Rubiaceae<br> -  -  -  -  - <i>Ludekia</i><br> -  -  -  -  -  - <i>Ludekia borneensis</i><br> -  -  -  -  - <i>Nauclea</i><br> -  -  -  -  -  - <i>Nauclea officinalis</i><br> -  -  -  -  -  - <i>Nauclea subdita</i><br> -  -  -  -  - <i>Neolamarckia</i><br> -  -  -  -  -  - <i>Neolamarckia cadamba</i><br> -  -  -  -  - <i>Neonauclea</i><br> -  -  -  -  -  - <i>Neonauclea gigantea</i><br> -  -  -  -  - <i>Psydrax</i><br> -  -  -  -  -  - <i>Psydrax dicoccos</i><br> -  -  -  -  - <i>Uncaria</i><br> -  -  -  -  -  - <i>Uncaria cordata</i><br> -  -  -  -  - <i>Urophyllum</i><br> -  -  -  -  -  - <i>Urophyllum polyneurum</i><br> -  -  - Lamiales<br> -  -  -  - Lamiaceae<br> -  -  -  -  - <i>Callicarpa</i><br> -  -  -  -  -  - <i>Callicarpa pentandra</i><br> -  -  -  - Oleaceae<br> -  -  -  -  - <i>Chionanthus</i><br> -  -  -  -  -  - <i>Chionanthus macrocarpus</i><br> -  -  -  -  -  - <i>Chionanthus pluriflorus</i><br> -  -  - Laurales<br> -  -  -  - Lauraceae<br> -  -  -  -  - <i>Actinodaphne</i><br> -  -  -  -  - <i>Beilschmiedia</i><br> -  -  -  -  -  - <i>Beilschmiedia micrantha</i><br> -  -  -  -  - <i>Caryodaphnopsis</i><br> -  -  -  -  -  - <i>Caryodaphnopsis tonkinensis</i><br> -  -  -  -  - <i>Cryptocarya</i><br> -  -  -  -  -  - <i>Cryptocarya nigra</i><br> -  -  -  -  -  - <i>Cryptocarya nitens</i><br> -  -  -  -  - <i>Dehaasia</i><br> -  -  -  -  -  - <i>Dehaasia caesia</i><br> -  -  -  -  -  - <i>Dehaasia incrassata</i><br> -  -  -  -  - <i>Eusideroxylon</i><br> -  -  -  -  -  - <i>Eusideroxylon zwageri</i><br> -  -  -  -  - <i>Lindera</i><br> -  -  -  -  -  - <i>Lindera lucida</i><br> -  -  -  -  - <i>Litsea</i><br> -  -  -  -  -  - <i>Litsea accedens</i><br> -  -  -  -  -  - <i>Litsea angulata</i><br> -  -  -  -  -  - <i>Litsea caulocarpa</i><br> -  -  -  -  -  - <i>Litsea cordata</i><br> -  -  -  -  -  - <i>Litsea garciae</i><br> -  -  -  -  -  - <i>Litsea grandis</i><br> -  -  -  -  -  - <i>Litsea rubiginosa</i><br> -  -  -  -  - <i>Nothaphoebe</i><br> -  -  -  -  -  - <i>Nothaphoebe umbelliflora</i><br> -  -  -  -  - <i>Phoebe</i><br> -  -  -  -  -  - <i>Phoebe grandis</i><br> -  -  - Magnoliales<br> -  -  -  - Annonaceae<br> -  -  -  -  - <i>Cyathocalyx</i><br> -  -  -  -  - <i>Maasia</i><br> -  -  -  -  -  - <i>Maasia sumatrana</i><br> -  -  -  -  - <i>Miliusa</i><br> -  -  -  -  -  - <i>Miliusa macropoda</i><br> -  -  -  -  - <i>Monoon</i><br> -  -  -  -  - <i>Neo-uvaria</i><br> -  -  -  -  -  - <i>Neo-uvaria acuminatissima</i><br> -  -  -  -  - <i>Orophea</i><br> -  -  -  -  -  - <i>Orophea myriantha</i><br> -  -  -  -  - <i>Phaeanthus</i><br> -  -  -  -  -  - <i>Phaeanthus splendens</i><br> -  -  -  -  - <i>Polyalthia</i><br> -  -  -  -  -  - <i>Polyalthia obliqua</i><br> -  -  -  -  - <i>Pseuduvaria</i><br> -  -  -  -  -  - <i>Pseuduvaria borneensis</i><br> -  -  -  -  - <i>Sageraea</i><br> -  -  -  -  -  - <i>Sageraea elliptica</i><br> -  -  -  -  - <i>Stelechocarpus</i><br> -  -  -  -  -  - <i>Stelechocarpus cauliflorus</i><br> -  -  -  -  - <i>Xylopia</i><br> -  -  -  -  -  - <i>Xylopia ferruginea</i><br> -  -  -  -  -  - <i>Xylopia stenopetala</i><br> -  -  -  - Magnoliaceae<br> -  -  -  -  - <i>Magnolia</i><br> -  -  -  -  -  - <i>Magnolia borneensis</i><br> -  -  -  -  -  - <i>Magnolia liliifera</i><br> -  -  -  -  -  - <i>Magnolia tsiampacca</i><br> -  -  -  - Myristicaceae<br> -  -  -  -  - <i>Horsfieldia</i><br> -  -  -  -  -  - <i>Horsfieldia crassifolia</i><br> -  -  -  -  - <i>Knema</i><br> -  -  -  -  -  - <i>Knema glauca</i><br> -  -  -  -  -  - <i>Knema latifolia</i><br> -  -  -  -  -  - <i>Knema laurina</i><br> -  -  -  -  -  - <i>Knema oblongata</i><br> -  -  -  -  - <i>Myristica</i><br> -  -  -  -  -  - <i>Myristica smythiesii</i><br> -  -  - Malpighiales<br> -  -  -  - Achariaceae<br> -  -  -  -  - <i>Hydnocarpus</i><br> -  -  -  -  -  - <i>Hydnocarpus woodii</i><br> -  -  -  -  - <i>Ryparosa</i><br> -  -  -  -  -  - <i>Ryparosa acuminata</i><br> -  -  -  - Calophyllaceae<br> -  -  -  -  - <i>Calophyllum</i><br> -  -  -  -  -  - <i>Calophyllum soulattri</i><br> -  -  -  -  -  - <i>Calophyllum woodii</i><br> -  -  -  -  - <i>Mesua</i><br> -  -  -  -  -  - <i>Mesua borneensis</i><br> -  -  -  -  -  - <i>Mesua macrantha</i><br> -  -  -  -  -  - <i>Mesua oblongifolia</i><br> -  -  -  - Centroplacaceae<br> -  -  -  -  - <i>Bhesa</i><br> -  -  -  -  -  - <i>Bhesa indica</i><br> -  -  -  - Chrysobalanaceae<br> -  -  -  -  - <i>Atuna</i><br> -  -  -  -  -  - <i>Atuna racemosa</i><br> -  -  -  -  - <i>Licania</i><br> -  -  -  -  -  - <i>Licania splendens</i><br> -  -  -  - Clusiaceae<br> -  -  -  -  - <i>Garcinia</i><br> -  -  -  -  -  - <i>Garcinia benthamiana</i><br> -  -  -  -  -  - <i>Garcinia forbesii</i><br> -  -  -  -  -  - <i>Garcinia nervosa</i><br> -  -  -  -  -  - <i>Garcinia parvifolia</i><br> -  -  -  - Euphorbiaceae<br> -  -  -  -  - <i>Blumeodendron</i><br> -  -  -  -  -  - <i>Blumeodendron kurzii</i><br> -  -  -  -  -  - <i>Blumeodendron tokbrai</i><br> -  -  -  -  - <i>Hancea</i><br> -  -  -  -  -  - <i>Hancea penangensis</i><br> -  -  -  -  - <i>Macaranga</i><br> -  -  -  -  -  - <i>Macaranga conifera</i><br> -  -  -  -  -  - <i>Macaranga gigantea</i><br> -  -  -  -  -  - <i>Macaranga hypoleuca</i><br> -  -  -  -  -  - <i>Macaranga pearsonii</i><br> -  -  -  -  -  - <i>Macaranga winkleri</i><br> -  -  -  -  - <i>Mallotus</i><br> -  -  -  -  -  - <i>Mallotus leucodermis</i><br> -  -  -  -  -  - <i>Mallotus miquelianus</i><br> -  -  -  -  -  - <i>Mallotus mollissimus</i><br> -  -  -  -  -  - <i>Mallotus wrayi</i><br> -  -  -  -  - <i>Neoscortechinia</i><br> -  -  -  -  -  - <i>Neoscortechinia kingii</i><br> -  -  -  -  -  - <i>Neoscortechinia philippinensis</i><br> -  -  -  -  - <i>Ptychopyxis</i><br> -  -  -  -  -  - <i>Ptychopyxis arborea</i><br> -  -  -  -  - <i>Spathiostemon</i><br> -  -  -  - Hypericaceae<br> -  -  -  -  - <i>Cratoxylum</i><br> -  -  -  - Irvingiaceae<br> -  -  -  -  - <i>Irvingia</i><br> -  -  -  -  -  - <i>Irvingia malayana</i><br> -  -  -  - Phyllanthaceae<br> -  -  -  -  - <i>Antidesma</i><br> -  -  -  -  - <i>Aporosa</i><br> -  -  -  -  -  - <i>Aporosa confusa</i><br> -  -  -  -  -  - <i>Aporosa falcifera</i><br> -  -  -  -  - <i>Baccaurea</i><br> -  -  -  -  -  - <i>Baccaurea lanceolata</i><br> -  -  -  -  -  - <i>Baccaurea macrocarpa</i><br> -  -  -  -  -  - <i>Baccaurea pubera</i><br> -  -  -  -  -  - <i>Baccaurea tetrandra</i><br> -  -  -  -  - <i>Cleistanthus</i><br> -  -  -  -  -  - <i>Cleistanthus hirsutulus</i><br> -  -  -  -  -  - <i>Cleistanthus hylandii</i><br> -  -  -  -  -  - <i>Cleistanthus oblongifolius</i><br> -  -  -  -  -  - <i>Cleistanthus paxii</i><br> -  -  -  -  -  - <i>Cleistanthus pubens</i><br> -  -  -  -  - <i>Glochidion</i><br> -  -  -  -  -  - <i>Glochidion borneensis</i><br> -  -  -  -  - <i>Phyllanthus</i><br> -  -  -  -  -  - <i>Phyllanthus lutescens</i><br> -  -  -  -  -  - <i>Phyllanthus ruber</i><br> -  -  -  - Putranjivaceae<br> -  -  -  -  - <i>Drypetes</i><br> -  -  -  -  -  - <i>Drypetes longifolia</i><br> -  -  -  - Salicaceae<br> -  -  -  -  - <i>Flacourtia</i><br> -  -  -  -  -  - <i>Flacourtia rukam</i><br> -  -  -  -  - <i>Homalium</i><br> -  -  -  -  -  - <i>Homalium foetidum</i><br> -  -  - Malvales<br> -  -  -  - Dipterocarpaceae<br> -  -  -  -  - <i>Dipterocarpus</i><br> -  -  -  -  -  - <i>Dipterocarpus caudiferus</i><br> -  -  -  -  - <i>Dryobalanops</i><br> -  -  -  -  -  - <i>Dryobalanops lanceolata</i><br> -  -  -  -  - <i>Hopea</i><br> -  -  -  -  -  - <i>Hopea plagata</i><br> -  -  -  -  -  - <i>Hopea sangal</i><br> -  -  -  -  - <i>Parashorea</i><br> -  -  -  -  -  - <i>Parashorea malaanonan</i><br> -  -  -  -  -  - <i>Parashorea smythiesii</i><br> -  -  -  -  -  - <i>Parashorea warburgii</i><br> -  -  -  -  - <i>Shorea</i><br> -  -  -  -  -  - <i>Shorea almon</i><br> -  -  -  -  -  - <i>Shorea angustifolia</i><br> -  -  -  -  -  - <i>Shorea argentifolia</i><br> -  -  -  -  -  - <i>Shorea beccariana</i><br> -  -  -  -  -  - <i>Shorea faguetiana</i><br> -  -  -  -  -  - <i>Shorea falciferoides</i><br> -  -  -  -  -  - <i>Shorea fallax</i><br> -  -  -  -  -  - <i>Shorea gibbosa</i><br> -  -  -  -  -  - <i>Shorea guiso</i><br> -  -  -  -  -  - <i>Shorea johorensis</i><br> -  -  -  -  -  - <i>Shorea laevis</i><br> -  -  -  -  -  - <i>Shorea leprosula</i><br> -  -  -  -  -  - <i>Shorea leptoderma</i><br> -  -  -  -  -  - <i>Shorea macrophylla</i><br> -  -  -  -  -  - <i>Shorea macroptera</i><br> -  -  -  -  -  - <i>Shorea ovalis</i><br> -  -  -  -  -  - <i>Shorea ovata</i><br> -  -  -  -  -  - <i>Shorea parvifolia</i><br> -  -  -  -  -  - <i>Shorea parvistipulata</i><br> -  -  -  -  -  - <i>Shorea pauciflora</i><br> -  -  -  -  -  - <i>Shorea pinanga</i><br> -  -  -  -  -  - <i>Shorea superba</i><br> -  -  -  -  -  - <i>Shorea symingtonii</i><br> -  -  -  -  -  - <i>Shorea xanthophylla</i><br> -  -  -  -  - <i>Vatica</i><br> -  -  -  -  -  - <i>Vatica dulitensis</i><br> -  -  -  -  -  - <i>Vatica odorata</i><br> -  -  -  - Malvaceae<br> -  -  -  -  - <i>Boschia</i><br> -  -  -  -  -  - <i>Boschia grandiflora</i><br> -  -  -  -  - <i>Durio</i><br> -  -  -  -  -  - <i>Durio graveolens</i><br> -  -  -  -  - <i>Heritiera</i><br> -  -  -  -  -  - <i>Heritiera elata</i><br> -  -  -  -  - <i>Microcos</i><br> -  -  -  -  -  - <i>Microcos crassifolia</i><br> -  -  -  -  - <i>Pentace</i><br> -  -  -  -  -  - <i>Pentace borneensis</i><br> -  -  -  -  - <i>Pterygota</i><br> -  -  -  -  -  - <i>Pterygota alata</i><br> -  -  -  -  - <i>Scaphium</i><br> -  -  -  -  -  - <i>Scaphium macropodum</i><br> -  -  -  -  - <i>Sterculia</i><br> -  -  -  -  -  - <i>Sterculia rubiginosa</i><br> -  -  -  -  -  - <i>Sterculia stipulata</i><br> -  -  -  - Thymelaeaceae<br> -  -  -  -  - <i>Aquilaria</i><br> -  -  -  -  -  - <i>Aquilaria beccariana</i><br> -  -  - Myrtales<br> -  -  -  - Combretaceae<br> -  -  -  -  - <i>Terminalia</i><br> -  -  -  -  -  - <i>Terminalia citrina</i><br> -  -  -  -  -  - <i>Terminalia foetidissima</i><br> -  -  -  - Lythraceae<br> -  -  -  -  - <i>Duabanga</i><br> -  -  -  -  -  - <i>Duabanga moluccana</i><br> -  -  -  - Melastomataceae<br> -  -  -  -  - <i>Clidemia</i><br> -  -  -  -  -  - <i>Clidemia hirta</i><br> -  -  -  -  - <i>Melastoma</i><br> -  -  -  -  -  - <i>Melastoma malabathricum</i><br> -  -  -  -  - <i>Memecylon</i><br> -  -  -  -  -  - <i>Memecylon oleifolium</i><br> -  -  -  - Myrtaceae<br> -  -  -  -  - <i>Syzygium</i><br> -  -  -  -  -  - <i>Syzygium caudatilimbum</i><br> -  -  -  -  -  - <i>Syzygium chloranthum</i><br> -  -  -  -  -  - <i>Syzygium elopurae</i><br> -  -  -  -  -  - <i>Syzygium grande</i><br> -  -  -  -  -  - <i>Syzygium griffithii</i><br> -  -  -  -  -  - <i>Syzygium kunstleri</i><br> -  -  -  -  -  - <i>Syzygium lineatum</i><br> -  -  -  -  -  - <i>Syzygium pancheri</i><br> -  -  -  -  -  - <i>Syzygium panzeri</i><br> -  -  -  -  -  - <i>Syzygium pustulatum</i><br> -  -  -  -  -  - <i>Syzygium racemosum</i><br> -  -  -  -  -  - <i>Syzygium rheophyticum</i><br> -  -  -  -  - <i>Tristaniopsis</i><br> -  -  -  -  -  - <i>Tristaniopsis whiteana</i><br> -  -  - Oxalidales<br> -  -  -  - Elaeocarpaceae<br> -  -  -  -  - <i>Elaeocarpus</i><br> -  -  -  -  -  - <i>Elaeocarpus floribundus</i><br> -  -  -  -  -  - <i>Elaeocarpus pedunculatus</i><br> -  -  -  -  -  - <i>Elaeocarpus stipularis</i><br> -  -  -  -  - <i>Sloanea</i><br> -  -  -  -  -  - <i>Sloanea javanica</i><br> -  -  - Rosales<br> -  -  -  - Cannabaceae<br> -  -  -  -  - <i>Gironniera</i><br> -  -  -  -  -  - <i>Gironniera nervosa</i><br> -  -  -  -  - <i>Trema</i><br> -  -  -  -  -  - <i>Trema orientalis</i><br> -  -  -  - Moraceae<br> -  -  -  -  - <i>Antiaris</i><br> -  -  -  -  -  - <i>Antiaris toxicaria</i><br> -  -  -  -  - <i>Artocarpus</i><br> -  -  -  -  -  - <i>Artocarpus anisophyllus</i><br> -  -  -  -  -  - <i>Artocarpus glaucus</i><br> -  -  -  -  -  - <i>Artocarpus integer</i><br> -  -  -  -  -  - <i>Artocarpus odoratissimus</i><br> -  -  -  -  -  - <i>Artocarpus tamaran</i><br> -  -  -  -  - <i>Ficus</i><br> -  -  -  -  -  - <i>Ficus hispida</i><br> -  -  -  -  -  - <i>Ficus septica</i><br> -  -  -  -  -  - <i>Ficus uncinata</i><br> -  -  -  -  -  - <i>Ficus variegata</i><br> -  -  -  - Rosaceae<br> -  -  -  -  - <i>Prunus</i><br> -  -  -  -  -  - <i>Prunus javanica</i><br> -  -  -  -  - <i>Pygeum</i><br> -  -  -  -  -  - <i>Pygeum beccarii</i><br> -  -  -  - Urticaceae<br> -  -  -  -  - <i>Dendrocnide</i><br> -  -  -  -  -  - <i>Dendrocnide elliptica</i><br> -  -  - Santalales<br> -  -  -  - Coulaceae<br> -  -  -  -  - <i>Ochanostachys</i><br> -  -  -  -  -  - <i>Ochanostachys amentacea</i><br> -  -  -  - Strombosiaceae<br> -  -  -  -  - <i>Scorodocarpus</i><br> -  -  -  -  -  - <i>Scorodocarpus borneensis</i><br> -  -  - Sapindales<br> -  -  -  - Anacardiaceae<br> -  -  -  -  - <i>Gluta</i><br> -  -  -  -  -  - <i>Gluta aptera</i><br> -  -  -  -  -  - <i>Gluta wallichii</i><br> -  -  -  -  - <i>Mangifera</i><br> -  -  -  -  -  - <i>Mangifera odorata</i><br> -  -  -  -  - <i>Melanochyla</i><br> -  -  -  -  -  - <i>Melanochyla bullata</i><br> -  -  -  -  -  - <i>Melanochyla tomentosa</i><br> -  -  -  -  - <i>Parishia</i><br> -  -  -  -  -  - <i>Parishia insignis</i><br> -  -  -  - Burseraceae<br> -  -  -  -  - <i>Canarium</i><br> -  -  -  -  -  - <i>Canarium decumanum</i><br> -  -  -  -  -  - <i>Canarium denticulatum</i><br> -  -  -  -  -  - <i>Canarium odontophyllum</i><br> -  -  -  -  -  - <i>Canarium pilosum</i><br> -  -  -  -  - <i>Dacryodes</i><br> -  -  -  -  -  - <i>Dacryodes rostrata</i><br> -  -  -  -  -  - <i>Dacryodes rugosa</i><br> -  -  -  -  - <i>Santiria</i><br> -  -  -  -  -  - <i>Santiria laevigata</i><br> -  -  -  - Meliaceae<br> -  -  -  -  - <i>Aglaia</i><br> -  -  -  -  -  - <i>Aglaia crassinervia</i><br> -  -  -  -  -  - <i>Aglaia leptantha</i><br> -  -  -  -  -  - <i>Aglaia macrocarpa</i><br> -  -  -  -  -  - <i>Aglaia odoratissima</i><br> -  -  -  -  -  - <i>Aglaia oligophylla</i><br> -  -  -  -  -  - <i>Aglaia silvestris</i><br> -  -  -  -  -  - <i>Aglaia tomentosa</i><br> -  -  -  -  - <i>Aphanamixis</i><br> -  -  -  -  -  - <i>Aphanamixis polystachya</i><br> -  -  -  -  - <i>Chisocheton</i><br> -  -  -  -  -  - <i>Chisocheton ceramicus</i><br> -  -  -  -  -  - <i>Chisocheton macranthus</i><br> -  -  -  -  -  - <i>Chisocheton patens</i><br> -  -  -  -  - <i>Dysoxylum</i><br> -  -  -  -  -  - <i>Dysoxylum cyrtobotryum</i><br> -  -  -  -  -  - <i>Dysoxylum densiflorum</i><br> -  -  -  -  - <i>Lansium</i><br> -  -  -  -  -  - <i>Lansium domesticum</i><br> -  -  -  -  - <i>Reinwardtiodendron</i><br> -  -  -  -  -  - <i>Reinwardtiodendron humile</i><br> -  -  -  -  - <i>Walsura</i><br> -  -  -  -  -  - <i>Walsura pinnata</i><br> -  -  -  - Rutaceae<br> -  -  -  -  - <i>Melicope</i><br> -  -  -  -  -  - <i>Melicope confusa</i><br> -  -  -  - Sapindaceae<br> -  -  -  -  - <i>Dimocarpus</i><br> -  -  -  -  -  - <i>Dimocarpus longan</i><br> -  -  -  -  - <i>Nephelium</i><br> -  -  -  -  -  - <i>Nephelium cuspidatum</i><br> -  -  -  -  - <i>Paranephelium</i><br> -  -  -  -  -  - <i>Paranephelium macrophyllum</i><br> -  -  -  -  -  - <i>Paranephelium xestophyllum</i><br> -  -  -  -  - <i>Pometia</i><br> -  -  -  -  -  - <i>Pometia pinnata</i><br> -  -  -  -  - <i>Tristiropsis</i><br> -  -  -  -  -  - <i>Tristiropsis acutangula</i><br> -  -  - Solanales<br> -  -  -  - Convolvulaceae<br> -  -  -  -  - <i>Decalobanthus</i><br> -  -  -  -  -  - <i>Decalobanthus borneensis</i><br> -  -  -  -  - <i>Jacquemontia</i><br> -  -  -  -  -  - <i>Jacquemontia tomentella</i><br> -  - Polypodiopsida<br> -  -  - Gleicheniales<br> -  -  -  - Gleicheniaceae<br> -  -  -  -  - <i>Dicranopteris</i><br> -  -  -  -  -  - <i>Dicranopteris pubigera</i><br> -  -  - Polypodiales<br> -  -  -  - Lomariopsidaceae<br> -  -  -  -  - <i>Nephrolepis</i><br> -  -  -  -  -  - <i>Nephrolepis biserrata</i><br></div><p></p>
Quantitative Trait Loci of Solanaceae species
<p>This archive contains experimental data on Quantitative Trait Loci (QTLs) mapped in <em>Solanacea</em> species (tomato and potato). QTLs were extracted from scientific literature using the QTLTableMiner++ tool. The resulting data are distributed in:</p> <ul> <li><a href="https://sqlite.org/">SQLite</a> database files (.db)</li> <li>CSV files (.csv)</li> <li><a href="https://www.w3.org/TR/turtle/">RDF/</a><a href="https://www.w3.org/TR/turtle/">Turle</a> files (gzip-ed .ttl)</li> </ul>
Fig. 3 in Morphological traits, allometric relationship and competition of two seed-feeding species of beetles in infested pods
Fig. 3. Negative allometry depicted by the slopes and their confidence intervals for the pronotum and elytron allometry (pronotum length and elytron length in relation to body weight) between infestation categories for both bruchine species. G1, low infestation (0–0.30% of attacked seeds); G2, medium infestation (0.31–0.60% of attacked seeds); G3, high infestation (0.61–0.90% of attacked seeds).
Fig. 1 in Morphological traits, allometric relationship and competition of two seed-feeding species of beetles in infested pods
Fig. 1. Variations in body weight, pronotum and elytron length between Merobruchus terani and Stator maculatopygus and for males and females. The analyses used a linear mixed model with a log-normal distribution and Tukey's pairwise comparison. MF, M. terani females; MM, M. terani males; SF, S.maculatopygus females; SM, S. maculatopygus males.
Inbreeding depression, functional traits and phenotypic plasticity in an endangered tree species from Congo basin with a mixed mating system
<h3><span>Inbreeding depression, functional traits and phenotypic plasticity in an endangered tree species from Congo basin with a mixed mating system</span></h3> <h1><a name="_Hlk166486742"></a><strong><span>Abstract</span></strong></h1> <p><span><span>1. Most tree species can suffer from inbreeding depression (ID), which they escape by reproducing predominantly through outcrossing. A remarkable exception is <em>Pericopsis elata</em>, an African timber species naturally producing 54% of self-fertilized seeds in the eastern Congo Basin. This species is highly logged and suffers from a deficit of natural regeneration, so that silviculture is needed for its sustainable management. While selecting good genetic material can increase the value of plantations, we lack fundamental biological knowledge on the effect of inbreeding and competition on growth potential, variability in leaf traits and phenotypic plasticity. We hypothesize that ID in <em>P. elata</em> could result from the expression of deleterious mutations affecting functional traits, or from a reduction of adaptive phenotypic plasticity in inbred genotypes.</span></span></p> <p><span><span>2. To test our hypotheses, 540 <em>P. elata</em> seedlings were monitored for 4 years in a Nelder-type device located in the DRC, in which trees were planted along concentric circles to generate a density gradient. Nine leaf morphological traits (including specific leaf area, stomata density and size), eight leaf chemical traits, diameter, and total height were measured regularly, while paternity analyses allowed distinguishing inbred and outbred plants. To explain the observed ID on growth, we tested whether inbreeding affected leaf traits and/or their plasticity expressed across years, across the density gradient or across sunlight exposure. </span></span></p> <p><span><span>3. Outbred plants grew faster than inbred ones, demonstrating ID for each level of competition. Despite the significant correlation found between specific leaf area and growth, and the impact of planting density, plant age, and leaf exposure to sunlight on multiple traits, mean leaf trait values did not differ according to inbreeding. However, </span></span><span><span>a few leaf traits (chlorophyl content, </span></span><span><span>maximum stomatal water vapor conductance</span></span><span><span>, and leaf fresh mass) showed significantly higher plasticity in outbred than inbred plants. </span></span></p> <p><span><span>4. Synthesis: the observed ID on growth was not explained by a direct effect of inbreeding on the mean values of functional traits but possibly by a reduction of phenotypic plasticity with inbreeding. Additional studies on the interplay between ID, functional traits and plasticity should be conducted at the intra-specific level to identify general patterns<em>.</em></span></span></p> <p><span><strong><span>Key-words : </span></strong></span><span><span>Inbreeding depression, phenotypic plasticity, silviculture, functionals traits, <em>Pericopsis elata</em>, mating system, Nelder device.</span></span></p>
Data from: Species-specific traits mediate avian demographic responses under past climate change
<p>Anticipating species' responses to environmental change is a<span> pressing mission in biodiversity conservation. Despite decades of research investigating how climate change may affect population sizes, historical context is lacking and the traits which mediate demographic sensitivity to changing climate remain elusive. We use whole-genome sequence data to reconstruct the demographic histories of 263 bird species over the past million years and identify networks of interacting morphological and life-history traits associated with changes in effective population size (<em>N<sub>e</sub></em>) in response to climate warming and cooling. Our results identify direct and indirect effects of key traits representing survival, reproduction, and dispersal processes on long-term demographic responses to climate change and highlight traits most likely to influence population responses to ongoing climate warming.</span></p>
Body size as a magic trait in two plant-feeding insect species
<p>When gene flow accompanies speciation, recombination can decouple divergently selected loci and loci conferring reproductive isolation. This barrier to sympatric divergence disappears when assortative mating and disruptive selection involve the same "magic" trait. Although magic traits could be widespread, the relative importance of different types of magic traits to speciation remains unclear. Because body size frequently contributes to host adaptation and assortative mating in plant-feeding insects, we evaluated several magic trait predictions for this trait in a pair of sympatric <em>Neodiprion</em> sawfly species adapted to different pine hosts. A large morphological dataset revealed that sawfly adults from populations and species that use thicker-needled pines are consistently larger than those that use thinner-needled pines. Fitness data from recombinant backcross females revealed that egg size is under divergent selection between the preferred pines. Lastly, mating assays revealed strong size-assortative mating within and between species in three different crosses, with the strongest prezygotic isolation between populations that have the greatest interspecific size differences. Together, our data support body size as a magic trait in pine sawflies and possibly many other plant-feeding insects. Our work also demonstrates how intraspecific variation in morphology and ecology can cause geographic variation in the strength of prezygotic isolation.</p>
Data for: Combining environmental niche models, multi-grain analyses, and species traits identifies pervasive effects of land use on butterfly biodiversity across Italy
<p><span>Understanding how species respond to human activities is paramount to ecology and conservation science, one outstanding question being how large-scale patterns in land use affect biodiversity. To facilitate answering this question, we propose a novel analytical framework that combines Environmental Niche Models, multi-grain analyses, and species traits. We illustrate the framework capitalizing on the most extensive dataset compiled to date for the butterflies of Italy (106,514 observations for 288 species), assessing how agriculture and urbanization have affected biodiversity of these taxa from landscape to regional scales (3–48 km grains) across the country while accounting for its steep climatic gradients.</span></p> <p><span>Multiple lines of evidence suggest pervasive and scale-dependent effects of land use on butterflies in Italy. While land use explained patterns in species richness primarily at grains ≤ 12 km, idiosyncratic responses in species highlighted "winners" and "losers" across human-dominated regions. Detrimental effects of agriculture and urbanization emerged from landscape (3-km grain) to regional (48-km grain) scales, disproportionally affecting small butterflies and butterflies with a short flight curve. Human activities have therefore reorganized the biogeography of Italian butterflies, filtering out species with poor dispersal capacity and narrow niche breadth not only from local assemblages but also from regional species pools. </span></p> <p><span>These results suggest that global conservation efforts neglecting large-scale patterns in land use risk falling short of their goals, even for taxa typically assumed to persist in small natural areas (e.g., invertebrates). Our study also confirms that consideration of spatial scales will be crucial to implementing effective conservation actions in the Post-2020 Global Biodiversity Framework. In this context, applications of the proposed analytical framework have broad potential to identify which mechanisms underlie biodiversity change at different spatial scales. </span></p> <p><span><em>Funding statement: </em>FR is supported by the PROBAE project "Protect butterflies across Europe through climate refugia" funded by the European Commission through Horizon 2020, Marie Skłodowska-Curie Actions (MSCA) individual fellowship, reintegration panel (Grant agreement ID: 101024579). Open Access Funding provided by Universita degli Studi di Torino within the CRUI-CARE Agreement.</span></p>
Data - Krieg et al. (2023) Functional Traits and Trait Co-ordination Change Over the Life of a Leaf in a Tropical Fern Species. AJB.
<p>Summary of the data set used in Krieg et al. (2023) Functional Traits and Trait Co-ordination Change Over the Life of a Leaf in a Tropical Fern Species. AJB.</p>
Nutrient-based species selection is a prevalent driver of community assembly and functional trait space in tropical forests
<p><span>1. Soil nutrient availability and functional traits interact in complex ways during the assembly of tree communities hindering our understanding of the implications that this may have for their phylogenetic and functional diversity. </span></p> <p><span>2. We combined abundance, taxonomic, phylogenetic and functional trait data of 222 tree species distributed along nutrient concentration gradients at twenty-four plots in two tropical forest study sites. We analysed micro and macronutrient concentration in organic and topsoil horizons and tested for: (1) nutrient-based species sorting due to contrasting trait-environment relationships; (2) whether nutrient filtering has consequences for phylogenetic and functional diversity, and functional space size and occupancy; and (3) we mapped trait distributions across the phylogeny of tree species to track the evolutionary signature of nutrient availability.</span></p> <p><span>3. We found that total nitrogen (N), available phosphorus and total potassium in soil accounted for 68% of the variation in tropical tree species community composition, with strong associations with nutrient concentration for 89% of the tree species included in the analysis. This nutrient-based species selection was mediated by interactions between the three soil nutrient concentrations with leaf nitrogen, leaf thickness and wood density. Soil N concentration was positively associated with the functional space at the site level. At a plot level soil N concentration positively correlated with functional evenness and it was negatively associated with the functional space not occupied by any species in the tree community. Despite the phylogenetic conservatism of leaf N across tree lineages even when not considering legumes, many sister-species pairs show contrasting values which match with their habitat preferences thus indicating the evolutionary lability of this trait, particularly within recently diversified clades. </span></p> <p><span>4. Synthesis. Our results demonstrate that soil nutrient-based species selection is a prevalent driver of community assembly in tropical forests, a process mediated by key functional traits within the leaf and wood economics spectrum. Functional space size and its filling increase with soil nutrient concentration, whereas niche vacancy decreases. This selection process has likely influenced tropical tree species diversification patterns via habitat specialization.</span></p>
Global intraspecific trait-climate relationships for grasses are linked to a species' typical form and function
<p>Plant traits are useful for predicting how species may respond to environmental change and/or influence ecosystem properties. Understanding the extent to which traits vary within species and across climatic gradients is particularly important for understanding how species may respond to climate change. We explored whether climate drives spatial patterns of intraspecific trait variation for three traits (specific leaf area (SLA), plant height, and leaf nitrogen content (Nmass)) across 122 grass species (family: Poaceae) with a combined distribution across six continents. We tested the hypothesis that the sensitivity (i.e., slope) of intraspecific trait responses to climate across space would be related to the species' typical form and function (e.g., leaf economics, stature, and lifespan). We observed both positive and negative intraspecific trait responses to climate with the distribution of slope coefficients across species straddling zero for precipitation, temperature, and climate seasonality. As hypothesized, variation in slope coefficients across species was partially explained by leaf economics and lifespan. For example, acquisitive species with nitrogen-rich leaves grew taller and produced leaves with higher SLA in warmer regions compared to species with low N<sub>mass</sub>. Compared to perennials, annual grasses invested in leaves with higher SLA yet decreased height and N<sub>mass</sub> in regions with high precipitation seasonality. Thus, while the influence of climate on trait expression may at first appear idiosyncratic, variation in trait-climate slope coefficients is at least partially explained by the species' typical form and function. Overall, our results suggest that a species' mean location along one axis of trait variation (e.g., leaf economics) could influence how traits along a separate axis of variation (e.g., plant size) respond to spatial variation in climate.</p>
CanFlyet: Habitat zone and diet trait dataset for Diptera species of Canada and Greenland
<p>True flies (Diptera) are an ecologically important group that play a role in agriculture, public health, and ecosystem functioning. As researchers continue to investigate this order, it is beneficial to link the growing occurrence data to biological traits. However, large-scale ecological trait data are not readily available for fly species. While some databases and datasets include fly data, many ecologically relevant traits for taxa of interest are not included. In this dataset we provide ecological traits (habitat and diet) for fly species of Canada and Greenland having occurrence records on the Barcode of Life Data Systems (BOLD). Trait data were compiled based on literature searches conducted from April 2021 - January 2023 and assigned at the lowest taxonomic level possible. The dataset contains traits for 983 species across 380 genera, 25 subfamilies, and 61 families. This dataset allows for assignment of traits to occurrence data for Diptera species and can be used for further research into the ecology, evolution, and conservation of this order. </p>
Data for: Traits help explain species' performance away from their climate niche centre
<p class="MsoNormal"><em><span>Aim: </span></em><span>Climate change impacts on biota are variable across sites, among species, and throughout individual species' ranges. Niche theory predicts that population performance should decline as site climate becomes increasingly different from the species' climate niche centre, though studies find significant variation from these predictions. Here, we propose that predictions about climate responses can be improved by incorporating species' trait information. </span></p> <p class="MsoNormal"><em><span>Location:</span></em><span> Europe</span></p> <p class="MsoNormal"><em><span>Methods: </span></em><span>We used observations of plant species abundance change over time to assess variation in climate difference sensitivity (CDS), defined as how species performance (colonization, extinction, and abundance change) relates to the difference of site climate from the mean temperature and precipitation of each species' range. We then investigated if leaf economics, plant size, and seed mass traits were associated with the species' climate difference sensitivity. </span></p> <p class="MsoNormal"><em><span>Results:</span></em><span> Species that performed better (e.g., increased in abundance) towards sites progressively cooler than their niche centre were shorter and had more resource-acquisitive leaves (i.e., lower leaf dry matter content or LDMC) relative to species with zero or the opposite pattern of temperature difference sensitivity. This result supports the hypothesis that if sites cooler than niche centre are more stressful for a species, then shorter stature is advantageous compared to taller species. The LDMC result suggests the environment selects for more resource-acquisitive leaf strategies towards relatively cooler climates with shorter growing seasons, counter to expectations that conservative strategies would be favoured in such environments. We found few consistent relationships between precipitation difference sensitivities and traits. </span></p> <p><em><span>Main conclusions: </span></em><span>The results supported key <em>a priori </em>foundations on how trait-based plant strategies dictate species responses to climate variation away from their niche centre. Further, plant height emerged as the most</span><span> consistent trait that varied with species climate difference sensitivity, suggesting height will be key for theory development around species response to climate change. </span></p>
Exotic fish species traits across levels of establishment
<p>Data for reproducing the results obtained by Bernery, Marino & Bellard (2023) in the paper "Relative importance of exotic species traits in determining invasiveness across levels of establishment: Example of freshwater fish"</p> <p>Data description and scripts for running the analyses are available at: https://github.com/claramarino/estab_levels_exotic_fish</p>
Impact of forest disturbance on microarthropod communities depends on underlying ecological gradient and species traits
<p>Dataset and R scripts used in the publication "Impact of forest disturbance on microarthropod communities depends on underlying ecological gradient and species traits", PeerJ</p>
Data from: Species-specific ecological traits, phylogeny, and geography underpin vulnerability to population declines for North American birds
<p>Species declines and extinctions characterize the Anthropocene. Determining species vulnerability to decline, and where and how to mitigate threats, are paramount for effective conservation. We hypothesized that species with shared ecological traits also share threats, and therefore may experience similar population trends. Here, we used a Bayesian modeling framework to test whether phylogeny, geography, and 22 ecological traits predict regional population trends for 380 North American bird species. Groups like blackbirds, warblers, and shorebirds, as well as species occupying Bird Conservation Regions at more extreme latitudes in North America, exhibited negative population trends, while groups such as ducks, raptors, and waders, as well as species occupying more inland Bird Conservation Regions, exhibited positive trends. Specifically, we found that in addition to phylogeny and breeding geography, multiple ecological traits contributed to explaining variation in regional population trends for North American birds. Furthermore, we found that regional trends and the relative effects of migration distance, phylogeny, and geography differ between shorebirds, songbirds, and waterbirds. Our work provides evidence that multiple ecological traits correlate with North American bird population trends, but that the individual effects of these ecological traits in predicting population trends often vary between different groups of birds. Moreover, our results reinforce the notion that variation in avian population trends is controlled by more than phylogeny and geography, where closely-related species within one region can show unique population trends due to differences in their ecological traits. We recommend that regional conservation plans, i.e. one-size-fits-all plans, be implemented only for bird groups with population trends under strong phylogenetic or geographic controls. We underscore the need to develop species-specific research and management strategies for other groups, like songbirds, that exhibit high variation in their population trends and are influenced by multiple ecological traits.</p>
Shortgrass prairie (Colorado, USA) and northern mixedgrass prairie (Wyoming, USA) species traits
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Evolution in interacting species alters predator life history traits, behavior and morphology in experimental microbial communities
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Data for: Combining environmental niche models, multi-grain analyses, and species traits identifies pervasive effects of land use on butterfly biodiversity across Italy
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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