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828 results for “species trait”
Plant traits of grass and legume species for flood resilience and N2O mitigation
<p>Flooding threatens the functioning of managed grasslands by decreasing primary productivity and increasing nitrogen losses, notably as the potent greenhouse gas nitrous oxide (N2O). Sowing species with traits that promote flood resilience and mitigate flood-induced N2O emissions within these grasslands could safeguard their productivity while mitigating nitrogen losses.</p> <p>We tested how plant traits and resource acquisition strategies could predict flood resilience and N2O emissions of 12 common grassland species (eight grasses and four legumes) grown in field soil in monocultures in a 14-week greenhouse experiment.</p> <p>We found that grasses were more resistant to flooding, while legumes recovered better. Resource-conservative grass species had higher resistance, while resource-acquisitive grasses species recovered better. Resilient grass and legume species lowered cumulative N2O emissions. Grasses with lower inherent leaf and root δ13C (and legumes with lower root δ13C) lowered cumulative N2O emissions during and after the flood.</p> <p>Our results highlight the differing responses of grasses with contrasting resource acquisition strategies, and of legumes to flooding. Combining grasses and legumes based on their traits and resource acquisition strategies could increase the flood-resilience of managed grasslands, and their capability to mitigate flood-induced N2O emissions.</p>
Data from: Within-species trait variation can lead to size limitations in seed dispersal of small-fruited plants
<p>The inability of small-gaped animals to consume very large fruits may limit seed dispersal of the respective plants. This has often been shown for large-fruited plant species that remain poorly dispersed when large-gaped animal species are lost due to anthropogenic pressure. Little is known about whether gape-size limitations similarly influence seed dispersal of small-fruited plant species that can show a large variation in fruit size within species.</p> <p>In this study, fruit sizes of 15 plant species were compared with the gape sizes of their 41 animal dispersers in the temperate, old-growth Białowieża Forest, Poland. The effect of gape-size limitations on fruit consumption was assessed at the plant species level, and for a subset of nine plant species, also at the individual level, and subindividual level (i.e., fruits of the same plant individual). In addition, for the species subset, fruit-seed trait relationships were investigated to determine whether a restricted access of small-gaped animals to large fruits results in the dispersal of fewer or smaller seeds per fruit.</p> <p>Fruit sizes widely varied among plant species (74.2%), considerably at the subindividual level (17.1%), and to the smallest extent among plant individuals (8.7%). Key disperser species should be able to consume fruits of all plant species and all individuals (except those of the largest-fruited plant species), even if they are able to consume only 28-55% of available fruits. Fruit and seed traits were positively correlated in eight out of nine plant species, indicating that gape size limitations will result in 49% fewer (in one plant species) or 16-21% smaller seeds (in three plant species) dispersed per fruit by small-gaped than by large-gaped main dispersers, respectively.</p> <p>Our results show that a large subindividual variation in fruit size is characteristic for small-fruited plant species, and increases their connectedness with frugivores at the level of plants species and individuals. Simultaneously, however, the large variation in fruit size leads to gape-size limitations that may induce selective pressures on fruit size if large-gaped dispersers become extinct. This study emphasizes the mechanisms by which gape-size limitation at the species, individual and subindividual level shape plant-frugivore interactions and the co-evolution of small-fruited plants.</p>
Traits data of exotic species in four tropical botanic gardens and adjacent natural forests
<p>The establishment of new botanic gardens in tropical regions highlights a need for weed risk assessment tools suitable for tropical ecosystems. The relevance of plant traits for invasion into tropical rainforests has not been well studied. </p> <p>Working in and around four botanic gardens in Indonesia where 600 exotic species have been planted, we estimated the effect of four plant traits and time since species were introduced on: a) naturalization probability of exotic species; b) the abundance (density) of naturalized species in adjacent native tropical rainforests; and c) the distance that naturalized exotics have spread from the botanic gardens. </p> <p>We found that specific leaf area (SLA) strongly differentiated 23 naturalized from 78 non-naturalized exotic species (randomly selected from 577 non-naturalized species) in our study. These trends may indicate that exotics with high SLA benefit from at least two factors when establishing in tropical forests: high growth rates and occupation of forest gaps. Exotic species that were present in the gardens for over 30 years and those with small seeds also had higher probabilities of becoming naturalized, indicating that plants can invade the understorey of closed canopy tropical rainforests, especially when invading species are shade-tolerant and have sufficient time to establish. On average, exotic species that were not animal dispersed spread 78 m further into the forests than animal-dispersed species. We did not detect relationships between the measured traits and estimated density of naturalized exotics in the adjacent forests.</p> <p><i><span>Synthesis</span></i>: Traits were able to differentiate exotic species that naturalized from botanic gardens from those that did not; this is promising for developing trait-based risk assessment in the tropics. We suggest tropical botanic gardens avoid planting exotic species with fast carbon capture strategies and those that are shade tolerant, to limit the risk of invasion and spread into adjacent native forests.</p>
Bud traits and post-fire responses of Cerrado woody species, Southeastern Brazil
<p>1) Species growing in fire-prone savannas usually persist by resprouting from their buds. In this study, we evaluated how various persistence traits allow bud protection for improved survival in fire-prone ecosystems.</p> <p>2) Using an integrative morphological and macroanatomical approach, we analyzed how woody plants protect their buds. We tested bud protection at the community level and evaluated: a) how bud protection changes along a fire frequency gradient, b) if it differs between shrubs and trees and c) whether the level of bud protection is related to post-fire responses of 28 woody savanna species.</p> <p>3) A mix of traits involving bud protection may enable woody species persistence in fire-prone ecosystems. Savanna species better protected their buds than forest species by developing bark and trichomes that allowed resprouting after fire. Regarding growth forms, shrub species capable of resprouting aboveground had their buds better protected than trees.</p> <p>4) Bud protection is not only linked with their position to the bark, but also with the presence of trichomes. Profuse trichomes covering buds were related to savanna species. Some species with no bud protection by bark but with trichomes covering their buds were able to resprout after fire. The presence of accessory buds is also a trait more related to savannas, possibly influencing the resprouting after fire as they are better protected and increase the bud bank. Finally, different persistence traits interact with one another to better protect the buds, requiring a detailed screening of the traits to assess species responses to fire.</p> <p>5) Synthesis. During fire, species have their aerial biomass consumed by the flames. To be able to resprout new branches and persist in the environment, they must have well-protected buds. In this study, we evaluated different ways that woody species protect their buds and related them with their resprouting strategy after fire. We investigated the protection by the bark, presence of trichomes and accessory buds. By studying the woody community in a gradient of savannas and forests we found that buds can be protected by bark, trichomes, or soil. Species can present a mix of these traits and strategies, which enhances their resprouting after fire.</p>
Anatomical wood traits of tree species in old-growth and selectively logged forest
<b>Description: </b><p>Traits matrix of wood anatomical characteristics 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=5513918">here</a></p><p><b>Files: </b>This consists of 1 file: Both_wood_anatomical_traits_complete_dataset.xlsx</p><p><b>Both_wood_anatomical_traits_complete_dataset.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Wood_anatomical_traits</b> (described in worksheet Wood_anatomical_traits)</p><p>Description: Traits matrix of wood anatomical characteristics 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>Number of fields: 18</p><p>Number of data rows: 596</p><p>Fields: </p><ul><li><b>location</b>: Location (Field type: location)</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>Wedge.area.micron2</b>: Area of wedge from microtome slice used for analysis. (Field type: numeric trait)</li><li><b>No.vessel.wedge</b>: Count of vessels in the respective wedge area. (Field type: numeric trait)</li><li><b>Vessel.diameter.micron</b>: Mean vessel diameter. Vessel diameter is determined as the mean of the maximum and minimum (lumen) diameters. (Field type: numeric trait)</li><li><b>Median.vessel.diameter.micron</b>: The middle value of the vessel diameter data set. (Field type: numeric trait)</li><li><b>Hydraulically.weighted.diameter.micron</b>: Hydraulically weighted mean diameter. Calculated as (∑ diameter^5) / (∑ diameter^4). (Field type: numeric trait)</li><li><b>Vessel.area.micron2</b>: Mean vessel area. Vessel area is determined by the average cross-sectional area of all vessel lumens (excluding vessel walls) in the wedge-shaped transect of the branch wood cross-section. (Field type: numeric trait)</li><li><b>Median.vessel.area.micron2</b>: The middle value of the vessel area data set. (Field type: numeric trait)</li><li><b>Vessel.lumen.tot.area</b>: Total area of the vessel lumens in the wedge-shaped transect of the branch wood cross-section. (Field type: numeric trait)</li><li><b>vessel.lumen.f.wedge</b>: Vessel lumen fraction. From the vessel areas and transect areas, vessel lumen fraction is calculated as the fraction of transect area filled by vessel lumens. (Field type: numeric trait)</li></ul></li></ol><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> -  -  -  Magnoliopsida <br> -  -  -  -  Malpighiales <br> -  -  -  -  -  Chrysobalanaceae <br> -  -  -  -  -  -  <i>Licania</i> <br> -  -  -  -  -  -  -  <i>Licania splendens</i> <br> -  -  -  -  -  Hypericaceae <br> -  -  -  -  -  -  <i>Cratoxylum</i> <br> -  -  -  -  -  Irvingiaceae <br> -  -  -  -  -  -  <i>Irvingia</i> <br> -  -  -  -  -  -  -  <i>Irvingia malayana</i> <br> -  -  -  -  -  Centroplacaceae <br> -  -  -  -  -  -  <i>Bhesa</i> <br> -  -  -  -  -  -  -  <i>Bhesa indica</i> (as synonym: <i>Bhesa paniculata</i>)<br> -  -  -  -  -  Clusiaceae <br> -  -  -  -  -  -  <i>Garcinia</i> <br> -  -  -  -  -  -  -  <i>Garcinia benthamiana</i> <br> -  -  -  -  -  -  -  <i>Garcinia forbesii</i> <br> -  -  -  -  -  -  -  <i>Garcinia parvifolia</i> <br> -  -  -  -  -  Salicaceae <br> -  -  -  -  -  -  <i>Homalium</i> <br> -  -  -  -  -  -  -  <i>Homalium foetidum</i> <br> -  -  -  -  -  Putranjivaceae <br> -  -  -  -  -  -  <i>Drypetes</i> <br> -  -  -  -  -  -  -  <i>Drypetes longifolia</i> <br> -  -  -  -  -  Achariaceae <br> -  -  -  -  -  -  <i>Hydnocarpus</i> <br> -  -  -  -  -  -  <i>Ryparosa</i> <br> -  -  -  -  -  -  -  <i>Ryparosa acuminata</i> <br> -  -  -  -  -  Euphorbiaceae <br> -  -  -  -  -  -  <i>Spathiostemon</i> <br> -  -  -  -  -  -  <i>Hancea</i> <br> -  -  -  -  -  -  -  <i>Hancea penangensis</i> (as synonym: <i>Mallotus penangensis</i>)<br> -  -  -  -  -  -  <i>Neoscortechinia</i> <br> -  -  -  -  -  -  -  <i>Neoscortechinia kingii</i> <br> -  -  -  -  -  -  -  <i>Neoscortechinia philippinensis</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>Ptychopyxis</i> <br> -  -  -  -  -  -  -  <i>Ptychopyxis arborea</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>Blumeodendron</i> <br> -  -  -  -  -  -  -  <i>Blumeodendron kurzii</i> <br> -  -  -  -  -  -  -  <i>Blumeodendron tokbrai</i> <br> -  -  -  -  -  Phyllanthaceae <br> -  -  -  -  -  -  <i>Aporosa</i> (as synonym: <i>Aporusa</i>)<br> -  -  -  -  -  -  <i>Cleistanthus</i> <br> -  -  -  -  -  -  -  <i>Cleistanthus hirsutulus</i> <br> -  -  -  -  -  -  -  <i>Cleistanthus hylandii</i> <br> -  -  -  -  -  -  -  <i>Cleistanthus oblongifolius</i> (as synonym: <i>Cleistanthus myrianthus</i>)<br> -  -  -  -  -  -  <i>Glochidion</i> <br> -  -  -  -  -  -  <i>Phyllanthus</i> <br> -  -  -  -  -  -  -  <i>Phyllanthus lutescens</i> (as synonym: <i>Glochidion lutescens</i>)<br> -  -  -  -  -  -  -  <i>Phyllanthus ruber</i> (as synonym: <i>Glochidion rubrum</i>)<br> -  -  -  -  -  -  <i>Baccaurea</i> <br> -  -  -  -  -  -  -  <i>Baccaurea lanceolata</i> <br> -  -  -  -  -  -  -  <i>Baccaurea macrocarpa</i> <br> -  -  -  -  -  -  -  <i>Baccaurea tetrandra</i> <br> -  -  -  -  -  Calophyllaceae <br> -  -  -  -  -  -  <i>Mesua</i> <br> -  -  -  -  -  -  -  <i>Mesua oblongifolia</i> (as synonym: <i>Kayea oblongifolia</i>)<br> -  -  -  -  -  -  -  <i>Mesua macrantha</i> <br> -  -  -  -  -  -  <i>Calophyllum</i> <br> -  -  -  -  -  -  -  <i>Calophyllum soulattri</i> <br> -  -  -  -  Malvales <br> -  -  -  -  -  Malvaceae <br> -  -  -  -  -  -  <i>Heritiera</i> <br> -  -  -  -  -  -  -  <i>Heritiera elata</i> <br> -  -  -  -  -  -  <i>Pterygota</i> <br> -  -  -  -  -  -  -  <i>Pterygota alata</i> <br> -  -  -  -  -  -  <i>Pentace</i> <br> -  -  -  -  -  -  -  <i>Pentace borneensis</i> (as synonym: <i>Pentace laxiflora</i>)<br> -  -  -  -  -  -  <i>Sterculia</i> <br> -  -  -  -  -  -  -  <i>Sterculia stipulata</i> <br> -  -  -  -  -  -  <i>Microcos</i> <br> -  -  -  -  -  -  -  <i>Microcos crassifolia</i> <br> -  -  -  -  -  -  <i>Scaphium</i> <br> -  -  -  -  -  -  -  <i>Scaphium macropodum</i> <br> -  -  -  -  -  -  <i>Boschia</i> <br> -  -  -  -  -  -  -  <i>Boschia grandiflora</i> (as synonym: <i>Durio grandiflorus</i>)<br> -  -  -  -  -  -  <i>Durio</i> <br> -  -  -  -  -  -  -  <i>Durio graveolens</i> <br> -  -  -  -  -  Dipterocarpaceae <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 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 parviflora</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>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 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 parviflora</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> -  -  -  -  -  -  <i>Hopea</i> <br> -  -  -  -  -  -  -  <i>Hopea plagata</i> <br> -  -  -  -  -  -  -  <i>Hopea sangal</i> <br> -  -  -  -  -  -  <i>Dipterocarpus</i> <br> -  -  -  -  -  -  -  <i>Dipterocarpus caudiferus</i> <br> -  -  -  -  -  -  <i>Dryobalanops</i> <br> -  -  -  -  -  -  -  <i>Dryobalanops lanceolata</i> <br> -  -  -  -  -  -  <i>Parashorea</i> <br> -  -  -  -  -  -  -  <i>Parashorea malaanonan</i> <br> -  -  -  -  -  -  -  <i>Parashorea smythiesii</i> <br> -  -  -  -  -  -  -  <i>Parashorea warburgii</i> (as synonym: <i>Parashorea tomentella</i>)<br> -  -  -  -  -  Thymelaeaceae <br> -  -  -  -  -  -  <i>Aquilaria</i> <br> -  -  -  -  -  -  -  <i>Aquilaria beccariana</i> <br> -  -  -  -  Celastrales <br> -  -  -  -  -  Celastraceae <br> -  -  -  -  -  -  <i>Lophopetalum</i> <br> -  -  -  -  -  -  -  <i>Lophopetalum beccarianum</i> <br> -  -  -  -  -  -  -  <i>Lophopetalum javanicum</i> <br> -  -  -  -  Santalales <br> -  -  -  -  -  Coulaceae <br> -  -  -  -  -  -  <i>Ochanostachys</i> <br> -  -  -  -  -  -  -  <i>Ochanostachys amentacea</i> <br> -  -  -  -  Fagales <br> -  -  -  -  -  Fagaceae <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>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> -  -  -  -  -  -  <i>Castanopsis</i> <br> -  -  -  -  -  -  -  <i>Castanopsis hypophoenicea</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> -  -  -  -  Rosales <br> -  -  -  -  -  Urticaceae <br> -  -  -  -  -  -  <i>Dendrocnide</i> <br> -  -  -  -  -  -  -  <i>Dendrocnide elliptica</i> <br> -  -  -  -  -  Rosaceae <br> -  -  -  -  -  -  <i>Prunus</i> <br> -  -  -  -  -  -  -  <i>Prunus javanica</i> <br> -  -  -  -  -  -  <i>Pygeum</i> <br> -  -  -  -  -  -  -  <i>Pygeum beccarii</i> (as synonym: <i>Prunus beccarii</i>)<br> -  -  -  -  -  Moraceae <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> -  -  -  -  -  -  <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> -  -  -  -  -  Cannabaceae <br> -  -  -  -  -  -  <i>Trema</i> <br> -  -  -  -  -  -  -  <i>Trema orientalis</i> <br> -  -  -  -  Cornales <br> -  -  -  -  -  Nyssaceae <br> -  -  -  -  -  -  <i>Mastixia</i> <br> -  -  -  -  -  -  -  <i>Mastixia trichotoma</i> <br> -  -  -  -  -  Cornaceae <br> -  -  -  -  -  -  <i>Alangium</i> <br> -  -  -  -  -  -  -  <i>Alangium javanicum</i> <br> -  -  -  -  Gentianales <br> -  -  -  -  -  Apocynaceae <br> -  -  -  -  -  -  <i>Alstonia</i> <br> -  -  -  -  -  -  -  <i>Alstonia angustiloba</i> <br> -  -  -  -  -  Rubiaceae <br> -  -  -  -  -  -  <i>Neonauclea</i> <br> -  -  -  -  -  -  -  <i>Neonauclea gigantea</i> <br> -  -  -  -  -  -  <i>Ludekia</i> <br> -  -  -  -  -  -  -  <i>Ludekia borneensis</i> <br> -  -  -  -  -  -  <i>Psydrax</i> <br> -  -  -  -  -  -  -  <i>Psydrax dicoccos</i> <br> -  -  -  -  -  -  <i>Urophyllum</i> <br> -  -  -  -  -  -  -  <i>Urophyllum polyneurum</i> (as synonym: <i>Pleiocarpidia polyneura</i>)<br> -  -  -  -  -  -  <i>Neolamarckia</i> <br> -  -  -  -  -  -  -  <i>Neolamarckia cadamba</i> <br> -  -  -  -  -  -  <i>Nauclea</i> <br> -  -  -  -  -  -  -  <i>Nauclea subdita</i> <br> -  -  -  -  Fabales <br> -  -  -  -  -  Fabaceae <br> -  -  -  -  -  -  <i>Sindora</i> <br> -  -  -  -  -  -  <i>Crudia</i> <br> -  -  -  -  -  -  -  <i>Crudia reticulata</i> <br> -  -  -  -  -  -  <i>Fordia</i> <br> -  -  -  -  -  -  -  <i>Fordia brachybotrys</i> <br> -  -  -  -  -  -  -  <i>Fordia splendidissima</i> <br> -  -  -  -  -  -  <i>Dialium</i> <br> -  -  -  -  -  -  -  <i>Dialium indum</i> <br> -  -  -  -  -  -  -  <i>Dialium kunstleri</i> <br> -  -  -  -  -  -  <i>Archidendron</i> <br> -  -  -  -  -  -  -  <i>Archidendron clypearia</i> <br> -  -  -  -  -  -  <i>Cynometra</i> <br> -  -  -  -  -  -  -  <i>Cynometra mirabilis</i> <br> -  -  -  -  Sapindales <br> -  -  -  -  -  Meliaceae <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>Aphanamixis</i> <br> -  -  -  -  -  -  -  <i>Aphanamixis polystachya</i> <br> -  -  -  -  -  -  <i>Lansium</i> <br> -  -  -  -  -  -  -  <i>Lansium domesticum</i> <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> -  -  -  -  -  Sapindaceae <br> -  -  -  -  -  -  <i>Nephelium</i> <br> -  -  -  -  -  -  <i>Paranephelium</i> <br> -  -  -  -  -  -  -  <i>Paranephelium macrophyllum</i> <br> -  -  -  -  -  -  -  <i>Paranephelium xestophyllum</i> <br> -  -  -  -  -  -  <i>Dimocarpus</i> <br> -  -  -  -  -  -  -  <i>Dimocarpus longan</i> <br> -  -  -  -  -  -  <i>Tristiropsis</i> <br> -  -  -  -  -  -  -  <i>Tristiropsis acutangula</i> <br> -  -  -  -  -  -  <i>Pometia</i> <br> -  -  -  -  -  -  -  <i>Pometia pinnata</i> <br> -  -  -  -  -  Burseraceae <br> -  -  -  -  -  -  <i>Santiria</i> <br> -  -  -  -  -  -  -  <i>Santiria laevigata</i> <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> -  -  -  -  -  Rutaceae <br> -  -  -  -  -  -  <i>Melicope</i> <br> -  -  -  -  -  -  -  <i>Melicope confusa</i> <br> -  -  -  -  -  Anacardiaceae <br> -  -  -  -  -  -  <i>Mangifera</i> <br> -  -  -  -  -  -  -  <i>Mangifera odorata</i> <br> -  -  -  -  -  -  <i>Parishia</i> <br> -  -  -  -  -  -  -  <i>Parishia insignis</i> <br> -  -  -  -  -  -  <i>Gluta</i> <br> -  -  -  -  -  -  -  <i>Gluta aptera</i> <br> -  -  -  -  -  -  -  <i>Gluta wallichii</i> <br> -  -  -  -  -  -  <i>Melanochyla</i> <br> -  -  -  -  -  -  -  <i>Melanochyla bullata</i> <br> -  -  -  -  -  -  -  <i>Melanochyla tomentosa</i> <br> -  -  -  -  Laurales <br> -  -  -  -  -  Lauraceae <br> -  -  -  -  -  -  <i>Actinodaphne</i> <br> -  -  -  -  -  -  <i>Beilschmiedia</i> <br> -  -  -  -  -  -  -  <i>Beilschmiedia micrantha</i> <br> -  -  -  -  -  -  <i>Phoebe</i> <br> -  -  -  -  -  -  -  <i>Phoebe grandis</i> <br> -  -  -  -  -  -  <i>Litsea</i> <br> -  -  -  -  -  -  -  <i>Litsea accedens</i> <br> -  -  -  -  -  -  -  <i>Litsea angulata</i> <br> -  -  -  -  -  -  -  <i>Litsea caulocarpa</i> <br> -  -  -  -  -  -  -  <i>Litsea garciae</i> <br> -  -  -  -  -  -  -  <i>Litsea grandis</i> <br> -  -  -  -  -  -  -  <i>Litsea cordata</i> (as synonym: <i>Litsea mappacea</i>)<br> -  -  -  -  -  -  -  <i>Litsea rubiginosa</i> <br> -  -  -  -  -  -  <i>Lindera</i> <br> -  -  -  -  -  -  -  <i>Lindera lucida</i> <br> -  -  -  -  -  -  <i>Eusideroxylon</i> <br> -  -  -  -  -  -  -  <i>Eusideroxylon zwageri</i> <br> -  -  -  -  -  -  <i>Nothaphoebe</i> <br> -  -  -  -  -  -  -  <i>Nothaphoebe umbelliflora</i> <br> -  -  -  -  -  -  <i>Cryptocarya</i> <br> -  -  -  -  -  -  -  <i>Cryptocarya nigra</i> <br> -  -  -  -  -  -  -  <i>Cryptocarya nitens</i> <br> -  -  -  -  -  -  <i>Caryodaphnopsis</i> <br> -  -  -  -  -  -  -  <i>Caryodaphnopsis tonkinensis</i> <br> -  -  -  -  -  -  <i>Dehaasia</i> <br> -  -  -  -  -  -  -  <i>Dehaasia caesia</i> <br> -  -  -  -  -  -  -  <i>Dehaasia incrassata</i> <br> -  -  -  -  Magnoliales <br> -  -  -  -  -  Annonaceae <br> -  -  -  -  -  -  <i>Cyathocalyx</i> <br> -  -  -  -  -  -  <i>Monoon</i> <br> -  -  -  -  -  -  <i>Polyalthia</i> <br> -  -  -  -  -  -  -  <i>Polyalthia obliqua</i> <br> -  -  -  -  -  -  <i>Sageraea</i> <br> -  -  -  -  -  -  -  <i>Sageraea elliptica</i> <br> -  -  -  -  -  -  <i>Miliusa</i> <br> -  -  -  -  -  -  -  <i>Miliusa macropoda</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> -  -  -  -  -  -  <i>Phaeanthus</i> <br> -  -  -  -  -  -  -  <i>Phaeanthus splendens</i> <br> -  -  -  -  -  -  <i>Maasia</i> <br> -  -  -  -  -  -  -  <i>Maasia sumatrana</i> <br> -  -  -  -  -  -  <i>Neo-uvaria</i> <br> -  -  -  -  -  -  -  <i>Neo-uvaria acuminatissima</i> <br> -  -  -  -  -  -  <i>Orophea</i> <br> -  -  -  -  -  -  -  <i>Orophea myriantha</i> <br> -  -  -  -  -  -  <i>Pseuduvaria</i> <br> -  -  -  -  -  -  -  <i>Pseuduvaria borneensis</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>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> -  -  -  -  -  -  <i>Horsfieldia</i> <br> -  -  -  -  -  -  -  <i>Horsfieldia crassifolia</i> <br> -  -  -  -  Ericales <br> -  -  -  -  -  Primulaceae <br> -  -  -  -  -  -  <i>Ardisia</i> <br> -  -  -  -  -  -  -  <i>Ardisia macrophylla</i> <br> -  -  -  -  -  Lecythidaceae <br> -  -  -  -  -  -  <i>Planchonia</i> <br> -  -  -  -  -  -  -  <i>Planchonia brevistipitata</i> <br> -  -  -  -  -  -  <i>Barringtonia</i> <br> -  -  -  -  -  -  -  <i>Barringtonia lanceolata</i> <br> -  -  -  -  -  -  -  <i>Barringtonia macrostachya</i> <br> -  -  -  -  -  -  -  <i>Barringtonia sarcostachys</i> <br> -  -  -  -  -  Symplocaceae <br> -  -  -  -  -  -  <i>Symplocos</i> <br> -  -  -  -  -  -  -  <i>Symplocos fasciculata</i> <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 tuberculata</i> <br> -  -  -  -  -  -  -  <i>Diospyros pilosanthera</i> <br> -  -  -  -  -  Theaceae <br> -  -  -  -  -  -  <i>Pyrenaria</i> <br> -  -  -  -  -  -  -  <i>Pyrenaria tawauensis</i> <br> -  -  -  -  -  Pentaphylacaceae <br> -  -  -  -  -  -  <i>Adinandra</i> <br> -  -  -  -  -  -  -  <i>Adinandra dumosa</i> <br> -  -  -  -  -  Sapotaceae <br> -  -  -  -  -  -  <i>Payena</i> <br> -  -  -  -  -  -  -  <i>Payena acuminata</i> <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 sericeum</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> -  -  -  -  Myrtales <br> -  -  -  -  -  Melastomataceae <br> -  -  -  -  -  -  <i>Memecylon</i> <br> -  -  -  -  -  -  -  <i>Memecylon oleifolium</i> <br> -  -  -  -  -  Combretaceae <br> -  -  -  -  -  -  <i>Terminalia</i> <br> -  -  -  -  -  -  -  <i>Terminalia citrina</i> <br> -  -  -  -  -  -  -  <i>Terminalia foetidissima</i> <br> -  -  -  -  -  Myrtaceae <br> -  -  -  -  -  -  <i>Syzygium</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 panzeri</i> <br> -  -  -  -  -  -  -  <i>Syzygium pustulatum</i> (as synonym: <i>Syzygium perpuncticulatum</i>)<br> -  -  -  -  -  -  -  <i>Syzygium racemosum</i> <br> -  -  -  -  -  -  -  <i>Syzygium rheophyticum</i> <br> -  -  -  -  -  -  <i>Syzygium</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 panzeri</i> <br> -  -  -  -  -  -  -  <i>Syzygium pustulatum</i> (as synonym: <i>Syzygium perpuncticulatum</i>)<br> -  -  -  -  -  -  -  <i>Syzygium racemosum</i> <br> -  -  -  -  -  -  -  <i>Syzygium rheophyticum</i> <br> -  -  -  -  -  -  <i>Syzygium</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 panzeri</i> <br> -  -  -  -  -  -  -  <i>Syzygium pustulatum</i> (as synonym: <i>Syzygium perpuncticulatum</i>)<br> -  -  -  -  -  -  -  <i>Syzygium racemosum</i> <br> -  -  -  -  -  -  -  <i>Syzygium rheophyticum</i> <br> -  -  -  -  -  Lythraceae <br> -  -  -  -  -  -  <i>Duabanga</i> <br> -  -  -  -  -  -  -  <i>Duabanga moluccana</i> <br></div><p></p>
melian009/Mispark: Preliminary analysis mutualistic networks in space, rarefaction, sierra size and sampling individuals, species, and traits
<p>Mutualistic networks in space, morphological traits and colors, or how to put all together to understand rare and common species in rapidly changing landscapes</p>
Selfing rate variation within species is unrelated to life-history traits or geographic range position
<p>Premise: In plants, populations and species vary widely along the continuum from outcrossing to selfing. Life-history traits and ecological circumstances influence among-species variation in selfing rates but their general role in explaining intraspecific variation is unknown. Using a database of plant species, we test whether life-history traits, geographic range position, or abundance predict selfing rate variation among populations. </p> <p>Methods: We identified species where selfing rates were estimated in at least three populations at known locations. Two key life-history traits (generation time and growth form) were used to predict within-species selfing rate variation. Populations sampled within a species' native range were assessed for proximity to the nearest edge and abundance. Finally, we conducted linear and segmented regressions to determine functional relationships between selfing rate and geographic range position within species.</p> <p>Key results: While woody species exhibit lower variation in selfing rates compared to herbs, this is explained by the lower average selfing rate of woody species. Relationships between selfing and peripherality or abundance significantly varied among species in their direction and magnitude. However, there was no general pattern of increased selfing towards range edges. A power analysis shows that tests of this hypothesis require studying many (i.e. 40+) populations.</p> <p>Conclusions: Intraspecific variation in plant mating systems is often substantial yet remains difficult to explain. Beyond sampling more populations, future tests of biogeographic hypotheses will benefit from phylogeographic information concerning specific range edges, the study of traits influencing mating system (e.g. herkogamy), and measures of abundance at local scales (e.g. population density).</p>
Trait-habitat associations explain novel bird assemblages mixing native and alien species across New-Zealand landscapes
<p><strong>Aim</strong>: Species introductions have reshaped island faunas for the last 200 years, often threatening native biodiversity. Approximately equal numbers of native and alien species currently co-occur in the New Zealand avifauna, but they show distinct habitat use. Antagonistic interactions, habitat affinities and legacies of introduction history may concur to explain their segregation along habitat gradients. To investigate these processes, we explored how habitat, ecological traits and introduction history relate with the current composition of bird assemblages.</p> <p><strong>Location</strong>: New Zealand</p> <p><strong>Taxon</strong>: Birds</p> <p><strong>Methods</strong>: We analysed 917 bird point counts spread along habitat and elevation gradients in the Canterbury region, South Island, and related 10 ecological traits to landscape composition using a three-table ordination method known as 'RLQ analysis', accounting for spatial autocorrelation and phylogeny. We tested whether alien species' positions in the RLQ were related to proxies of introduction history.</p> <p><strong>Results</strong>: Eighteen endemic, 11 native and 19 alien species were distributed along a gradient from forest to open-habitat assemblages, in relation to foraging mode, nesting site and body size. A second gradient segregated species between native and exotic forests according to territoriality, sedentarity and diet. Traits accounted for the separation of native and alien bird species in forests, but not in open habitats. Phylogenetic signals emerged from the separation of native and alien species by forest type, and spatial structures suggested a landscape-level, rather than regional or local determinism. These correlations were independent of introduction history, although open-habitat assemblages tended to host alien species introduced later in time. </p> <p><strong>Main conclusions: </strong>Habitat type and resource availability explain the spatial partitioning of New Zealand bird assemblages between native and alien species more consistently than competitive exclusion. We conclude that trait-mediated ecological differences among species have likely played a predominant role in species' segregation among landscapes, while maintaining endemic bird assemblages in native forests. </p>
How detritivores, plant traits and time modulate coupling of leaf versus woody litter decomposition rates across species
<p>1. Plant functional traits are increasingly used to understand ecological relationships and (changing) ecosystem functions. For understanding ecosystem-level biogeochemistry, we need to understand how (much) traits co-vary between different plant organs across species, and its implications for litter decomposition. However, we do not know how the degree of synchronous variation in decomposition rates between organs across species could be influenced by different keystone invertebrates decomposing different senesced plant organs, especially in warm-climate forests. Here we asked whether interspecific patterns in wood and leaf decomposition rates and in the spectra of resource economics traits underpinning them, co-vary across woody species; and how (much) the keystone invertebrate decomposers of the litter of these organs enhance or lower such co-variation of decomposition rates through time. </p> <p>2. We addressed these questions through an 18-month "common-garden" decomposition experiment using leaf, twig and branch litter of 41 woody species in two distant subtropical forest sites in east China. We quantified the effects of leaf, twig, and branch functional traits and their respective key invertebrates (moth larvae, termites) on the decomposition rates of those organs. </p> <p>3. Interspecific variation in wood traits was partly decoupled from that in leaf traits across species, while strong coupling was found between twigs and branches. The co-variation between leaf and woody organ decomposition rates was altered dynamically through the shifting activities of the key decomposers, which created non-linear relationships of invertebrate litter consumption as a function of species rankings along the resource economic trait spectra of leaves and branches.</p> <p>4. The deviations from coupling of decomposition rates between organs were likely caused by combinations of three mechanisms: (1) (de-)coupling between organs of other traits, not commonly considered in resource economics spectra (e.g., resins) (2) leaf and wood decomposers having specific diet requirements, and (3) temporal patterns of the decomposers' activity.</p> <p>5. Synthesis. Our study highlights the importance of considering the different ways by which invertebrate detritivores drive decomposition processes through time. Under the ongoing biodiversity decline, future research would benefit from a better understanding of the role of the dynamic interactions between detritivore activities and plant functional traits on the carbon turnover in ecosystems.</p>
Functional traits of Arctiinae species of Barro Colorado Island, Panama
<p>A matrix of trait data for 192 species of Arctiinae moth recorded on Barro Colorado Island from 2009 to 2019, collected as part of the Forest GEO arthropod initiative. </p>
Hydraulic traits are not robust predictors of tree species stem growth during a drought in a wet tropical forest
<p>Severe droughts have led to lower plant growth and high mortality in many ecosystems worldwide, including tropical forests. Drought vulnerability differs among species but there is limited consensus on the nature and degree of this variation in tropical forest communities. Understanding species-level vulnerability to drought requires examination of hydraulic traits since these reflect the different strategies species employ for surviving drought. Here we examined hydraulic traits and growth reductions during a severe drought for 12 common woody species in a wet tropical forest community in Puerto Rico to ask:</p> <p>Q1. To what extent can hydraulic traits predict growth declines during drought? We expected that species with more hydraulicly vulnerable xylem and narrower safety margins would grow less during drought.</p> <p>Q2. How do species successional association relate to levels of vulnerability to drought and hydraulic strategies? We predicted that early- and mid-successional species would exhibit more acquisitive strategies, making them more susceptible to drought than shade-tolerant species.</p> <p>Q3. What are the different hydraulic strategies employed by species and are there trade-offs between drought avoidance and drought tolerance?</p> <p>We anticipated that species with greater water storage capacity would have leaves that lose turgor at higher xylem water potential and be less resistant to embolism forming in their xylem (P50). We found a large range of variation in hydraulic traits across species; however, they did not closely capture the magnitude of growth declines during drought. Among larger trees (≥10 cm diameter at breast height—DBH), some tree species with high xylem embolism vulnerability and risk of hydraulic failure experienced substantial declines during drought but this pattern was consistent across species. We found a trade-off among species between drought avoidance (capacitance) and drought tolerating (P50) in this tropical forest community. Hydraulic strategies did not align with successional associations. Instead, some of the more drought-vulnerable species were shade-tolerant dominants in the community, suggesting that a drying climate could lead to shifts in long-term forest composition and function in Puerto Rico and the Caribbean.</p>
Data from: Hedging at the rear edge: Intraspecific trait variability drives the trajectory of marginal populations in a widespread boreal tree species
<p>Rear-edge populations at the warm margin of species distribution are small, isolated and face environmental conditions at the limit of species bioclimatic envelope. Intraspecific phenotypic variation contributing to the persistence of peripheral populations is expected to become increasingly important under future climate conditions in order to avoid local extirpation where range shifts lag behind climate change velocity.</p> <p>We investigated the putative role of intraspecific phenotypic variation for the maintenance of rear-edge populations of fire-prone jack pine (<em>Pinus banksiana</em>), an obligate pyriscent boreal species. We assessed whether variation in cone serotiny is associated with the population trajectory of marginal stands located south of the boreal biome, in the temperate forest where natural wildfires are infrequent and unpredictable. To this end, we estimated stand-scale serotiny, minimal age and tree size structure in 26 jack pine stands from the rear edge (n = 17 sites) and the core (n = 9 sites) of the species' range in eastern Canada.</p> <p>On average, rear-edge jack pine populations are less serotinous albeit more variably compared to range-core populations where serotiny is more uniformly high. Rear-edge stands are generally older and display reverse J-shape tree size structure indicative of a multi-aged demographic equilibrium, whereas range-core stands are younger and show a unimodal stand structure depicting a single aging cohort generally lacking interfire recruitment. Eco-evolutionary dynamics shifts from a dependency on wildfires in range-core populations to stands that can regenerate and persist without recurrent fires at the rear edge, where stand-scale serotiny reaches values below 85%.</p> <p>Synthesis: Unlike range-core populations, rear-edge jack pine populations can locally rely on a dual life-history strategy to ensure both steady recruitment during fire-free intervals and successful postfire regeneration. This capacity to cope with infrequent and unpredictable fire regime should increase the resilience and resistance of jack pine populations as global changes alter fire dynamics of the boreal forest. More generally, unique intraspecific phenotypic variation in rear-edge populations contributes to long-term species persistence in marginal environmental conditions that might scale up with global changes. The conservation of rear-edge populations and their genetic legacy appears crucial for the resilience of species.</p>
Data and code for: Functional traits mediate individualistic species-environment distributions at broad spatial scales while fine-scale species' associations remain unpredictable
<p>Ecological communities are structured by a diverse set of processes acting at different spatial scales. In plant communities, assembly processes like ecological sorting, limiting similarity, and stochastic events are all expected to influence plant distributions and co-occurrence patterns. We assembled a data set describing the distribution of 139 herbaceous plant species within and among 257 forest stands in Wisconsin (USA) to elucidate the spatial scales at which these assembly processes operate. Analyses of these data in conjunction with detailed information about environmental conditions, plant functional traits, and phylogenetic relationships provided new insights into the scale-dependent drivers of plant community assembly in temperate forest understories. Traits like leaf height, specific leaf area, and seed mass all influenced individualistic plant distributions along landscape-scale gradients in soil texture, soil fertility, light availability, and climate while phylogenetic relationships did not predict species-environment relationships. These findings point to the importance of trait-mediated ecological sorting in shaping individualistic plant distributions at broad spatial scales. Contrary to our expectations about the importance of limiting similarity at local scales, neither functionally similar nor phylogenetically related herbs segregated among microsites within forest stands. We hypothesize strong ecological sorting among forest stands coupled with stochastic fine-scale interactions among species appear deterministic, niche-based assembly processes at local scales.</p>
Mapping trait versus species turnover reveals spatiotemporal variation in functional redundancy and network robustness in a plant‐pollinator community
<p>1. Functional overlap among species (redundancy) is considered important in shaping competitive and mutualistic interactions that determine how communities respond to environmental change. Most studies view functional redundancy as static, yet traits within species – which ultimately shape functional redundancy – can vary over seasonal or spatial gradients. We therefore have limited understanding of how trait turnover within and between species could lead to changes in functional redundancy or how loss of traits could differentially impact mutualistic interactions depending on where and when the interactions occur in space and time.</p> <p>2. Using an Arctic bumblebee community as a case study, and 1,277 individual measures from 14 species over three annual seasons, we quantified how inter- and intraspecific body-size turnover compared to species turnover with elevation and over the season. Coupling every individual and their trait with a plant visitation, we investigated how grouping individuals by a morphological trait or by species identity altered our assessment of network structure and how this differed in space and time. Finally, we tested how the sensitivity of the network in space and time differed when simulating extinction of nodes representing either morphological trait similarity or traditional species groups. This allowed us to explore the degree to which trait-based groups increase or decrease interaction redundancy relative to species-based nodes.</p> <p>3. We found that i) groups of taxonomically and morphologically similar bees turn over in space and time independently from each other, with trait turnover being larger over the season; ii) networks composed of nodes representing species versus morphologically similar bees were structured differently; and iii) simulated loss of bee trait groups caused faster coextinction of bumblebee species and flowering plants than when bee taxonomic groups were lost. Crucially, the magnitude of these effects varied in space and time, highlighting the importance of considering spatiotemporal context when studying the relative importance of taxonomic and trait contributions to interaction network architecture.</p> <p>4. Our finding that functional redundancy varies spatiotemporally demonstrates how considering the traits of individuals within networks is needed to understand the impacts of environmental variation and extinction on ecosystem functioning and resilience.</p>
MammalBase — Database of traits, measurements and diets of the species in class Mammalia
<p><strong>MammalBase is a database of traits, measurements and diets of the species in class Mammalia. It also provides Proximate Analysis data for several diet items.</strong></p> <p><strong>MammalBase aims to provide general information on mammals for broad-scale analyses in Macroecology, Palaeontology and mammalian Community structures.</strong></p> <p><strong>The database is maintained at the Natural Sciences Unit of the Finnish Museum of Natural History LUOMUS — a research institution under the University of Helsinki in Finland.</strong></p>
Trait adaptation enhances species coexistence and reduces bistability in an intraguild predation module
<p><span>Disentangling how species coexist in an intraguild predation (IGP) module is a great step towards understanding biodiversity conservation in complex natural food webs. Trait variation enabling </span><span>individual species</span><span> to adjust</span><span> to ambient conditions may facilitate coexistence. However, it is still unclear how </span><span>co-adaptation of </span><span>all species within the IGP module</span><span>, constrained by complex</span><span> trophic </span><span>interactions</span><span> and </span><span>trade-offs among species-specific traits,</span><span> interactively affects species coexistence and population dynamics.</span> <span>We developed an adaptive IGP model allowing prey and predator species to mutually adjust their </span><span>species-specific</span><span> defensive and offensive strategies to each other. We investigated species persistence, the temporal variation of population dynamics, and the occurrence of bistability in IGP models without and with trait adaptation along a gradient of enrichment</span><span> represented by </span><span>carrying capacity of the basal prey for </span><span>different</span><span> widths</span><span> and speeds of trait adaptation within each species</span><span>. </span><span>Results showed that trait adaptation within multiple species greatly enhanced the coexistence of all three species in the module. A larger width of trait adaptation facilitated species coexistence independent of the speed of trait adaptation at lower enrichment levels, while a sufficiently large and fast trait adaptation promoted species coexistence at higher enrichment levels. Within the oscillating regime, increasing the speed of trait adaptation reduced the temporal variability of biomasses of all species. Finally, species co-adaptation strongly reduced the presence of bistability and promoted the attractor with all three species coexisting.</span> <span>These findings resolve the contradiction between the widespread occurrence of IGP in nature and the theoretical predictions that IGP should only occur under restricted conditions and lead to unstable population dynamics, which broadens the mechanisms presumably underlying the maintenance of IGP modules in nature. Generally, this study </span><span>demonstrates</span> <span>a decisive role of mutual adaptation among complex trophic interactions, </span><span>for enhancing interspecific diversity and </span><span>stabilizing </span><span>food web </span><span>dynamics, arising e.g. from </span><span>intraspecific diversity.</span></p>
Source Data for: Temperature, species identity and morphological traits predict carbonate excretion and mineralogy in tropical reef fishes
<p>Source Data underlying figures of the paper "Temperature, species identity and morphological traits predict carbonate excretion and mineralogy in tropical reef fishes" by Mattia Ghilardi, Michael A. Salter, Valeriano Parravicini, Sebastian C. A. Ferse, Tim Rixen, Christian Wild, Matthias Birkicht, Chris T. Perry, Alex Berry, Rod W. Wilson, David Mouillot, Sonia Bejarano</p>
Leaf decomposition, flammability and functional trait data for tropical swamp forest tree species
<p>Decomposition and fire are major carbon pathways in many ecosystems, yet the contribution of species identity to these processes can be difficult to predict. Plant decomposability and flammability have usually been studied separately but could be linked through shared predictive traits. We explored how decomposability and flammability were related to each other and to key plant functional traits in a tropical swamp forest in Singapore.</p> <p>Full methodological details <em>in situ</em> decomposition experiment in Nee Soon freshwater swamp forest, Singapore, laboratory flammability experiment, and leaf functional trait measurements can be found in the published article and supporting information stated below.</p> <p>Nur E. B. Rahman, Stuart W. Smith, Weng Ngai Lam, Kwek Yan Chong, Matthias S. E. Chua, Pei Yun Teo, Daniel W. J. Lee, Shi Yu Phua, Cheryl Y. Aw, Janice S. H. Lee, David A. Wardle. Leaf decomposition and flammability are largely decoupled across species in a tropical swamp forest despite sharing some predictive leaf functional traits. <em>New Phytologist</em></p> <p>In this data repository, we have uploaded the following decomposition, flammability and trait data as well as secondary data used in our statistical analyses to generate the findings presented in the paper. Specific datasets include the following:</p> <ul> <li>litter_mass_loss.csv : raw data of leaf litterbag dry masses before and after 1 year in situ decomposition experiment in Nee Soon Swamp Forest</li> <li>flammability_leaf_temperature.csv : raw data of temperature recorded during flammability experiments of leaf litter and fresh leaves</li> <li>flammability_timings.csv : raw data of timings of flammability events, namely smouldering and pyrolysis recorded from video footage of flammability experiments</li> <li>senesced_leaf_dryweights_area.csv : senesced leaf raw data for calculating physical traits</li> <li>senesced_leaf_dryweights.csv: senesced leaf dry weights raw data</li> <li>freshtraits_measurements.csv: fresh leaf raw data for calculating physical traits</li> <li>decomposition_constants.csv: derived decomposition constants (k) for each species from the analysis of decomposition experiments.</li> <li>functional_traits_z_standardized.csv : all traits required for the analysis, consolidated following z-standardized transformation</li> <li>functional_traits_untransformed_decomposition_flammability.csv : all traits required for the analysis, untransformed (for back transforming axis labels) and species decomposition and flammability variables</li> </ul> <p>Raw leaf litter mass loss and leaf flammability data are associated meta-data file explaining the column headers and variables. For all other datasets please refer to the paper and supporting information.</p>
Model outputs and species-level data for "Functional traits and climate drive interspecific differences in disturbance-induced tree mortality"
<p>This repository is divided in three sub-directories: </p> <ul> <li><em><strong>sensitivity </strong></em>contains the posterior of each parameter estimated by the bayesian mortality model in a rdata file. This file was generated by the script https://github.com/jbarrere3/SalvageModel/tree/withFinland</li> <li><em><strong>climate </strong></em>contains for each tree species the climatic variables (mean annual temperature, minimum annual temperature and annual precipitation) extracted from CHELSA and the disturbance-related climatic indices (Fire Weather Index, Snow Water Equivalent and Gust Wind Speed)</li> <li><em><strong>traits </strong></em>contains the traits calculated directly with NFI data (bark thickness, height to dbh ratio, maximum growth), and a text file with the Species and Trait ID to request to TRY database. </li> </ul> <p>The content of this repository can be used to reproduce the analyses of the paper, with the script stored in in https://github.com/jbarrere3/DisturbancePaper</p> <p><strong>Edit (19/09/2023):</strong> A minor coding error was found in the pre-formatted data of the paper, which did not affect the main results but led to minor change in the value of the posterior estimates. An updated version of the posterior estimates of this dataset was made available at https://zenodo.org/record/8358921. </p>
Data from: Scale-dependent effects of landscape structure on pollinator traits, species interactions and pollination success
<p>Data: Plant-pollinator interactions, pollinator body size (inter-tegular distance, ITD) and plant reproductive success (number of seeds produced).<br><br>Data collected by Christie J. Webber. <br><br>Data collected in 14 experimental flowering plant patches during December 2012–February 2013. Patches were located in a 105 hectare sheep farm pasture in Oxford, North Canterbury, New Zealand (43°19'21"S 172°12'25"E).</p> <p>Files:</p> <ul> <li>Data_S1: contains plant-pollinator interactions sampled and pollinator inter-tegular distance (ITD). Data_S1 columns: patch ID where the interaction was recorded, plant species, pollinator ITD (mm), and pollinator family, genus and species.</li> <li>Data_S2: contains the number of seeds produced by each of the five flowers of each plant individual from each plant species on each patch. Data_S2 columns: patch ID where the measurement was taken, plant species, plant number (individual sampled), number of seeds.</li> </ul> <p>Dataset used in "Scale-dependent effects of landscape structure on pollinator traits, species interactions and pollination success" by G. Peralta, C.J. Webber, G.L.W. Perry, D.B. Stouffer, D.P. Vázquez and J.M. Tylianakis.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.