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310 results for “Tree growth”
Long Term Tree Growth Sites: Hourly Temperature and Hourly Relative Humidity at 150 cm from 1988 to Present
Data logger instrumentation was installed at several of the of the Long Term Tree Growth (LTTG) study sites to monitor air temperature and relative humidity in various forest types.
Air Temperature and Relative Humidity at Long Term Tree Growth Sites; 1989-Present: Hourly
This dataset contains the hourly output for Air Temperature and Relative Humidity sensors located at various Long Term Tree Growth Plots (LTTG).
Soil Temperature measurements at Long Term Tree Growth Sites; 1989-Present: Hourly
This dataset contains the hourly output for Soil Temperature sensors located at various Long Term Tree Growth Plots (LTTG).
Air Temperature and Relative Humidity at Long Term Tree Growth Sites; 2001-Present: Hourly
This dataset contains the hourly output for Air Temperature and Relative Humidity sensors located at various Long Term Tree Growth Plots (LTTG). In addition to expanding the number of sites being monitored, some sites contain Omnidata Easy Loggers in which ES-110 sensors used to measure AT/RH have exceeded their lifespan . This dataset is to expand on and replace those older sensors to ensure a continueing dataset.
Tree growth (1999-2012) for the Functional Diversity project, Coweeta Hydrologic Laboratory, Otto, North Carolina
The importance of the herbaceous layer in regulating ecosystem processes in deciduous forests is generally unknown. We use a manipulative study in a rich, mesophytic cove forest in the southern Appalachians to test the following hypotheses: (i) the herbaceous functional group (HFG) in mesophytic coves accelerates carbon and nutrient cycling, (ii) high litter quality input and rapid nutrient turnover associated with HFG will have a positive effect on overstory tree growth, and (iii) the HFG regulates tree regeneration with negative effects on seedling establishment due to competition for resources. We established treatment plots in a mesic, cove-hardwoods forest and removed the herbaceous flora (HR, removed twice per year) or added herbaceous organic material (OMA, once per year) for comparison to a no removal (NR) reference for a total of 14 years. The OMA treatment stimulated soil N-mineralization and increased litterfall mass and N content. OMA N-mineralization rates were more than two times greater than both the NR and HR treatments; however, we did not detect significant differences in soil CO2 efflux among treatments. Higher overstory litterfall mass and N in the OMA treatment plots indicated that overstory trees were benefiting from the enhanced soil N-mineralization. Higher overstory leaf mass and N suggests an important linkage between HR and aboveground net primary production even though this did not translate into greater tree basal area increment. We found an increase in regeneration of all tree species with HFG removal, and the response was particularly evident for Acer rubrum seedlings.
Eastern Hemlock (Tsuga canadensis) Tree Growth Study
We initiated a study to assess the impacts of the Hemlock Wooly Adelgid on Eastern Hemlock, Tsuga canadensis, communities at Coweeta. The Hemlock Wooly Adelgid, Adelges tsugae, was first found at Coweeta in 2003. We established 12 20 x 20 m plots: 4 were control hardwood stands, 4 were untreated hemlock communities, and 4 were hemlock that were girdled so we could assess the immediate impact that hemlock death would have on nutrient cycling, the herbaceous community, and other ecosystem functions. This data set is based on yearly dendrometer band and DBH readings to assess tree growth and to track the death and in-growth of individual trees. The study has been continued through 2019.
Hubbard Brook Experimental Forest: Soil Freeze Study - Tree Growth
The climate is changing in many temperate forests with the amount of forest area dominated by sugar maple experiencing an insulating snowpack expected to shrink between 49 and 95% compared to 1951-2005 values. A reduced snowpack and increased depth and duration of soil frost can injure or kill fine roots, which are essential for plant water and nutrient uptake. These adverse impacts on tree roots can have important impacts on tree growth and ecosystem carbon sequestration. We evaluated the effects of changing winter climate, including snow and soil frost dynamics, by using tree cores to measure sugar maple radial growth rates in the Soil Freezing Study plots at the Hubbard Brook Experimental Forest. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. Analysis of these data are published in: Reinmann AB, Susser JR, Demara EMC, and Templer PH. 2019. Declines in northern forest tree growth following snowpack decline and soil freezing. Global Change Biology. 25(2):420-430. https://doi.org/10.1111/gcb.14420
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest: Tree Growth Data in support of "Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems", Conrad-Rooney et al. PNAS 2025
Data associated with the publication: Conrad-Rooney E, AB Reinmann, PH Templer. Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems. Proceedings of the National Academy of Sciences, 2025. This dataset includes cumulative stem biomass carbon data (from pre-treatment in 2012 until 2022) and annual stem biomass growth rates (not cumulative) for 2015-2022 for the red maple trees at the Climate Change Across Seasons Experiment. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Variations in tree growth provide limited evidence of species mixture effects in Interior West U.S.A. mixed-conifer forests
<p>1. In mixed stands, species complementarity (e.g., facilitation and competition reduction) may enhance forest tree productivity. Although positive mixture effects have been identified in forests worldwide, the majority of studies have focused on two-species interactions in managed systems with high functional diversity. We extended this line of research to examine mixture effects on tree productivity across landscape-scale compositional and environmental gradients in the low functional diversity, fire-suppressed, mixed-conifer forests of the U.S. Interior West.</p> <p>2. We investigated mixture effects on the productivity of <i>Pinus ponderosa</i>, <i>Pseudotsuga menziesii</i>, and <i>Abies concolor</i>. Using region-wide forest inventory data, we created individual-tree generalized linear mixed models and examined the growth of these species across community gradients. We compared the relative influences of stand structure, age, competition, and environmental stress on mixture effects using multi-model inference. We analyzed growth of neighboring tree species to infer whether a mixture effect in a single species translated to the stand-level.</p> <p>3. We found support for a positive mixture effect in <i>P. menziesii</i>, although our results were equivocal in light of a weaker but still plausible alternative model. Growth of <i>P. menziesii</i> neighboring species in mixed stands declined or held constant depending on aridity, suggesting that a positive mixture effect in <i>P. menziesii</i> does not necessarily extend to the stand level. We found no evidence for mixture effects in <i>P. ponderosa</i>, <i>A. concolor</i> or their neighboring species.</p> <p>4. Complementarity appears to have a limited influence on tree growth in the mixed-conifer systems of the U.S. Interior West, reflecting limited functional diversity. Historical changes in stand structure following fire exclusion, particularly high stand densities, may limit the potential for positive species mixture effects. The limited species pool of Interior West forests increases the risk that, without careful management, what functional diversity exists could be lost to compositional changes resulting from stand dynamics or disturbance.</p>
Robot Self-Assembly as Adaptive Growth Process: Collective Selection of Seed Position and Self-Organizing Tree-Structures
<p>Autonomous self-assembly allows to create structures and scaffolds on demand and automatically. The desired structure may be predetermined or alternatively it is the result of an artificial growth process that adapts to environmental features and to the intermediate structure itself. In a self-organizing and decentralized control approach the robots interact only locally and form the structure collectively. Designing a complete approach that allows the robot group to collectively decide on where to start the self-assembly, that adapts at runtime to environmental conditions, and that guarantees the structural stability is challenging and does not yet exist. We present an approach to self-assembly inspired by diffusion-limited aggregation that generates an adaptive structure reacting to environmental conditions in an artificial growth process. During a preparatory stage the robots collectively decide where to start the self-assembly also depending on environmental conditions. In the actual self-assembly stage, the robots create tree-like structures that grow towards light. We report the results of robot self-assembly experiments with 50 Kilobots. Our results demonstrate how an adaptive growth process can be implemented in robots. We explain how our approach will be extended to a 3-d growth process and how robot self-assembly as an open-ended adaptive growth process opens up a multiplicity of future opportunities.</p>
Similarity data set used to test Synchronous Growth Changes (SGC) on dendrochronological data using tree-ring series from the ITRDB
<p>Dataset used to test the SGC, SSGC and AGC in:</p> <div> <div>Visser, RM. 2021 On the similarity of tree-ring patterns: Assessing the influence of semi-synchronous growth changes on the Gleichläufigkeitskoeffizient for big tree-ring data sets. <em>Archaeometry</em> 63(1): 204–215. DOI: <a href="https://doi.org/10.1111/arcm.12600">https://doi.org/10.1111/arcm.12600</a>.</div> </div> <p>The dataset contains the database used in this study</p> <ul> <li><em>itrdb_structure.sql</em> described the structure of the database (PostgreSQL/PostGIS)</li> <li>Tables <ul> <li><em>GC_??_tbl</em> are tables with ?? denoting the continent (see below) containg the comparisons between tree-ring series and the growth changes <ul> <li>The following columns are present: <ul> <li>ID1 and ID2: These are the ID's of the series compared.</li> <li>SGC: Synchronous Growth Changes</li> <li>SSGC: Semi Synchronous Growth Changes</li> <li>Overlap: the number of tree-rings compared</li> </ul> </li> <li>Data files with values in each table. The continents are as defined in the ITRDB (https://www.ncei.noaa.gov/access/paleo-search/?dataTypeId=18) <ul> <li>GC_af_tbl_202005 (Africa)</li> <li>GC_as_tbl_202005 (Asia)</li> <li>GC_au_tbl_202005 (Australia)</li> <li>GC_ca_tbl_202005 (Canada)</li> <li>GC_eu_tbl_202005 (Europe)</li> <li>GC_mx_tbl_202005 (Mexico)</li> <li>GC_sa_tbl_202005 (South America)</li> <li>GC_us_tbl_202005 (North America)</li> </ul> </li> </ul> </li> <li><em>headers</em>: <ul> <li>The following columns are present: <ul> <li>continent: two letter code of the continent (ITRDB)</li> <li>filename: orginal filename as deposited in the ITRDB</li> <li>line_nr: line number of the header</li> <li>header_text: text of the header related to the line number</li> </ul> </li> <li>Datafile: headers_201905222007.csv</li> </ul> </li> <li><em>names</em>: <ul> <li>The following columns are present: <ul> <li>filename: orginal filename as deposited in the ITRDB</li> <li>name_orig: orginal name of the tree-ring series as deposited in the ITRDB</li> <li>name_new: the IDs of the tree-ring series were replaced with a two‐letter code for the continent (AF, AS, AU, CA, EU, SA, US) and a sequence code to prevent duplicate IDs. These are used as ID1 and ID2 in the tables <em>GC_??_tbl</em></li> </ul> </li> <li>Datafile: names_201905240643.csv</li> </ul> </li> </ul> </li> <li>file: <em>geo_location_201906250635.csv</em> <ul> <li>Contains the locations related to each site in the database</li> <li>The following columns: <ul> <li>filename: orginal filename as deposited in the ITRDB</li> <li>continent: two letter code of the continent (ITRDB)</li> <li>lat: latitude</li> <li>long: longitude</li> <li>geom_point: WGS84 coordinates expressed as well-known text (WKT)</li> </ul> </li> </ul> </li> </ul> <p>For the related code, see also: </p> <p>Ronald Visser. (2022). Code and data related to semi-synchronous growth changes and the similarity of tree-ring patterns (v1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7157738</p> <p>Or: https://github.com/RonaldVisser/SGC</p>
Cross-biome synthesis of source versus sink limits to tree growth
<p>Uncertainties surrounding tree carbon allocation to growth are a major limitation to projections of forest carbon sequestration and response to climate change. The prevalence and extent to which carbon assimilation (source) or cambial activity (sink) mediate wood production are fundamentally important and remain elusive. We quantified source-sink relations across biomes by combining eddy-covariance gross primary production with extensive on-site and regional tree ring observations. We found widespread temporal decoupling between carbon assimilation and tree growth, underpinned by contrasting climatic sensitivities of these two processes. Substantial differences in assimilation-growth decoupling between angiosperms and gymnosperms were determined, as well as stronger decoupling with canopy closure, aridity, and decreasing temperatures. Our results reveal pervasive sink control over tree growth that is likely to be increasingly prominent under global climate change.</p>
Data from journal article "Amplifying effects of recurrent drought on the dynamics of tree growth and water use in a subalpine forest"
<p>This dataset contains all data used in the above mentioned publication (DOI: tba). The data was obtained in a field drought experiment in a subalpine forest in the Austrian Central Alps, where adult trees were exposed to either ambient conditions or recurrent summer drought. The experiment was conducted from 2016-2018. All data were measured on individual tree level. All dataset contains the following, pre-processed data (processed as described in the corresponding journal article):<br> - Micrometeorological data<br> - Dendrometer data<br> - Tree ring data<br> - Sapflow data<br> - Stem electrical resistivity data<br> - Non-structural carbohydrate (NSC) and soluble sugar carbon isotopic composition (d13C) data</p> <p>The metadata.xlsx file contains all metadata, including units and descriptions of the variables.</p>
Data for: Red foxes enhance long-term tree growth near the Arctic treeline
<p>Recent climate warming is expected to increase tree growth and productivity, substantially altering ecological function and boundaries in northern ecosystems. Temperature and precipitation largely determine the range and growth of trees in any biome, yet variations in microsite conditions can also influence tree growth on a finer scale. By altering essential resources and habitat conditions, terrestrial organisms could modify Subarctic tree growth. Red foxes (<em>Vulpes vulpes</em>) are found in most terrestrial ecosystems and are considered ecosystem engineers by enriching soil nutrients and plant composition through denning. Added soil nutrients from prey remains, feces, and urine could benefit tree growth in Subarctic regions by alleviating soil nutrient limitations. We examined growth in white spruce (<em>Picea glauca</em>) trees growing on eight red fox dens and paired control sites near Churchill, Manitoba, Canada, at the Arctic treeline. Radial growth was 55% higher for trees on dens than on control sites between 1897 and 2017, despite similarities in tree ages, densities, and regional climate across all sites. By promoting tree growth near the treeline, red foxes may influence the position of the Arctic treeline. Although the impacts on tree growth largely depend on the spatial distribution of dens and predator activity in the boreal forest, predators can create distinct microhabitats across the landscape via ecosystem engineering processes, leading to increased vegetation productivity, persisting over many decades.</p>
Code and data related to semi-synchronous growth changes and the similarity of tree-ring patterns
<p>This dataset contains the data and code related to Visser, RM. 2021 On the similarity of tree-ring patterns: Assessing the influence of semi-synchronous growth changes on the Gleichläufigkeitskoeffizient for big tree-ring data sets. <em>Archaeometry 63(1)</em>: 204–215. DOI: <a href="https://doi.org/10.1111/arcm.12600">https://doi.org/10.1111/arcm.12600</a>.</p>
Phosphorous fertilization and soil pH affect the growth of deciduous trees in a temperate hardwood forest
<p>To better understand how a forest’s response to P limitation and acidic deposition can change over time, we added P, limestone to raise pH, and a cross-treatment where both P and limestone were added to 3 different northeastern Ohio forest stands over a 12-year period. Internally, we call this experiment APEX, which stands for Acid Precipitation EXperiment. We tracked diameter at breast height (DBH) of the trees annually, conducted foliar nutrient analyses, and collected tree roots to assess treatment impacts on mycorrhizal colonization. We analyzed our dataset in three sections: the first 6 years after manipulation, the latter 6 years, and the entire 12-year period. These sections allowed us to compare differences between early responses to manipulation and later responses. The R code included here shows how these sections of data were analyzed using linear mixed effect models and Tukey post hoc tests (with the R packages lme4 and multcomp, respectively) and graphed (with the package ggplot2). The three R code files include analyses of 1) litter biomass and chemistry (APEX_leaf_litter_R_code.R), 2) ectomycorrhizal (EM) and arbscular mycorrhizal (AM) fungal colonization and root biomass estimates from trees associated with these mycorrhizal types (APEX_mycorrhizal_roots_R_code.R), and 3) relative basal area increment that was calculated for different tree species and mycorrhizal association types using DBH measurements (APEX_RBAI_R_code.R). All input csv files are included here.</p>
Data from: Tree growth-forms reveal dominant browsers shaping the vegetation
<p>This data repository belongs to the publication "Tree growth-forms reveal dominant browsers shaping the vegetation" by Churski et al. in Functional Ecology</p> <p>Authors Marcin Churski<sup>1</sup>, Dries P.J. Kuijper<sup>1</sup>, Katharina Semmelmayer<sup>1</sup>, William J. Bond<sup>2</sup>, Joris P.G.M. Cromsigt<sup>3</sup><sup>,</sup><sup>4</sup>, Yan Wang<sup>5</sup> & Tristan Charles-Dominique<sup>6</sup><sup>,</sup><sup>7</sup></p> <p>Author for correspondence: Marcin Churski email: <a href="mailto:mchurski@ibs.bialowieza.pl">mchurski@ibs.bialowieza.pl</a></p> <p><sup>1</sup>Mammal Research Institute Polish Academy of Sciences, ul. Stoczek 1, 17-230 Białowieża; <sup>2</sup>University of Cape Town, HW Pearson Building, University Ave N, Rondebosch, Cape Town, 7701; <sup>3</sup>SLU, Department of Wildlife, Fish and Environmental Studies, 901 83 Umeå, Sweden; <sup>4</sup>Centre for African Conservation Ecology, Department of Zoology, Nelson Mandela University, PO Box 77000, Gqeberha, 6031, South Africa; <sup>5</sup>Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki, Finland; <sup>6</sup>AMAP, University of Montpellier, CIRAD, CNRS, INRAE, IRD, Montpellier, France; <sup>7</sup>CNRS UMR7618; Sorbonne University; Institute of Ecology and Environmental Sciences Paris; 4, place Jussieu 75005 PARIS</p> <div> <h4>Summary</h4> <a href="https://github.com/mripasteam/transformers#summary"></a></div> <ul> <li>Plants adopt particular growth-forms when they are exposed to extreme environmental conditions. In this study, we describe a unique woody plant growth-form induced by large mammalian herbivores and discuss that this growth-form could have evolved as a strategy for escaping the browser zone in herbivore driven ecosystems.</li> <li>We analysed responses of key architectural and morphological attributes (branching and thorn density, tree dimensions, presence of flowers and fruits) of three Eurasian spiny tree species (Malus sylvestris, Prunus cerasifera, Pyrus pyraster) to different levels of browsing by large herbivores in the temperate Białowieża Forest, Poland.</li> <li>Under high browsing pressure, studied trees displayed two distinct forms of the crown: a bottom sterile part developing into a densely branched structure with high density of thorns (‘cage-form’), and an upper reproductive part that escaped from herbivore control (‘escaped-form’). The size of cage-form influenced the feeding behaviour of red deer (Cervus elaphus) by increasing the time deer spend foraging and increasing the bite rate. The height at which cages started to escape and their diameter matched with foraging reach of red deer.</li> <li>Synthesis. We argue that the frequency and cage dimensions of this woody growth-form in the landscape could inform on the type and intensity of recent herbivory. Moreover, its distinctive inducibility suggests that this growth-form did not emerge recently under anthropogenic pressure but could be the legacy of ancient herbivory effects. Observational evidence suggests that this growth-form emerged in several herbivore-driven systems around the globe and may be used to identify the dominant herbivores that control vegetation structure in these ecosystems.</li> </ul> <p>Data</p> <p>The table 'cage_traits.csv' contains data on morphological traits measured on individual trees and was used to describe the key architectural attributes defining the cage and escape forms (trapped branches vs. escaped branches), test if the cage form is induced by mammalian herbivores or not and if the dimensions of the cage form could inform on which animal induced them.</p> <div> <pre><code>Column headers description: N_Protocol: Tree ID Status: if the tree individual grow taller than animal reach (escaped or trapped) Species: tree species Branch_N: observed branch ID Length: branch length (cm) N_Thorns: number of thorns N_Twigs: number of twigs Longest_thorn: the length of longest thorn on the branch (mm) N_browsed_Twigs: Number of browsed twigs (1) vs non browsed (0) twigs on a branch Branch_esc: branch position, "escape" indicates the branch growing on the escaped part of a tree FlowerOrFruit: flower or fruit number found on the branch BDI: branch density index. It is calculated by twigs number divided by branch length Thorn_density:Thorn number divided by branch length BrowRate: observed number of browsed_Twigs divided by branch length Bite: 1 indicates the branch was browsed, 0 indicated the branch was not browsed. browsing_environment: if the tree is exposed to high browsing environment or not. </code></pre> <div> </div> </div> <p>The table 'foraging_time_barplot.csv' contains camera trap data on total foraging time of all the animal on all the tree species and was used to answer the question how the presence of cage form affect herbivore foraging behaviour. This data set was specifically used to produce the bar plot in Figure 5C.</p> <div> <pre><code>Column headers description: N_Protocol : Tree ID animal_species : observed animal species Species: tree species Foraging_time: observed total foraging time. </code></pre> <div> </div> </div> <p>The table 'foraging_time.csv' contains camera trap data on total foraging time of all the animal on all the tree species and was used to answer the question how the presence of cage form affect herbivore foraging behaviour.</p> <div> <pre><code>Column headers description: N_Protocol: Tree ID Total_foraging_time: total record foraging time per tree individual Total_bite_rate : bite rate per tree individual Bite_rate : bite rate per tree branch BDI: branch density index. Foraging_time_av: record foraging time per tree branch Surface: the surface of the crown </code></pre> <div> </div> </div> <p>The table 'escape_height.csv' contains data on individual tree heights in relation to their status (escaped vs trapped). This data set was used to test if the dimensions of the cage form could inform on which animal induced them.</p> <div> <pre><code>Column headers description: N_Protocol: Tree ID Status: if the tree individual grow taller than animal reach Species: Tree species Height: Tree height</code></pre> </div>
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>
Data for: Hardwoods influence effect of climate and intraspecific competition on growth of woodland longleaf pine trees
<p>Longleaf pine woodlands of the North American Coastal Plain are proposed to be resilient to climate change impacts, but little is known about changes in limiting factors to longleaf pine growth as climate has changed in the late 20<sup>th</sup> and early 21<sup>st</sup> centuries. Moreover, the role that neighborhood trees play in the context of climate change remains largely unexplored. We used static and moving-window tree-ring and climatic analyses to measure the effects of climate on longleaf pine growth at a site in southwest Georgia, USA. We then performed maximum likelihood analysis to examine the influence of neighboring hardwoods on the response of longleaf pine growth to the joint effects of competition and climate. Analysis of climate data from local stations in southwest Georgia over six decades indicated that mean air temperature decreased until the late 20<sup>th </sup>century and then began to rise, and that the variability of spring and summer precipitation has increased. Tree ring and climate analyses indicated longleaf pine radial growth is sensitive to precipitation and air temperature, and that the strength of correlation of longleaf pine growth to summer air temperature and summer precipitation increased since the 1950s. Likelihood models, which were applied over a shorter (23-year) period and explicitly incorporated competition, did not support a link between summer temperature and growth but did indicate summer precipitation increased growth. Furthermore, basal area of neighboring hardwoods was correlated with greater pine growth per millimeter of precipitation. Basal area of neighboring longleaf pine negatively affected the growth of conspecific trees; the presence of hardwoods increased the competitive effect when basal area of neighboring pine trees was low (<10 m<sup>2</sup> ha<sup>-1</sup>) but decreased the competitive effect when basal area of neighboring pine trees was high (≥ 10 m<sup>2</sup> ha<sup>-1</sup>). These results suggest that retention or recruitment of hardwood trees when restoring longleaf pine woodlands may contribute to increased ability to withstand dry summers and may help to allay concerns of managers that retention of hardwoods will unduly affect the growth of residual mature longleaf pines.</p>
The trait-mediated trade-off between growth and survival depends on tree sizes and environmental conditions
<p><span>Interspecific relationships between growth and survival are critical determinants of tree species diversity maintenance in forests. The trade-offs between growth and survival in co-occurring tree species are believed to arise along a continuum of life-history strategies. For example, co-occurring species range from those that grow slowly and survive well in resource-poor environments to those that grow quickly but have low survival rates in resource-rich environments. However, uncertainties remain regarding how growth-survival trade-offs are related to species traits, tree sizes, or environmental conditions.</span></p> <p><span>We examined how the relationships between species traits and growth–survival relationships shift in response to changes in stem sizes and across census periods with different climate conditions (frequency of strong winds, drought intensity) across 45 co-occurring tree species based on 23 years of growth and survival records in a warm temperate rain forest on Yakushima Island, Japan. We developed hierarchical Bayesian models of relative growth and survival rates, including leaf traits, wood density, and 95-percentile maximum stem diameter as explanatory variables. We tested the relationships between estimated trait-mediated growth–survival relationships and the intensities of climate events during five census periods.</span></p> <p><span>Each trait's effects on growth–survival relationships differed across the five census periods in response to climate conditions. Interspecific growth–survival relationships affected by a single trait axis for leaves or wood tended to be negative. In contrast, those affected by the maximum stem diameter tended to be positive. Such trends </span><span>increased with more frequent </span><span>strong winds or more intense droughts. The single-trait effects on growth–survival relationships were stronger for smaller sizes than for larger sizes. For all traits combined, we found a significant growth–survival trade-off only for small-sized stems in three of five census periods.</span></p> <p><span>Synthesis: Our results indicate that the effect of species traits on the growth–survival relationships depended on tree sizes, the census periods, or both in response to the frequency or intensity of climate events. We argue the importance of incorporating spatial and temporal variations in environmental conditions into long-term data from tree census to predict forest dynamics.</span></p>
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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.