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153 results for “growth traits”
Effect of Warming on Thermal Adaptation of Soil Microbial Growth Traits at Harvard Forest 2013-2023
Adaptation of soil microbes due to warming from climate change has been observed, but it remains unknown what microbial growth traits are adaptive to warming. We studied bacterial isolates from the Harvard Forest Long-Term Ecological Research site, where field soils have been experimentally heated to 5ºC above ambient temperature with unheated controls for thirty years. We hypothesized that Alphaproteobacteria from warmed plots have (1) less temperature sensitive growth rates; (2) higher optimum growth temperatures; and (3) higher maximum growth temperatures compared to isolates from control plots. We made high-throughput measurements of bacterial growth in liquid cultures over time and across temperatures from 22-37ºC in 2-3ºC increments. We estimated growth rates by fitting Gompertz models to the growth data. Temperature sensitivity of growth rate, optimum growth temperature, and maximum growth temperature were estimated by the Ratkowsky 1983 model and a modified Macromolecular Rate Theory (MMRT) model. To determine evidence of adaptation, we ran phylogenetic generalized least squares tests on isolates from warmed and control soils. Our results showed evidence of adaptation of higher optimum growth temperature of bacterial isolates from heated soils. However, we observed no evidence of adaptation of temperature sensitivity of growth and maximum growth temperature. Our project begins to capture the shape of the temperature response curves, but illustrates that the relationship between growth and temperature is complex and cannot be limited to a single point in the biokinetic range.
Genotyping-by-sequencing (GBS) dataset for genome wide associations of growth, phenology and plasticity traits in willow (Salix viminalis (L.))
<p>These vcf-files constitute underlying raw data material for the manuscript "Genome wide associations of growth, phenology and plasticity traits in willow (Salix viminalis (L.))". For more detailed information please consult the README file in the repository.</p>
Morpho-anatomical traits explain the effects of bacterial-feeding nematodes on soil bacterial community composition and plant growth and nutrition
<p>Soil Bacterial populations</p> <p>V3-V4, of the 16S rRNA gene using the primers 341F CCTAYGGGRBGCASCAG and 806R GGACTACNNGGGTATCTAAT.</p>
How is tree growth rate linked to root functional traits in phylogenetically related poplar hybrids?
<p>Fine roots play a crucial role in soil nutrient and water acquisition, significantly contributing to tree growth. Fine roots with a high specific root length (SRL) and small diameter are often considered to help trees grow fast. However, inconsistencies in the literature do not provide a clear basis on the effect of root functional traits, such as SRL or root mass density (RMD), on tree growth rate in phylogenetically related trees. Our aim was to examine relationships between tree growth rate and root functional traits, using clones displaying different growth rates in a hybrid poplar plantation located in New Liskeard, ON, Canada. Fine roots (diameter < 2 mm) samples were collected using soil cores at depths of 0–20, 20–40 and 40–60 cm, and analyzed for morphological, chemical and architectural traits. High SRL and thin fine roots were associated with the least productive clones, which is not consistent with the root economics spectrum (RES) theory. However, the most productive clone had larger fine root diameter and higher root lignin concentrations, probably reducing root construction and maintenance costs and C losses. Therefore, at the 0–20 and 20–40 cm depths, tree growth rates showed positive correlations with root diameter and root lignin concentrations, but negative correlations with SRL and root soluble compounds concentration. Increasing RMD at the 0–20 cm depth promoted tree growth rates, showing the importance of soil exploration in the topsoil for tree growth. We conclude that fine root variation does not always follow the RES hypothesis and argue that the rapid growth rate of trees may also be driven by fine root growth in diameter and mass in phylogenetically related trees.</p>
Leaf traits plus growth and dieback data for cloud forest epiphytes in a cloud exclusion treatment at Wayqecha Biological Station, Peru
Morphological traits [specific leaf area, stomatal length and density, leaf thickness, cuticle thickness and hydrenchymal layer thickness] and physiological traits [stomatal conductance, minimum leaf conductance and foliar water uptake capacity] along with pressure volume curves were measured at the Wayqecha Biological Station, Peru. Vascular epiphytes were sampled from a control plot and fog reduction treatment plot constructed from two 30 m tall aluminum towers, 40 m apart with panels of polyethylene mesh strung between the towers. Measurements of leaf morphological traits were taken in June-July 2022 in the control and treatment plots to assess plasticity to fog reductionin the fifth year of the experiment. Samples of branches and leaves for each individual approximately 1-2 meters off the ground were collected in the plot, close enough to the curtain to maximize any effects of fog interception. Growth and dieback data were also collected species of vascular and non-vascular epiphytes attached to wooden transplant boards in the control and treatment plot in 2017. Rates of growth and dieback were recorded for vascular epiphytes from 2017-2019 and for non-vascular epiphytes from 2018-2019. The 2017 data collection took place in November while data for 2018 and 2019 were collected in June.
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest: growth and enzyme activity traits of soil fungi isolated from CCASE in July 2017, grown under a common garden experiment in the laboratory that mimicked CCASE soil temperature treatments
Projections for the northeastern U.S. indicate that mean air temperatures will rise and snowfall will become less frequent, causing more frequent soil freezing. To test fungal responses to these combined chronic and extreme soil temperature changes, we conducted a laboratory-based common garden experiment with soil fungi that had been subjected to different combinations of growing season soil warming, winter soil freeze/thaw cycles, and ambient conditions for four years in the field. We found that fungi originating from field plots experiencing a combination of growing season warming and winter freeze/thaw cycles had inherently lower activity of acid phosphatase, but higher cellulase activity, that could not be reversed in the lab. In addition, fungi quickly adjusted their physiology to freeze/thaw cycles in the laboratory, reducing growth rate and potentially reducing their carbon use efficiency. Our findings suggest that less than four years of new soil temperature conditions in the field can lead to physiological shifts by some soil fungi, as well as irreversible loss or acquisition of extracellular enzyme activity traits by other fungi. These findings could explain field observations of shifting soil carbon and nutrient cycling under simulated climate change. 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.
Data from: Association genetics of growth and adaptive traits in loblolly pine (Pinus taeda L.) using whole-exome-discovered polymorphisms
In the United States, forest genetics research began over 100 years ago and loblolly pine breeding programs were established in the 1950s. However, the genetics underlying complex traits of loblolly pine remains to be discovered. To address this, adaptive and growth traits were measured and analyzed in a clonally tested loblolly pine (Pinus taeda L.) population. Over 2.8 million single nucleotide polymorphism (SNP) markers detected from exome sequencing were used to test for single locus associations, SNP-SNP interactions and correlation of individual heterozygosity with phenotypic traits. A total of 36 SNP-trait associations were found for specific leaf area (5 SNPs), branch angle (2), crown width (3), stem diameter (4), total height (9), carbon isotope discrimination (4), nitrogen concentration (2), and pitch canker resistance traits (7). Eleven SNP-SNP interactions were found to be associated with branch angle (1 SNP-SNP interaction), crown width (2), total height (2), carbon isotope discrimination (2), nitrogen concentration (1), and pitch canker resistance (3). Non-additive effects imposed by dominance and epistasis account for a large fraction of the genetic variance for the quantitative traits. Genes that contain the identified SNPs have a wide spectrum of functions. Individual heterozygosity positively correlated with water use efficiency and nitrogen concentration. In conclusion, multiple effects identified in this study influence the performance of loblolly pines, provide resources for understanding the genetic control of complex traits, and have potential value for assessing with breeding through marker assisted selection and genomic selection.
Leaf growth response to mild drought: natural variation sheds light on trait architecture
<p>Plant growth and crop yield are negatively affected by a reduction in water availability. However, a clear understanding of how growth is regulated under non-lethal drought conditions is lacking. Recent advances in genomics, phenomics and transcriptomics allow in-depth analysis of natural variation. In this study, we conducted a detailed screening of leaf growth responses to mild drought in a worldwide collection of <em>Arabidopsis thaliana</em> accessions. </p> <p>The raw phenotyping can be found in:<br> - cellularData.txt -> mature (23 days after stratification; DAS) leaf epidermis (third leaf) analysed for cell area, cell number, pavement cell area, pavement cell number, stomatal index and leaf area of the analysed leaf.</p> <p>- leaf3AreaMaturity.txt -> area of the third leaf at maturity (23DAs) in mm<sup>2.</sup></p> <p>- leaf3AreaProliferation.txt -> area of the third leaf at proliferation (last day of full cell proliferation; 8-10 DAS) in mm<sup>2</sup>.</p> <p>- rosetteArea Maturity.txt -> projected rosette area at maturity (22DAS)</p> <p>The phenotyping results have been normalised for batch effects ('experiment' in raw data)</p> <p>- allPhenotypesNormalised.txt -> contains the normalised data for all the measured phenotypes</p> <p>All datafiles indicate the accession name ('Accession'), the unique identifier for each accessions ('Ecotype_ID') as used in the 1001genomes project (www.1001genomes.org) and the treatment ('C' indicate well-watered plants, 'S' the mild-drought treated plants).</p> <p>These results and methodological results are described in Clauw et al. (2016, The Plant Cell).</p> <p>Citation:</p> <p><strong>Clauw, Pieter, Frederik Coppens, Arthur Korte, Dorota Herman, Bram Slabbinck, Stijn Dhondt, Twiggy Van Daele, et al. 2016. “Leaf Growth Response to Mild Drought: Natural Variation in Arabidopsis Sheds Light on Trait Architecture.” The Plant Cell, October. doi:10.1105/tpc.16.00483.</strong></p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Growth traits of a tropical timber species at Southeast Asia, Shorea macrophylla, and scripts for genome wide association study and genomic prediction
<p><em><span>Shorea macrophylla</span></em><span> is a commercially important tropical tree species grown for timber and oil. It is amenable to plantation forestry due to its fast initial growth. Genomic selection (GS) has been used in tree breeding studies to shorten long breeding cycles but has not previously been applied to <em>S. macrophylla</em>. To build genomic prediction models for GS, leaves and growth trait data were collected from a half-sib progeny population of <em>S. macrophylla</em> in Sari Bumi Kusuma forest concession, central Kalimantan, Indonesia. 18037 SNP markers were identified in two ddRAD-seq libraries. Genomic prediction models based on these SNPs were then generated for breast height and total height in the 7th year from planting (D7 and H7). These traits were chosen because of their relatively high narrow-sense genomic heritability and because seven years was considered long enough to assess initial growth. Genomic prediction models were built using 12 methods with the full set of identified SNPs and subsets of 48, 96, and 192 SNPs selected based on the results of a genome-wide association study (GWAS). The GBLUP and RKHS methods gave the highest predictive ability (PA) for D7 and H7 and showed that D7 has an additive genetic architecture while H7 has an epistatic genetic architecture. LightGBM and CNN1D also achieved high PA for D7 with 48 and 96 selected SNPs, and for H7 with 96 and 192 selected SNPs, showing that gradient boosting decision trees and deep learning can be useful in genomic prediction. For almost all methods and both traits, PA was higher when SNPs were selected based on their GWAS P-values than when using the full set of SNPs. These results suggest that GS with GWAS-based SNP selection could be used in <em>S. macrophylla </em>breeding to improve initial growth and reduce genotyping costs for next generation seedlings.</span></p>
Fig. 7. Vertebral character trait evolution across phocoenids and related delphinoids. A. Character 2, thoracic vertebral counts. B. Character 8 in New fossil remains from the Pliocene Koetoi Formation of northern Japan provide insights into growth rates and the vertebral evolution of porpoises
Fig. 7. Vertebral character trait evolution across phocoenids and related delphinoids. A. Character 2, thoracic vertebral counts. B. Character 8, ratio of centrum length/centrum height of lumbar vertebrae. C. Character 12, height of neural spine. D. Character 14, regional anterior inclination of neural arches. See Table 2 for detailed character descriptions.
Figure 7 in Application Of Lichen Functional Traits In Identification Of Temperate Old-Growth Broad-Leaved Forests
Figure 7. Lichen thallus color in old (oldgrowth), middle (middleaged) and young broadleaved forest stands.
Figure 6 in Application Of Lichen Functional Traits In Identification Of Temperate Old-Growth Broad-Leaved Forests
Figure 6. Lichen growth forms in old (oldgrowth), middle (middleaged) and young broadleaved forest stands.
Figure 9 in Application Of Lichen Functional Traits In Identification Of Temperate Old-Growth Broad-Leaved Forests
Figure 9. Lichen photobiont type in old (oldgrowth), middle (middleaged) and young broadleaved forest stands.
Figure 8 in Application Of Lichen Functional Traits In Identification Of Temperate Old-Growth Broad-Leaved Forests
Figure 8. Lichen reproduction type in old (oldgrowth), middle (middleaged) and young broadleaved forest stands.
Figure 2 in Application Of Lichen Functional Traits In Identification Of Temperate Old-Growth Broad-Leaved Forests
Figure 2. Sample plot. Abbreviations: S – South, N – North. Arrow shows the direction of the sampling in transect. Tree number shows the order of surveyed trees.
Figure 5 in Application Of Lichen Functional Traits In Identification Of Temperate Old-Growth Broad-Leaved Forests
Figure 5. Number of lichen taxa with category of conservation concern in old (oldgrowth), middle (middleaged) and young broadleaved forest stands.
Sugarcane Culturable microbiome prospection for plant growth promotion traits in Cynodon dactylon
<p>Data set of running experiments for the prospection of traits for plant growth promotion of bacterial communities from sugarcane tissues: rhizospheric soil, roots, stalks, and leaves. For this experiment, we are using a model plant: Cynodon dactylon known as Bermuda grass.</p>
Community-weighted mean traits in old-growth and selectively logged forest
<p><strong>Description: </strong></p> <p>Community-weighted mean traits from tree species that make up more than 80% basal area in plots 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><strong>Project: </strong>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/55"><strong>Biodiversity and land-use impacts on tropical ecosystem function (BALI): Quantifying functional trait distributions across the disturbance gradient</strong></a></p> <p><strong>Funding: </strong>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><strong>Permits: </strong>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><strong>XML metadata: </strong>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3247602">here</a></p> <p><strong>Files: </strong>This dataset consists of 3 files: Both_CWM_traits.xlsx, CSP_protocol_Chlorophyll_and_Carotenoids.pdf, CSP_protocol_Phenols_Tannins_Analysis.pdf</p> <p><strong>Both_CWM_traits.xlsx</strong></p> <p>This file contains dataset metadata and 1 data tables:</p> <ol> <li> <p><strong>CMW_traits</strong> (described in worksheet CMW_traits)</p> <p>Description: Community-weighted mean traits of tree in plots in SAFE , Danum Valley and Maliau Basin sampled during the BALI project traits campaign</p> <p>Number of fields: 36</p> <p>Number of data rows: 8</p> <p>Fields:</p> <ul> <li><strong>location</strong>: Location (Field type: Categorical)</li> <li><strong>forest_type</strong>: Forest type (Field type: Categorical)</li> <li><strong>forestplots_name</strong>: Plot name coherent with forestplots database (Field type: ID)</li> <li><strong>plot_name_trait_campaign</strong>: Plot name used during the BALI trait campaign (Field type: ID)</li> <li><strong>CWM_total_K_mg.g_log</strong>: CWM foliar potassium concentration in mg per g dry weight, log transformed data (Field type: Numeric)</li> <li><strong>CWM_total_Ca_mg.g_log</strong>: CWM foliar calcium concentration in mg per g dry weight, log transformed data (Field type: Numeric)</li> <li><strong>CWM_total_Mg_mg.g_log</strong>: CWM foliar magnesium concentration in mg per g dry weight, log transformed data (Field type: Numeric)</li> <li><strong>CWM_total_P_mg.g_log</strong>: CWM foliar phosporus concentration in mg per g dry weight, log transformed data (Field type: Numeric)</li> <li><strong>CWM_N_perc</strong>: CWM foliar nitrogen concentration (Field type: Numeric)</li> <li><strong>CWM_15N_per_mil</strong>: CWM foliar 15N isotope concentration (Field type: Numeric)</li> <li><strong>CWM_C_perc</strong>: CWM foliar carbon concentration (Field type: Numeric)</li> <li><strong>CWM_13C_per_mil</strong>: CWM foliar 13C isotope concentration, expressed relative to Vienna Pee Dee Belemnite (VPDB) as δ13C in units of per mil [‰] (Field type: Numeric)</li> <li><strong>CWM_DR</strong>: CWM dark respiration measured on leaf attached to a branch that is cut under water and remains in water (Field type: Numeric)</li> <li><strong>CWM_Asat</strong>: CWM light-saturated net photosynthesis measured on leaf attached to a branch that is cut under water and remains in water. (Field type: Numeric)</li> <li><strong>CWM_Amax</strong>: CWM maximum photosynthetic capacity measured on leaf attached to a branch that is cut under water and remains in water. (Field type: Numeric)</li> <li><strong>CWM_leaf_thickness_mm_log</strong>: CWM thickness of leaf, log transformed data (Field type: Numeric)</li> <li><strong>CWM_dry_weight_mg_log</strong>: CWM leaf oven-dried weight, log transformed data (Field type: Numeric)</li> <li><strong>CWM_LA_mm2_log</strong>: CWM leaf area (LA) calculated from fresh leaves collected from branches, scanned immediately, log transformed data (Field type: Numeric)</li> <li><strong>CWM_SLA_mm2_mg</strong>: CWM specific leaf area (SLA) determined as the one-sided area of a fresh leaf, divided by its oven-dry mass. (Field type: Numeric)</li> <li><strong>CWM_LDMC_mg.g</strong>: CWM 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)</li> <li><strong>CWM_chla_mg.g</strong>: CWM foliar chlorophyll a content (Field type: Numeric)</li> <li><strong>CWM_chlb_mg.g</strong>: CWM foliar chlorophyll b content (Field type: Numeric)</li> <li><strong>CWM_carot_mg.g</strong>: CWM foliar carotenoids content (Field type: Numeric)</li> <li><strong>CWM_Fp_N_mm_log</strong>: CWM force to punch leaf, dividing the observed force (N) required to puncture the leaf lamina by the circumference of the instrument's rod, log transformed data (Field type: Numeric)</li> <li><strong>CWM_specific_Fp_log</strong>: CWM specific force to punch (Fp divided by lamina thickness), log transformed data (Field type: Numeric)</li> <li><strong>CWM_WD_B</strong>: CWM branch wood density from branch segment with bark (Field type: Numeric)</li> <li><strong>CWM_hemicellulose_perc</strong>: CWM foliar hemicellulose concentration (Field type: Numeric)</li> <li><strong>CWM_cellulose_perc</strong>: CWM foliar cellulose concentration (Field type: Numeric)</li> <li><strong>CWM_lignin_recalcitrants_perc</strong>: CWM foliar lignin and recalcitrants concentration (Field type: Numeric)</li> <li><strong>CWM_total_tannin_mg.g</strong>: CWM foliar tannin concentration (Field type: Numeric)</li> <li><strong>CWM_total_phenol_mg.g</strong>: CWM total foliar phenol concentration (Field type: Numeric)</li> <li><strong>CWM_chla_mg.mm2</strong>: CWM foliar chlorophyll a content expressed on leaf area basis (Field type: Numeric)</li> <li><strong>CWM_chlb_mg.mm2</strong>: CWM foliar chlorophyll b content expressed on leaf area basis (Field type: Numeric)</li> <li><strong>CWM_carot_mg.mm2</strong>: CWM foliar carotenoids content expressed on leaf area basis (Field type: Numeric)</li> <li><strong>CWM_N_mg.mm2</strong>: CWM foliar nitrogen concentration expressed on leaf area basis (Field type: Numeric)</li> <li><strong>CWM_total_P_mg.mm2.l</strong>: CWM foliar phosporus concentration expressed on leaf area basis, log transformed data (Field type: Numeric)</li> </ul> </li> </ol> <p><strong>CSP_protocol_Chlorophyll_and_Carotenoids.pdf</strong></p> <p>Description: Methodology of chlorophyll and carotenoids analysis, Carnegie Spectranomics protocol: https://drive.google.com/file/d/0B58dyv8L3FpMdGw0QWtiZElHQzQ/view</p> <p><strong>CSP_protocol_Phenols_Tannins_Analysis.pdf</strong></p> <p>Description: Methodology of phenols and tannins analysis, Carnegie Spectranomics protocol: https://drive.google.com/file/d/0B58dyv8L3FpMcTBHblQwRHdyRE0/view</p> <p><strong>Date range: </strong>2014-05-01 to 2018-09-01</p> <p><strong>Latitudinal extent: </strong>4.5000 to 5.0700</p> <p><strong>Longitudinal extent: </strong>116.7500 to 117.8200</p>
Functional traits of tree species in old-growth and selectively logged forest
<b>Description: </b><p>Traits matrix for tree species in selectively logged forest at SAFE and in old-growth forest in Danum Valley and Maliau Basin. Sampled during the BALI project traits campaign</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/55"><b>Biodiversity and land-use impacts on tropical ecosystem function (BALI): Quantifying functional trait distributions across the disturbance gradient</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC (Standard grant, NE/K016253/1)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (Research licence JKM/MBS.1000-2.2(385))</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3247631">here</a></p><p><b>Files: </b>This dataset consists of 3 files: Both_tree_functional_traits.xlsx, CSP_protocol_Chlorophyll_and_Carotenoids.pdf, CSP_protocol_Phenols_Tannins_Analysis.pdf</p><p><b>Both_tree_functional_traits.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Tree_functional_traits</b> (described in worksheet Tree_functional_traits)</p><p>Description: Traits matrix for tree species at SAFE and in Danum Valley, Maliau Basin sampled during the BALI project traits campaign</p><p>Number of fields: 84</p><p>Number of data rows: 717</p><p>Fields: </p><ul><li><b>location</b>: Location (Field type: Categorical)</li><li><b>forest_type</b>: Forest type: OG: old-growth plots, Maliau and Danum; SL: selectively logged plots at SAFE (Field type: Categorical)</li><li><b>forestplots_name</b>: Plot name coherent with forestplots database (Field type: ID)</li><li><b>plot_name_trait_campaign</b>: Plot name used during the BALI trait campaign (Field type: ID)</li><li><b>sample_code</b>: Sample code referencing: plot-'T'(ree) ID-branch type (Field type: ID)</li><li><b>branch_type</b>: Binary classification of branch sampled depending on their position in the tree crown. BS: sun branch; BSH: shade branch (Field type: ID)</li><li><b>sampling_date</b>: Date of sampling (Field type: Date)</li><li><b>tree_id</b>: Reference for tree tag label (Field type: ID)</li><li><b>species</b>: Tree species (Field type: Taxa)</li><li><b>height.m</b>: Height of tree individual (Field type: Numeric trait)</li><li><b>total_K_mg.g</b>: Foliar potassium content in mg per g dry weight (Field type: Numeric trait)</li><li><b>total_Ca_mg.g</b>: Foliar calcium content in mg per g dry weight (Field type: Numeric trait)</li><li><b>total_Mg_mg.g</b>: Foliar magnesium content in mg per g dry weight (Field type: Numeric trait)</li><li><b>total_P_mg.g</b>: Foliar phosporus content in mg per g dry weight (Field type: Numeric trait)</li><li><b>N_perc</b>: Foliar nitrogen concentration (Field type: Numeric trait)</li><li><b>15N_per_mil</b>: Foliar 15N isotope concentration (Field type: Numeric trait)</li><li><b>C_perc</b>: Foliar carbon concentration (Field type: Numeric trait)</li><li><b>13C_per_mil</b>: Foliar 13C isotope concentration, expressed relative to Vienna Pee Dee Belemnite (VPDB) as δ13C in units of per mil [‰] (Field type: Numeric trait)</li><li><b>CN</b>: Foliar carbon nitrogen ratio (Field type: Numeric trait)</li><li><b>DR_mean</b>: Mean dark respiration measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric trait)</li><li><b>DR_sd</b>: Standard deviation of dark respiration measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric)</li><li><b>DR_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>Asat_cons_mean</b>: Mean light-saturated net photosynthesis measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch. Data cleaning very conservative: subset of values only with conductance higher 0.04, Ci between 150 - 300, and PS higher than 1, leading to fewer data points. (Field type: Numeric trait)</li><li><b>Asat_cons_sd</b>: Standard deviation of light-saturated net photosynthesis measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric)</li><li><b>Asat_cons_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>Amax_cons_mean</b>: Mean maximum photosynthetic capacity measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch. Data cleaning very conservative: subset of values only with conductance higher 0.04, Ci between 150 - 300, and PS higher than 1, leading to fewer data points. (Field type: Numeric trait)</li><li><b>Amax_cons_sd</b>: Standard deviation of maximum photosynthetic capacity measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric)</li><li><b>Amax_cons_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>Asat_mean</b>: Mean light-saturated net photosynthesis measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric trait)</li><li><b>Asat_sd</b>: Standard deviation of light-saturated net photosynthesis measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric)</li><li><b>Asat_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>Amax_mean</b>: Mean maximum photosynthetic capacity measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric trait)</li><li><b>Amax_sd</b>: Standard deviation of maximum photosynthetic capacity measured on leaf of a branch that is cut under water and remains in water, calculated from replicated leaves per branch (Field type: Numeric)</li><li><b>Amax_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>LA_cm2_mean</b>: Mean leaf area (LA) calculated from fresh leaves collected from branches, scanned immediately. (Field type: Numeric trait)</li><li><b>LA_cm2_sd</b>: Standard deviation of leaf area (Field type: Numeric)</li><li><b>LA_cm2_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>leaf_thickness_mm_mean</b>: Mean thickness of leaf (Field type: Numeric trait)</li><li><b>fresh_weight_g_mean</b>: Mean leaf fresh weight (Field type: Numeric trait)</li><li><b>dry_weight_g_mean</b>: Mean leaf oven-dried weight (Field type: Numeric trait)</li><li><b>dry_weight_mg_mean</b>: Mean leaf oven-dried weight (Field type: Numeric trait)</li><li><b>LDMC_mg.g_mean</b>: Leaf dry-matter content (LDMC) is the oven-dry mass (mg) of a leaf, divided by its water-saturated fresh mass (g) mg g–1 (Field type: Numeric trait)</li><li><b>leaf_thickness_mm_sd</b>: Standard deviation of leaf thickness (Field type: Numeric)</li><li><b>fresh_weight_g_sd</b>: Standard deviation of fresh leaf weight (Field type: Numeric)</li><li><b>dry_weight_g_sd</b>: Standard deviation of dry leaf weight (Field type: Numeric)</li><li><b>dry_weight_mg_sd</b>: Standard deviation of dry leaf weight (Field type: Numeric)</li><li><b>LDMC_mg.g_sd</b>: Standard deviation of leaf dry matter content (Field type: Numeric)</li><li><b>leaf_thickness_mm_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>fresh_weight_g_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>dry_weight_g_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>dry_weight_mg_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>LDMC_mg.g_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Replicate)</li><li><b>branch_height_m</b>: Height from where branch sample was taken (Field type: Numeric trait)</li><li><b>chla_mg.g</b>: Foliar chlorophyll a content (Field type: Numeric trait)</li><li><b>chlb_mg.g</b>: Foliar chlorophyll b content (Field type: Numeric trait)</li><li><b>carot_mg.g</b>: Foliar carotenoids content (Field type: Numeric trait)</li><li><b>Fp_N_mm_mean</b>: Mean force to punch leaf, dividing the observed force (N) required to puncture the leaf lamina by the circumference of the instrument's rod (Field type: Numeric trait)</li><li><b>Fp_N_mm_sd</b>: Standard deviation for force to punch (Field type: Numeric trait)</li><li><b>Fp_N_mm_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Numeric trait)</li><li><b>specific_Fp_mean</b>: Mean specific force to punch (Fp divided by lamina thickness) (Field type: Numeric trait)</li><li><b>specific_Fp_sd</b>: Standard deviation for force to punch (Field type: Numeric trait)</li><li><b>specific_Fp_n</b>: Number of replicates, i.e. leaves per branch used for mean trait (Field type: Numeric trait)</li><li><b>WD_B</b>: Branch wood density from branch segment with bark (Field type: Numeric trait)</li><li><b>WD_NB</b>: Branch wood density from branch segment without bark (bark removed prior measurement) (Field type: Numeric trait)</li><li><b>hemicellulose_perc</b>: Foliar hemicellulose concentration (Field type: Numeric trait)</li><li><b>cellulose_perc</b>: Foliar cellulose concentration (Field type: Numeric trait)</li><li><b>lignin_recalcitrants_perc</b>: Foliar lignin and recalcitrants concentration (Field type: Numeric trait)</li><li><b>Total_tannin_mg.g</b>: Total foliar tannin concentration (Field type: Numeric trait)</li><li><b>Total_phenol_mg.g</b>: Total foliar phenol concentration (Field type: Numeric trait)</li><li><b>SLA_mm2.mg_mean</b>: Specific leaf area (SLA) determined as the one-sided area of a fresh leaf, divided by its oven-dry mass. (Field type: Numeric trait)</li><li><b>total_K_mg.mm2</b>: Foliar potassium content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>total_Ca_mg.mm2</b>: Foliar calcium content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>total_Mg_mg.mm2</b>: Foliar magnesium content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>total_P_mg.mm2</b>: Foliar phosporus content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>chla_mg.mm2</b>: Foliar chlorophyll a content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>chlb_mg.mm2</b>: Foliar chlorophyll b content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>carot_mg.mm2</b>: Foliar carotenoids content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>tannin_mg.mm2</b>: Foliar tannin content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>phenol_mg_mm2</b>: Foliar phenol content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>N_mg.mm2</b>: Foliar nitrogen content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>C_mg.mm2</b>: Foliar carbon content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>hemicellulose_mg.mm2</b>: Foliar hemicellulose content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>cellulose_mg.mm2</b>: Foliar cellulose content expressed on leaf area basis (Field type: Numeric trait)</li><li><b>lignin_recalcitrants_mg.mm2</b>: Foliar lignin and recalcitrants content expressed on leaf area basis (Field type: Numeric trait)</li></ul></li></ol><p><b>CSP_protocol_Chlorophyll_and_Carotenoids.pdf</b></p><p>Description: Methodology of chlorophyll and carotenoids analysis, Carnegie Spectranomics protocol: https://drive.google.com/file/d/0B58dyv8L3FpMdGw0QWtiZElHQzQ/view</p><p><b>CSP_protocol_Phenols_Tannins_Analysis.pdf</b></p><p>Description: Methodology of phenols and tannins analysis, Carnegie Spectranomics protocol: https://drive.google.com/file/d/0B58dyv8L3FpMcTBHblQwRHdyRE0/view</p><p><b>Date range: </b>2014-05-01 to 2018-09-01</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div>Plantae<br> - Tracheophyta<br> -  - Liliopsida<br> -  -  - Poales<br> -  -  -  - Poaceae<br> -  -  -  -  - <i>Dinochloa</i><br> -  -  -  -  -  - <i>Dinochloa trichogona</i><br> -  -  -  -  - <i>Imperata</i><br> -  -  -  -  -  - <i>Imperata cylindrica</i><br> -  -  -  -  - <i>Paspalum</i><br> -  -  -  -  -  - <i>Paspalum virgatum</i><br> -  -  - Zingiberales<br> -  -  -  - Marantaceae<br> -  -  -  -  - <i>Phrynium</i><br> -  -  -  -  -  - <i>Phrynium pubinerve</i><br> -  -  -  - Zingiberaceae<br> -  -  -  -  - <i>Etlingera</i><br> -  - Magnoliopsida<br> -  -  - Asterales<br> -  -  -  - Asteraceae<br> -  -  -  -  - <i>Mikania</i><br> -  -  -  -  -  - <i>Mikania micrantha</i><br> -  -  - Celastrales<br> -  -  -  - Celastraceae<br> -  -  -  -  - <i>Lophopetalum</i><br> -  -  -  -  -  - <i>Lophopetalum beccarianum</i><br> -  -  -  -  -  - <i>Lophopetalum glabrum</i><br> -  -  -  -  -  - <i>Lophopetalum javanicum</i><br> -  -  - Cornales<br> -  -  -  - Cornaceae<br> -  -  -  -  - <i>Alangium</i><br> -  -  -  -  -  - <i>Alangium javanicum</i><br> -  -  -  - Nyssaceae<br> -  -  -  -  - <i>Mastixia</i><br> -  -  -  -  -  - <i>Mastixia trichotoma</i><br> -  -  - Ericales<br> -  -  -  - Ebenaceae<br> -  -  -  -  - <i>Diospyros</i><br> -  -  -  -  -  - <i>Diospyros andamanica</i><br> -  -  -  -  -  - <i>Diospyros curranii</i><br> -  -  -  -  -  - <i>Diospyros daemona</i><br> -  -  -  -  -  - <i>Diospyros dictyoneura</i><br> -  -  -  -  -  - <i>Diospyros macrophylla</i><br> -  -  -  -  -  - <i>Diospyros muricata</i><br> -  -  -  -  -  - <i>Diospyros pilosanthera</i><br> -  -  -  -  -  - <i>Diospyros toposia</i><br> -  -  -  -  -  - <i>Diospyros tuberculata</i><br> -  -  -  - Lecythidaceae<br> -  -  -  -  - <i>Barringtonia</i><br> -  -  -  -  -  - <i>Barringtonia lanceolata</i><br> -  -  -  -  -  - <i>Barringtonia macrostachya</i><br> -  -  -  -  -  - <i>Barringtonia sarcostachys</i><br> -  -  -  -  - <i>Planchonia</i><br> -  -  -  -  -  - <i>Planchonia brevistipitata</i><br> -  -  -  - Pentaphylacaceae<br> -  -  -  -  - <i>Adinandra</i><br> -  -  -  -  -  - <i>Adinandra dumosa</i><br> -  -  -  - Primulaceae<br> -  -  -  -  - <i>Ardisia</i><br> -  -  -  -  -  - <i>Ardisia macrophylla</i><br> -  -  -  -  - <i>Maesa</i><br> -  -  -  -  -  - <i>Maesa macrothyrsa</i><br> -  -  -  - Sapotaceae<br> -  -  -  -  - <i>Madhuca</i><br> -  -  -  -  -  - <i>Madhuca dubardii</i><br> -  -  -  -  -  - <i>Madhuca korthalsii</i><br> -  -  -  -  - <i>Palaquium</i><br> -  -  -  -  -  - <i>Palaquium dasyphyllum</i><br> -  -  -  -  -  - <i>Palaquium obovatum</i><br> -  -  -  -  -  - <i>Palaquium sericeum</i><br> -  -  -  -  - <i>Payena</i><br> -  -  -  -  -  - <i>Payena acuminata</i><br> -  -  -  - Symplocaceae<br> -  -  -  -  - <i>Symplocos</i><br> -  -  -  -  -  - <i>Symplocos fasciculata</i><br> -  -  -  - Theaceae<br> -  -  -  -  - <i>Pyrenaria</i><br> -  -  -  -  -  - <i>Pyrenaria tawauensis</i><br> -  -  - Fabales<br> -  -  -  - Fabaceae<br> -  -  -  -  - <i>Archidendron</i><br> -  -  -  -  -  - <i>Archidendron clypearia</i><br> -  -  -  -  - <i>Crudia</i><br> -  -  -  -  -  - <i>Crudia reticulata</i><br> -  -  -  -  -  - <i>Crudia tenuipes</i><br> -  -  -  -  - <i>Cynometra</i><br> -  -  -  -  -  - <i>Cynometra mirabilis</i><br> -  -  -  -  - <i>Dialium</i><br> -  -  -  -  -  - <i>Dialium indum</i><br> -  -  -  -  -  - <i>Dialium kunstleri</i><br> -  -  -  -  - <i>Fordia</i><br> -  -  -  -  -  - <i>Fordia brachybotrys</i><br> -  -  -  -  -  - <i>Fordia splendidissima</i><br> -  -  -  -  - <i>Sindora</i><br> -  -  -  -  - <i>Spatholobus</i><br> -  -  -  -  -  - <i>Spatholobus macropterus</i><br> -  -  -  - Polygalaceae<br> -  -  -  -  - <i>Xanthophyllum</i><br> -  -  -  -  -  - <i>Xanthophyllum flavescens</i><br> -  -  - Fagales<br> -  -  -  - Fagaceae<br> -  -  -  -  - <i>Castanopsis</i><br> -  -  -  -  -  - <i>Castanopsis hypophoenicea</i><br> -  -  -  -  - <i>Lithocarpus</i><br> -  -  -  -  -  - <i>Lithocarpus blumeanus</i><br> -  -  -  -  -  - <i>Lithocarpus conocarpus</i><br> -  -  -  -  -  - <i>Lithocarpus echinifer</i><br> -  -  -  -  -  - <i>Lithocarpus gracilis</i><br> -  -  -  -  -  - <i>Lithocarpus leptogyne</i><br> -  -  -  -  -  - <i>Lithocarpus sundaicus</i><br> -  -  -  -  - <i>Quercus</i><br> -  -  -  -  -  - <i>Quercus argentata</i><br> -  -  -  -  -  - <i>Quercus lowii</i><br> -  -  -  -  -  - <i>Quercus merrillii</i><br> -  -  -  -  - <i>Trigonobalanus</i><br> -  -  -  -  -  - <i>Trigonobalanus verticillata</i><br> -  -  - Gentianales<br> -  -  -  - Apocynaceae<br> -  -  -  -  - <i>Alstonia</i><br> -  -  -  -  -  - <i>Alstonia angustiloba</i><br> -  -  -  - Rubiaceae<br> -  -  -  -  - <i>Ludekia</i><br> -  -  -  -  -  - <i>Ludekia borneensis</i><br> -  -  -  -  - <i>Nauclea</i><br> -  -  -  -  -  - <i>Nauclea officinalis</i><br> -  -  -  -  -  - <i>Nauclea subdita</i><br> -  -  -  -  - <i>Neolamarckia</i><br> -  -  -  -  -  - <i>Neolamarckia cadamba</i><br> -  -  -  -  - <i>Neonauclea</i><br> -  -  -  -  -  - <i>Neonauclea gigantea</i><br> -  -  -  -  - <i>Psydrax</i><br> -  -  -  -  -  - <i>Psydrax dicoccos</i><br> -  -  -  -  - <i>Uncaria</i><br> -  -  -  -  -  - <i>Uncaria cordata</i><br> -  -  -  -  - <i>Urophyllum</i><br> -  -  -  -  -  - <i>Urophyllum polyneurum</i><br> -  -  - Lamiales<br> -  -  -  - Lamiaceae<br> -  -  -  -  - <i>Callicarpa</i><br> -  -  -  -  -  - <i>Callicarpa pentandra</i><br> -  -  -  - Oleaceae<br> -  -  -  -  - <i>Chionanthus</i><br> -  -  -  -  -  - <i>Chionanthus macrocarpus</i><br> -  -  -  -  -  - <i>Chionanthus pluriflorus</i><br> -  -  - Laurales<br> -  -  -  - Lauraceae<br> -  -  -  -  - <i>Actinodaphne</i><br> -  -  -  -  - <i>Beilschmiedia</i><br> -  -  -  -  -  - <i>Beilschmiedia micrantha</i><br> -  -  -  -  - <i>Caryodaphnopsis</i><br> -  -  -  -  -  - <i>Caryodaphnopsis tonkinensis</i><br> -  -  -  -  - <i>Cryptocarya</i><br> -  -  -  -  -  - <i>Cryptocarya nigra</i><br> -  -  -  -  -  - <i>Cryptocarya nitens</i><br> -  -  -  -  - <i>Dehaasia</i><br> -  -  -  -  -  - <i>Dehaasia caesia</i><br> -  -  -  -  -  - <i>Dehaasia incrassata</i><br> -  -  -  -  - <i>Eusideroxylon</i><br> -  -  -  -  -  - <i>Eusideroxylon zwageri</i><br> -  -  -  -  - <i>Lindera</i><br> -  -  -  -  -  - <i>Lindera lucida</i><br> -  -  -  -  - <i>Litsea</i><br> -  -  -  -  -  - <i>Litsea accedens</i><br> -  -  -  -  -  - <i>Litsea angulata</i><br> -  -  -  -  -  - <i>Litsea caulocarpa</i><br> -  -  -  -  -  - <i>Litsea cordata</i><br> -  -  -  -  -  - <i>Litsea garciae</i><br> -  -  -  -  -  - <i>Litsea grandis</i><br> -  -  -  -  -  - <i>Litsea rubiginosa</i><br> -  -  -  -  - <i>Nothaphoebe</i><br> -  -  -  -  -  - <i>Nothaphoebe umbelliflora</i><br> -  -  -  -  - <i>Phoebe</i><br> -  -  -  -  -  - <i>Phoebe grandis</i><br> -  -  - Magnoliales<br> -  -  -  - Annonaceae<br> -  -  -  -  - <i>Cyathocalyx</i><br> -  -  -  -  - <i>Maasia</i><br> -  -  -  -  -  - <i>Maasia sumatrana</i><br> -  -  -  -  - <i>Miliusa</i><br> -  -  -  -  -  - <i>Miliusa macropoda</i><br> -  -  -  -  - <i>Monoon</i><br> -  -  -  -  - <i>Neo-uvaria</i><br> -  -  -  -  -  - <i>Neo-uvaria acuminatissima</i><br> -  -  -  -  - <i>Orophea</i><br> -  -  -  -  -  - <i>Orophea myriantha</i><br> -  -  -  -  - <i>Phaeanthus</i><br> -  -  -  -  -  - <i>Phaeanthus splendens</i><br> -  -  -  -  - <i>Polyalthia</i><br> -  -  -  -  -  - <i>Polyalthia obliqua</i><br> -  -  -  -  - <i>Pseuduvaria</i><br> -  -  -  -  -  - <i>Pseuduvaria borneensis</i><br> -  -  -  -  - <i>Sageraea</i><br> -  -  -  -  -  - <i>Sageraea elliptica</i><br> -  -  -  -  - <i>Stelechocarpus</i><br> -  -  -  -  -  - <i>Stelechocarpus cauliflorus</i><br> -  -  -  -  - <i>Xylopia</i><br> -  -  -  -  -  - <i>Xylopia ferruginea</i><br> -  -  -  -  -  - <i>Xylopia stenopetala</i><br> -  -  -  - Magnoliaceae<br> -  -  -  -  - <i>Magnolia</i><br> -  -  -  -  -  - <i>Magnolia borneensis</i><br> -  -  -  -  -  - <i>Magnolia liliifera</i><br> -  -  -  -  -  - <i>Magnolia tsiampacca</i><br> -  -  -  - Myristicaceae<br> -  -  -  -  - <i>Horsfieldia</i><br> -  -  -  -  -  - <i>Horsfieldia crassifolia</i><br> -  -  -  -  - <i>Knema</i><br> -  -  -  -  -  - <i>Knema glauca</i><br> -  -  -  -  -  - <i>Knema latifolia</i><br> -  -  -  -  -  - <i>Knema laurina</i><br> -  -  -  -  -  - <i>Knema oblongata</i><br> -  -  -  -  - <i>Myristica</i><br> -  -  -  -  -  - <i>Myristica smythiesii</i><br> -  -  - Malpighiales<br> -  -  -  - Achariaceae<br> -  -  -  -  - <i>Hydnocarpus</i><br> -  -  -  -  -  - <i>Hydnocarpus woodii</i><br> -  -  -  -  - <i>Ryparosa</i><br> -  -  -  -  -  - <i>Ryparosa acuminata</i><br> -  -  -  - Calophyllaceae<br> -  -  -  -  - <i>Calophyllum</i><br> -  -  -  -  -  - <i>Calophyllum soulattri</i><br> -  -  -  -  -  - <i>Calophyllum woodii</i><br> -  -  -  -  - <i>Mesua</i><br> -  -  -  -  -  - <i>Mesua borneensis</i><br> -  -  -  -  -  - <i>Mesua macrantha</i><br> -  -  -  -  -  - <i>Mesua oblongifolia</i><br> -  -  -  - Centroplacaceae<br> -  -  -  -  - <i>Bhesa</i><br> -  -  -  -  -  - <i>Bhesa indica</i><br> -  -  -  - Chrysobalanaceae<br> -  -  -  -  - <i>Atuna</i><br> -  -  -  -  -  - <i>Atuna racemosa</i><br> -  -  -  -  - <i>Licania</i><br> -  -  -  -  -  - <i>Licania splendens</i><br> -  -  -  - Clusiaceae<br> -  -  -  -  - <i>Garcinia</i><br> -  -  -  -  -  - <i>Garcinia benthamiana</i><br> -  -  -  -  -  - <i>Garcinia forbesii</i><br> -  -  -  -  -  - <i>Garcinia nervosa</i><br> -  -  -  -  -  - <i>Garcinia parvifolia</i><br> -  -  -  - Euphorbiaceae<br> -  -  -  -  - <i>Blumeodendron</i><br> -  -  -  -  -  - <i>Blumeodendron kurzii</i><br> -  -  -  -  -  - <i>Blumeodendron tokbrai</i><br> -  -  -  -  - <i>Hancea</i><br> -  -  -  -  -  - <i>Hancea penangensis</i><br> -  -  -  -  - <i>Macaranga</i><br> -  -  -  -  -  - <i>Macaranga conifera</i><br> -  -  -  -  -  - <i>Macaranga gigantea</i><br> -  -  -  -  -  - <i>Macaranga hypoleuca</i><br> -  -  -  -  -  - <i>Macaranga pearsonii</i><br> -  -  -  -  -  - <i>Macaranga winkleri</i><br> -  -  -  -  - <i>Mallotus</i><br> -  -  -  -  -  - <i>Mallotus leucodermis</i><br> -  -  -  -  -  - <i>Mallotus miquelianus</i><br> -  -  -  -  -  - <i>Mallotus mollissimus</i><br> -  -  -  -  -  - <i>Mallotus wrayi</i><br> -  -  -  -  - <i>Neoscortechinia</i><br> -  -  -  -  -  - <i>Neoscortechinia kingii</i><br> -  -  -  -  -  - <i>Neoscortechinia philippinensis</i><br> -  -  -  -  - <i>Ptychopyxis</i><br> -  -  -  -  -  - <i>Ptychopyxis arborea</i><br> -  -  -  -  - <i>Spathiostemon</i><br> -  -  -  - Hypericaceae<br> -  -  -  -  - <i>Cratoxylum</i><br> -  -  -  - Irvingiaceae<br> -  -  -  -  - <i>Irvingia</i><br> -  -  -  -  -  - <i>Irvingia malayana</i><br> -  -  -  - Phyllanthaceae<br> -  -  -  -  - <i>Antidesma</i><br> -  -  -  -  - <i>Aporosa</i><br> -  -  -  -  -  - <i>Aporosa confusa</i><br> -  -  -  -  -  - <i>Aporosa falcifera</i><br> -  -  -  -  - <i>Baccaurea</i><br> -  -  -  -  -  - <i>Baccaurea lanceolata</i><br> -  -  -  -  -  - <i>Baccaurea macrocarpa</i><br> -  -  -  -  -  - <i>Baccaurea pubera</i><br> -  -  -  -  -  - <i>Baccaurea tetrandra</i><br> -  -  -  -  - <i>Cleistanthus</i><br> -  -  -  -  -  - <i>Cleistanthus hirsutulus</i><br> -  -  -  -  -  - <i>Cleistanthus hylandii</i><br> -  -  -  -  -  - <i>Cleistanthus oblongifolius</i><br> -  -  -  -  -  - <i>Cleistanthus paxii</i><br> -  -  -  -  -  - <i>Cleistanthus pubens</i><br> -  -  -  -  - <i>Glochidion</i><br> -  -  -  -  -  - <i>Glochidion borneensis</i><br> -  -  -  -  - <i>Phyllanthus</i><br> -  -  -  -  -  - <i>Phyllanthus lutescens</i><br> -  -  -  -  -  - <i>Phyllanthus ruber</i><br> -  -  -  - Putranjivaceae<br> -  -  -  -  - <i>Drypetes</i><br> -  -  -  -  -  - <i>Drypetes longifolia</i><br> -  -  -  - Salicaceae<br> -  -  -  -  - <i>Flacourtia</i><br> -  -  -  -  -  - <i>Flacourtia rukam</i><br> -  -  -  -  - <i>Homalium</i><br> -  -  -  -  -  - <i>Homalium foetidum</i><br> -  -  - Malvales<br> -  -  -  - Dipterocarpaceae<br> -  -  -  -  - <i>Dipterocarpus</i><br> -  -  -  -  -  - <i>Dipterocarpus caudiferus</i><br> -  -  -  -  - <i>Dryobalanops</i><br> -  -  -  -  -  - <i>Dryobalanops lanceolata</i><br> -  -  -  -  - <i>Hopea</i><br> -  -  -  -  -  - <i>Hopea plagata</i><br> -  -  -  -  -  - <i>Hopea sangal</i><br> -  -  -  -  - <i>Parashorea</i><br> -  -  -  -  -  - <i>Parashorea malaanonan</i><br> -  -  -  -  -  - <i>Parashorea smythiesii</i><br> -  -  -  -  -  - <i>Parashorea warburgii</i><br> -  -  -  -  - <i>Shorea</i><br> -  -  -  -  -  - <i>Shorea almon</i><br> -  -  -  -  -  - <i>Shorea angustifolia</i><br> -  -  -  -  -  - <i>Shorea argentifolia</i><br> -  -  -  -  -  - <i>Shorea beccariana</i><br> -  -  -  -  -  - <i>Shorea faguetiana</i><br> -  -  -  -  -  - <i>Shorea falciferoides</i><br> -  -  -  -  -  - <i>Shorea fallax</i><br> -  -  -  -  -  - <i>Shorea gibbosa</i><br> -  -  -  -  -  - <i>Shorea guiso</i><br> -  -  -  -  -  - <i>Shorea johorensis</i><br> -  -  -  -  -  - <i>Shorea laevis</i><br> -  -  -  -  -  - <i>Shorea leprosula</i><br> -  -  -  -  -  - <i>Shorea leptoderma</i><br> -  -  -  -  -  - <i>Shorea macrophylla</i><br> -  -  -  -  -  - <i>Shorea macroptera</i><br> -  -  -  -  -  - <i>Shorea ovalis</i><br> -  -  -  -  -  - <i>Shorea ovata</i><br> -  -  -  -  -  - <i>Shorea parvifolia</i><br> -  -  -  -  -  - <i>Shorea parvistipulata</i><br> -  -  -  -  -  - <i>Shorea pauciflora</i><br> -  -  -  -  -  - <i>Shorea pinanga</i><br> -  -  -  -  -  - <i>Shorea superba</i><br> -  -  -  -  -  - <i>Shorea symingtonii</i><br> -  -  -  -  -  - <i>Shorea xanthophylla</i><br> -  -  -  -  - <i>Vatica</i><br> -  -  -  -  -  - <i>Vatica dulitensis</i><br> -  -  -  -  -  - <i>Vatica odorata</i><br> -  -  -  - Malvaceae<br> -  -  -  -  - <i>Boschia</i><br> -  -  -  -  -  - <i>Boschia grandiflora</i><br> -  -  -  -  - <i>Durio</i><br> -  -  -  -  -  - <i>Durio graveolens</i><br> -  -  -  -  - <i>Heritiera</i><br> -  -  -  -  -  - <i>Heritiera elata</i><br> -  -  -  -  - <i>Microcos</i><br> -  -  -  -  -  - <i>Microcos crassifolia</i><br> -  -  -  -  - <i>Pentace</i><br> -  -  -  -  -  - <i>Pentace borneensis</i><br> -  -  -  -  - <i>Pterygota</i><br> -  -  -  -  -  - <i>Pterygota alata</i><br> -  -  -  -  - <i>Scaphium</i><br> -  -  -  -  -  - <i>Scaphium macropodum</i><br> -  -  -  -  - <i>Sterculia</i><br> -  -  -  -  -  - <i>Sterculia rubiginosa</i><br> -  -  -  -  -  - <i>Sterculia stipulata</i><br> -  -  -  - Thymelaeaceae<br> -  -  -  -  - <i>Aquilaria</i><br> -  -  -  -  -  - <i>Aquilaria beccariana</i><br> -  -  - Myrtales<br> -  -  -  - Combretaceae<br> -  -  -  -  - <i>Terminalia</i><br> -  -  -  -  -  - <i>Terminalia citrina</i><br> -  -  -  -  -  - <i>Terminalia foetidissima</i><br> -  -  -  - Lythraceae<br> -  -  -  -  - <i>Duabanga</i><br> -  -  -  -  -  - <i>Duabanga moluccana</i><br> -  -  -  - Melastomataceae<br> -  -  -  -  - <i>Clidemia</i><br> -  -  -  -  -  - <i>Clidemia hirta</i><br> -  -  -  -  - <i>Melastoma</i><br> -  -  -  -  -  - <i>Melastoma malabathricum</i><br> -  -  -  -  - <i>Memecylon</i><br> -  -  -  -  -  - <i>Memecylon oleifolium</i><br> -  -  -  - Myrtaceae<br> -  -  -  -  - <i>Syzygium</i><br> -  -  -  -  -  - <i>Syzygium caudatilimbum</i><br> -  -  -  -  -  - <i>Syzygium chloranthum</i><br> -  -  -  -  -  - <i>Syzygium elopurae</i><br> -  -  -  -  -  - <i>Syzygium grande</i><br> -  -  -  -  -  - <i>Syzygium griffithii</i><br> -  -  -  -  -  - <i>Syzygium kunstleri</i><br> -  -  -  -  -  - <i>Syzygium lineatum</i><br> -  -  -  -  -  - <i>Syzygium pancheri</i><br> -  -  -  -  -  - <i>Syzygium panzeri</i><br> -  -  -  -  -  - <i>Syzygium pustulatum</i><br> -  -  -  -  -  - <i>Syzygium racemosum</i><br> -  -  -  -  -  - <i>Syzygium rheophyticum</i><br> -  -  -  -  - <i>Tristaniopsis</i><br> -  -  -  -  -  - <i>Tristaniopsis whiteana</i><br> -  -  - Oxalidales<br> -  -  -  - Elaeocarpaceae<br> -  -  -  -  - <i>Elaeocarpus</i><br> -  -  -  -  -  - <i>Elaeocarpus floribundus</i><br> -  -  -  -  -  - <i>Elaeocarpus pedunculatus</i><br> -  -  -  -  -  - <i>Elaeocarpus stipularis</i><br> -  -  -  -  - <i>Sloanea</i><br> -  -  -  -  -  - <i>Sloanea javanica</i><br> -  -  - Rosales<br> -  -  -  - Cannabaceae<br> -  -  -  -  - <i>Gironniera</i><br> -  -  -  -  -  - <i>Gironniera nervosa</i><br> -  -  -  -  - <i>Trema</i><br> -  -  -  -  -  - <i>Trema orientalis</i><br> -  -  -  - Moraceae<br> -  -  -  -  - <i>Antiaris</i><br> -  -  -  -  -  - <i>Antiaris toxicaria</i><br> -  -  -  -  - <i>Artocarpus</i><br> -  -  -  -  -  - <i>Artocarpus anisophyllus</i><br> -  -  -  -  -  - <i>Artocarpus glaucus</i><br> -  -  -  -  -  - <i>Artocarpus integer</i><br> -  -  -  -  -  - <i>Artocarpus odoratissimus</i><br> -  -  -  -  -  - <i>Artocarpus tamaran</i><br> -  -  -  -  - <i>Ficus</i><br> -  -  -  -  -  - <i>Ficus hispida</i><br> -  -  -  -  -  - <i>Ficus septica</i><br> -  -  -  -  -  - <i>Ficus uncinata</i><br> -  -  -  -  -  - <i>Ficus variegata</i><br> -  -  -  - Rosaceae<br> -  -  -  -  - <i>Prunus</i><br> -  -  -  -  -  - <i>Prunus javanica</i><br> -  -  -  -  - <i>Pygeum</i><br> -  -  -  -  -  - <i>Pygeum beccarii</i><br> -  -  -  - Urticaceae<br> -  -  -  -  - <i>Dendrocnide</i><br> -  -  -  -  -  - <i>Dendrocnide elliptica</i><br> -  -  - Santalales<br> -  -  -  - Coulaceae<br> -  -  -  -  - <i>Ochanostachys</i><br> -  -  -  -  -  - <i>Ochanostachys amentacea</i><br> -  -  -  - Strombosiaceae<br> -  -  -  -  - <i>Scorodocarpus</i><br> -  -  -  -  -  - <i>Scorodocarpus borneensis</i><br> -  -  - Sapindales<br> -  -  -  - Anacardiaceae<br> -  -  -  -  - <i>Gluta</i><br> -  -  -  -  -  - <i>Gluta aptera</i><br> -  -  -  -  -  - <i>Gluta wallichii</i><br> -  -  -  -  - <i>Mangifera</i><br> -  -  -  -  -  - <i>Mangifera odorata</i><br> -  -  -  -  - <i>Melanochyla</i><br> -  -  -  -  -  - <i>Melanochyla bullata</i><br> -  -  -  -  -  - <i>Melanochyla tomentosa</i><br> -  -  -  -  - <i>Parishia</i><br> -  -  -  -  -  - <i>Parishia insignis</i><br> -  -  -  - Burseraceae<br> -  -  -  -  - <i>Canarium</i><br> -  -  -  -  -  - <i>Canarium decumanum</i><br> -  -  -  -  -  - <i>Canarium denticulatum</i><br> -  -  -  -  -  - <i>Canarium odontophyllum</i><br> -  -  -  -  -  - <i>Canarium pilosum</i><br> -  -  -  -  - <i>Dacryodes</i><br> -  -  -  -  -  - <i>Dacryodes rostrata</i><br> -  -  -  -  -  - <i>Dacryodes rugosa</i><br> -  -  -  -  - <i>Santiria</i><br> -  -  -  -  -  - <i>Santiria laevigata</i><br> -  -  -  - Meliaceae<br> -  -  -  -  - <i>Aglaia</i><br> -  -  -  -  -  - <i>Aglaia crassinervia</i><br> -  -  -  -  -  - <i>Aglaia leptantha</i><br> -  -  -  -  -  - <i>Aglaia macrocarpa</i><br> -  -  -  -  -  - <i>Aglaia odoratissima</i><br> -  -  -  -  -  - <i>Aglaia oligophylla</i><br> -  -  -  -  -  - <i>Aglaia silvestris</i><br> -  -  -  -  -  - <i>Aglaia tomentosa</i><br> -  -  -  -  - <i>Aphanamixis</i><br> -  -  -  -  -  - <i>Aphanamixis polystachya</i><br> -  -  -  -  - <i>Chisocheton</i><br> -  -  -  -  -  - <i>Chisocheton ceramicus</i><br> -  -  -  -  -  - <i>Chisocheton macranthus</i><br> -  -  -  -  -  - <i>Chisocheton patens</i><br> -  -  -  -  - <i>Dysoxylum</i><br> -  -  -  -  -  - <i>Dysoxylum cyrtobotryum</i><br> -  -  -  -  -  - <i>Dysoxylum densiflorum</i><br> -  -  -  -  - <i>Lansium</i><br> -  -  -  -  -  - <i>Lansium domesticum</i><br> -  -  -  -  - <i>Reinwardtiodendron</i><br> -  -  -  -  -  - <i>Reinwardtiodendron humile</i><br> -  -  -  -  - <i>Walsura</i><br> -  -  -  -  -  - <i>Walsura pinnata</i><br> -  -  -  - Rutaceae<br> -  -  -  -  - <i>Melicope</i><br> -  -  -  -  -  - <i>Melicope confusa</i><br> -  -  -  - Sapindaceae<br> -  -  -  -  - <i>Dimocarpus</i><br> -  -  -  -  -  - <i>Dimocarpus longan</i><br> -  -  -  -  - <i>Nephelium</i><br> -  -  -  -  -  - <i>Nephelium cuspidatum</i><br> -  -  -  -  - <i>Paranephelium</i><br> -  -  -  -  -  - <i>Paranephelium macrophyllum</i><br> -  -  -  -  -  - <i>Paranephelium xestophyllum</i><br> -  -  -  -  - <i>Pometia</i><br> -  -  -  -  -  - <i>Pometia pinnata</i><br> -  -  -  -  - <i>Tristiropsis</i><br> -  -  -  -  -  - <i>Tristiropsis acutangula</i><br> -  -  - Solanales<br> -  -  -  - Convolvulaceae<br> -  -  -  -  - <i>Decalobanthus</i><br> -  -  -  -  -  - <i>Decalobanthus borneensis</i><br> -  -  -  -  - <i>Jacquemontia</i><br> -  -  -  -  -  - <i>Jacquemontia tomentella</i><br> -  - Polypodiopsida<br> -  -  - Gleicheniales<br> -  -  -  - Gleicheniaceae<br> -  -  -  -  - <i>Dicranopteris</i><br> -  -  -  -  -  - <i>Dicranopteris pubigera</i><br> -  -  - Polypodiales<br> -  -  -  - Lomariopsidaceae<br> -  -  -  -  - <i>Nephrolepis</i><br> -  -  -  -  -  - <i>Nephrolepis biserrata</i><br></div><p></p>
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.