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82 results for “tree density”
Data from: Density-dependent effects of a widespread invasive herbivore on tree survival and biomass during reforestation
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Data from: Mating system and genetic diversity of progenies before and after logging: a case study of Bagassa guianensis (Moraceae), a low-density dioecious tree of the Amazonian forest
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Data from: Functional attributes of savannah soils: contrasting effects of tree canopies and herbivores on bulk density, nutrients and moisture dynamics
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Data from: Relationships between population density, fine-scale genetic structure, mating system and pollen dispersal in a timber tree from African rainforests.
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Data from: Recurrent fruit harvesting reduces seedling density but increases the frequency of clonal reproduction in a tropical tree
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Data from: Tree-centric mapping of forest carbon density from airborne laser scanning and hyperspectral data
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Data from: The importance of trees for woody pasture bird diversity and effects of the European Union's tree density policy
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Tree mycorrhizal type mediates the strength of negative density dependence in temperate forests
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Data from: Loss of animal seed dispersal increases extinction risk in a tropical tree species due to pervasive negative density dependence across life stages
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Data from: Limited contributions of plant pathogens to density-dependent seedling mortality of mast fruiting Bornean trees
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Tree light availability:FAB 1 : Forests and Biodiversity Experiment - High density diversity
A forest biodiversity experiment (FAB) focused on trees of our region investigates the consequences of multiple dimensions of tree diversity for soil, food webs, plant communities and ecosystems. FAB is designed to unravel effects of three forms of biological diversity: species richness (SR), functional diversity (FD), and phylogenetic diversity (PD). We define FD as the representation of multiple traits of leaves, roots, seeds, and the whole organism that are correlated with species positions along gradients of resource supply, growth, and decomposition. PD is the representation of evolutionary lineages measured as the genetic distances between species. While PD and FD are often correlated, convergent evolution and adaptive differentiation can decouple them. When functional traits that drive specific ecosystem functions are not phylogenetically conserved, PD and FD may give contrasting predictions. SR, PD, and FD are not independent, and we posit that PD may help explain SR effects, and FD may help explain both PD and SR effects. Thus FAB is designed to examine the separate and combined effects of all three components of diversity for multiple ecosystem functions and to distinguish between ???sampling??? and ???complementarity??? effects of biodiversity. Due to the long lag between planting tree seedlings and determining effects of tree composition and diversity on ecosystem functioning, fewer experiments have been established to elucidate the role of biodiversity in the functioning of forest ecosystems than grassland experiments. FAB will contribute to this gap and is a member of the IDENT and TreeDiv network of forest biodiversity experiments (www.treedivnet.ugent.be). Hypotheses: 1. PD, FD, and SR will all contribute to increased productivity, stability, and diversity of other trophic levels (herbivores, predators, parasitoids, soil microbes, soil flora and fauna) as well as to greater soil C sequestration. 2. Because PD incorporates both the number of species a
Which enemies mediate distance- and density-dependent mortality of tree seeds and seedlings? A meta-analysis of fungicide, insecticide, and exclosure studies
<p>Conspecific negative distance- and density-dependence is believed to be one of the most important mechanisms controlling forest community assembly and species diversity globally. SoilPlant pathogens, and insect and mammalian herbivores, are the most common natural enemy types that have been implicated in this phenomenon, but their relative importancegeneral effects at different plant life stages isare still unclear. Here, we conduct a meta-analysis of studies that involved robust manipulative experiments, using fungicides, insecticides, and exclosures, to assess the contributions of different natural enemy types to distance- and density-dependent effects at seed and seedling stages. We found that natural enemies cause stronger distance- and density-dependent mortality caused by natural enemies was most likely at the seedling stage than the seed stage. Fungicide treatments can change significantand was greater at higher mean annual temperatures. Seedling mortality was significantly weakened when fungi were removed. By contrast, negative distance- and density-dependent mortality to non-significance at the seedling stage. Negative conspecific distance- and density-dependence is not a general pattern at the seed stage. High seed mass reduced distance- and density-dependent mortality. Seed studies excluding only large mammals found significant negative conspecific distance-dependent mortality, but exclusion of all mammals resulted in a non-significant mortality.effect of conspecifics. Our study suggests that soilplant pathogens are a major cause of distance- and density-dependent mortality at the seedling stage, althoughwhile the impacts of herbivores on seedlings have been understudied. At the seed stage, large and small mammals respectively weaken and enhance negative conspecific distance-dependent mortality. Future research should identify specific agents of mortality, investigate the interactions among different enemy types, and assess how global change drivers may affect the dynamics of natural enemies and thus influence the strength of conspecific distance- and density-dependence.</p>
Nutrients and wood density in coarse root, trunk and branches in Bornean tree species
<b>Description: </b><p>Carbon (C), nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) concentrations in woody tissue and bark, and wood density, were quantified for ten common Bornean tree species. The study took advantage of the ongoing logging in August 2014, sampling trees felled in the logging sites (near D Matrix, exact locations of the sampled trees not recorded). Each tree species had three replicates. The diameter of the sampled trees ranged from 12 cm to 44 cm. Sampled trees had no visible damage (e.g. no insect damage, chlorotic leaves and bent stems). The species IDs of the sampled trees were confirmed at the herbarium of the Forest Research Centre in Sepilok, Sandakan.<br><br>Several points along the length of the tree were sampled: coarse root; trunk bottom, trunk middle and trunk top (highest point of the main stem); and the lowest branch of the tree, from branch bottom, branch middle and branch tip. The sampled components were cut directly after felling using a chainsaw. The samples were then transported to the chemistry laboratory of the Forest Research Centre in Sepilok, Sandakan.<br><br>Bark (both the outer bark and phloem) was separated from the wood, except for the trunk top and branch tip samples, where the bark layer was too thin. Wood samples were divided into sapwood and heartwood if possible, based on a distinguishable colour difference after mechanical sanding. Sapwood and heartwood for most branch and coarse root samples were not separated due to the absence of colour boundary, but they probably consists mostly of sapwood.<br><br>For chemical analyses, all samples were oven dried at 50°C to constant weight for five days and ground with a Thomas Wiley Mill to pass through a 100-mush (212-μm) sieve. Each sample was digested following the sulphuric acid-hydrogen peroxide-lithium sulphate digest procedure for vegetation described in Allen (1989). Phosphorus in the digest was determined using the molybdenum-blue method described in Anderson and Ingram (1993) and read at 880 nm on a spectrophotometer (HITACHI UV-VIS, Tokyo, Japan), while K, Ca and Mg contents were measured on an atomic absorption spectrophotometer (GBC Scientific Equipment, Victoria, Australia). Total C and N contents (as total element contents) were determined by a dry combustion method at 900°C using an Elementar Vario Max CN analyzer (Elementar Analysensysteme, Hanau, Germany). Analysis protocols are described in more detail in Majalap and Chu (1992).<br><br>Wood density was quantified for trunk bottom and trunk middle samples. A strip, running through the wood disk slightly off centre, proportionally covering both sapwood and heartwood, was cut, and three (minimum of two, maximum of five, depending on the lenght of the strip) cubes (tangent ~20 mm × axial ~20 mm × radial ~20 mm length, exact dimensions recorded) were cut for wood density measurements, following the procedure ISO 3131:1975 (E) Wood -- Determination of Density for Physical and Mechanical Tests. Wood density was defined as the oven-dry mass per unit volume of fresh wood cube. Dry mass was measured after oven drying the samples at 103±2°C until the dry mass was stabilised. <br><br>References:<br>Allen, S. E. (1989). Chemical analysis of ecological materials (2nd ed.). Oxford, England; Boston; Blackwell Scientific Publications.<br>Anderson, J. M., & Ingram, J. S. I. (1993). Tropical soil biology and fertility: a handbook of methods (2nd ed.). Wallingford, UK: C.A.B. International.<br>Majalap, N., & Chu, N. H. (1992). Laboratory Manual for Chemical Analysis. Sandakan, Sabah, Malaysia: Forest Research Centre, Sabah Forestry Department.</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/113"><b>Changing carbon dioxide and water budgets from deforestation and habitat modification</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>Sime Darby Foundation (Grant, SAFE Core data)</li><li>Joint Japan/World Bank Graduate Scholarship Program (JJ/WBGSP) (Scholarship, JJ/WBGSP)</li><li>European Research Council Advanced Investigator Grant, GEM-TRAIT (Grant, Grant number 321131)</li><li>NERC Human-Modified Tropical Forests Programme: Biodiversity And Land-use Impacts on tropical ecosystem function (BALI) Project (Grant, NE/K016369/1)</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 (SABC) (Research licence JKM/MBS.1000-2/2 (187))</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=8158811">here</a></p><p><b>Files: </b>This consists of 1 file: Inagawa_TreeComponentData_Nutrients_WoodDensity_SAFEdatabase_2023-07-10.xlsx</p><p><b>Inagawa_TreeComponentData_Nutrients_WoodDensity_SAFEdatabase_2023-07-10.xlsx</b></p><p>This file contains dataset metadata and 3 data tables:</p><ol><li><p><b>TreeInfo</b> (described in worksheet TreeInfo)</p><p>Description: Local name, confirmed species id, family, and diameter of the sampled trees</p><p>Number of fields: 6</p><p>Number of data rows: 30</p><p>Fields: </p><ul><li><b>TreeNumber</b>: Running number of the sampled trees (Field type: id)</li><li><b>Species_LocalName</b>: Local name of the sampled tree (Field type: comments)</li><li><b>Family</b>: Family (Field type: comments)</li><li><b>Species</b>: Tree species (Field type: taxa)</li><li><b>DBH</b>: Diameter at the 1.3 m heigth (Field type: numeric trait)</li><li><b>SamplingLocation</b>: Location within the SAFE landscape (Field type: location)</li></ul></li><li><p><b>Nutrients</b> (described in worksheet Nutrients)</p><p>Description: Data on nutrients in bark and wood, along the length of the tree (coarse roots, along the trunk, branches) and radially (sapwood and heartwood).</p><p>Number of fields: 11</p><p>Number of data rows: 420</p><p>Fields: </p><ul><li><b>LabNumber</b>: Code assigned to each sample at the receiving chemistry lab (Field type: id)</li><li><b>TreeNumber</b>: Running number of the sampled trees (Field type: id)</li><li><b>SamplingPoint</b>: Site of the sample, from the bottom to the top of the tree: coarse root (CR), trunk bottom (TB), trunk middle (TM), brach bottom (BB), branch middle (BM), branch top (BT), trunk top (TT) (Field type: categorical)</li><li><b>TissueType</b>: Tissue type: bark, heartwood, sapwood, wood (if not possible to separate the sample into heart and sapwood), wood and bark (in case of branch tip and trunk tip, not possible to separate wood and bark). (Field type: categorical trait)</li><li><b>Species</b>: Tree species (Field type: taxa)</li><li><b>K_total</b>: Total potassium content (Field type: numeric trait)</li><li><b>Ca_total</b>: Total calsium content (Field type: numeric trait)</li><li><b>Mg_total</b>: Total magnesium content (Field type: numeric trait)</li><li><b>P_total</b>: Total phosphorus content (Field type: numeric trait)</li><li><b>N_total</b>: Total nitrogen content (Field type: numeric trait)</li><li><b>C_total</b>: Total carbon content (Field type: numeric trait)</li></ul></li><li><p><b>WoodDensity</b> (described in worksheet WoodDensity)</p><p>Description: Data on wood density at the bottom and at the middle of the trunk.</p><p>Number of fields: 13</p><p>Number of data rows: 207</p><p>Fields: </p><ul><li><b>TreeNumber</b>: Running number of the sampled trees (Field type: id)</li><li><b>Species</b>: Tree species (Field type: taxa)</li><li><b>SamplingPoint</b>: Site of the wood sample, either trunk bottom (TB) or trunk middle (TM). (Field type: categorical)</li><li><b>Replicate</b>: Replicate wood cube sampled for each wood disk (Field type: replicate)</li><li><b>Length_Tangential_Fresh</b>: Length of the wood cube edge in tangential direction, before drying (fresh). (Field type: numeric trait)</li><li><b>Length_Axial_Fresh</b>: Length of the wood cube edge in axial direction, before drying (fresh). (Field type: numeric trait)</li><li><b>Length_Radia_Fresh</b>: Length of the wood cube edge in radial direction, before drying (fresh). (Field type: numeric trait)</li><li><b>Mass_Fresh</b>: Fresh mass of wood cube, before drying. (Field type: numeric trait)</li><li><b>Length_Tangential_Dry</b>: Length of the wood cube edge in tangential direction, after oven drying. (Field type: numeric trait)</li><li><b>Length_Axial_Dry</b>: Length of the wood cube edge in axial direction, after oven drying. (Field type: numeric trait)</li><li><b>Length_Radial_Dry</b>: Length of the wood cube edge in radial direction, after oven drying. (Field type: numeric trait)</li><li><b>Mass_Dry</b>: Dry mass of wood cube, after oven drying (Field type: numeric trait)</li><li><b>WoodDensity</b>: Wood density, calculated as dry mass divided by fresh volume (Field type: numeric trait)</li></ul></li></ol><p><b>Date range: </b>2014-08-01 to 2015-11-30</p><p><b>Latitudinal extent: </b>4.1830 to 4.1830</p><p><b>Longitudinal extent: </b>114.0220 to 114.0220</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Plantae <br> -  -  Tracheophyta <br> -  -  -  Magnoliopsida <br> -  -  -  -  Malvales <br> -  -  -  -  -  Malvaceae <br> -  -  -  -  -  -  <i>Pentace</i> <br> -  -  -  -  -  -  -  <i>Pentace borneensis</i> (as synonym: <i>Pentace laxiflora</i>)<br> -  -  -  -  -  Dipterocarpaceae <br> -  -  -  -  -  -  <i>Shorea</i> <br> -  -  -  -  -  -  -  <i>Shorea johorensis</i> <br> -  -  -  -  -  -  -  <i>Shorea leprosula</i> <br> -  -  -  -  -  -  -  <i>Shorea micans</i> <br> -  -  -  -  -  -  -  <i>Shorea parvifolia</i> <br> -  -  -  -  -  -  <i>Parashorea</i> <br> -  -  -  -  -  -  -  <i>Parashorea malaanonan</i> <br> -  -  -  -  Fagales <br> -  -  -  -  -  Fagaceae <br> -  -  -  -  -  -  <i>Lithocarpus</i> <br> -  -  -  -  -  -  -  <i>Lithocarpus leptogyne</i> <br> -  -  -  -  Gentianales <br> -  -  -  -  -  Rubiaceae <br> -  -  -  -  -  -  <i>Neolamarckia</i> <br> -  -  -  -  -  -  -  <i>Neolamarckia cadamba</i> <br> -  -  -  -  Rosales <br> -  -  -  -  -  Cannabaceae <br> -  -  -  -  -  -  <i>Trema</i> <br> -  -  -  -  -  -  -  <i>Trema orientalis</i> <br> -  -  -  -  Malpighiales <br> -  -  -  -  -  Euphorbiaceae <br> -  -  -  -  -  -  <i>Macaranga</i> <br> -  -  -  -  -  -  -  <i>Macaranga pearsonii</i> <br></div><p></p>
Which enemies mediate distance- and density-dependent mortality of tree seeds and seedlings? A meta-analysis of fungicide, insecticide, and exclosure studies
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Data from: Tree mortality across biomes is promoted by drought intensity, lower wood density and higher specific leaf area
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Data from: Interspecific functional convergence and divergence and intraspecific negative density dependence underlie the seed-to-seedling transition in tropical trees
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Data from: High-density sex-specific linkage maps of a European tree frog (Hyla arborea) identify the sex chromosome without information on offspring sex
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BOREAS HYD-03 1996 Tree Stem Density Data
The BOREAS HYD-03 team collected several data sets related to the hydrology of forested areas. This data set contains measurements of stem density from a variety of sites. Stem density measurements were made during the FFC-W 1996 in the SSA only using standard techniques. This study was undertaken to predict spatial distributions of energy transfer, snow properties important to the hydrology, remote sensing signatures, and transmissivity of gases through the snow and their relation to forests in boreal ecosystems.
Data from: Insect herbivory on seedlings of rainforest trees: effects of density and distance of conspecific and heterospecific neighbours
1. Natural enemies of plants such as insect herbivores can contribute to structuring and maintaining plant diversity in tropical forests. Most research in this area has focused on the role of specialised enemies and the extent to which herbivory on individual plant species is density-dependent. 2. Relatively few insect herbivores specialise on a single host plant species. Insect herbivores that feed on more than one plant species may link the regeneration dynamics of their host species through 'apparent competition' or 'apparent mutualism'. 3. We investigated herbivory and survival of seedlings of two tropical tree species (Cordia alliodora and Cordia bicolor) in the forests of Barro Colorado Island (Panama). We used experiments and observations to assess seedling fate in relation to the presence of conspecifics and heterospecifics across a range of spatial scales. 4. Herbivory significantly increased seedling mortality and was highest at high local densities of C. alliodora seedlings. There was also evidence that high local densities of C. alliodora increased herbivory on co-occurring C. bicolor seedlings. 5. Synthesis. The elevated rates of seedling herbivory at high densities of conspecifics documented in our study are consistent with the predictions of the Janzen-Connell hypothesis, which explains how so many plant species can coexist in tropical forests. Our data also highlight the possibility that herbivore-mediated density-dependence, facilitated by herbivores that feed on multiple plant species, can also occur across plant species. Enemy-mediated indirect effects of this sort have the potential to structure plant communities.
Data from: Insect herbivory on seedlings of rainforest trees: effects of density and distance of conspecific and heterospecific neighbours
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