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181 results for “tree communities.”

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edi56/100

Tree-Associated Fungal and Bacterial Communities at Harvard Forest 2021

Cities are investing in tree-planting initiatives to protect their citizens from climate change-related heat and pollution exposure, yet Boston’s street trees are growing nearly four times as fast and dying twice as young as Massachusetts’ rural forest trees. Our research aims to characterize the belowground variables and microbial community composition that might explain the differences in growth and mortality rates observed between urban and rural trees. In 2021, soil, leaf, and root samples were taken from 25 trees in Harvard Forest to use as a rural comparison to Boston’s street trees and trees in other forests along an urban-to-rural gradient from Boston into Western Massachusetts. At each tree, three 12” deep, 2.4-centimeter radius soil cores were taken within the drip line, and soil cores were divided into the top 6” and lower 6” of soil. Fine roots were picked from each soil core. Six leaf samples were taken from the mid-canopy of each tree, where possible. Soil variables including temperature, moisture, percent organic matter, soluble nitrogen availability, bulk density, and root biomass were measured. Thus far, we have found that urban trees have fewer roots than Harvard Forest trees (F1,252) = 10.88, p = 0.0011), and that urban trees establish more root biomass deeper into the soil than Harvard Forest trees (p = 4.84e-5).

openCC0Mar 2025View details →
zenodo52/100

Pawpaws prevent predictability: A locally-dominant tree alters understory beta-diversity and community assembly

<p>Data used in "Pawpaws Prevent Predictability: A locally-dominant tree alters understory beta-diversity and community assembly" (Wassel and Myers) accepted for publication in Ecosphere.<br><br><strong>Metadata for Zenodo.pdf&nbsp;</strong>contains more information on the following data files including descriptions of the columns.&nbsp;</p> <p>The file <strong>understory_abundance_data2021.csv</strong>&nbsp;contains all species abundances in 1x1m plots. This data was used for analyses in publication. Each row is a plot, each column is a speceis or plot descriptor, values for columns 5 and higher are species abundances. Data was collected July-August 2021 by Anna Wassel in Missouri, USA.&nbsp;</p> <p>The file <strong>understory_species_list2021.csv&nbsp;</strong>contains a list of the species codes used in the first file with their scientific names and their status as herbs or woody. This was used to filter out herbaceous species from the data set for herbaceous-only analyses.&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Nov 2024View details →
edi52/100

Tree Health Conditions (mortality, damage, disease, bark beetles) in Fuel Reduction Treatments Located Near Communities in Interior Alaska and the Cook Inlet Region of Alaska - Observations from July-August 2023

This dataset contains tree-, transect-, and site-level observations of forest stands at sites that received a fuel reduction treatment. Tree-level observations include species, diameter, living status, damage, disease, and bark beetle presence. Transect-level observations include level of coarse woody debris and bark beetle presence. Sites are categorized by region (recent/ongoing spruce beetle oubreak or endemic spruce beetle population levels) and treatment type (hand-thinned or mechanincally felled and masticated). These observations are from July-August 2023. Sites are located near communities in Interior Alaska and the Cook Inlet Region.

openOpenAug 2025View details →
edi48/100

Tree survey:Effects of Long Term Fertilization and Oak Canopy Cover on Plant Communities and Ecosystem Processes

In 1996 E142 was established in field D on top of the E004 macroplots. E004 was conducted in fields A, B, C and D by Dave Tilman. The purpose of E004 was to see what effect NH4NO3 addition has on large areas over a longer period of time with exposure to naturally-occurring levels of herbivory. The nutrient addition treatments in E004, E142 plots have been applied annually since 1982. These experiments, along with others at Cedar Creek, examine the community and ecosystem consequences of chronic nutrient loading.

openCC0Aug 2025View details →
edi48/100

Consequences of non-random tree species loss on litter mass loss, nutrient dynamics, carbon cycling, and decomposer communities across a terrestrial-aquatic interface at Coweeta Hydrologic Lab, Otto, NC

Although litter decomposition is a fundamental ecological process, most of our understanding comes from studies of single-species decay. Recently, litter-mixing studies have tested whether monoculture data can be applied to mixed-litter systems. These studies have mainly attempted to detect non-additive effects of litter mixing, which address potential consequences of random species loss. The focus is not on which species are lost, but the decline in diversity per se. Under global change, species loss is likely to be non-random, with some species more vulnerable to extinction than others. Under such scenarios, the effects of individual species (additivity) as well as of species interactions (non-additivity) on decomposition rates are of interest. To examine potential impacts of non-random species loss on ecosystems, we studied additive and non-additive effects of litter mixing on decomposition. A full-factorial litterbag experiment was conducted using four deciduous leaf species, from which mass loss and nitrogen content were measured. Data were analysed using a statistical approach that first looks for additive identity effects based on the presence or absence of species and then significant species interactions occurring beyond those. It partitions non-additive effects into those caused by richness and or composition.

openCustomJan 2020View details →
zenodo44/100

Data from: Choosy beetles: how host trees and southern boreal forest naturalness may determine dead wood beetle communities

<p>See methods section of paper for detailed information on dataset&nbsp;and sources; briefly, these .csv&nbsp;files includes numbers of each beetle species captured at all sites used in the project, as well as information about each site and about each species.</p> <p>&nbsp;</p> <p>Data from:</p> <p><strong>Choosy beetles: how host trees and southern boreal forest naturalness may determine dead wood beetle communitie</strong><strong>s</strong></p> <p>Ryan C. Burner, Tone Birkemoe, J&ouml;rg G. Stephan, Lukas Drag, J&ouml;rg Muller, Otso Ovakainen, M&aacute;ria Potterf, Olav Skarpaas, Tord Snall, Anne Sverdrup-Thygeson</p> <p>Forest Ecology and Management, 2021</p> <p>&nbsp;</p> <p>From abstract of paper:</p> <p>Wood-living beetles make up a large proportion of forest biodiversity, and contribute to important ecosystem services, including decomposition. Beetle communities in managed southern boreal forests are less species rich than in natural and near-natural forest stands. In addition, many beetle species rely primarily on specific tree species. Yet, the associations between individual beetle species, forest management category, and tree species are seldom quantified, even for red-listed beetles. We compiled a beetle capture dataset from flight intercept traps placed in Norway spruce (<em>Picea abies</em>), oak (<em>Quercus sp.</em>), and Eurasian aspen (<em>Populus tremulae</em>) trees in 413 sites in mature managed forest, near-natural forest, and clear-cuts in southeastern Norway. We used joint species distribution models to estimate the strength of associations for 368 saproxylic beetle species (including 20 vulnerable, endangered, or critical red-listed species) for each forest management category and tree species. Tree species on which traps were mounted had the largest effect on beetle communities; oaks had the most highly associated beetle species, including most of the red-listed species, followed by Norway spruce and Eurasian aspen. Most beetle species were more likely to be captured in near-natural than in mature managed forest. Our estimated associations were compatible &ndash; for many species &ndash; with categorical classifications found in several existing databases of saproxylic beetle preferences. These quantitative beetle-habitat associations will improve future analyses that have typically relied on categorical classifications. Our results highlight the need to prioritize conservation of near-natural forests and oak trees in Scandinavia to protect the habitat of many red-listed species in particular. Furthermore, we underline the importance of carefully considering the species of trees on which traps are mounted in order to representatively sample beetle communities in forest stands.</p>

opencc-by-4.0Jan 2021View details →
edi44/100

canopy herbivory and leaf traits of tree communities in tropical montane rainforests of southern Ecuador

This dataset contains herbivory data estimated as leaf area loss [cm²] and [%] and several leaf traits measured either conventionally or via spectral sensing-based techniques from canopies of tree communities in tropical montane rainforests of the Andes in southern Ecuador between February and March in 2019. The data were used by Schön et al. (in prep) to evaluate whether leaf traits are valuable indicators of canopy herbivory mainly caused by arthropods and further, whether chemical leaf traits estimated via spectral sensing-based techniques have similar strong relations to herbivory as leaf traits measured conventionally. Herbivory was estimated with the software WinFOLIA ™ 2019a from scanned mature and sun-exposed leaves of tree canopies. Spectral sensing-based leaf traits comprising secondary plant metabolites and both structural and nutritional cell components were estimated from leaves with an OceanOptics spectrometer HDX. Conventionally measured leaf traits comprising morphological and nutritional traits were derived by applying both elemental and morphometrical analyses (e.g., ICP analysis, a digital micrometer and penetrometer). For detailed descriptions of the methodology see Schön et al. (in prep), Homeier et al. (2021), and Limberger et al. (2021). Research was conducted by the subprojects A1, B1, and B4 within the framework of the RESPECT project (Environmental changes in biodiversity hotspot ecosystems of South Ecuador: RESPonse and feedback effECTs) funded by the DFG with the grant numbers: BE1780/51-1, BE1780/51-2, Ho3296/6-1, FA 925/11-1, FA 925/11-2, FA 925/16-1, BR1293/17-1.

openCC (other)Aug 2024View details →
edi44/100

Alaskan Peatland Experiment: Community structure and productivity data for 2007-2010 VI - Tree Biomass and NPP

This dataset contains both tree biomass and net primary productivity for Picea mariana (living and standing dead) within the bog of the Alaskan Peatland Experiment as measured in the fall of 2010. Plot within the bog include a plot established within the lowland black spruce permafrost plateau (permafrost), and two plots established within collapse scars embedded within the plateau. One collapse scar formed ~ 45 years ago (old collapse) and the other formed ~ 25 years ago based upon aerial photography provided by the BCEF LTER. The data provided in this data set can be sorted by site and plot.

openOpenAug 2011View details →
zenodo40/100

Figure 3 in Changes in a soil microarthropod community in the vicinity of dominant tree species under trampling management at the Safari Zoological Center, Israel

Figure 3 The taxon richness, Shannon index, Simpson index, and Evenness index (mean ± SD) of soil Acari at different treatment sites at the Safari Zoological Center, Israel, December 2013. OE = open places under enclosure, OT = open places under trampling; EE = E. camaldulensis canopy habitat under enclosure, ET =E. camaldulensis canopy habitat under trampling, TE =T. aphylla canopy habitat under enclosure, TT =T. aphylla canopy habitat under trampling, CE =C. sempervirens canopy habitat under enclosure, CT =C. sempervirens canopy habitat under trampling. Different letters represent significance at p&lt;0.05.

opencc-by-4.0Jan 2019View details →
zenodo40/100

Figure 2 in Changes in a soil microarthropod community in the vicinity of dominant tree species under trampling management at the Safari Zoological Center, Israel

Figure 2 The abundance (individuals per 10 g dry soil substrate; mean ± SD) of soil microarthropod taxa extracted from core samples at different treatment sites at the Safari Zoological Center, Israel, December 2013. OE = open places under enclosure, OT = open places under trampling; EE =E. camaldulensis canopy habitat under enclosure, ET =E. camaldulensis canopy habitat under trampling, TE = T. aphylla canopy habitat under enclosure, TT =T. aphylla canopy habitat under trampling, CE = C. sempervirens canopy habitat under enclosure, CT =C. sempervirens canopy habitat under trampling. Different letters within the same group represent significance at p&lt;0.05.

opencc-by-4.0Jan 2019View details →
zenodo40/100

Figure 1 in Changes in a soil microarthropod community in the vicinity of dominant tree species under trampling management at the Safari Zoological Center, Israel

Figure 1 Location of study sites at the Safari Zoological Center, Israel. OE = open places under enclosure, OT = open places under trampling; EE =E. camaldulensis canopy habitat under enclosure, ET = E. camaldulensis canopy habitat under trampling, TE =T. aphylla canopy habitat under enclosure, TT = T. aphylla canopy habitat under trampling, CE =C. sempervirens canopy habitat under enclosure, CT = C. sempervirens canopy habitat under trampling.

opencc-by-4.0Jan 2019View details →
zenodo40/100

Figure 2 in Epiphytic Bryophyte And Lichen Communities In Relation To Tree And Forest Stand Variables In Populus Tremula Forests Of South-East Latvia

Figure 2. Epiphytic bryophyte and lichen species in the studied territories. Tade Micr – Microreserve in Tadenava, Augs land – Augšzeme Protected Landscape Area, Star Rese – Starinas mežs Nature Reserve. Signal species include all WKH indicator species and red-listed species.

opencc-by-4.0Dec 2010View details →
zenodo40/100

Figure 1. Studied territories. 1 in Epiphytic Bryophyte And Lichen Communities In Relation To Tree And Forest Stand Variables In Populus Tremula Forests Of South-East Latvia

Figure 1. Studied territories. 1 – Microreserve in Tadenava, 2– Augšzeme Protected Landscape Area, 3 – Starinas mežs Nature Reserve.

opencc-by-4.0Dec 2010View details →
dryad40/100

Functional biogeography of Neotropical moist forests: trait-climate relationships and assembly patterns of tree communities

<p>Aim: Here we examine the functional profile of regional tree species pools across the latitudinal distribution of Neotropical moist forests, and test trait-climate relationships among local communities. We expected opportunistic strategies (acquisitive traits, small seeds) to be overrepresented in species pools further from the equator due to long-term instability, but also in terms of abundance in local communities in currently wetter, warmer and more seasonal climates.</p> <p>Location: Neotropics.</p> <p>Time period: Recent.</p> <p>Major taxa studied: Trees.</p> <p>Methods: We obtained abundance data from 471 plots across nine Neotropical regions, including ~100,000 trees of 3,417 species, in addition to six functional traits. We compared occurrence-based trait distributions among regional species pools, and evaluated single trait-climate relationships across local communities using community abundance-weighted means (CWM). Multivariate trait-climate relationships were assessed by a double-constrained correspondence analysis that tests both how CWMs relate to climate and how species distributions, parameterized by niche centroids in climate space, relate to their traits.</p> <p>Results: Regional species pools were undistinguished in functional terms, but opportunistic strategies dominated local communities further from the equator, particularly in the northern hemisphere. Climate explained up to 57% of the variation in CWM traits, with increasing prevalence of lower-statured, light-wooded and softer-leaved species bearing smaller seeds in more seasonal, wetter and warmer climates. Species distribution were significantly but weakly related to functional traits.</p> <p>Main conclusions: Neotropical moist forest regions share similar sets of functional strategies, from which local assembly processes, driven by current climatic conditions, select for species with different functional strategies. We can thus expect functional responses to climate change driven by changes in relative abundances of species already present regionally. Particularly, equatorial forests holding the most conservative traits and large seeds are likely to experience the most severe changes if climate change triggers the proliferation of opportunistic tree species.</p>

opencc-zeroDec 2020View details →
zenodo40/100

Data from: Temporal changes in taxonomic and functional alpha and beta diversity across tree communities in subtropical Atlantic forests

<h2><strong>The study is published in Oikos and available at:&nbsp;<a href="https://doi.org/10.1111/oik.10961">https://doi.org/10.1111/oik.10961</a></strong></h2> <p>Here we aim to assess temporal taxonomic and functional alpha and beta diversity of adult and juvenile tree communities across 11 sites in the subtropical Brazilian Atlantic Forest to infer about trends and drivers of biodiversity change. The tree communities were evaluated for temporal changes in: (1) taxonomic and functional alpha diversity, (2) taxonomic and functional composition (beta diversity), and (3) identifying potential abiotic and biotic drivers of these changes, considering three censuses across a period of 10 years.</p> <p>&nbsp;</p> <h2>Files description:</h2> <p><strong>traits-adults.csv</strong> - adult tree species and their functional traits values.</p> <p><strong>traits-juveniles.csv</strong> - juvenile tree species and their functional trait values.</p> <p><strong>abundance-adults_synthesis.csv</strong> - adult tree species abundance over the three time periods of forest surveys (T1, T2, and T3).&nbsp;Raw data on tree individual level is available at ForestPlots.net database (<a href="https://forestplots.net/">https://forestplots.net/</a>) under request.</p> <p><strong>abundance-juveniles_synthesis.csv</strong> - juvenile tree species abundance over the three time periods of forest surveys (T1, T2, and T3). Raw data on tree individual level is available at ForestPlots.net database (<a href="https://forestplots.net/">https://forestplots.net/</a>) under request.</p> <p>Functional traits abbreviations are defined as follows: LA = leaf area; SLA = specific leaf area; WD = wood density; SM = seed mass; range_temp = range of mean annual temperature; range_CWD = range of climatological water deficit; and biomes_distrib = number of Brazilian biomes that the species occur according to Flora and Funga do Brazil.</p> <p>&nbsp;</p> <h2><strong>Acknowledgments</strong></h2> <p>This study was financed in part by the Coordena&ccedil;&atilde;o de Aperfei&ccedil;oamento de Pessoal de N&iacute;vel Superior &ndash; Brazil (CAPES) &ndash; Finance Code 001, through Portal de Peri&oacute;dicos and scholarships granted to JMFK, JK and RCP. The fieldwork was supported by Funda&ccedil;&atilde;o de Amparo &agrave; Pesquisa do Estado do Rio Grande do Sul (FAPERGS grant numbers 2218 &ndash; 2551/12-2 and 19/2551-0001698-0), Conselho Nacional de Desenvolvimento Cient&iacute;fico e Tecnol&oacute;gico (CNPq/FAPERGS/PELD number 441590/2020-9), and the Instituto Nacional de Ci&ecirc;ncia e Tecnologia (INCT) in Ecology, Evolution and Biodiversity Conservation, supported by MCTIC/CNPq (grant number 465610/2014-5). KMB gratefully acknowledge the financial support by the National Institute of Science and Technology in Low Carbon Emission Agriculture (INCT-ABC) sponsored by Brazil&rsquo;s National Council for Scientific and Technological Development (CNPq, grant no. 406635/2022-6), the Foundation for Research Support of the State of Rio Grande do Sul (Fapergs, grant no. 22/2551-0000392-3), and the Ministry of Agriculture (MAPA). SCM is supported by Conselho Nacional de Desenvolvimento Cient&iacute;fico e Tecnol&oacute;gico (CNPq; grant number 309659/2019-1.</p> <p>&nbsp;</p> <h3><strong>Please find below the data used in the study.</strong></h3>

opencc-by-4.0Feb 2024View details →
zenodo40/100

FIGURE 6. Classification Tree results and predictions for the five fossil localities. A in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)

FIGURE 6. Classification Tree results and predictions for the five fossil localities. A) Results and predictions for CT1, vegetative cover. B) Results and predictions for CT2, biogeographic realm. Abbreviations: LV, La Venta; QH, Quebrada Honda; RU, Rümikon; SC, Santa Cruz; TG, Tinguiririca.

opencc-by-4.0Dec 2020View details →
zenodo40/100

Figure 2 in Changes in galling insect community on Caryocar brasiliense trees mediated by soil chemical and physical attributes

Figure 2. Principal components regressions among: (A) Eurytoma sp. galling insect adults (Eur.) with phosphorus-Mehlich 1 (mg dm-3) contents (P.C.) and silt (dag kg-1) (Si.); (B) numbers of Eurytoma sp. glodoid galls (E.G.G.) with pH in water, capacity of cationic exchange (cmol dm-3) (C.C.E.), and P.C.; (C) area (mm2) of Eurytoma sp. glodoid galls (A.E.G.) with pH and clay (dag kg-1) (Cl.); (D) c length of conglomerate of Eurytoma sp. globoid galls (L.G.E.) with pH and Cl.; (E) width of conglomerate of Eurytoma sp. globoid galls (W.G.E.) with pH and Cl.; and (F) number of Hymenopteran discoid galls (H.D.G.) with aluminum (cmol dm-3) contents (A.C.), C.C.E., c and percentage of soil base saturation of the capacity of cationic exchange to pH 7.0 (S.B.S.) on Caryocar brasiliense trees in three years. The symbols represent the averages and the bars the standard errors. n = 111.

opencc-by-4.0Dec 2022View details →
zenodo40/100

Figure 1 in Changes in galling insect community on Caryocar brasiliense trees mediated by soil chemical and physical attributes

Figure 1. Principal components regressions among: (A) abundance of galling insects (A.G.I.) with phosphorus-Mehlich 1 (mg dm-3) contents (P.C.) and sand (dag kg-1) (Sa.); (B) species richness of galling insects (S.R.G.I.) with capacity of cationic exchange (cmol dm-3) c (C.C.E.); (C) diversity of galling insects (D.G.I.) with C.C.E. and Sa.; (D) percentage of galled leaflet by all galls (P.G.L.) with pH in water and clay (dag kg-1) (Cl.); and (E) percentage of leaflet area taken by all galls (P.L.A.G.) with aluminum (cmol dm-3) contents (A.C.) and c C.C.E. on Caryocar brasiliense trees in three years. The symbols represent the averages and the bars the standard errors. n = 111.

opencc-by-4.0Dec 2022View details →
zenodo40/100

Figure 4 in Changes in galling insect community on Caryocar brasiliense trees mediated by soil chemical and physical attributes

Figure 4. Principal components regressions among: (A) abundance of predators (A.Pr.) with phosphorus-Mehlich 1 (mg dm-3) contents (P.C.) and clay (dag kg-1) (Cl.); (B) species richness of predators (S.R.Pr.) with number of Hymenoptera discoid galls (H.D.G.), species richness of parasitoids (S.R.P.), and Cl.; (C) diversity of predators (D.Pr.) with diversity of parasitoids (D.P.) and Cl.; (D) number of Zelus armillatus (Zar.) with P.C., percentage of soil base saturation of the capacity of cationic exchange to pH 7.0 (S.B.S.), silt (dag kg-1) (Si.), numbers of Eurytoma sp. glodoid galls (E.G.G.), and capacity of cationic exchange (cmol dm-3) (C.C.E.); (E) number of Epipolops sp. (Epi.) c with protocooperanting ants (Ants), Cl., and pH in water; and (F) number of spiders (Spi.) with Ants, P.C., and Si. on Caryocar brasiliense trees in three years. The symbols represent the averages and the bars the standard errors. n = 111.

opencc-by-4.0Dec 2022View details →
zenodo40/100

Figure 2 in Edaphic characteristics and environmental impact of rubber tree plantations on soil mite (Acari) communities

Figure 2 Abundance logarithmic transformation – logx (+1) of Gamasida (A) and Oribatida (B) major groups across the land use types. SF: secondary forests, R7: 7-year-old rubber plantations, R12: 12- year-old rubber plantations, R25: 25-year-old rubber plantations. N = 120; one-way ANOVA test,p

opencc-by-4.0Nov 2018View details →

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Last verified 2026-04-30Open record

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Last verified 2026-04-30Open record

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dandi-nwb
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Last verified 2026-04-30Open record

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Last verified 2026-04-29Open record

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openneuro
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Last verified 2026-04-29Open record