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430 results for “Forest Structure”

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zenodo32/100

Figure 3 in Structure of insect community in the fungus Inonotus radiatus in riparian boreal forests

Figure 3. Species accumulation curves (and 95% confidence intervals) in Inonotus radiatus samples of different decay stages. The curves for fresh decay stages (n = 16 samples) and advanced decay stages (n = 36) have been extrapolated to a common sample size of 49 samples with both living and dead basidiomes (i.e. mixed). Only taxa that were considered to breed in the basidiomes were included.

opennotspecifiedMar 2016View details →
dryad32/100

Fire alters diversity, composition and structure of dry tropical forests in the Eastern Ghats

<p>Fire is known to have dramatic consequences on forest ecosystems around the world, and on the livelihoods of forest-dependent people. While the Eastern Ghats of India have high abundances of fire-prone dry tropical forests, little is known about how fire influences the diversity, composition and structure of these communities. Our study aims to fill this knowledge gap by examining the effects of presence and absence of recent fire on tropical dry forest communities within Kadiri watershed, Eastern Ghats. We sampled plots with and without evidence of recent fire in the Eswaramala Reserve Forest in 2008 and 2018. Our results indicate that even though stem density increases in the recently burned areas, species richness is lower because communities become dominated by a few species with fire resistance and tolerance traits, such as thick bark and clonal sprouting. Further, in the presence of fire, the size structure of these fire-tolerant species shifts towards smaller-sized, resprouting individuals. Our results demonstrate that conservation actions are needed to prevent further degradation of forests in this region and the ecosystem services they provide.</p>

opencc-zeroMar 2022View details →
zenodo32/100

Fig. 1 in How Do Regeneration Stages of Caatinga Forests Influence the Structure of Dung Beetle (Coleoptera: Scarabaeidae) Assemblage?

Fig. 1. Location in Brazil (A) and aerial view (B) of Tamanduá Farm with plots of the sampling sites (INI = initial stage of regeneration; INT = intermediate; LAT = late), Para´ıba, northeastern Brazil.

opennotspecifiedSep 2017View details →
zenodo32/100

Fig. 3 in How Do Regeneration Stages of Caatinga Forests Influence the Structure of Dung Beetle (Coleoptera: Scarabaeidae) Assemblage?

Fig. 3. Species abundance rank of dung beetles obtained in initial, intermediate and late fragments of Caatinga on Tamanduá Farm, Para´ıba, Brazil.

opennotspecifiedSep 2017View details →
zenodo32/100

Fig. 2 in How Do Regeneration Stages of Caatinga Forests Influence the Structure of Dung Beetle (Coleoptera: Scarabaeidae) Assemblage?

Fig. 2. General linear models characterizing dung beetle abundance (A, C, E) and richness (B, D, F) in three Caatinga regeneration stages with two bait types and in two seasonal periods in Caatinga fragments on Tamanduá Farm, Para´ıba, Brazil.

opennotspecifiedSep 2017View details →
dryad32/100

Scavenger community structure along an environmental gradient from boreal forest to alpine tundra in Scandinavia

<p>Scavengers can have strong impacts on food webs, and awareness of their role in ecosystems have increased during the last decades. In our study, we used baited camera traps to quantify the structure of the winter scavenger community in central Scandinavia across a forest-alpine continuum and assess how climatic conditions affected spatial patterns of species occurrences. Canonical correspondence analysis revealed that the main habitat type (forest or alpine tundra) and snow depth were main determinants of community structure. According to hierarchical modelling of the species community, species richness was higher in forest than in alpine habitat but was only weakly associated with temperature and snow depth. However, we observed stronger and more diverse impacts of these covariates on individual species. Occurrence at baits of habitat generalists (red fox, golden eagle and common raven) typically increased at low temperatures and high snow depth, probably due to increased energetic demands and lower live prey availability in harsh winter conditions. On the contrary, occurrence of forest specialists (e.g. Eurasian jay) tended to decrease in deep snow, which is possibly a consequence of reduced bait detectability and accessibility. In general, the influence of environmental covariates on species richness and occurrence was lower in alpine tundra than in forests, and habitat generalists dominated the scavenger communities in both habitat types. Following forecasted climate change, altered environmental conditions is likely to cause range expansion of boreal species and range contraction of typical alpine species such as the arctic fox. Our results suggest that altered snow conditions will be a main driver of change.</p>

opencc-zeroSep 2021View details →
dryad32/100

The trajectories of vegetative structure and soil microbial function diverged across a fire chronosequence of the boreal forests in Northeast China

<p>The role of boreal forest to ameliorate the effect of global climate change largely depends on the regeneration of postfire forests in northeast China. The postfire recovery of boreal forest can be evaluated by the aboveground vegetative structure and soil microbial function. In present study, a 50-year fire chronosequence was established, and the biomass of forbs, shrub and woody plant was separately weighted to assess their contribution to the whole community with the year since fire (YSF). Simultaneously, soil biophysical properties were measured for stands in different time period after fire. Soil microbial functions, i.e., growth efficiency (GE) and carbon use efficiency (CUE), were calculated basing on ecoenzymatic and soil nutrient stoichiometry. In terms of vegetative structure, forbs' proportion decreased from 75% to 1.5%, but the proportion of woody plant increased from 0.04% to 70% across this fire chronosequence. In contrast, soil microbial function reached the highest value in 15 YSF and then began to decrease. As an important variable, soil metal content, particularly the calcium content, showed a positive correlation with woody plant biomass and a negative with soil microbial function. Furthermore, soil metal content was significantly increased in the late stage of this fire chronosequence. Overall, the present work highlighted that the time period of 15 YSF and 31 YSF was a hallmark stage for aboveground vegetative structure and soil microbial function to change in different trends, and the calcium content may partly account for these two divergent trajectories.</p>

opencc-zeroOct 2021View details →
zenodo32/100

Data set of 1) plant abundance in the herb layer and 2) Shrub and tree composition and structure following forest management along a chronosequence

<p>In each site (1200 m&sup2;), three circular plots (400 m&sup2;) were established (total of 198 plots).&nbsp;Data presented here for 1) plant&nbsp;of the herb layer and 2) shrub and tree are grouped by site (addition of three plots).&nbsp;</p> <p>In the herb layer, total plant species identity and abundance (percentage cover) were sampled in each plot using eight circular micro-plots of 4 m&sup2;.&nbsp;Data were collected in 2016 and 2017, between June and August. To minimize seasonal variability and allow detection of early spring species, plants (identity and abundance) in the herb layer were measured twice (once in June to early-July, and once in late-July to August).</p> <p>For tree, in each plot, species identity, diameter at breast height (DBH, 1.3 m) and locations of each tree &gt; 9.1 cm DBH were determined. In each plot, species identity and DBH of shrubs and small trees (DBH range: 1.1&nbsp;to 9.1 cm) were measured in three circular micro-plots of 25 m&sup2;. Data that were related to the shrub-canopy layer included all trees and shrubs with DBH &gt; 1.1 cm. Here, in each site, forest composition and structure&nbsp;is represented by&nbsp;different combinations of DBH classes (1.1-4 cm, 4-9.1 cm, 9.1-20 cm, 20-35 cm, &gt;35 cm) and species.</p> <p>Plant community composition and abundance were assessed in unmanaged forests (sites of old-growth forest &gt; 100 years, with dominant and co-dominant trees older than 200 years, and no obvious sign of past harvesting), and in even-aged&nbsp;and uneven-aged managed forests along a chronosequence (&lt; 5 years, 15 years, 30 years after forest harvesting).</p>

opencc-by-4.0Oct 2021View details →
zenodo32/100

Population structure and genetic variation of fragmented mountain birch forests in Iceland

<p>Data avilability for the manuscript JOH-2022-096.R2 accepted for application</p>

opencc-by-4.0Oct 2022View details →
zenodo32/100

Figure 1 in Effect of habitat structure on abundance and body conditions of two sympatric geckos, Cyrtodactylus saiyok and Cyrtodactylus tigroides, in the karst forest of western Thailand

Figure 1. Study site in Wang Krajae Sub-district, Sai Yok District, Kanchanaburi Province, Western Thailand (red circle).

opennotspecifiedMar 2023View details →
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Figure 4 in Effect of habitat structure on abundance and body conditions of two sympatric geckos, Cyrtodactylus saiyok and Cyrtodactylus tigroides, in the karst forest of western Thailand

Figure 4. Non-metric multidimensional scaling (NMDS) diagram representing the microhabitat distances of Cyrtodactylus saiyok (SA, black circles) and Cyrtodactylus tigroides (TI, red crosses).

opennotspecifiedMar 2023View details →
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Figure 3 in Effect of habitat structure on abundance and body conditions of two sympatric geckos, Cyrtodactylus saiyok and Cyrtodactylus tigroides, in the karst forest of western Thailand

Figure 3. Microhabitat variables that affect Cyrtodactylus occurrence: (a) canopy cover; (b) limestone karst; (c) shrub; (d) bamboo.

opennotspecifiedMar 2023View details →
zenodo32/100

Short-Term Effects of Moderate Severity Disturbances on Forest Canopy Structure- Derived Data

<p>NEON plot-level derived tables used in this study. All the derived data were openly available from&nbsp;The National Science Foundation&#39;s National Ecological Observatory Network (NEON).</p> <ul> <li>01: R codes for 01) LiDAR-derived canopy metrics calculation; 02) Modelling</li> <li>02: Input ground survey data with removed duplicate rows (tree_rm_duplicates.csv); CSV files - NEON vegestructure data (disturbance_structural_diversity_data_2022_1109_den4.csv)</li> </ul> <p>All NEON&rsquo;s Discrete return LiDAR point cloud (DP1.30003.001) (NEON 2021a) and Vegetation structure (DP1.10098.001) (NEON 2022) data are available on NEON data portal as follows: <a href="https://data.neonscience.org/data-products/DP1.30003.001">https://data.neonscience.org/data-products/DP1.30003.001</a> (<a href="https://doi.org/10.48443/6E8K-3343">https://doi.org/10.48443/6E8K-3343</a>), and <a href="https://data.neonscience.org/data-products/DP1.10098.001/RELEASE-2022">https://data.neonscience.org/data-products/DP1.10098.001/RELEASE-2022</a> (<a href="https://doi.org/10.48443/RE8N-TN87">https://doi.org/10.48443/RE8N-TN87</a>), respectively.</p> <p>R scripts for calculating canopy metrics (Hardiman et al. 2021) are available on Environmental Data Initiative (EDI): <a href="https://doi.org/10.6073/pasta/97f8092c10aecbc62aec12557ecb52bd">https://doi.org/10.6073/pasta/97f8092c10aecbc62aec12557ecb52bd</a></p> <p>&nbsp;</p> <p>Reference</p> <ul> <li>Hardiman, B.S., E.A. LaRue, J.R. Foster, R. Fahey, and J. Hatala Matthes. 2021. Forest structural diversity at NEON sites in the continuous USA that experienced recent moderate disturbance ver 1. Environmental Data Initiative. https://doi.org/10.6073/pasta/97f8092c10aecbc62aec12557ecb52bd (Accessed 2023-05-24).</li> <li>NEON. 2021a. Discrete return LiDAR point cloud (DP1.30003.001). National Ecological Observatory Network (NEON). doi: <a href="https://doi.org/10.48443/6E8K-3343">https://doi.org/10.48443/6E8K-3343</a>.</li> <li>NEON. 2022. Vegetation structure (DP1.10098.001). National Ecological Observatory Network (NEON). doi: <a href="https://doi.org/10.48443/RE8N-TN87">https://doi.org/10.48443/RE8N-TN87</a>.</li> </ul>

opencc-by-4.0May 2023View details →
zenodo32/100

Monitoring programme on strict forest reserves in Flanders (Belgium) - site level stand structure, regeneration and vegetation data

<p>This dataset contains comprehensive statistics on stand structure, rejuvenation, and vegetation for each forest reserve included in the monitoring program on strict forest reserves in Flanders (Belgium). The data collection and processing methodology used are described in <a href="https://purews.inbo.be/ws/portalfiles/portal/41050863/Vandekerkhove_etal_2021_MonitoringProgrammeOnStrictForestReservesFlanders.pdf">Vandekerkhove et al., 2021</a>.</p> <p>The dataset encompasses information on 15 distinct strict forest reserves and covers one to three consecutive forest inventories following a 10-year cycle.&nbsp;</p> <p>The &quot;<strong>site_info.xlsx</strong>&quot; file provides details on the 15 sites, including central coordinates, surface area, forest type, and the year when they were set aside. For detailed descriptions of the information provided, please refer to the &quot;<strong>_metadata_site_info.xlsx</strong>&quot; file.</p> <p>The &ldquo;<strong>statistics_per_reserve.zip</strong>&rdquo; file contains 12 separate csv-files with the following data:</p> <ul> <li> <p><strong>stat_dendro(_by)(_diam)(_species).csv</strong> : statistics on basic stand structure attributes (volume, basal area, number of trees per hectare, &hellip;) for living and dead standing trees (DBH-threshold 5cm): overall values and values per diameter class and/or species&nbsp;</p> </li> <li> <p><strong>stat_carbon.csv </strong>: statistics on biomass and carbon stock related to living trees</p> </li> <li> <p><strong>stat_logs(_by)(_decay)(_species).csv</strong> : statistics on volume per hectare of lying deadwood: values per decay stage and/or species&nbsp;</p> </li> <li> <p><strong>stat_reg(_by)(_height)(_species).csv</strong> : statistics on rejuvenation (numbers per ha of young trees - seedlings up to trees with DBH&lt; 5cm): overall values and values per heightclass and/or species&nbsp;</p> </li> <li> <p><strong>stat_veg.csv</strong> : statistics on vegetation characteristics, including number of species, moss, herb, shrub, tree and waterlayer cover, cumulated canopy cover and soil disturbance by game</p> </li> <li> <p><strong>stat_herbs.csv</strong> : species-specific mean cover, percentage of plots where each species occurs</p> </li> </ul> <p>For descriptions of the common fields used in the above csv-files, please consult the &quot;<strong>_metadata_statistics.xlsx</strong>&quot; file.&nbsp;</p> <p>For detailed and comprehensive information regarding the meaning and characteristics of the calculated variables, please refer to the &quot;<strong>_metadata_variables.xlsx</strong>&quot; file.&nbsp;</p> <p>Plot-level results regarding dendrometry and regeneration are published separately<a href="https://zenodo.org/record/7588680"> here</a>, while information on vegetation can be found<a href="https://zenodo.org/record/7870740"> here</a>.</p> <p><strong>For any inquiries or further information, please contact Kris.vandekerkhove@inbo.be or Anja.leyman@inbo.be</strong>. The provided csv-files will be updated as required to address any issues or include data from additional surveys. . Please check for updated versions periodically.</p> <p><strong>We ask the users of the dataset to notify us of its use.</strong></p>

opencc-by-4.0Jun 2023View details →
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An evaluation of isolation by distance (IBD) and isolation by resistance (IBR) on genetic structure of the Persian squirrel (Sciurus anomalus) in the Zagros forests of Iran

<p>For conservation of wild species, it is important to understand how landscape change and land management can affect gene flow and movement. Landscape genetic analyses provide a powerful approach to infer effects of various landscape factors on gene flow, thereby informing conservation actions. The Persian squirrel is a keystone species in the woodlands and oak forests of Western Asia, where it has experienced recent habitat loss and fragmentation. We conducted landscape genetic analyses of individuals sampled in the northern Zagros Mountains of Iran (provinces of Kurdistan, Kermanshah, and Ilam), focusing on evaluation of isolation by distance (IBD) and isolation by resistance (IBR), using 16 microsatellite markers. The roles of geographical distance and landscape features including roads, rivers, developed areas, farming and agriculture, forests, lakes, plantation forests, rangelands, shrublands and rocky areas of varying canopy cover, and swamp margins on genetic structure were quantified using individual-based approaches and resistance surface modelling. We found a significant pattern of IBD but only weak support for an effect of forest cover on genetic structure and gene flow. It seems that geographical distance is an important factor limiting the dispersal of the Persian squirrel in this region. The results of the current study inform ongoing conservation programs for the Persian squirrel in the Zagros oak forest.</p>

opencc-zeroJun 2023View details →
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The legacies of land-clearance and trophic downgrading accumulate to affect structure and function of kelp forests

Open the record for dataset details and reuse information.

publicSep 2022View details →
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Data from: The effect of habitat fragmentation on the genetic structure of a top predator: loss of diversity and high differentiation among remnant populations of Atlantic Forest jaguars (Panthera onca)

Open the record for dataset details and reuse information.

publicAug 2010View details →
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Data from: Tropical forests structure and diversity: a comparison of methodological choices

Open the record for dataset details and reuse information.

publicJul 2021View details →
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Data from: Cryptic diversity and population genetic structure in the rare, endemic, forest-obligate, slender geckos of the Philippines

Open the record for dataset details and reuse information.

publicOct 2013View details →
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Data from: Geographic population structure of the African malaria vector Anopheles gambiae suggests a role for the forest-savannah biome transition as a barrier to gene flow

Open the record for dataset details and reuse information.

publicMay 2013View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record