Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
201
datasets available to search
ShareScore release 0.9.0
Dataset results
201 results for “mixed forest”
Variations in tree growth provide limited evidence of species mixture effects in Interior West U.S.A. mixed-conifer forests
<p>1. In mixed stands, species complementarity (e.g., facilitation and competition reduction) may enhance forest tree productivity. Although positive mixture effects have been identified in forests worldwide, the majority of studies have focused on two-species interactions in managed systems with high functional diversity. We extended this line of research to examine mixture effects on tree productivity across landscape-scale compositional and environmental gradients in the low functional diversity, fire-suppressed, mixed-conifer forests of the U.S. Interior West.</p> <p>2. We investigated mixture effects on the productivity of <i>Pinus ponderosa</i>, <i>Pseudotsuga menziesii</i>, and <i>Abies concolor</i>. Using region-wide forest inventory data, we created individual-tree generalized linear mixed models and examined the growth of these species across community gradients. We compared the relative influences of stand structure, age, competition, and environmental stress on mixture effects using multi-model inference. We analyzed growth of neighboring tree species to infer whether a mixture effect in a single species translated to the stand-level.</p> <p>3. We found support for a positive mixture effect in <i>P. menziesii</i>, although our results were equivocal in light of a weaker but still plausible alternative model. Growth of <i>P. menziesii</i> neighboring species in mixed stands declined or held constant depending on aridity, suggesting that a positive mixture effect in <i>P. menziesii</i> does not necessarily extend to the stand level. We found no evidence for mixture effects in <i>P. ponderosa</i>, <i>A. concolor</i> or their neighboring species.</p> <p>4. Complementarity appears to have a limited influence on tree growth in the mixed-conifer systems of the U.S. Interior West, reflecting limited functional diversity. Historical changes in stand structure following fire exclusion, particularly high stand densities, may limit the potential for positive species mixture effects. The limited species pool of Interior West forests increases the risk that, without careful management, what functional diversity exists could be lost to compositional changes resulting from stand dynamics or disturbance.</p>
Data from: Thinning and prescribed burning increase shade-tolerant conifer regeneration in a fire excluded mixed-conifer forest
<p>Fire exclusion and past management have altered the composition, structure, and function of frequent-fire forests throughout western North America. In mixed-conifer forests of the California Sierra Nevada, fire exclusion has exacerbated the effects of drought and endemic bark beetles, resulting in extensive mortality of fire-adapted pine species. Thinning and prescribed fire are widely used in these forests to reduce fuels, moderate fire behavior, and restore ecosystems. Tree regeneration influences future forest composition and structure, and therefore future resilience to disturbances, but long-term effects of thinning and prescribed burning on tree regeneration after prolonged fire exclusion are poorly understood. We measured tree regeneration one year prior to, and periodically for 16 years following thinning and prescribed burning in a mixed-conifer forest in the Sierra Nevada, California, USA. We asked three questions. How did the composition and density of tree regeneration change after thinning and prescribed burning? Did pretreatment vegetation types influence conifer regeneration density after treatments? Did planting after overstory thinning increase regeneration density of native pine species?</p> <p>Sixteen years after treatments, combined natural regeneration of shade-tolerant white fir (Abies concolor) and incense-cedar (<em>Calocedrus</em> <em>decurrens</em>) averaged 2,032 trees per hectare (tph) after understory thinning, and 7,745 tph after understory thinning combined with prescribed burning, increases of 37% and 146% from pretreatment densities. In contrast, combined natural regeneration of white fir and incense-cedar averaged 497 tph after overstory thinning, 780 tph after overstory thinning with prescribed burning, 113 tph after prescribed burning alone, and 807 tph in untreated controls, all of which were declines from pretreatment densities. Natural regeneration of white fir and incense-cedar was consistently an order of magnitude greater than Jeffrey pine (<em>Pinus</em> <em>jeffreyi</em>) and sugar pine (<em>Pinus</em> <em>lambertiana</em>), whose combined densities 16 years after treatments averaged 37 tph across treatments and did not significantly respond to thinning and/or prescribed burning. Natural conifer regeneration after treatments varied by pre-treatment vegetation type (closed canopy, <em>Ceanothus</em> <em>cordulatus</em> shrub-dominated, and open sparse), with large increases of natural regeneration after understory thinning in closed canopy and <em>Ceanothus</em> shrub vegetation types. Planting increased sugar pine regeneration density after overstory thinning, marginally increased Jeffrey pine regeneration after overstory thinning combined with prescribed burning, and increased white fir regeneration after overstory thinning with and without burning. No treatments reduced white fir and incense-cedar natural regeneration while simultaneously increasing natural pine regeneration, suggesting new thinning, burning, and planting approaches may be required to meet regeneration restoration objectives.</p>
Data for: Specialist carabids in mixed montane forests are positively associated with biodiversity-oriented forestry and abundance of roe deer
<p>The ongoing transition within forest management towards more biodiversity-oriented practices, such as close-to-nature forestry and retention forestry, may benefit forest fauna such as forest-specialized ground beetles (Coleoptera: Carabidae). However, it remains unclear how forest carabids are jointly affected by these practices in Central European montane forests, which host particularly sensitive, range-restricted carabid species, and where biodiversity-oriented forestry is widely applied. Moreover, roe deer (<em>Capreolus capreolus</em>), the most common large herbivore in these forests, is intensively managed to reduce browsing pressure, but it is yet unknown how this may affect carabids, alongside the effect of silviculture. On 66 1-ha plots in the Black Forest region of Germany, we sampled carabids with pitfall traps, measured roe deer abundances using camera trapping, and measured several structural variables directly related to close-to-nature and retention practices, as well as variables describing microclimate and landscape-level forest cover. We found that the carabid assemblage was dominated by forest specialists, with little influence from fragmentation of the surrounding forest. Higher broadleaf share (and canopy cover for montane specialists) was correlated with higher carabid activity-density. Increasing stand maturity (and lying deadwood volume for montane specialists), was correlated with higher species richness. Plots with higher roe deer abundances showed higher carabid richness and activity-density. Assemblage composition changed along the altitudinal gradient, and both richness and activity-density increased with elevation. Thus, carabid communities, including montane specialists and several species of conservation interest, stand to benefit from close-to-nature and retention practices, if applied throughout the altitude range of montane forests. Forest carabids may additionally profit from maintaining higher roe deer abundances, but further research is needed to understand this causal link, as well as to weigh the costs and benefits of deer culling for forest biodiversity.</p>
Mapping Tree Species Fractions in Temperate Mixed Forests Using Sentinel-2 Time Series and Synthetically Mixed Training Data
<p>This dataset contains the latest version of a selection of result data of the paper "Mapping Tree Species Fractions in Temperate Mixed Forests Using Sentinel-2 Time Series and Synthetically Mixed Training Data" (DOI: https://doi.org/10.1016/j.rse.2025.114740 )</p> <p>The dataset contains:</p> <ol> <li>A geopackage of training points of pure tree species</li> <li>The resulting 12-band tree species fraction map of Rhineland-Palatinate</li> <li>HSV-colored map of dominant tree species. For information which tree species are represented by the different colors, refer to the Supplemental in the original paper.</li> <li>CSV-table of predicted and reference propotion of the tree species in the validation polygon (the original polygon data can not be published due to data privacy regulations) </li> </ol> <p> </p>
A dataset of bird assemblages in different successional pathways– a comparative study in hemiboreal mixed forests
<p><strong>Abstract:</strong></p> <p><strong>Context </strong>The most productive forest lands have naturally the richest bird assemblages but tend to be also most intensively managed. Sustainable solutions to this conflict are unclear.</p> <p><strong>Aim </strong>To assess bird assemblages and their successional dynamics in planted Norway spruce (<em>Picea abies </em>L.) stands compared to naturally developing stands.</p> <p><strong>Methods </strong>We mapped breeding bird assemblages in forty 5-ha plots on highly productive soils in Estonia. The plots included sets of naturally regenerated and planted stands, and (as successional endpoints) clear-cuts and old stands.</p> <p><strong>Results </strong>Planted stands had fewer bird species and pairs than naturally regenerated stands; the latter having a species composition resembling late-successional deciduous-dominated stands. Importantly, the species composition in mature spruce plantations converged toward the composition observed in late-successional conifer-dominated stands. Downed dead wood, stand age, deciduous trees, and stock density were the most significant stand characteristics shaping bird assemblages.</p> <p><strong>Conclusion</strong> The habitat value of established spruce plantations can be primarily improved by allowing for some deciduous trees and gaps with deciduous undergrowth. At the landscape scale, the bird diversity of even-aged systems would be enhanced by multi-scale applications of retention forestry – from retention trees to old-growth set-asides.</p> <p> </p> <p> </p> <p>The given dataset includes observations of breeding pairs on all 40 study plots with different management types. Variables explained in supplementary txt file. </p> <p> </p>
Fig. 5 in Helminths Of The Mallard, Anas Platyrhynchos (Aves, Anatidae) In Ukraine: Analysis Of The Diversity In Mixed Forest Zone And The Black Sea Region
Fig. 5. Configuration of 2-dimensional MDS for specimens of Mallard from the mixed forest zone (P) and from the steppe zone (B) with overlapping clusters at similarity level of 15 %.
Fig. 3 in Helminths Of The Mallard, Anas Platyrhynchos (Aves, Anatidae) In Ukraine: Analysis Of The Diversity In Mixed Forest Zone And The Black Sea Region
Fig. 3. Prevalence (with lower and upper confidence intervals at significant level 95 %) and mean intensity (with range; in case when only one or two birds were infected by a certain type of helminth, then the actual intensity values are given) of Mallard´s infection with: A — trematodes from the mixed forest zone; B — trematodes from the steppe zone. * Logarithmic scale was used
Text-fig. 1. Modern vegetation proxies as delivered by the Drudge 1 and 2 tools for Parschlug. Left column results from KovarEder et al. (2021) based on the floristic spectrum published by Kovar-Eder et al. (2004). The other three columns result from three variants using the enlarged floristic spectrum herein. Differences between variants 1–3 from this study are caused by differences in assignment of some taxa and morphotypes (see Appendix 1). European vegetation formations: Formation C – Subarctic, boreal and nemoral-montane open woodlands as well as subalpine and oro-Mediterranean vegetation; Formation D – Mesophytic and hygromesophytic coniferous and mixed broad-leaved-coniferous forests; Formation F – Mesophytic broadleaved deciduous and mixed broadleaved/conifer forests; Formation G – Thermophilous mixed deciduous broadleaved forests; Formation J – Mediterranean sclerophyllous forests and scrub; Formation K – Xerophytic coniferous forests, coniferous woodland and scrub. East Asian vegetation types: MCF China, Japan – Montane Coniferous Forests China, Honshu, Yakushima; BLDF N and NE Provinces, China – Broad-leaved Deciduous Forests of the Northern and Northeastern Provinces (China); BLDF Upper Yangtze, Honshu – Broad-leaved Deciduous Forest, Upper Yangtze Provinces, Mt. Emei, and Honshu; MMF China – Mixed Mesophytic Forest, Lower Yangtze Provinces; BLEF China, Japan – Broad-leaved Evergreen Forests, China, Japan; Meili Snow Mt. high altitude SCL and BLF, China – Meili Snow Mt., Sclerophyllous and broad-leaved forest zone (2,580-3,650 m alt.). (Designations of European vegetation formations follow Bohn et al. (2004) and Asian ones follow Kovar-Eder et al. (2021). in Floristic, Vegetation And Climate Assessment Of The Early/Middle Miocene Parschlug Flora Indicates A Distinctly Seasonal Climate
Text-fig. 1. Modern vegetation proxies as delivered by the Drudge 1 and 2 tools for Parschlug. Left column results from KovarEder et al. (2021) based on the floristic spectrum published by Kovar-Eder et al. (2004). The other three columns result from three variants using the enlarged floristic spectrum herein. Differences between variants 1–3 from this study are caused by differences in assignment of some taxa and morphotypes (see Appendix 1). European vegetation formations: Formation C – Subarctic, boreal and nemoral-montane open woodlands as well as subalpine and oro-Mediterranean vegetation; Formation D – Mesophytic and hygromesophytic coniferous and mixed broad-leaved-coniferous forests; Formation F – Mesophytic broadleaved deciduous and mixed broadleaved/conifer forests; Formation G – Thermophilous mixed deciduous broadleaved forests; Formation J – Mediterranean sclerophyllous forests and scrub; Formation K – Xerophytic coniferous forests, coniferous woodland and scrub. East Asian vegetation types: MCF China, Japan – Montane Coniferous Forests China, Honshu, Yakushima; BLDF N and NE Provinces, China – Broad-leaved Deciduous Forests of the Northern and Northeastern Provinces (China); BLDF Upper Yangtze, Honshu – Broad-leaved Deciduous Forest, Upper Yangtze Provinces, Mt. Emei, and Honshu; MMF China – Mixed Mesophytic Forest, Lower Yangtze Provinces; BLEF China, Japan – Broad-leaved Evergreen Forests, China, Japan; Meili Snow Mt. high altitude SCL and BLF, China – Meili Snow Mt., Sclerophyllous and broad-leaved forest zone (2,580-3,650 m alt.). (Designations of European vegetation formations follow Bohn et al. (2004) and Asian ones follow Kovar-Eder et al. (2021).
A Convolutional Neural Network classifier identifies tree species in mixed-conifer forest from hyperspectral imagery
<p>Published online: <a href="https://www.mdpi.com/2072-4292/11/19/2326">https://www.mdpi.com/2072-4292/11/19/2326</a></p> <p>DOI: 10.3390/rs11192326</p> <p><strong>Abstract:</strong></p> <p>In this study, we automate tree species classification and mapping using field-based training data, high spatial resolution airborne hyperspectral imagery, and a convolutional neural network classifier (CNN). We tested our methods by identifying seven dominant trees species as well as dead standing trees in a mixed-conifer forest in the Southern Sierra Nevada Mountains, CA (USA) using training, validation, and testing datasets composed of spatially-explicit transects and plots sampled across a single strip of imaging spectroscopy. We also used a three-band ‘Red-Green-Blue’ pseudo true-color subset of the hyperspectral imagery strip to test the classification accuracy of a CNN model without the additional non-visible spectral data provided in the hyperspectral imagery. Our classifier is pixel-based rather than object based, although we use three-dimensional structural information from airborne Light Detection and Ranging (LiDAR) to identify trees (points > 5 m above the ground) and the classifier was applied to image pixels that were thus identified as tree crowns. By training a CNN classifier using field data and hyperspectral imagery, we were able to accurately identify tree species and predict their distribution, as well as the distribution of tree mortality, across the landscape. Using a window size of 15 pixels and eight hidden convolutional layers, a CNN model classified the correct species of 713 individual trees from hyperspectral imagery with an average F-score of 0.87 and F-scores ranging from 0.67–0.95 depending on species. The CNN classification model performance increased from a combined F-score of 0.64 for the Red-Green-Blue model to a combined F-score of 0.87 for the hyperspectral model. The hyperspectral CNN model captures the species composition changes across ~700 meters (1935 to 2630 m) of elevation from a lower-elevation mixed oak conifer forest to a higher-elevation fir-dominated coniferous forest. High resolution tree species maps can support forest ecosystem monitoring and management, and identifying dead trees aids landscape assessment of forest mortality resulting from drought, insects and pathogens. We publicly provide our code to apply deep learning classifiers to tree species identification from geospatial imagery and field training data</p> <p>Digital Publication of the training data polygons and hyperspectral imagery used in the manuscript "A Convolutional Neural Network classifier identifies tree species in mixed-conifer forest from hyperspectral imagery".</p> <p>Code is available in a Jupyter Notebook and can be found here: <a href="https://github.com/jonathanventura/canopy">https://github.com/jonathanventura/canopy</a></p> <p>National Ecological Observatory Network. 2018. Provisional data downloaded from <a href="http://data.neonscience.org/">http://data.neonscience.org</a> on 22 June 2018. Battelle, Boulder, CO, USA</p>
Fig. 2 in A Camera Trapping Inventory For Mammals In A Mixed Use Planted Forest In Sarawak
Fig. 2. Some of the photographs taken by camera during the study period showing how animals respond to a lure. A, Helarctos malayanus, Malayan Sun Bear; B, Sus barbatus, Bearded Pig; C, Viverra tangalunga, Malay Civet / Tangalung.
Fig. 1 in A Camera Trapping Inventory For Mammals In A Mixed Use Planted Forest In Sarawak
Fig. 1. Location of Planted Forest Zone within Bintulu Division in Sarawak, Malaysia. Planted Forest Zone is indicated in dark striped areas in center of map.
Variations in tree growth provide limited evidence of species mixture effects in Interior West U.S.A. mixed-conifer forests
Open the record for dataset details and reuse information.
Data from: Thinning and prescribed burning increase shade-tolerant conifer regeneration in a fire excluded mixed-conifer forest
Open the record for dataset details and reuse information.
FATES projections of forest structure and composition (1830-2098) at a mixed conifer site in the southern Sierra Nevada
Open the record for dataset details and reuse information.
Data for: Specialist carabids in mixed montane forests are positively associated with biodiversity-oriented forestry and abundance of roe deer
Open the record for dataset details and reuse information.
A Chronosequence of Biomass and Carbon and Nitrogen Stocks Across Boreal Deciduous, Mixed, and Black Spruce Forests in Interior Alaska
This dataset contains forest structure data and estimates of above- and belowground carbon and nitrogen pools for a chronosequence of sites that vary in time after fire. Sites are spread throughout interior Alaska and were selected to represent the range of forest composition, from black spruce (Picea mariana) dominance, to deciduous tree dominance (Betula neoalaskana and Populus tremuloides). Multiple transects were measured in each site
Data from: Root morphology and mycorrhizal type strongly influence root production in nutrient hot spots of mixed forests
1. Plants compete for nutrients using a range of strategies. We investigated nutrient foraging within nutrient hot-spots simultaneously available to plant species with diverse root traits. We hypothesized that there would be more root proliferation by thin-root species than by thick-root species, and that root proliferation by thin-root species would limit root proliferation by thick-root species. 2. We conducted a root ingrowth experiment in a temperate forest in eastern USA where root systems of different tree species could interact. Tree species varied in the thickness of their absorptive roots, and were associated with either ectomycorrhizal (EM) or arbuscular mycorrhizal (AM) fungi. Thus, there were thin- and thick-root AM and thin- and thick-root EM plant functional groups. Half the ingrowth cores were amended with organic nutrients (dried green leaves). Relative root length abundance, the proportion of total root length in a given soil volume occupied by a particular plant functional group, was calculated for the original root population and ingrowth roots after 6 months. 3. The shift in relative root length abundance from original to ingrowth roots was positive in thin-root species but negative in thick-root species (P < 0.001), especially in unamended patches (AM: +6% vs. -7%; EM: +8% vs. -9%). Being thin-rooted may thus allow a species to more rapidly recolonize soil after a disturbance, which may influence competition for nutrients. Moreover, we observed that nutrient additions amplified the shift in root length abundance of thin over thick roots in AM trees (+13% vs. -14%), but not in EM trees (+1% vs -3%). In contrast, phospholipid fatty acid biomarkers suggested that EM fungal hyphae strongly proliferated in nutrient hot-spots whereas AM fungal hyphae exhibited only modest proliferation. 4. We found no evidence that when growing in the shared patch, the proliferation of thin roots inhibited the growth of thick roots. 5. Synthesis. Knowledge of root morphology and mycorrhizal type of co-existing tree species may improve prediction of patch exploitation and nutrient acquisition in heterogeneous soils.
Photochemical Reflectance Index (PRI) captures the ecohydrological sensitivity of a semi-arid mixed conifer forest
The Photochemical Reflectance Index (PRI) corresponds to the de-epoxidation state of the xanthophyll cycle and is one of the few pigment-based vegetation indices sensitive to rapid plant physiological responses. As such, new remotely-sensed PRI products present opportunities to study diurnal and seasonal processes in evergreen conifer forests, where complex vegetation dynamics are not well reflected by the small annual changes in chlorophyll content or leaf structure. Because PRI is tied explicitly to short and long term changes in xanthophyll pigments which are responsible for regulatig stress, this study characterized PRI in a semi-arid, sub-alpine mixed conifer forest, in order to assess its potential as a proxy for water stress by extension of its association with photoprotection. To determine the sensitivity of PRI to seasonal changes in ecohydrological variability and gross primary productivity, canopy spectral measurements were combined with eddy covariance flux and sap flow methods. Seasonally, there was a significant relationship between PRI and sap flow velocity (R2=0.56), and multiple linear regression analysis demonstrated the PRI response to dynamic water and energy limitations in this system. Although PRI was an effective indicator of stomatal response to ecohydrological constraints on a seasonal time scale, top-of-canopy leaf-level gas exchange, chlorophyll fluorescence, and hyperspectral reflectance measurements suggest that diurnal PRI saturates under conditions of severe light stress. This research indicates that remotely-sensed PRI has potential to fill spatial and temporal gaps in the ability to distinguish how water availability influences carbon dynamics of forested ecosystems.
A new map of South Manchurian mixed forests
<p>We publish the results of mapping the South Manchurian mixed forests (SMMFs) for 2021, with comparative analysis against 2001. SMMFs represent one of the most biodiverse temperate forest ecosystems globally, spanning northeastern China, southern Primorsky Krai (Russia), and the Korean Peninsula. These forests face significant degradation, with large areas replaced by secondary growth, agricultural land, and anthropogenic vegetation. Precise quantification of remaining SMMFs is critical due to their high conservation value.</p> <p>Our methodology integrated an original SMMFs distribution dataset (vegetation relevés, literature records, and regional maps) to train satellite data classifiers. We utilized Global Land Analysis and Discovery (GLAD) analysis-ready Landsat time-series at 30m resolution. Mapping employed decision tree ensembles calibrated with manually collected training data, with stratified sampling for accuracy assessment. Potential distribution modeling incorporated community-level presence/absence datasets using topographic (elevation, slope, aspect) and bioclimatic predictors.</p> <p><strong>Training Data.csv</strong> – Training dataset: Vegetation relevés and verified occurrence points for SMMFs</p> <p><strong>forest2001mask.tif</strong> and <strong>forest2021mask.tif</strong> – Binary forest cover masks (1: forest, 0: non-forest) for 2001 and 2021</p> <p><strong>smmf_2001_binary.tif</strong> and <strong>smmf_2021_binary.tif</strong> – SMMFs distribution maps (binary: 1 = SMMFs, 0 = other land cover)</p> <p><strong>Sampling.csv</strong> – Stratified sampling points for accuracy assessment</p> <p><strong>sampling_sum.tif</strong> – Stratified aggregation layer for error quantification</p> <p><strong>smmf_combined.tif</strong> – Composite SMMFs distribution raster (2021)</p> <p><strong>Map_SMMFs_area.shp</strong> – SMMF area distribution per 10×10 km grid cell</p> <p><strong>Map_SMMFs_patches.shp</strong> – Spatial boundaries of SMMFs forest patches with size attributes</p> <p><strong>proj_Current_SMMF.tb[...].tif</strong> – Potential SMMFs distribution models (target-background sampling ensemble)</p> <p><strong>proj_Current_SMMF.sample[...].tif</strong> – Potential distribution models (stratified sampling ensemble)</p> <p><strong>Results_by_algo_SMMF_tb.csv </strong>– Model evaluation metrics (target-background approach)</p> <p><strong>Results_by_algo_SMMF_sample.csv </strong>– Model evaluation metrics (stratified sampling approach)</p>
Developing crown width model for mixed forests using soil, climate, and stand factors
<ol> <li>The tree crown is a useful measure of tree vigor and is highly relevant to a tree's environmental adaptability. Crown allometry depends on environmental and stand conditions. Several studies have focused on the effects of climate change and competitive intensity on the crown, but the regulatory role of soil resources and diversity on crown allometry and carbon allocation has been neglected.</li> <li>Data from 20,994 trees in 232 mixed forests collected between 2011 and 2019 was located near four major mountain ranges in northeast China. The proposed crown width model includes the stand developmental stage, soil, climate, competition intensity, species mixture, species diversity, structural diversity, and their interactions.</li> <li>We observed that the cross-species allometric scaling exponent does not conform to the universal scaling law. Our results showed that crown width increased with increasing soil bulk density, quadratic mean diameter, and coefficient of diameter variation but decreased with increasing de Martonne aridity index, basal area, Simpson index, and species mixture. The interaction of quadratic mean diameter and soil bulk density had a significant negative effect on crown width. The influence of a particular factor within the interaction term on crown width was modulated by the gradients of other factors. Furthermore, soil bulk density contributed more to crown width modeling than the aridity index, and structural diversity had a greater effect on crown width than species diversity.</li> <li> <em>Synthesis</em>. Our results provide new insights into the environmental variability of crown allometry in mixed forests under global change, which is critical for improving regional and global estimates of forest biomass and carbon stocks.</li> </ol>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.