Skip to main content
Powered by ShareScore

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.

40

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

40 results for “Tropical vegetation”

Learn how ShareScore rates datasets ↗
edi48/100

Tropical green roofs vegetation dynamics data

The data archive is here: https://doi.org/10.2737/RDS-2021-0024 please use this DOI when citing this dataset. This publication contains data collected in 2017 from three green roofs at the International Institute of Tropical Forestry in San Juan, Puerto Rico and one green roof at the Social Sciences Faculty of the University of Puerto Rico in Río Piedras. Data from these extensive green roofs include substrate depth as well as species counts within a sampled quadrant, as well as species identification information. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.

openCC (other)Apr 2023View details →
zenodo44/100

Can Artificial Intelligence help in the study of vegetative growth dynamics from herbarium collections? An evaluation of the tropical flora of the French Guiana forest

<p>Dataset was used for the article &quot;Can Artificial Intelligence help in the study of vegetative growth dynamics from herbarium collections? An evaluation of the tropical flora of the French Guiana forest&quot;.</p> <p>The related work proposes to study to what extent the use of automated visual analysis techniques, based on deep learning, can help not only to detect relatively rare vegetative structures in herbarium collections but also to automatically classify them by type of growing shoot (continuous or rhythmic).</p> <p>Abstract of the paper:</p> <p>A better knowledge of tree vegetative growth patterns and their relationship to environmental variables is crucial in understanding forest growth dynamics and how climate change may affect them. Generally less studied than reproductive structures, the phenology of tree vegetative growth mainly focuses on the analysis of growing shoots, from vegetative buds development to leaf fall. This growth process usually strongly differs between temperate and tropical regions. In temperate regions, this pattern is quite well known. Low winter temperatures impose a stop of the vegetative growth shoots and lead to the typical expression of an annual growth cycle for the vast majority of tree species. In moist tropical regions, on the other hand, the seasonality is much less marked. In addition, these regions contain a much wider variety of tree species. These two aspects lead to a tremendous diversity of phenological patterns that are still poorly known and understood. In particular, not much is known on the periodicity and timing of growth at individual trees, population, or community levels.</p> <p>The work carried out in this study aims to advance knowledge in this area, focusing more particularly on herbarium scans, as herbarium collections offer the promise of monitoring plant phenology over long time periods. However, such a study requires the ability to detect a sufficiently large number of growing shoots in herbarium collections to draw statistically relevant conclusions, which can be very costly if the work is done manually. Furthermore, herbarium collections traditionally focus on reproductive organs, and herbarium specimens showing growing shoots are pretty rare.</p> <p>We propose in this paper to study to what extent the use of automated visual analysis techniques, based on deep learning, can help not only to detect these relatively rare vegetative structures in herbarium collections but also to automatically classify them by type of growing shoot (continuous or rhythmic). Our results show the relevance of using herbarium data for vegetative phenology research, as well as the potential of deep learning approaches for growth shoot detection.</p>

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

Variation in the Composition of Understory Vegetation in a Tropical Rain Forest as a Function of Soil and Topographic Position. 1986 - 1990

Understory plants are a major contribution to the high plant species diversity of Neotropical rain forests. Shrubs, understory trees, saplings of overstory trees, and herbs occupy a habitat of generally low light levels and high humidity in which there seem to be few obvious mechanisms to support habitat partitioning. Moreover several plant families are characterized by a high number of co-occurring understory species. In 1987-1989 we sampled understory vegetation in 18 sites at the La Selva Biological Station of the Organization for Tropical Studies in Heredia Province, Costa Rica. At each site we used 20 nested quadrats to investigate the effects of soil type on replicated sites of mapped alluvial and residual volcanic soils (5 map units) and topographic positions (ridges, midslopes and flats) on composition, density and diversity of small (1m tall to 5cm dbh, 25 m2 quadrat) and large(5-10cm dbh, 100 m2 quadrat) understory plants. We also measured fine litter dry mass, extractable P, total organic matter, percent slope and percent incident light radiation in each quadrat.

openCC (other)Feb 2019View details →
zenodo40/100

Text-fig. 5. Vegetation zones in P. R. China (Editorial Committee of Vegetation Map of China, The Chinese Academy of Sciences 2007), and assumed location of extant reference vegetation type of Wiesa fossil assemblage (rectangle), as revealed from qualitative floristic analysis. Extant reference vegetation type present in southern belt of zone of subtropical evergreen broadleaved forest, with minor overlap into zone of tropical forest. in Assessment Of Phytogeographic Reference Regions For Cenozoic Vegetation: A Case Study On The Miocene Flora Of Wiesa (Germany)

Text-fig. 5. Vegetation zones in P. R. China (Editorial Committee of Vegetation Map of China, The Chinese Academy of Sciences 2007), and assumed location of extant reference vegetation type of Wiesa fossil assemblage (rectangle), as revealed from qualitative floristic analysis. Extant reference vegetation type present in southern belt of zone of subtropical evergreen broadleaved forest, with minor overlap into zone of tropical forest.

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

Figure 4 in Population Dynamics of Amoeboid Protists in a Tropical Desert: Seasonal Changes and Effects of Vegetation and Soil Conditions

Figure 4. Relationship between amoeboid protist richness and soil parameters during the wet season in three microhabitats by CCA: PL: Pr. laevigata, PP: Pa. praecox, and BS: bare soil. The names and abbreviations of the amoeboid protist species can be found in table 3.

opencc-by-4.0Dec 2018View details →
zenodo40/100

Figure 2 in Population Dynamics of Amoeboid Protists in a Tropical Desert: Seasonal Changes and Effects of Vegetation and Soil Conditions

Figure 2. Cumulative richness plots of amoeboid protists present under Pr. laevigata (PL), Pa. praecox (PP) and bare soil (BS) during dry and wet seasons at 0–30 cm. a) eruptive pseudopods, and b) acanthopodial pseudopods. ND: not determined.

opencc-by-4.0Dec 2018View details →
zenodo40/100

Figure 1 in Population Dynamics of Amoeboid Protists in a Tropical Desert: Seasonal Changes and Effects of Vegetation and Soil Conditions

Figure 1. Study area, showing vegetation patches in the desert of Tehuacán, Puebla, Mexico. In addition, the analyzed microhabitats are shown: Pr. laevigata, Pa. praecox and bare soil.

opencc-by-4.0Dec 2018View details →
dryad36/100

Data for: The interplay of environmental cues and wood density in the vegetative and reproductive phenology of seasonally dry tropical forest trees

<p>The great phenological diversification characteristic of seasonally dry tropical forests (SDTF) suggests that these patterns result from a complex interplay between exogenous (e.g., climatic) and endogenous (e.g., morphological, physiological, anatomical) factors. Based on the well-established relationships of wood density with water-storing capacity and cavitation vulnerability in woody plants, we hypothesized differential vegetative and reproductive phenological responses to environmental cues for hardwood and softwood species. To test this hypothesis, we compared phenological patterns of pairs of conspecific populations of 10 species differing in wood density, occurring in two localities with slightly different climatic regimes, and evaluated the influence of three environmental variables (rainfall, photoperiod, temperature) on them. Our results, based on the assessment of the overlap of the phenological curves of conspecific populations occurring in different sites and on linear modeling, showed different effects of the environmental factors on phenophase attributes, depending on wood density of the study species, thus supporting our hypothesis. Leaf out in softwood species took place in the dry season, they shed the foliage at the first signs of drought, and once leafless, they flowered and fruited shortly after. By contrast, hardwood species bore leaves and flowers in the rainy season, shed their leaves several months after the rain ceased, and produced fruits during the dry season. We conclude that the role of environmental variables in cueing growth and reproduction cycles in SDTF tree species is interrelated with their wood density, a key endogenous factor crucially linked to plant hydraulics in these water-limited ecosystems.</p>

opencc-zeroJan 2022View details →
dryad36/100

Weak effects of birds, bats and ants on their arthropod prey on pioneering tropical forest gap vegetation

<p>The relative roles of plants competing for resources versus top-down control of vegetation by herbivores, in turn impacted by predators, during early stages of tropical forest succession remain poorly understood. Here we examine the impact of insectivorous birds, bats and ants exclusion on arthropods communities on replicated 5x5 m of pioneering early successional vegetation plots in lowland tropical forest gaps in Papua New Guinea. In plots from which focal taxa of predators were excluded we observed increased biomass of herbivorous and predatory arthropods, and increased density, and decreased diversity of herbivorous insects. However, changes in the biomass of plants, herbivores and arthropod predators were positively correlated or uncorrelated between these three trophic levels and also between individual arthropod orders. Arthropod abundance and biomass correlated strongly with the plant biomass irrespective of the arthropods' trophic position – a signal of bottom-up control. Patterns in herbivore specialization confirm lack of a strong top-down control and were largely unaffected by the exclusion of insectivorous birds, bats and ants. No changes of plant-herbivore interaction networks were detected except for decrease in modularity of the exclosure plots. Our results suggest weak top-down control of herbivores, limited compensation between arthropod and vertebrate predators, and limited intra-guild predation by birds, bats and ants. Possible explanations are strong bottom-up control, a low activity of the higher order predators, especially birds, possibly also bats, in gaps, and continuous influx of herbivores from surrounding mature forest matrix.</p>

opencc-zeroFeb 2022View details →
dryad36/100

Highly-replicated soil, topography and vegetation sampling across an old-growth tropical rain forest landscape

<p class="MsoNormal">Here we present data from highly-replicated sampling of soil, topography, and vegetation across an old-growth tropical rainforest landscape at the La Selva Biological Station, Costa Rica.  Samples were taken at 100 x 50 m spacing using an existing surveyed grid system.  The 573-ha sample area spanned a variety of soil, topographic and vegetation conditions, including flat terraces on old alluvial soil, ridge tops and steep slopes on residual soil, riparian habitats and fresh-water swamps.  At each of 1170 grid points we established a circular 0.01 ha quadrat (radius = 5.64 m).  We sampled soil at 30-50 cm depth with a soil augur and collected a sample for subsequent analysis.  We measured slope angle with a clinometer and slope direction with a compass.  We measured stem diameter to <u>+</u>1 mm with a synthetic fabric diameter tape for all stems <u>&gt;</u>10 cm diameter (N= 5236) at 1.3 m from the ground or to ~ 6 m height if there were basal irregularities.  We classified stems to life form (tree, palm, liana), and identified all trees and palms to species or morphospecies (N=266; lianas were not identified to species).  We collected vouchers from all trees that we could not positively identify in the field (N=920).</p> <p class="MsoNormal">As a whole the data set presents an integrated view of soil, topography and vegetation across a mesoscale old-growth tropical rain forest landscape.  The data have been used to refine a reserve-wide soils map for La Selva, and for a variety of papers analyzing the interactions of soil, topography and species distributions at landscape scales (see the 10 papers listed in the Related Works section below).</p> <p class="MsoNormal">There are no restrictions at all on the use of these data, and we think they will be useful for teaching and analysis projects as well as further original research applications.  The data also provide a detailed benchmark of the status of old-growth vegetation in 1993-95 for one of the most intensively studied tropical rain forest landscapes in the world.  Because the data are accurately georeferenced and detailed metadata on all methods are provided, this study could be repeated at any time to assess the trajectory of vegetation changes at La Selva, particularly in relation to local disturbances and changing regional and global climates.   </p>

opencc-zeroJun 2022View details →
zenodo36/100

Estimates of soil nutrient limitation on the CO2 fertilization effect for tropical vegetation

<p>Data for CO2 fertilization experiments and CMIP6 model simulations used in publication: &quot;Estimates of soil nutrient limitation on the CO2 fertilization effect for tropical vegetation&quot;</p>

opencc-by-4.0Jul 2022View details →
dryad36/100

Landslide age, elevation and residual vegetation determine tropical montane forest canopy recovery and biomass accumulation after landslide disturbances in the Peruvian Andes

<p>Landslides are common natural disturbances in tropical montane forests. While the geomorphic drivers of landslides in the Andes have been studied, factors controlling post-landslide forest recovery across the steep climatic and topographic gradients characteristic of tropical mountains are poorly understood.</p> <p>Here we use a LiDAR-derived canopy height map coupled with a 25-year landslide time series map to examine how landslide, topographic, and biophysical factors, along with residual vegetation, affect canopy height and heterogeneity in regenerating landslides. We also calculate aboveground biomass accumulation rates and estimate the time for landslides to recover to mature forest biomass levels.</p> <p>We find that age and elevation are the biggest determinants of forest recovery, and that the jump-start in regeneration that residual vegetation provides lasts for at least 18 years. Our estimates of time to biomass recovery (31.6-37.1 years) are surprisingly rapid, and as a result we recommend that future research pair LiDAR with hyperspectral imagery to estimate forest aboveground biomass in frequently disturbed landscapes.</p> <p>Synthesis: Using a high-resolution LiDAR dataset and a time-series inventory of 608 landslides distributed across a wide elevational gradient in Andean montane forest, we show that age and elevation are the most influential predictors of forest canopy height and canopy variability. Other features of landslides, in particular the presence of residual vegetation, shape post-landslide regeneration trajectories. LiDAR allows for a detailed analysis of forest structural recovery across large landscapes and numbers of disturbances, and provides a reasonable upper bound on aboveground biomass accumulation rates. However, because this method does not capture the effect of compositional change through succession on aboveground biomass, wherein high-wood density species gradually replace light-wooded pioneer species, it overestimates aboveground biomass. Given previously estimated stem turnover rates along this elevational gradient, we posit that aboveground biomass recovery takes at least three times as long as our recovery time estimates based on LiDAR-derived structure alone.</p>

opencc-zeroJun 2021View details →
dryad36/100

Data from: Interplay between rainfall and hillslope hydrology determines drought resistance of tropical vegetation

<p><span>Droughts are predicted to increase in both frequency and intensity by the end of the 21st century, but ecosystem response is not expected to be uniform. At the landscape scale, ecosystem response to drought is highly heterogeneous. Here we assess the importance of the hill-to-valley hydrologic gradient in shaping vegetation hydraulic properties related to drought resistance for three locations across a rainfall seasonality gradient in South America. For this, we use hydraulic traits related to xylem resistance to embolism and compare the functional composition and diversity of tree communities. We show that the hydrologic gradient systematically selects for community assemblages that are more vulnerable to embolism in valleys, regardless of rainfall. Under the same rainfall regime, diversity in resistance to embolism is higher on hills than valleys, suggesting that strategies to cope with drought are more important on hills. With increasing seasonality, diversity in embolism resistance increases on hills and decreases in valleys. Our results show that differential groundwater access from hilltops to valleys select for distinctive hydraulic properties, potentially explaining species turnover along topographical gradients. Incorporating this relationship might improve the representation of vegetation in climate models and the prediction of how different communities will respond to extreme droughts.</span></p>

opencc-zeroMar 2023View details →
dryad36/100

Weak effects of birds, bats and ants on their arthropod prey on pioneering tropical forest gap vegetation

Open the record for dataset details and reuse information.

publicFeb 2022View details →
dryad36/100

Data from: Application of a trait‐based species screening framework for vegetation restoration in a tropical coral island of China

Open the record for dataset details and reuse information.

publicMar 2020View details →
dryad36/100

Data for: The interplay of environmental cues and wood density in the vegetative and reproductive phenology of seasonally dry tropical forest trees

Open the record for dataset details and reuse information.

publicJan 2022View details →
dryad36/100

Data from: The role of tropical forest fragment vegetation in maintaining arthropod diversity and spillover to adjacent sugarcane fields

Open the record for dataset details and reuse information.

publicAug 2025View details →
dryad36/100

Data from: Interplay between rainfall and hillslope hydrology determines drought resistance of tropical vegetation

Open the record for dataset details and reuse information.

publicMar 2023View details →
dryad36/100

Highly-replicated soil, topography and vegetation sampling across an old-growth tropical rain forest landscape

Open the record for dataset details and reuse information.

publicAug 2022View details →
dryad36/100

Data from: Tropical Central African bomb radiocarbon reveals antiphase air-mass atmospheric fluxes and vegetation-growth relationships

Open the record for dataset details and reuse information.

publicJul 2025View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

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