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.
96
datasets available to search
ShareScore release 0.9.0
Dataset results
96 results for “Agroforestry”
Multispectral drone images of cocoa agroforestry in Cote d'Ivoire - Raw images
<p>This repository hosts the raw multispectral imagery dataset from drone surveys of cocoa production plots in the Central-West Region of Côte d'Ivoire.</p><p>The dataset encompasses high-resolution multispectral images from 10 cocoa production plots. These images were captured using the DJI Phantom 4 Multispectral (P4M) drone, fitted with an array of sensors capable of capturing data in RGB, red, green, blue, red edge, and near-infrared bands. </p><p>The study area comprises diverse cocoa agroforestry systems, recorded to reflect the varying structural complexities and stages of growth within the plots.</p><p>All imagery was acquired during UAV flights on May 4 and 5, 2022, between the hours of 10 AM and 2 PM (UTC). These flights were carefully scheduled to ensure optimal lighting conditions and minimal shadow interference, conducive to high-quality data capture. The region's tropical climate, marked by consistent temperatures and regular rainfall, adds to the relevance of this dataset for agricultural and ecological studies.</p><p> </p>
Fig. 1 in Helminth communities of sigmonontine rodents in cocoa agroforestry systems in Brazil
Fig. 1. Study area of the Cabruca System including nine sampling localities of agroforestry farms, where the small mammal survey was carried out, Ilhéus, state of Bahia, Brazil.
Figure 20 from: Santos B, Aguiar A, Tedesco A (2012) Trigonalidae (Hymenoptera) from cacao agroforestry systems in northeastern Brazil, with two new species of Trigonalys Westwood. Journal of Hymenoptera Research 25: 19-33. https://doi.org/10.3897/jhr.25.1810
Figure 20 - Trigonalys sanctaecatharinae (Schulz), lateral habitus (Morphobank accession number M99949). Picture by David Smith (NMNH).
Figures 13-19 from: Santos B, Aguiar A, Tedesco A (2012) Trigonalidae (Hymenoptera) from cacao agroforestry systems in northeastern Brazil, with two new species of Trigonalys Westwood. Journal of Hymenoptera Research 25: 19-33. https://doi.org/10.3897/jhr.25.1810
Figures 13-19 - Trigonalis gotica Santos et Aguiar, sp. n. Holotype female except Figure 14. 13 Lateral habitus (Morphobank accession number M99940) 14 Paratype female, head, antero-ventral (M99941) 15 Head, antero-dorsal (M99942) 16 Head, dorsal (M99943) 17 Mesothorax, dorsal (M99944) 18 Propodeum, dorsal (M99945) 19 Apical segments of metasoma, latero-ventral, left, showing ovipositor (M99946).
Figures 3-12 from: Santos B, Aguiar A, Tedesco A (2012) Trigonalidae (Hymenoptera) from cacao agroforestry systems in northeastern Brazil, with two new species of Trigonalys Westwood. Journal of Hymenoptera Research 25: 19-33. https://doi.org/10.3897/jhr.25.1810
Figures 3-12 - Trigonalys erythrocephala Santos et Aguiar, sp. n. Holotype female. 3 Lateral habitus (Morphobank accession number M90448) 4 Head, antero-ventral (M90449) 5 Head, antero-dorsal, to show ocelli (M90450) 6 Head, dorsal (M90451) 7 Mesothorax, dorsal (M90452) 8 Propodeum and base of petiole, dorsal (M90453) 9 Apical segments of metasoma, latero-ventral, left, showing metasomal armature and ovipositor; arrow indicates position of longitudinal carina (M90454) 10 Pronotum, left (M90455) 11 Left hind coxa, to show lateral longitudinal carinae (arrows) and dorso-mesal strigation (M90456) 12 Apical tergites, to show abnormal development of tergites (M90457).
Figures 1-2 from: Santos B, Aguiar A, Tedesco A (2012) Trigonalidae (Hymenoptera) from cacao agroforestry systems in northeastern Brazil, with two new species of Trigonalys Westwood. Journal of Hymenoptera Research 25: 19-33. https://doi.org/10.3897/jhr.25.1810
Figures 1-2 - Trigonalys melanoleuca Westwood. 1 Lateral habitus. Morphobank accession number (M99947) 2 Dorsal habitus. Morphobank accession number (M99948)
Agroforestry datasets and calculations
<p>Agroforestry datasets and calculations</p>
Highlighting the potential of multilevel statistical models for analysis of individual agroforestry systems (companion working R code)
<p>A companion working R code and crop yield dataset that illustrate key concepts presented in a scientific publication titled 'Highlighting the potential of multilevel statistical models for analysis of individual agroforestry systems' published in Agroforestry Systems (July 2023). For the shape file of tree strips, please refer to the publication's supplementary material (adjust the name accordingly). </p>
LBA-ECO ND-11 Litter Decomposition, Carbon, and Nitrogen Dynamics in Agroforestry
It has been proposed that the C/N ratio, or quality, of litter or mulch mixtures affects N release. Although total N release from these mixtures and the effects on soil N are relatively well understood, a mechanistic understanding of the interactions between litter species with respect to their N release is still lacking. This study examines decomposition and N dynamics in mixtures of high-quality leguminous mulch, gliricidia [Gliricidia sepium (Jacq.) Kunth. ex Walp.] with a C/N ratio of 13, and low-quality cupuacu [Theobroma grandiflorum (Wild. ex Spring) Schumann] litter with a C/N ratio of 42, which occur in combination in agroforestry systems. Ratios of 100:0, 80:20, 50:50, 20:80, 0:100 of fresh 15N-enriched gliricidia leaves and senescent cupuacu leaves, totaling the same dry weight of 6.64 t ha-1, were applied to an Oxisol and sampled at 6, 14, 38, and 96 days after application. After more than 40% of the N in the gliricidia leaves had been released and the microbial biomass N reached its peak, a significant increase in available soil N occurred at day 14, which was more pronounced with greater amounts of gliricidia in the leaf mixture. However, relative to the N applied in the leaf mixture, there was no significant difference in available soil N with greater proportions of gliricidia. Total N release from the mixtures corresponded to the total N applied by gliricidia. Until day 38, cupuaçu C mineralization was significantly faster in the presence of the highest proportion of gliricidia compared to lower proportions. This faster C mineralization of more than 0.5% per day, however, did not increase total C loss or N release from cupuaçu leaves after 96 days. The use of 15N tracers identified an N transfer from gliricidia leaves and the soil to cupuaçu leaves and consequently, a lower N release from gliricidia to the soil in the presence of cupuaçu leaves. Though we expected that available N in the soil would also decrease with greater amounts of cupuaçu litter in the mixture, our results indicated an additive effect of the two species on N release and soil mineral N, with gross interactions between them canceling net interactive effects. Therefore, N release of leaf mixtures behaved as predicted from a calculated sum of individual release patterns, in spite of a transfer of N from the high- to the low-quality leaves.
DENTRO Tree Matrix: dataset behind DENTRO - a Tree Species Selection Guide for Agroforestry
<p><strong>As a choice has to be made on whether a tree species matches the conditions of an agroforestry project in terms of e.g. soil characteristics and objectives, this dataset can support the tree species selection process.</strong></p> <p>This dataset, called <strong>‘’DENTRO Tree Matrix’’ (EN)</strong> or <strong>‘’DENTRO Bomenmatrix’’ (NL)</strong>, contains information about how tree species match certain relevant parameters varying from abiotic conditions (e.g. soil, weather, light, etc.), animals, objectives (e.g. wood/fruit/nut production and ecological function), and feasibility (e.g. disease risks and planting material availability).</p> <p>In recent years, a growing interest in agroforestry systems has been observed in Belgium and the Netherlands. Therefore, it is important to pay sufficient attention to the tree species selection process as this plays a major role in whether the agroforestry project is successful or not. Also in terms of climate change, it is important to select a tree species that both fits the farmer’s field conditions and can handle well with the extreme weather conditions occurring in the region in which the plot is located. This is why the DENTRO Tree Matrix also includes parameters such as strong wind, drought, frost, heat waves, and floods.</p> <p>The objective of the DENTRO Tree Matrix is to offer knowledge about commonly planted tree species in temperate regions (with a focus on Belgium and The Netherlands), so the right choices considering e.g. field and weather conditions can be made by the end user (farmers, advisors, ...).</p> <p>The DENTRO Tree Matrix also serves as a back-end dataset behind a set of decision support and/or tree species selection tools (currently (<strong>BETULA, AgroforesTreeAdvice, and DENTRO</strong>). </p> <p>The use of BETULA (a), DENTRO (a) and AgroforesTreeAdvice (b) is free, and these tools can be accessed through the following links:</p> <p>(a) <a href="https://www.agroforestryvlaanderen.be/en/agroforestry-planner-2">https://www.agroforestryvlaanderen.be/en/agroforestry-planner-2</a> </p> <p>(b) <a href="https://agroforestreeadvice.sk8.inrae.fr/">AgroforesTreeAdvice (inrae.fr)</a></p> <p>The background info sheet can be read here: <a href="https://www.agroforestryvlaanderen.be/nl/nieuws/boomsoortenselectie-waarmee-rekening-houden">Boomsoortenselectie: waarmee rekening houden? - Agroforestry (agroforestryvlaanderen.be)</a> (currently in Dutch).</p> <p>More info? Contact us through info@agroforestryvlaanderen.be </p>
Agroforestry walnut allometry data from 5 locations in the Netherlands (n=263)
<p>Allometry data on walnut (<em>Juglans regia</em>) in agroforestry-like systems (7-10 meters spacing) with different age (7-29 years old) was collected in the summer of 2024 across 5 locations (sandy and clayey soils) in the Netherlands. In total for 263 trees the diameter at breast height (DBH), the merchantable stem height, and total tree height were measured. For a selection of 42 out of the 263 trees, the canopy diameter in two directions, the stem diameter at the stem base, and the stem diameter at the stem top were measured. The data was collected in order to provide training and validation data for artificial intelligence (AI) models that use field-data combined with satellite data (hyperspectral, LiDAR) with the aim to predict carbon storage in the aboveground biomass (AGB) of walnut trees. The overarching goal was to contribute to cost-efficient yet reliable methods for monitoring, reporting, and verification (MRV) for agroforestry carbon farming certification schemes. The data was collected as part of the project: “Verdienmodellen voor koolstofvastlegging; gebiedsgerichte pilot in Zuid-Nederland”. The project was requested by BoerenNatuur Brabant West, executed by the Zuidelijke Land- en Tuinbouworganisatie (ZLTO) and Louis Bolk Instituut (LBI), with contributions from Space4Good on the AI model development hosted by a web-based platform "CarboCatch". The project was funded under the subsidy “Samenwerken aan groen-economisch herstel” and was granted by the Rijksdienst van Ondernemend Nederland (RVO). The data was collected by Waas Thissen (LBI) and Zarah Tomesen. Contact person for requesting the dataset is Waas Thissen.</p>
Decision Analysis of agroforestry interventions in Northwest Vietnam
<p>Repository that includes all the input data tables and model script for the article "Decision Analysis of agroforestry options reveals adoption risks for resource-poor farmers"</p>
Figure 1 in New records and a voucher collection of parasitoid wasps (Hymenoptera) inhabiting agroforestry systems in the colombian amazon basin
Figure 1. Sampling localities in the Amazonian basin of Colombia. Voucher collection and Imaging
INTACT: dataset behind the INTeractive Agroforestry Cost-benefit analysis Tool
<p><strong>A new agroforestry project often means a new (big) investment for the farmer. To get insight into which costs and benefits can be expected from a farmer's new project, the web tool INTACT can guide the farmer to relevant costs and benefits. </strong></p> <p>In recent years, a growing interest in agroforestry systems has been observed in Belgium and the Netherlands. Therefore, it is important to give farmers a 'financial picture' of their new agroforestry project. This allows to measure the impact of choices on the agroforestry project's profitability. To guarantee a non-complex interface, the developers have chosen to create a web tool instead of keeping the Excel as a tool. Though, this dataset is the backbone of the web tool INTACT.</p> <p>This dataset contains information about the farmer's starting point (field characteristics and hourly wages), costs (plant purchase, terrain preparation, planting trees, tree protection, tree management, and harvest) and benefits (fruits, nuts, and wood yield):</p> <p> </p> <p>The objectives of INTACT are 1) to guarantee insight into costs and benefits related to the tree and shrub component within agroforestry systems, 2) to guarantee open access, 2) to guarantee flexibility for the user, and 4) to enhance the user experience. Both the dataset and the web tool are initially written in Dutch as it is created for Flanders (Belgium) and The Netherlands. Though, translator plug-ins allow the user to translate the page with buttons (either English or Czech). </p> <p>The use of INTACT is free, and it can be accessed through this link: <a href="https://bdbnet.bdb.be/pls/apex/f?p=147:11">Welcome to AgroForestry Planner! AgroForestry Flanders (bdb.be)</a></p> <p>The manual can be read here: <a href="https://www.agroforestryvlaanderen.be/nl/agroforestryplanner">Agroforestryplanner - Agroforestry (agroforestryvlaanderen.be)</a> (bibliography included supporting INTACT's theoretical background).</p> <p>More info? Contact us through info@agroforestryvlaanderen.be </p>
MIMOSA: dataset behind the interactive tool for selection of nut harvesting machinery in agroforestry context (MachInes en Methodes voor de OogSt van noten in Agroforestry)
<p>This dataset contains all the information which is used to run the calculations in the interactive decision support tool "MIMOSA" (MachInes en Methodes voor de OogSt van noten in Agroforestry), intended to select nut harvesting machinery in an agroforestry context. This tool is developed for use in Belgium and The Netherlands, and is currently only available in Dutch.</p> <p>In recent years, a growing interest in agroforestry systems combined with nut production has been observed in Belgium and the Netherlands. Thereby, it is important to also pay sufficient attention to the harvesting method, even before the trees are planted. For example, grouped planting of varieties according to harvest time is recommended, or the distance between tree rows also determines the possibility of being able to access the field with certain machines. The use of harvesting machines usually also requires an almost perfectly even surface. But the harvesting method itself can also save a lot of time and money.</p> <p>When harvesting, one can wait until the green husk bursts and the nut falls down naturally or use shaking machines to make the nuts fall faster and at the same time. A choice also has to be made on whether to use nets under the trees or not. If nets are not used, consideration should be given to what other method of harvesting can be used: manually for smaller plots or with different types of pick-up machines or a suction system for larger plantings.</p> <p>The objective of MIMOSA is to support making the right choices considering scale and farm specific preferences, labour availability, etc.</p> <p><span>Based on your personal data, this interactive calculation tool gives you targeted advice for cost-efficient harvesting of your acreage of nuts. Together with the fixed parameters (working width, harvesting speed, fuel consumption, purchase price, depreciation period and machine loading capacity), it then calculates the cost price of harvesting your acreage with different machines for your specific situation (both with and without shaker). Of course, we do want to stress that this is a proposal based on theoretical calculations and only a limited number of machines are included in this calculation tool. It therefore remains important to check for yourself whether the proposed machines are suitable for your farming system.</span></p> <p>The use of the MIMOSA tool is free, and it can be accessed through this link <a href="https://bdbnet.bdb.be/pls/apex/f?p=147:10">https://bdbnet.bdb.be/pls/apex/f?p=147:10</a></p> <p>The background info sheet can be read here: <a href="https://www.agroforestryvlaanderen.be/nl/nieuws/oogst-van-noten-welke-methodes-en-machines">https://www.agroforestryvlaanderen.be/nl/nieuws/oogst-van-noten-welke-methodes-en-machines</a> (in Dutch).</p> <p>More info? Contact us through info@agroforestryvlaanderen.be </p>
QSMs, Prunus avium, agroforestry trees, South-Western Germany
<p>The data contains models of 39 <i>Prunus avium</i> trees on a agroforestry research site in South-Western Germany. The parameters were estimated using a combination of terrestrial laser scanning (TLS) and quantitative structure models (QSMs). To reconstruct the QSMs, the TreeQSM software was used (https://github.com/InverseTampere/TreeQSM). Each file contains 30 QSMs of one tree.</p>
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.