Find research datasets worth reusing

opencc-by-4.0Sep 2022View details →

Rising agriculture water scarcity in China is driven by expansion of irrigated cropland in water-scarce regions

The datasets contain original data from the article titled" Rising agriculture water scarcity in China is driven by expansion of irrigated cropland in water-scarce regions "

opencc-by-4.0Nov 2020View details →

Fig. 1. A in Agricultural Trichothecene Mycotoxin Contamination Affects The Life-History And Reduced Glutathione Content Of Folsomia Candida Willem (Collembola)

Fig. 1. A relative growth of Folsomia candida on the relation of the contaminated food; significant difference in mean B. Total reproduction of Folsomia candida in the contaminated

opencc-by-4.0Oct 2022View details →

Dataset for paper "Solutions to global agricultural green water scarcity under climate change"

These are datasets used to generate figures of paper  "Solutions to global agricultural green water scarcity under climate change". (1) fig1_GWS_Baseline, fig1_GWS_1.5C and fig1_GWS_1.5C are NetCDF files reporting agricultural green water scarcity (GWS) under Baseline climate conditions (1996-2005 period), 1.5°C and 3°C warmer climates, respectively.  (2) fig2_num_of_month_Baseline, fig2_num_of_month_1.5C and fig2_num_of_month_3C are NetCDF files reporting the number of months that each grid cell faces GWS (with threshold 0.2) under Baseline climate conditions (1996-2005 period), 1.5°C and 3°C warming climates, respectively. fig2_data_Baseline, fig2_data_1.5C and fig2_data_3C are csv files reporting the countries with the highest exposure to GWS and number of months under Baseline, 1.5 °C and 3 °C warmer climates, respectively.  (3) fig3_data_01, fig3_data_02 and fig3_data_03 are csv files reporting the area of rain-fed croplands facing agricultural GWS in each month under GWS thresholds 0.1, 0.2 and 0.3, respectively.  (4) fig4_data is the csv file reporting the number of people impacted by crop production loss induced by GWS under Baseline, 1.5 °C and 3 °C warmer climates with GWS thresholds of 0.1, 0.2 and 0.3. (5) fig5_Baseline, fig5_1.5C and fig5_3C are csv files reporting the reduction of area facing GWS and increased people fed due to green water management solutions with different evapotranspiration reduction and infiltration increase levels, under Baseline, 1.5 °C and 3 °C warmer climates, respectively. (6) fig6_data_area and fig6_data_population are csv files reporting reduced rain-fed croplands facing GWS and additional people fed from decreased GWS, respectively, with evapotranspiration reduction and infiltration increase levels as 0.2. (7) irrigation_fraction is the NetCDF file reporting the percent of irrigated cropland in each grid cell. We use it as a mask to exclude croplands with larger than 5% irrigation. It is calculated based on "Mehta, P. et al. Majority of 21st century global irrigation expansion has been in water stressed regions. (2022)."

dryad40/100

Random forest climatic modeling of agricultural insurance loss across the inland Pacific Northwest region of the United States

We compared climatic relationships to insurance loss across the inland Pacific Northwest region of the United States, using a design matrix methodology, to identify optimum temporal windows for climate variables by county in relationship to wheat insurance loss due to drought. The results of our temporal window construction for water availability variables (precipitation, temperature, evapotranspiration, and the Palmer drought severity index [PDSI]) identified spatial patterns across the study area that aligned with regional climate patterns, particularly with regards to drought-prone counties of eastern Washington. Using these optimum time-lagged correlational relationships between insurance loss and individual climate variables, along with commodity pricing, we constructed a regression-based random forest model for insurance loss prediction and evaluation of climatic feature importance. Our cross-validated model results indicated that PDSI was the most important factor in predicting total seasonal wheat/drought insurance loss, with wheat pricing and potential evapotranspiration having noted contributions. Our overall regional model had a R2 of 0.49 and a RMSE of $30.8 million. Model performance typically underestimated annual losses, with moderate spatial variability in terms of performance between counties.

opencc-zeroOct 2022View details →

opencc-by-4.0Oct 2022View details →

Dataset to: Deforestation for agriculture leads to soil warming and enhanced litter decomposition in subarctic soils

Deforestation for agriculture leads to soil warming and enhanced litter decomposition in subarctic soils T. Peplau, C. Poeplau, E. Gregorich, J. Schroeder This repository contains a dataset of soil temperature, soil parameters, farm management and additional site informations. Soil_temperature_data_Yukon.zip: Temperature data from different farms across the Yukon. Each .xlsx file contains data from one temperature logger that logged soil temperature every 2 hours. The individual sheets are named in the following scheme: Farm_landuse_depth.xlsx Farm contains two letters corresponding to the identifier in the soil data set landuse contains either F ("Forest"), CM ("Cropland / Market Garden") or G ("Grassland") Depth is either 10 cm or 50 cm teabags.csv contains raw data about the initial weight of the teabags buried, their location and their weight after two years in the soil tea_decomposition contains the mean decomposition (n=3) of the tabags from each plot and corresponding temperature statistics, based on the logger data Soil_I_IV.csv contains soil parameters from soil samples at 0-10 cm and 40-60 cm site_data_R.csv contains geographical information and soil data that has only been measured once per site

opencc-by-4.0Apr 2024View details →

Carbon stock increase during post-agricultural succession in central France: no change of the superficial soil stock and high variability within forest stages

Open the record for dataset details and reuse information.

opencc-by-4.0Feb 2021View details →

Рис. 1. Àинамика посевных пΛощаΔей сои в Приморском крае в 1996–2018 гг. (по Δанным Àепартамента сеΛьского хозяйства и проΔовоΛьствия Приморского края) Fig. 1. The dynamic of soybean crop area at Primorsky Region in 1996–2018 (based on data from the Department of Agriculture and provision of the Primorsky Region) in Reproductive potential of Soybean Cyst Nematode Heterodera glycines - quarantine pest of soybean - in Primorsky Region conditions

Рис. 1. Àинамика посевных пΛощаΔей сои в Приморском крае в 1996–2018 гг. (по Δанным Àепартамента сеΛьского хозяйства и проΔовоΛьствия Приморского края) Fig. 1. The dynamic of soybean crop area at Primorsky Region in 1996–2018 (based on data from the Department of Agriculture and provision of the Primorsky Region)

The CWR richness dataset of manuscript "ENHANCING IN SITU CONSERVATION OF CROP WILD RELATIVES FOR FOOD AND AGRICULTURE IN LITHUANIA"

The CWR National Inventory database has been created by combining data from the Database of EU Habitat Mapping in Lithuania (BIGIS), the Herbarium Database of the Nature Research Centre (BILAS), the Lithuanian Vegetation Database (EU-LT-001), and the Global Biodiversity Information Facility (GBIF). It was used to calculate CWR richness in 4 by 4 kilometres grid cell. The dataset contains three GIS files (.shp) - Boundaries of Lithuania, CWR richness in grid cells and 45 potential genetic reserve sites.

opencc-zeroMay 2024View details →

dryad40/100

Data from: Island-wide characterization of agricultural production challenges the demographic collapse hypothesis for Rapa Nui (Easter Island)

Communities in resource-poor areas face health, food production, sustainability, and overall survival challenges. Consequently, they are commonly featured in global debates surrounding societal collapse. Rapa Nui (Easter Island) is often used as an example of how over-exploitation of limited resources resulted in a catastrophic population collapse. A vital component of this narrative is that the rapid rise and fall of pre-contact Rapanui population growth rates was driven by the construction and overexploitation of once extensive rock gardens. However, the extent of island-wide rock gardening, while key for understanding food systems and demography, must be better understood. Here, we use shortwave infrared (SWIR) satellite imagery and machine learning to generate an islandwide estimate of rock gardening and re-evaluate prior population size models for Rapa Nui. We show that the extent of this agricultural infrastructure is substantially less than previously claimed and likely could not have supported the large population sizes that have been assumed.

A questionnaire survey of expected characteristics of i-voting systems among students and graduates of agricultural colleges

In order to find out the opinions on the transparency of remote electronic voting, a questionnaire survey was conducted among students and graduates of Czech universities with agricultural specialization. We assume that these are people with higher technical literacy who may be potential users of i-voting systems in farms in the near future. For the composition of the questions, the framework from Agbesi et al. (2023) was used to investigate the dimensions of transparency for Internet voting, supplemented with a few specific questions. Agbesi et al. (2023) identify five core dimensions, namely information accessibility, clarity, monitoring and verifiability, corrective action and testing, these dimensions influence the perception of transparency which in turn influences trust in the overall system. The anonymous questionnaire survey was conducted online via the Dotaznik.czu.cz platform operated by the Czech University of Life Sciences Prague. The invitation to participate in the survey was extended primarily to Czech students and graduates of agricultural universities. The questionnaire survey was conducted from 24 October 2023 to 12 May 2024. The questionnaire was freely accessible on the platform, therefore some respondents may be outside the target population within the limitations of the research. Participants were shown all information including consent to data processing on the homepage of the survey. Respondents answered on a seven-point Likert scale ranging from Strongly Disagree (0) to Strongly Agree (6) to statements within the five defined dimensions. A total of 177 individuals were recorded as completing the questionnaire. A total of 108 questionnaires were completed in full. Of these, 8 more questionnaires were removed because the control question "This question is not part of the survey and just helps us to detect bots and automated scripts. To confirm that you are a human, please choose 'Strongly agree' here" was answered differently than Strongly agree. Of the 100 responses examined, 64 were male, 35 were female, and 1 respondent did not indicate their gender. 72 respondents are aged 18-30, 18 aged 31-40, 5 aged 41-50, 2 aged 51-60 and 3 aged 61-70. 72 respondents have completed secondary education, 10 have a Bachelor's degree, 12 have a Master's degree and 6 have a PhD.

LPJmL5 agricultural system simulations for use in MAgPIE for ISIMIP3 scenarios

This data set contains output data from simulations with the model LPJmL version 5 for further use in the MAgPIE model. Simulations are based on the ISIMIP3a/b climate input data, assuming no nitrogen limitations and no water limitations in irrigated systems. No natural vegetation is considered here, simulations are for agricultural systems (cropland, managed grassland). Geospatial information in files <code>grid.clm</code>, data processing is recommended using <a href="https://github.com/PIK-LPJmL/lpjmlkit" target="_blank" rel="noopener">lpjmlkit</a>. The first version was buggy and could not be unpacked properly. The second version (v2) is identical from the content but the file can be processed.

Soil Moisture, Soil NOx and Regional Air Quality in the Agricultural Central United States: Data

The data in this repository are associated with the manuscript from Huber et al. (2024) titled "Soil Moisture, Soil NOx and Regional Air Quality in the Agricultural Central United States" in the Journal of Geophysical Research: Atmospheres. Additional information regarding these data can be found in the attached readme file.

Fig. 4 in The anuran fauna in a protected West African rainforest and surrounding agricultural systems

Fig. 4. Selected amphibian species from Taï National Park and surrounding agroforestry systems. (A) Conraua alleni inhabits rainforest streams. (B) Ptychadena cf. aequiplicata is a typical inhabitant of primary forest. (C) Chiromantis rufescens breeds in puddles along forest roads and stagnant ponds and puddles in the forest. (D) Arthroleptis cf. poecilonotus (a complex of at least two species) occurs in primary and degraded forest, and is particularly abundant in agroforestry systems. (E) Amnirana galamensis is a typical inhabitant of African savannas and was detected for the first time in the Taï area. (F) Ptychadena mascareniensis is a very abundant frog in rice fields.

Fig. 2 in The anuran fauna in a protected West African rainforest and surrounding agricultural systems

Fig. 2. The different habitats in and around Taï National Park which were surveyed for amphibians. (A) and (B) near primary forest; (C) cocoa plantation; (D) rubber plantation; (E) heavily degraded forest edge; (F) rice field.

Fig. 3 in The anuran fauna in a protected West African rainforest and surrounding agricultural systems

Fig. 3. Species accumulation curve (triangles) and estimated amphibian species richness (Chao 2, squares; and Jack-knife 1, circles) of the Taï National Park and surrounding agroforestry system. The mean values of 500 random runs of the daily species lists are given. A daily species list comprised the presence/absence records collected during seven hours of sampling (four hours during daylight, and three hours during night) on one plot by two people for a total of 14 person-hours.

Fig. 1 in The anuran fauna in a protected West African rainforest and surrounding agricultural systems

Fig. 1. Locations of the 32 study plots in the Taï National Park and surrounding agroforestry systems (see Appendix 1 for the plot list and habitat descriptions). Inset figure: position of Taï National Park in Côte d'Ivoire.

opencc-by-4.0Mar 2023View details →

Global agricultural costing model

The agricultural costing model is a cost calculator that includes national-scale information on costs of production in two versions: 1) ten major crops including, barley, groundnut, maize, potato, rice, sorghum, soybean, sugar beet, sunflower, and wheat, and 2) vegetables, including onion, cucumber, cabbage, carrot, spinach, lettuce, cauliflower, broad beans, pumpkin, peas, and ‘vegetables’ combining the aforementioned in a single group and, works in combination to FABLE calculator. The present version of the costing inventory includes five cost items corresponding to costs for the production inputs of fertiliser, pesticides, labour, machinery and fuel. The current setting of the cost calculation is based on the integration of physical requirement (volumes) per hectare for any given production input, the respective cost per unit of input and the cropland extent.

Urban Agriculture and Health: Insights from Anonymized Expert Interviews on Spatial Planning in Greater Lomé, Togo

Transcripts of anonymized interviews with 11 urban planning experts in Greater Lomé on the subject of urban agriculture, health and spatial planning.

opencc-zeroMay 2024View details →

dryad40/100

Data from: Semi-natural habitat, but not aphid amount or continuity, predicts lady beetle abundance across agricultural landscapes

The amount of semi-natural habitat surrounding farm fields is a common but inconsistent predictor of natural enemy populations and predation services. Standard land cover metrics may not accurately capture the actual availability of limiting resources for natural enemies and can miss important dynamics across space and time. Theory from animal movement and landscape ecology predicts that regions with more, spatio-temporally continuous resources (i.e. food, shelter) should have larger predator populations and enhanced biological control. To test these predictions empirically, we designed a study measuring aphids, lady beetles, and predation services in agricultural landscapes in Wisconsin, USA. In two study years, we sampled lady beetles and aphids in 336 crop fields (corn, soybean, alfalfa, and small grains) and adjacent semi-natural habitat patches (grasslands and woodlands) across 24 1.5 km buffer landscapes at 4–7 time points each, and in one year we assessed predation rates with sentinel egg cards. We used aphid counts to model habitat-specific aphid phenologies, from which we calculated landscape indices of prey amount and continuity. These indices, along with semi-natural habitat area, were used to predict lady beetle abundance. While there were strong differences in the abundance and timing of aphids by habitat, semi-natural habitat amount was still a better predictor of lady beetle counts and sentinel egg predation than either aphid amount or continuity indices in these landscapes. Synthesis and application: Our findings confirm the robust relationship between lady beetles and semi-natural habitat in agricultural landscapes, and highlight the complexities of measuring fine-scale resource heterogeneity in real landscapes. Retaining or adding woodland and grassland patches in agricultural landscapes is likely to support larger lady beetle populations and enhance predation in crop fields. Our results suggest that these habitats may be more important for shelter than prey continuity, though this mechanism warrants further investigation. Future work should continue to refine experimental methods for the successful integration of landscape ecology and animal behavior to support conservation goals.