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Dataset results
12 results for “livestock production”
CLRD-GLPS: A Long-term Seasonal Dataset of Ruminant Livestock Distribution in China's Grazing Production Systems (2000-2021) Using Stacking-based Interpretable Machine Learning
<p>Advanced computational methods integrating ensemble learning with interpretable machine learning are essential for precision livestock management under increasing environmental constraints and food security pressures. This study develops a novel stacking-based interpretable machine learning (IML) framework that combines multiple algorithms with SHAP analysis techniques to generate the China's Long-term Ruminant Livestock Distribution in Grazing Livestock Production Systems (CLRD-GLPS) dataset. Our computational approach addresses critical challenges in livestock distribution modelling: livestock segmentation and spatial prediction accuracy. The framework integrates Random Forest, XGBoost, CatBoost, LightGBM, and Extra Trees through a two-layer stacking architecture, enhanced with SHAP (Shapley Additive Explanations) analysis for model interpretability. We also implemented interpretable machine learning for livestock production system segmentation to distinguish grazing from total livestock populations. The stacking ensemble demonstrated superior performance over individual algorithms, achieving R² values of 0.954-0.961 for cattle and 0.896-0.901 for sheep and goats, with improvements of up to 8.3% compared to best performance single-model approaches. Multi-scale validation confirmed computational robustness: livestock segmentation achieved R² = 0.80 at county level, while independent city-level validation of CLRD-GLPS datasets yielded R² = 0.76-0.80. SHAP interpretability analysis revealed distinct environmental drivers, with vegetation indices and topography primarily influencing cattle distribution, while snow conditions and elevation dominated sheep and goat patterns. This computational framework advances livestock distribution modelling through enhanced prediction accuracy, model stability, and interpretability, while the CLRD-GLPS dataset provides essential spatial-temporal information for rangeland sustainability assessments and evidence-based livestock management policies. This dataset is supported by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP, grant no. 2019QZKK0906).</p>
Supplementary Information S1 - Detailed results of the CAPRI N-LCA and S2 - Quantification of the main N budget flows in the EU25 agriculture sector of Leip, A., Billen, G., Garnier, J., Grizzetti, B., Lassaletta, L., Reis, S., Simpson, D., Sutton, M. a, de Vries, W., Weiss, F., Westhoek, H. (2015). Impacts of European livestock production: nitrogen, sulphur, phosphorus and greenhouse gas emissions, land-use, water eutrophication and biodiversity. Environ. Res. Lett. 10, 115004. doi:10.1088/1748-9326/10/11/115004
<p>Table S1-1 Quantification of GHG and Nr flow intensities [kg CO2eq (kg product)<sup>-1</sup> yr<sup>-1</sup>] or [g N (kg product)<sup>-1</sup> yr<sup>-1</sup>] with the CAPRI N-LCA model for six main livestock products (BEEF: beef, PORK: pork, EGGS: eggs, POUM: poultry meat; DAIR: milk and dairy products, SGMP: meat from sheep and goats) and six main vegetable food groups (POTA: potatoes, SUGB: sugar beet before processing, OILP: oil seeds before processing; CERR: cereals, LEGU: leguminous crops) as well as other crops (OCRP) and aggregated livestock (ANIMP) and vegetable (CROPP) food. </p> <p>Table S2-1 Quantification of the main N budget flows in the EU25 agriculture sector</p>
The key role of production efficiency changes in livestock methane emission mitigation
<p>This dataset contains the R code, the input data, the parameters used, and the updated livestock methane emission for the period 1961-2023 using methods from Chang, J., Peng, S., Yin, Y., Ciais, P., Havlik, P., Herrero, M. (2021). The key role of production efficiency changes in livestock methane emission mitigation. AGU Advances, 2, e2021AV000391. DOI: https://doi. org/10.1029/2021AV000391 </p> <p>1. R code: Chang_et_al_Global_Livestock_CH4_Assessment_1961_2023.R<br>2. Input data and parameters: Data.zip (statistics on historical livestock numbers and production need to be downloaded from FAOSTAT (http://www.fao.org/faostat/en/)<br>3. Results on global livestock methane emissions during 1961-2023 were presented in the Global_Results.xlsx<br>4. Results on livestock methane emissions from enteric fermentation and manure management during the period 1961-2023 in each country/area were shown in the folder named Country_Results: Files are organized as "Country_[XX]CH4_[YY]_[ZZ].csv" where XX indicate emission from enteric fermentation (EF) or manure management (MM); YY indicates method used for the estimates; and ZZ indicates livestock categories.<br>5. Results on gridded livestock methane emissions at a resolution of 5 arc-min using the IPCC Mixed Tier 1 and Tier 2 (2019MT) and Tier 1 (2019T1) methods following the 2019 refinement to the 2006 IPCC guidelines for National Greenhouse Gas Inventories (Vol. 4) (IPCC, 2019): Livestock_CH4_map_5arcmin_1961_2023_2019MT_2019T1.nc4</p> <p>Please contact: Dr. Jinfeng Chang (changjf@zju.edu.cn) for any question on the dataset.</p>
Supplement code and data for "A global multi-indicator assessment of the environmental impact of livestock products"
<p>This data and code supplements the publication "A global multi-indicator assessment of the environmental impact of livestock products" by Giorgio A. Bidoglio, Florian Schwarzmueller, Thomas Kastner available here: https://doi.org/10.1016/j.gloenvcha.2024.102853<br><br></p> <p>Version 1.1 add the code to the visualization tool available online at https://livestockimpactassessment.shinyapps.io/multi-indicator_impact_assessment_of_livestock_products/</p>
THE IMPACT OF LOCAL PRODUCT BRANDING ON THE ECONOMIC PERFORMANCE OF AGRICULTURAL AND LIVESTOCK AGRO-PROCESSING INDUSTRIES IN VLORA
<p>This study aims to examine the impact of local product branding on the economic performance of the agricultural and livestock agro-processing industries in the region of Vlora. Based on the data collected from local agro-processing and agro-tourism industries, the purpose of this research is to analyze how branding strategies contribute to increasing the level of sales, the level of income, creating a strong identity, and improving the performance of businesses and the territory where these businesses are concentrated. The study includes in the analysis the influence of the local brand in the creation of the identity, in the level of sales, in the income, the profit margins, and the improvement of the economic performance of the agricultural and livestock agro-processing industries. For this reason, the research was conducted with the inclusion of over 100 industries/agritourism, and the analysis of the questionnaire data was conducted with the STATA program. From the results of the research, it is clear that investment in the branding of products with local indicators is necessary to stimulate economic development and to strengthen the market positioning of businesses in the agricultural and livestock sectors. Also, this research provides important recommendations for improving branding practices as a strategic tool for the development and consolidation of agro-processing industries in the region.</p>
Data from: Livestock activity increases exotic plant richness, but wildlife increases native richness, with stronger effects under low productivity
1.Grazing by domestic livestock is one of the most widespread land uses worldwide, particularly in rangelands, where it co-occurs with grazing by wild herbivores. Grazing effects on plant diversity are likely to depend on intensity of grazing, herbivore type, coevolution with plants and prevailing environmental conditions. 2.We collected data on climate, plant productivity, soil properties, grazing intensity and herbivore type; and measured their effects on plant species richness from 451 sites across 0.4 M km2 of semi-arid rangelands in eastern Australia. We used structural equation modelling to examine the direct and indirect effects of increasing grazing intensity by different herbivores (cattle, sheep, kangaroos, rabbits) on native and exotic plant species richness across all sites, and in subsets focusing on three woodland communities spanning a gradient in productivity. 3.Direct effects of grazing by all herbivores were strongest under low productivity but waned with increasing productivity. Increases in the intensity of recent and historic livestock grazing corresponded with greater exotic plant richness under low productivity and less native plant richness under both low and moderate productivity. Rabbit effects were greatest under moderate productivity. Overall effects of kangaroos were benign. Grazing indirectly affected native and exotic plant richness by increasing soil phosphorus and reducing soil health (i.e., nutrient cycling). 4.Synthesis and applications. Our study shows that livestock grazing increases exotic species richness but reduces native richness, while kangaroo grazing increases native richness in environments with low productivity. The results provide clear messages for land managers and policy makers: (1) the coexistence of livestock grazing and plant diversity is only possible within more productive environments and (2) grazing under low or moderate productivity will impact upon native and exotic plant richness.
Data from: Livestock activity increases exotic plant richness, but wildlife increases native richness, with stronger effects under low productivity
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Livestock grazing impacts upon components of the breeding productivity of a common upland insectivorous passerine: results from a long-term experiment
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Validation of the best bet Urochloa (Brachiaria) grass cultivars for increasing feed availability and improve livestock productivity in selected sites in Kenya
<p>The trials were carried out at the Kenya Agricultural and Livestock Research Organization's Centre Mwea and Kamweti Agricultural Training Centre (ATC), both in Kirinyaga County.</p>
TECHNOLOGY OF BIOGAS PRODUCTION FROM LIVESTOCK WASTE IN A TRADITIONAL WAY
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Validation of the best bet Urochloa (Brachiaria) grass cultivars for increasing feed availability and improve livestock productivity in selected sites in Kenya
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Water use in global livestock production–opportunities and constraints for increasing water productivity
<p>This dataset contains estimates of consumptive water use from four different water sources (in m3), production quantities of meat, milk, and eggs (in kg protein), percentage of crops, and percentage of crop residues in feed mix for 919 livestock production units.</p> <p>The dataset represents the core output of the analysis presented in the final version of: Heinke, J., Lannerstad, M., Gerten, D., Havlík, P., Herrero, M., Notenbaert, A., Hoff, H., and Müller, C.: Water use in global livestock production–opportunities and constraints for increasing water productivity, Water Resources Research, in review, 2020. Please refer to this publication for a comprehensive description of methods and references to the datasets and materials used to produce this data.</p> <p>When using the data, cite it as follows: Heinke, Jens, Lannerstad, Mats, Gerten, Dieter, Havlík, Petr, Herrero, Mario, Notenbaert, An, Hoff, Holger & Müller, Christoph (2019). Water use in global livestock production–opportunities and constraints for increasing water productivity [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4265089. Please also cite the reference article that this dataset belongs to.</p> <p> </p>
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