Adrian Treves, Andrea Fergus, Samuel J. Hermanstorfer, Naomi X. Louchouarn, Omar Ohrens, Alexandra Pineda-Guerrer. Gold-standard experiments to deter predators from attacking livestock.. 2023. agriXiv.2023.00196
DOI:10.31220/agriRxiv.2023.00196
Gold-standard experiments to deter predators from attacking livestock.
-
Abstract: Abstract We summarize qualitative data on experiences with gold standard, randomized, controlled trials with crossover design to evaluate the effectiveness of non-lethal methods to reduce carnivore attacks on domestic animals in four countries. We synthesize lessons learned in four categories: Experiences with randomized, controlled trials (RCTs), Design recommendations, Effectiveness of non-lethal methods to prevent wild carnivore predation on working livestock, and Conclusions. We place these in a global context with similar trials. We discuss gaps in evidence that should motivate investments in research and precautions among decision-makers at all levels. 1. The long-held belief that randomized, controlled trials (RCTs) are impossible in wild ecosystems with working livestock is laid to rest. 2. Crossover designs reduce most confounding variables between subjects and strengthen inference beyond the gold-standard of RCTs, yet we describe limitations precisely. 3. Non-lethal methods can be effective in preventing carnivore approaches and attacks on working livestock in fenced pastures or open rangelands. The relationship between approaches and attacks remains uncertain. 4. Lethal methods of predator control have been subjected to less robust study designs that suggest mixed results including increases in livestock losses. 5. Non-lethal methods promise the elusive triple-win for wildlife, domestic animals, and livelihoods.
Key words: lethal; methods; livestock; attacks; carnivore; randomize提交时间:2023-01-01
版权声明:作者本人独立拥有该论文的版权,预印本系统仅拥有论文的永久保存权利。任何人未经允许不得重复使用。 -
图表
-
Andrea Fergus, Samuel J. Hermanstorfer, Adrian Treve. Combining two non-lethal methods in crossover design randomized experiments.. 2023. doi: 10.31220/agriRxiv.2023.00203
Edward M. Hill, Naomi S. Prosser, Eamonn Ferguson, Jasmeet Kaler, Martin Green, Matt J. Keeling, Michael J. Tildesle. Modelling livestock infectious disease control policy under differing social perspectives on vaccination behaviour.. 2021. doi: 10.31220/agriRxiv.2021.00100
Nigusie Abebe Sori, Kebede Nanesa Tufa, Jemal Mohammed Hassen, Adugna Wakjira, Fikadu Robi Boran. Effect of furrow irrigation methods and deficit irrigation levels on yield and water productivity of onion ( Allium cepa L.) at Amibara, Middle Awash Valley, Ethiopia.. 2021. doi: 10.31220/agriRxiv.2021.00045
Michelle A. North, James Franke, Birgitt Ouweneel, Christopher H. Triso. Global risk of heat stress to cattle under climate change.. 2020. doi: 10.31220/agriRxiv.2020.00022
Camila Bonilla-Cedrez, Peter Steward, Todd S. Rosenstock, Philip K. Thornton, Jacobo Arango, M.J. Kropff, Julián Ramírez-Villega. Priorities for investing in low-emissions and climate-resilient livestock production systems.. 2022. doi: 10.31220/agriRxiv.2022.00163
Chauncy Fan. Research trend of antimicrobial resistance in livestock farm of China in 21 century: a bibliometric analysis.. 2021. doi: 10.31220/agriRxiv.2021.00056
John Fredy Ramírez-Agudelo, Carlos Santiago Escobar-Restrepo, Rafael Muñoz Tamayo, Sandra L. Posada-Ochoa, Ricardo Rosero-Noguer. Intake time as potential predictor of methane emissions from cattle.. 2022. doi: 10.31220/agriRxiv.2022.00134
Diego A. Delgadillo-Duran, César Augusto Vargas-García, Viviana Marcela Varón-Ramírez, Francisco Calderón, Andrea C. Montenegro, Paula H. Reyes‐Herrer. Using vis-NIRS and machine learning methods to diagnose sugarcane soil chemical properties.. 2021. doi: 10.31220/agriRxiv.2020.00028
Antonia Patt, Lorenz Gygax, Edna Hillmann, Nina M. Kei. Signs of hunger in dairy calves indicate suboptimal periods in two weaning methods.. 2020. doi: 10.31220/agriRxiv.2020.00020
Robert L. Crabtree, Dean Koch, Subhash R. Lel. Misleading overestimation bias in methods to estimate wolf abundance that use spatial models.. 2023. doi: 10.31220/agriRxiv.2023.00215
-
序号 提交日期 编号 操作 -
公开评论 匿名评论 仅发给作者
引用格式
访问统计
- 阅读量:46
- 下载量: 0
- 评论数:0



