Evaluating the effects of wolf culling on livestock predation when considering wolf population dynamics in an individual-based model

The efficiency of the management of predations on livestock by gray wolves (Canis lupus) through culling is under debate. Evaluating wolf culling efficiency requires to simultaneously analyze the effects of culling on the wolf population and the repercussions of these population changes on livestock predation. This protocol is technically difficult to implement in the field. To properly assess culling efficiency, we provided an integrated and flexible individual-based model that simulated interactions between wolf population dynamics, predation behavior and culling management. We considered many social processes in wolves. We calibrated the model to match the Western Alps as a case study. By considering the prey community in this area and the opportunistic nature of wolf predation, we assumed that predation on livestock at the wolf territory level increased with pack’s food needs. Under this assumption and considering livestock availability as high and livestock vulnerability as uniform..., , , # Data from: Evaluating the effects of wolf culling on livestock predation when considering wolf population dynamics in an individual-based model [https://doi.org/10.5061/dryad.v15dv4243](https://doi.org/10.5061/dryad.v15dv4243) ## Description of the data and file structure You can find the three R scripts required to run the model: * The script describing each of the modules of the model (**submodels.R**): Reproduction, Aging, Natural mortality, Pack dissolution, Breeding access to female subordinates, Dispersal, Migration (Immigration, Emigration), Adoption, Breeding access to dispersing wolves, Pairing, Budding, Establishment alone, Breeding access to male subordinates, Pack Needs, Culling. * The script giving all the parameters used to parameterize the model (**initParam.R**), see below for a detailed description. * The script running the model, that uses the two previous scripts. It defines and runs the cycle of the model, by giving the order of the modules (**run.R**). The raw...通过扑杀管控灰狼（Canis lupus）对家畜的捕食行为的有效性目前尚存争议。评估灰狼扑杀的有效性，需同时分析扑杀对灰狼种群的影响，以及此类种群变化对家畜捕食事件的连锁反应。该研究方案在野外实际开展存在显著技术难度。为准确评估扑杀有效性，本研究构建了一套集成且灵活的基于个体的模型（individual-based model），用以模拟灰狼种群动态、捕食行为与扑杀管理之间的相互作用。本模型纳入了灰狼的多项社会行为过程，并以西阿尔卑斯山为案例研究区域完成模型校准。结合该区域的猎物群落特征与灰狼捕食的机会主义特性，本研究提出假设：灰狼领地范围内的家畜捕食量会随狼群的食物需求增长而上升。基于该假设，并假设家畜可获得性较高且家畜被捕食的脆弱性均一…… 数据来源：《基于个体模型评估灰狼种群动态下扑杀对家畜捕食的影响》 https://doi.org/10.5061/dryad.v15dv4243 数据与文件结构说明 本研究提供了运行模型所需的三份R脚本： * 描述模型各模块的脚本（**submodels.R**）：涵盖繁殖、衰老、自然死亡、狼群解体、雌性从属个体繁殖准入、扩散、迁徙（迁入、迁出）、收养、扩散个体繁殖准入、配对、群体分群、单独定居、雄性从属个体繁殖准入、狼群食物需求、扑杀等模块。 * 用于配置模型所有参数的脚本（**initParam.R**），详细说明见下文。 * 模型运行脚本（**run.R**）：调用上述两份脚本，通过定义模块执行顺序来搭建并运行模型循环。原始……