End-user involvement to improve predictions and management of populations with complex dynamics and multiple drivers

Sustainable management of wildlife populations can be aided by building models that both identify current drivers of natural dynamics and provide near-term predictions of future states. We employed a Strategic Foresight Protocol (SFP) involving stakeholders to decide the purpose and structure of a dynamic state-space model for the population dynamics of the willow ptarmigan - a popular game species in Norway. Based on local knowledge of stakeholders, it was decided that the model should include food web interactions and climatic drivers to provide explanatory predictions. Modelling confirmed observations from stakeholders that climate change impacts ptarmigan populations negatively through intensified outbreaks of insect defoliators and later onset of winter. Stakeholders also decided that the model should provide anticipatory predictions. The ability to forecast population density ahead of the harvest season was valued by the stakeholders as it provides the management extra time to con...

野生动物种群的可持续管理，可通过构建同时识别当前自然动态驱动因子、并对种群未来状态提供短期预测的模型获得助力。本研究采用包含利益相关方（stakeholders）参与的战略前瞻协议（Strategic Foresight Protocol, SFP），共同确定了针对挪威热门狩猎物种柳松鸡（Willow Ptarmigan）种群动态的动态状态空间模型（dynamic state-space model）的目标与架构。基于利益相关方的本土认知，团队明确模型需纳入食物网交互作用与气候驱动因子，以生成具备解释效力的预测结果。建模结果验证了利益相关方的观测结论：气候变化通过加剧食叶昆虫的暴发、延后冬季来临时间，对柳松鸡种群产生负面影响。利益相关方同时要求模型需提供前瞻性预测能力。利益相关方十分看重模型在狩猎季前预测种群密度的功能，因其可为管理部门预留额外的应对时间以……