燃料处理规划：在保持动物栖息地的可用性和连通性的同时，将高燃料负荷地区分割开来
Fuel treatment planning: fragmenting high fuel load areas while maintaining availability and connectivity of faunal habitat
摘要：
减少火灾多发地区的燃料负荷旨在减轻灾难性野火的风险，但会产生生态后果。在保持足够范围和连通性的动物栖息地的同时，将高燃料负荷地区分割开来，这给土地管理者提出了看似相反的目标。面对这种二分法，我们提出了一个混合整数规划（MIP）模型，可以最佳地安排燃料处理，以减少燃料的危险，通过分割高燃料负荷区域，同时考虑在时间和空间上的关键生态要求。该模型既考虑了植被所能承受的火灾频率，也考虑了依赖火灾的物种所需的火灾频率。我们的方法还确保受处理区域影响的动物可获得合适的替代栖息地。更重要的是，为了保护动物群，该模型为任何时候的栖息地连通性设定了最低可接受目标。这些因素都包括在一个模型的制定，产生一个多时期的空间明确的治疗计划的时间表。我们的方法，然后证明了一系列的计算实验与假设的景观，一个单一的植被类型和一组动物物种具有相同的栖息地要求。我们的实验表明，有可能降低野火的风险，同时确保栖息地在空间和时间上的充分连通性。此外，它表明，栖息地连接性约束比邻里栖息地约束更有效。这对保护动物群至关重要，对脆弱或濒危物种也特别重要。
英文摘要：
Reducing the fuel load in fire-prone landscapes is aimed at mitigating the risk of catastrophic wildfires but there are ecological consequences. Maintaining habitat for fauna of both sufficient extent and connectivity while fragmenting areas of high fuel loads presents land managers with seemingly contrasting objectives. Faced with this dichotomy, we propose a Mixed Integer Programming (MIP) model that can optimally schedule fuel treatments to reduce fuel hazards by fragmenting high fuel load regions while considering critical ecological requirements over time and space. The model takes into account both the frequency of fire that vegetation can tolerate and the frequency of fire necessary for fire-dependent species. Our approach also ensures that suitable alternate habitat is available and accessible to fauna affected by a treated area. More importantly, to conserve fauna the model sets a minimum acceptable target for the connectivity of habitat at any time . These factors are all included in the formulation of a model that yields a multi-period spatially-explicit schedule for treatment planning. Our approach is then demonstrated in a series of computational experiments with hypothetical landscapes, a single vegetation type and a group of faunal species with the same habitat requirements. Our experiments show that it is possible to reduce the risk of wildfires while ensuring sufficient connectivity of habitat over both space and time. Furthermore, it is demonstrated that the habitat connectivity constraint is more effective than neighbourhood habitat constraints. This is critical for the conservation of fauna and of special concern for vulnerable or endangered species.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
