Optimising multifunctional land-use decisions through robust combined models: a pollination-crop yield-landscape aesthetics case study

做出土地使用决策是复杂的，因为我们的景观有许多相互竞争的需求（环境，社会和经济）。我们在小范围内做出的决定可能会产生更大和更长期的影响。例如，在可耕地景观中，将田地边缘转换为作物以最大限度地提高给定田地的作物产量（经济效益），将减少作物旁边的行人通道（社会效益），并减少支持大规模生物多样性的资源（环境效益）。较低的生物多样性反过来又会减少授粉服务，从而减少作物产量，不仅在原来的领域，而且在周围的领域。因此，一个领域的土地使用选择的后果可能远远超出该领域，并影响到许多不同的利益。这意味着必须同时评估土地使用决定对所有这些利益的影响，以便在景观尺度上作出最知情的土地使用决定。虽然许多统计模型允许我们在整个景观中非常详细地测量个体效益，但很少有联合收割机结合多种效益，并且那些这样做的，通常不考虑不同效益之间的反馈，因为它们的附加模型结构。此外，这些现有的综合模式很少考虑到所产生的惠益的时间依赖性，而这对于林地创造等土地使用选择可能很重要，因为这需要几十年的时间才能充分实现其生物多样性惠益。我们的项目将结合联合收割机物理科学的专业知识，在建立空间明确的时间依赖的计算机模型，在生态学，社会学和经济学的专业知识，开发第一个模型框架，结合多个相互作用的规模效益模型，以确定土地使用的选择，最大限度地提高生态，社会和经济效益的景观随着时间的推移。该项目将利用传粉媒介及其在农业景观中提供的惠益作为模型开发的案例研究，因为支持传粉媒介的农业土地使用干预措施同时影响环境（通过支持生物多样性）、社会（通过影响农田的景观质量）和经济（通过确定对作物的授粉服务）惠益。因此，我们的模型将联合收割机结合和相互联系的三个单独的效益模型-传粉者丰富的生物多样性效益模型，美学价值的社会效益模型和货币作物价值的经济效益模型-到一个单一的凝聚力的整体。它还将说明花带和绿篱等干预措施提供的惠益如何随着时间的推移而变化。我们将测试一系列的真实的农业景观模型，包括不同数量的传粉者干预，以确定最佳比例的干预措施，以最大限度地提高环境，社会和经济效益的景观随着时间的推移。该项目的成果与设计未来的英国农业环境计划直接相关，我们将与项目合作伙伴合作，展示组合模型框架为现实世界的土地使用决策提供信息的潜力。今后可以扩大模型框架，以包括其他惠益（例如其他物种的丰度、水质/水量等）。并为其他具有竞争性环境、社会和经济需求的土地使用系统确定最佳解决方案（例如，新的开发项目在住房需求与绿色基础设施之间取得平衡）。

Making land-use decisions is complicated because there are many competing demands (environmental, social and economic) placed on our landscapes. The decisions we make at small scales can have much larger and longer-term consequences. For instance, in arable landscapes, converting field margins to crop to maximise crop yield in a given field (economic benefit), will reduce pedestrian access beside crops (social benefit) and reduce resources supporting landscape-scale biodiversity (environmental benefit). Lower biodiversity can in turn reduce pollination service and therefore crop yield, not only in the original field, but also in surrounding fields. The consequences of a land-use choice in one field can therefore spread far beyond that field and affect many different benefits. This means that it is essential to assess the impacts of land-use decisions on all of these benefits simultaneously, in order to make the most informed land-use decisions at the landscape scale. Although many statistical models allow us to measure individual benefits in great detail across the landscape, very few combine multiple benefits, and those that do, typically do not consider the feedbacks between different benefits due to their additive model structure. Furthermore, these existing combined models rarely account for the time-dependent aspects of benefits derived, which can be significant for land-use choices such as woodland creation, which takes decades to reach their full biodiversity benefits. Our project will combine physical science expertise in building spatially-explicit time-dependent computer models with expertise in ecology, sociology and economics to develop the first modelling framework that combines multiple interacting landscape-scale benefit models, to identify land-use choices that maximise the ecological, social and economic benefits provided by the landscape over time. The project will use pollinators and the benefits they provide in agricultural landscapes as a case study for model development, because agricultural land-use interventions for supporting pollinators affect environmental (by supporting biodiversity), social (by affecting the scenic quality of farmland), and economic (by determining pollination service to crops) benefits simultaneously. Our model will therefore combine and interlink three individual benefit models - a pollinator abundance biodiversity-benefit model, an aesthetic value social-benefit model and a monetary crop value economic-benefit model - into a single cohesive whole. It will also account for how the benefits provided by interventions such as flower strips and hedgerow creation can change over time. We will test the model on a series of real agricultural landscapes incorporating varying amounts of pollinator interventions to identify the optimum proportions of interventions required to maximise the environmental, social and economic benefits provided by the landscapes over time. The outcomes of this project are directly relevant to designing future UK agri-environment schemes, and we will work with project partners to demonstrate the potential of the combined model framework to inform real-world land-use decisions. The modelling framework can then be expanded in future to include other benefits (e.g. abundance of other species, water quality/quantity etc.) and identify optimum solutions for other land-use systems with competing environmental, social and economic demands (e.g. new developments balancing housing needs with green infrastructure).