Land Allocation and Valuation Models Phase 2

土地分配和估价模型第二阶段

• 批准号: NE/T012277/1
• 负责人: Peter Smith
• 金额: $ 11.56万
• 依托单位: University of Aberdeen
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FT012277%2F1
• 关键词: Land; Allocation; Valuation; Models; Phase

Land allocation models or Ecosystem service tools (ES tools) are simple descriptions of complex landscape processes which includes biogeochemical processes as well as demographic and socioeconomic influence. These ecosystem service tools range from simple excel based tools, to complex and detailed biophysical models with GIS mapping-based toolkits using simpler biophysical models, or empirical models providing an intermediate option. Simple tools such as the Natural Capital Planning tool (NCPT) or Eco-metric approaches are score-based approaches where as complex integrated models like InVEST can provide detailed quantitative, as well as economic, estimation of land management on various ecosystem services. These tools are often used for real decision making, estimating financial incentives associated with an investment on land management or predicting how sustainable development goals could be achieved through better land use. These tools vary greatly in their approaches and assumptions to simulate these complex human and nature interactions and recently there has been few model inter-comparison studies using mostly integrated models such as InVEST, LUCI and ARIES. However, more robust comparison of these simple to complex tools is required to understand how decision making can be influenced with use of tools of different complexity. In the Phase 1 stage of the work six ES tools/methods and a number of potential case studies were shortlisted, through consultation with stakeholders and steering group members and review of past studies. In Phase 2 we will road test the short-listed ES tools with real world case studies to test the following overarching hypothesis:1. Models of different complexity are comparable in providing evidence for decision making for land cover or land use management. Simple score based approaches could be used in a data /technical capacity limiting situation or may be as a tiered approach where simple tool can be used to decide the direction of impact with the land use change and in the next stage depending on the data/resource/technical capacity availability more complex detailed integrated models could be used for quantitative analysis and valuation (monetary or non-monetary) of future ecosystem services. 2. Impact of uncertainties in data input, model parameters and structure influences the outcome greatly. New approaches such as "Goal structured notations approach" could be used to assess assumptions in the tool.The project will bring together a group of modellers using different models, stakeholders which also includes case study experts who will provide input data for simulations and policy makers to one platform for a better understanding on how ES tools can help landscape decision making. Outcomes of this work will be individual high impact peer review papers for individual ES tools with simulation for few case studies and one model inter-comparison paper.

土地分配模型或生态系统服务工具（ES工具）是复杂景观过程的简单描述，其中包括生物地球化学过程以及人口统计和社会经济影响。这些生态系统服务工具从简单的基于Excel的工具到使用更简单的生物物理模型的基于GIS映射的工具包的复杂而详细的生物物理模型，或提供中间选项的经验模型。简单的工具，例如自然资本计划工具（NCPT）或生态 - 金属方法是基于分数的方法，因为像Invest这样的复杂综合模型可以提供详细的定量和经济，对各种生态系统服务的土地管理估算。这些工具通常用于真正的决策，估计与土地管理投资相关的经济激励措施，或者通过更好的土地使用来预测如何实现可持续发展目标。这些工具在模拟这些复杂的人类和自然相互作用的方法和假设上差异很大，最近很少有模型间比较比较研究主要使用Invest，Luci和Aries等集成模型。但是，需要对这些简单至复杂的工具进行更强大的比较，以了解如何使用不同复杂性的工具来影响决策。在工作的第1阶段，通过与利益相关者和指导小组成员进行磋商以及对过去的研究审查，六个ES工具/方法和许多潜在的案例研究被入围。在第2阶段，我们将通过现实世界的案例研究进行道路测试简短的ES工具，以检验以下基本假设：1。不同复杂性的模型在提供土地覆盖或土地利用管理的决策证据方面是可比的。简单的基于得分的方法可以用于数据/技术能力限制情况中，也可以作为一种分层方法，可以使用简单的工具来确定对土地使用变化的影响方向，并且在下一阶段，根据数据/资源/技术能力可用性，可以使用更复杂的详细集成模型来定量分析和估值（金钱或非企业）（未来的生态系统）。 2。不确定性在数据输入，模型参数和结构中的影响极大地影响了结果。诸如“目标结构符号方法”之类的新方法可用于评估工具中的假设。该项目将使用不同的模型，包括案例研究专家，将模拟专家组合在一起，这些专家将为一个平台提供仿真和政策制定者的输入数据，以更好地了解ES工具如何帮助制定景观。这项工作的结果将是单个高影响同行评审论文，用于单个ES工具，其中包括一些案例研究和一份模型间比较论文。