Land Allocation and Valuation Models Phase 2

土地分配模型或生态系统服务工具（ES工具）是对复杂景观过程的简单描述，包括生物地球化学过程以及人口和社会经济影响。这些生态系统服务工具的范围从简单的基于excel的工具，到复杂而详细的生物物理模型，以及基于GIS制图的工具包，使用更简单的生物物理模型，或者提供中间选择的经验模型。简单的工具，如自然资本规划工具（npt）或生态计量方法是基于分数的方法，而像InVEST这样的复杂综合模型可以提供详细的定量和经济的土地管理对各种生态系统服务的估计。这些工具通常用于真正的决策，估计与土地管理投资有关的财政激励，或预测如何通过更好地利用土地来实现可持续发展目标。这些工具在模拟这些复杂的人类与自然相互作用的方法和假设方面差异很大，最近很少有使用InVEST、LUCI和ARIES等主要集成模型的模型间比较研究。然而，需要对这些简单工具和复杂工具进行更可靠的比较，以了解使用不同复杂性的工具如何影响决策。在第一阶段的工作中，经谘询持份者和督导小组成员，以及检讨过往的研究，六项环境评估工具/方法和若干可能的个案研究被列入候选名单。在第二阶段，我们将用现实世界的案例研究来测试入围的ES工具，以测试以下总体假设：不同复杂程度的模型在为土地覆盖或土地利用管理决策提供证据方面具有可比性。在数据/技术能力有限的情况下，可以使用简单的基于分数的方法，也可以作为一种分层方法，使用简单的工具来决定土地利用变化的影响方向，在下一阶段，根据数据/资源/技术能力的可用性，可以使用更复杂、详细的综合模型对未来生态系统服务进行定量分析和评估（货币或非货币）。2. 数据输入、模型参数和结构的不确定性对结果的影响很大。可以使用诸如“目标结构化符号方法”之类的新方法来评估工具中的假设。该项目将把一组使用不同模型的建模者、利益相关者（包括为模拟提供输入数据的案例研究专家）和政策制定者聚集在一个平台上，以更好地了解ES工具如何帮助景观决策。这项工作的结果将是针对个别ES工具的个别高影响力同行评议论文，其中包括对少数案例研究的模拟和一份模型相互比较论文。

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.