Exploring the incentivisation and biodiversity returns of treescapes using agent based models

该项目的广泛目标是通过了解政策干预产生的反馈，帮助从健康的树枝逃生中提供保护成果。树丛是林地的延伸网络，提供许多生态系统服务，例如福祉、文化服务、生物多样性。这些网络的时空结构(“连通性”)影响生物多样性和对气候变化的稳健性，但也会暴露在病虫害等威胁之下。从土地管理者的决策中获得的广泛的私人和社会效益受到多种行为者之间相互作用的影响，这些决策是在不确定和不完善的信息背景下作出的，以及自然-社会系统对政策干预的反应。标准的博弈论模型框架无法捕捉到这些相互作用的时空复杂性。我们将使用一种新的基于主体的建模方法，在政策激励和其他计划(如环境土地管理计划和“大型自然基金”)的背景下，捕捉这些社会生态相互作用。具体地说：(I)我们将模拟土地管理者(例如农民)的决策如何受到他们的信念和预期的经济利益、邻近农民的行为以及他们管理的景观的结果的影响；(Ii)我们将使用人口-和集合人口动态来模拟这些树木逃生地带的自然人口。这将使我们能够探索不同激励结构(不同的支付方案、不同的指标)在交付保护成果方面的有效性，并确定意想不到的后果(例如，增加连通性可以使生物多样性受益，但也会增加疾病和极端事件的风险)。

The broad aim of this project is to help deliver conservation outcomes from healthy treescapes by understanding the feedbacks created by policy interventions. Treescapes are extended networks of woodland that provide many ecosystem services, e.g. wellbeing, cultural services, biodiversity. The spatiotemporal structure ("connectivity") of these networks affects biodiversity and robustness to climate change, but also exposure to threats such as pests and diseases. The wide range of private and social benefits derived from land managers' decisions are affected by the interactions among the multiple actors across the landscape, the uncertainty and imperfect information context in which these decisions take place, as well as the response of natural-social systems to policy interventions. Standard game-theoretic modelling frameworks cannot capture the spatio-temporal complexity of these interactions.We will use a novel agent-based modelling approach to capture these socio-ecological interactions in the context of policy incentives and other schemes (e.g. Environmental Land Management Scheme & "Big Nature Fund"). Specifically: (i) we will model how the decisions of land managers (e.g. farmers) are affected by their beliefs and expected economic benefits, the behaviour of neighbouring farmers, and the outcomes in the landscapes they manage; (ii) we will use population- and metapopulation dynamics to model the natural populations in these treescapes. This will allow us to explore the effectiveness of different incentive structures (different payment schemes, different metrics) in delivering conservation outcomes, and identify unintended consequences (e.g. increased connectivity can benefit biodiversity, but also promote risks from disease and extreme events).