CNH2-L: Solving Grand Challenges in Coupled Natural Human Systems: Predicting Effective Governance Strategies for Managing Invasive Species

生态系统面临着来自入侵物种的新的、意想不到的威胁--植物或动物被引入到它们并不起源的地方。美国著名的入侵物种包括欧洲椋鸟、斑马贻贝和水牛草。入侵物种会增加野火的风险，减少农业产量，破坏宝贵的自然生态系统。这些问题对决策者来说尤其令人烦恼，因为他们有责任避免新的环境威胁造成的危害，而这些威胁的原因和后果尚未得到很好的理解。该奖项将探讨在亚利桑那州南部入侵水牛草的传播。这项研究将集中在水牛草对生态条件的反应，土地利用模式和土地所有者使用的根除技术。研究结果将用于预测应对入侵物种政策的长期影响。研究结果将为自然资源管理人员和决策者提供新的方法和工具，以建立有效应对新出现的威胁的管理系统。与环境变化、生物入侵、人类迁移和土地利用变化相关的外部威胁威胁着全球综合社会环境（CNH2）系统的稳定性和弹性。决策者应对这些威胁的能力受到以下因素的限制：对综合社会环境系统如何应对紧急威胁的知识不全面，特别是对生态因素、土地使用做法、社会态度和行为以及政策反应如何共同影响生态系统的知识不全面。该奖项将以亚利桑那州南部的水牛草入侵为模型系统，探讨CNH系统动态如何应对紧急威胁，以及哪些政策和治理变化将促使土地管理者采取有效、积极和持续的行动来应对这些紧急威胁。将发展新的方法和理论来预测综合社会环境系统如何对变化作出反应：1）发展空间-人类-生态模型，一个基于主体的模型来预测自然和人类系统之间的相互作用; 2）进行调查，访谈和植物人口统计学研究，以经验参数化和运行模型; 3）与利益相关者和从业人员合作，共同产生关于政策选择的知识，其影响可以在模型中预测;以及4）询问迭代模型运行的结果，以发展关于在综合社会环境系统中实现有效预期治理的条件的可推广的理论。这项研究解决了发展预测方法的迫切需要，以模拟生态，社会，该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识产权进行评估来支持。优点和更广泛的影响审查标准。

Ecological systems face novel, unexpected threats from invasive species- plants or animals that are introduced to a place where they did not originate. Examples of well-known invasive species in the United States include European starlings, zebra mussels, and buffelgrass. Invasive species can increase the risk of wildfires, diminish agricultural yields, and destroy valued natural ecosystems. These problems are particularly vexing for policy makers, who are responsible for avoiding harms from new environmental threats whose causes and consequences are not yet well-understood. This award will explore the spread of invasive buffelgrass in Southern Arizona. The research will focus on buffelgrass response to ecological conditions, land-use patterns, and eradication techniques used by landowners. The results of the study will be used to predict the long-term effects of policies to address invasive species. The results will provide natural resource managers and policy makers with new approaches and tools to develop management systems that respond effectively to emerging threats. The project will also provide diverse students with interdisciplinary STEM training.External threats associated with environmental change, biological invasions, human migration, and changing land use threaten the stability and resiliency of integrated socio-environmental (CNH2) systems globally. Policy makers' ability to address these threats is limited by incomplete knowledge of how integrated socio-environmental systems will respond to emergent threats, particularly knowledge of how ecological factors, land-use practices, social attitudes and behaviors, and policy responses can jointly affect ecological systems. Using buffelgrass invasion in southern Arizona as a model system, the award will address how do CNH system dynamics change in response to emergent threats, and what policy and governance changes will prompt land managers to take effective, proactive, and sustained actions to address these emergent threats. New methods and theory will be developed to predict how integrated socio-environmental systems respond to change by: 1) developing the spatial-human-ecology model, an agent-based model to predict interactions between natural and human systems; 2) conducting surveys, interviews, and plant demographics studies to empirically parameterize and run the model; 3) working with stakeholders and practitioners to co-produce knowledge about policy options whose effects can be predicted in the model; and 4) interrogating the results of iterative model runs to develop generalizable theory about the conditions that enable effective anticipatory governance in integrated socio-environmental systems. This research addresses a critical need for development of predictive methods to model dynamic interactions between ecological, social, and policy systems and develops the scientific knowledge needed to provide resource managers with the necessary knowledge and tools to enable proactive management of emergent threats to CNH systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.