DISES: Cumulative effects of ecological and social stressors on the dynamics of integrated ranching-wildlife systems: drought, wolves, and human decision-makers

随着世界各地环境变化的加剧，人类和野生动物都面临着更大的不确定性和风险，威胁着人类的生计和野生动物的生物多样性。这项研究旨在了解多种压力来源如何影响美国西部共享牧场的人类，自由放养的牲畜和野生动物。越来越频繁和严重的干旱使得野生食草动物和牛的植物饲料变得难以预测和丰富，即使灰狼回归部分地区增加了被捕食的风险。因此，鹿和麋鹿等野生动物，以及自由放养的牲畜，可能被迫在食物和安全之间进行权衡，而在公共土地上放牧的牧场主可能面临更多的不确定性。本研究将评估(1)干旱和狼如何相互作用影响野生食草动物和自由放养的牛在景观中的分布；(2)决策者如何应对这两种压力来源；(3)通过新的野生动物和植物预测应用程序提供的信息如何被牧场主和野生动物管理者接收和使用。该项目还将通过一部纪录片提高公众对牧场生态系统中人类与野生动物的联系和相互作用的认识，并培训公民科学家对牧场野生动物被相机捕获的图像进行分类。在这个项目的过程中，将培养一批不同的本科生和研究生，以及一名博士后研究员。该项目的成果包括更好地了解气候和食肉动物风险如何影响人类决策，以及人类如何通过放牛和野生动物迁移影响牧场食物网，从而可能增加人类与野生动物在不断变化的环境中共存的机会。气候变化带来的生态变化可能与其他变化源（如大型食肉动物的重新定居）发生强烈的相互作用，从而改变食物网动态，并可能减少生态系统对人类的供应。这种互动产生的不确定性也对人类的决策提出了挑战。关于气候变化如何通过野生食物网影响人类-野生动物系统，以及自然资源决策者如何应对这种压力，我们的知识存在一个关键空白。我们假设多种环境压力因素（如气候变化和新的捕食者）将对人类-野生动物系统产生复杂的相互作用。影响可能通过共享食物网中捕食者、猎物、家畜和植物之间的营养相互作用发生，可能减少人类对共享生态系统的供给，降低人类对掠食性和竞争性野生动物的容忍度，并增加自然资源决策者的不确定性。迫切需要发展模型、工具和理论，以(a)了解多种压力源如何相互影响人类和家畜所处的食物网，以及(B)识别和量化自然资源决策者和人类-野生动物系统对多种环境压力的反馈。这些信息将有助于确定系统弹性的潜在“临界点”，并允许更好地管理相互作用的荒地和农业系统。利用俄勒冈州和爱达荷州狼群存在和干旱组合的研究地点的因子设计，我们将研究牧场主-野生动物-植物的动态。数据将来自牧场主调查、野生动物相机网格、地面调查和遥感植物数据。我们将社会和生态数据整合到一个结构方程模型框架中，这将为牧场主和管理者在未来的决策中提供牲畜捕食和竞争风险的生态预测。为了理解自然资源管理者的决策，这比牧场主的决策发生在更大的空间尺度上，我们将使用公开的野生动物和社会数据以及遥感环境特征对美国西部的牧场SES进行大尺度分析。通过分析这些空间尺度上的决策，我们期望能够识别牧场SES中人类和野生动物组成部分的关键反馈、突发现象和潜在的恢复力临界点。该项目由综合社会环境系统动力学（DISES）和促进竞争研究的既定计划（EPSCoR）共同资助。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

As environmental changes intensify around the world, both humans and wildlife face greater uncertainty and risk, threatening both human livelihoods and wildlife biodiversity. This research seeks to understand how multiple sources of stress impact humans, free-ranging livestock, and wildlife in shared rangelands in the western US. Increasingly frequent and more severe droughts make plant forage for wild herbivores and cattle less predictable and abundant, even as the return of gray wolves to parts of the landscape increases predation risk. As a result, wildlife such as deer and elk, as well as free-ranging livestock, may be forced to trade off food and security, and ranchers grazing their cattle on public land may face more uncertainty. This research will assess (1) how drought and wolves interact to affect wild herbivores and free-ranging cattle distributions across the landscape, (2) how decision-makers respond to these two sources of stress, and (3) how information, provided via a new wildlife and plant forecasting application, is received and used by both ranchers and wildlife managers. The project will also increase public awareness of human and wildlife connections and interactions in rangeland ecosystems via a documentary film, as well as by training citizen scientists to classify camera-trapped images of rangeland wildlife. A diverse group of undergraduate and graduate students as well as a post-doctoral researcher will be trained over the course of this project. Outcomes of this project include a better understanding of how climate and carnivore risks affect human decision-making, as well as how humans impact rangeland food webs via cattle stocking and wildlife removal, potentially leading to increased opportunities for coexistence between humans and wildlife in changing environments.Ecological shifts brought about by climatic change can strongly interact with other sources of change, such as recolonizing large carnivores, to alter food web dynamics and potentially reduce ecosystem provisioning for humans. The uncertainty created by such interactions also challenges human decision-making. A critical gap exists in our knowledge of how climate change affects human-wildlife systems via wild food webs, and how natural resource decision-makers respond to such stress. We hypothesize that multiple environmental stressors (e.g., climate change and novel predators) will have complex and interactive effects on human-wildlife systems. Effects will likely occur via trophic interactions among predators, prey, domestic animals, and plants within shared food webs, potentially reducing the provisioning of humans from the shared ecosystem and human tolerance for predatory and competitive wildlife, and increasing uncertainty for natural resource decision-makers. There is a pressing need to advance models, tools and theory to (A) understand how multiple stressors interactively affect food webs in which humans and domestic animals are embedded, and (B) identify and quantify feedbacks among natural resource decision-makers and human-wildlife systems in response to multiple environmental stressors. Such information would assist in identifying potential “tipping points” in system resiliency and allow for better management of interacting wildland and agricultural systems. Using a factorial design of study sites across combinations of wolf presence and drought in Oregon and Idaho, we will study rancher-wildlife-plant dynamics. Data will stem from rancher surveys, wildlife camera grids, and ground-surveyed and remotely-sensed plant data. We will integrate social and ecological data into a structural equation modeling framework, which will drive ecological forecasts of predation and competition risk to livestock for ranchers and managers to use in future decision making. To understand natural resource manager decisions, which occur at larger spatial scales than rancher decisions, we will conduct a broad-scale analysis of the rangeland SES across the Western US using publicly-available wildlife and social data and remotely-sensed environmental characteristics. By analyzing decision-making across these spatial scales, we anticipate being able to identify key feedbacks, emergent phenomena, and potential tipping points in resilience for the human and wildlife components of the rangeland SES.This project is jointly funded by the Dynamics of Integrated Socio-Environmental Systems (DISES) and the Established Program to Stimulate Competitive Research (EPSCoR).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.