James Strittholt and Mike White have published a chapter in Making Transparent Environmental Management Decisions: Applications of the Ecosystem Management Decision Support System called Forest Conservation Planning.
The Ecosystem Management Decision Support (EMDS) system has been used around the world to support environmental analysis and planning in many different application areas, and it has been applied over a wide range of geographic scales, from forest stands to entire countries. An extensive sampling of this diversity of applications is presented in section 2, in which EMDS application developers describe the varied uses of the system. These accounts, together with the requisite background in section 1, provide valuable practical insights into how the system can be applied in the general domain of environmental management.Part II contains nine chapters that describe use of the system in specific application areas. In general, each chapter provides some background on the application domain, motivations for using EMDS in this context, a brief review of other EMDS applications in the domain, if applicable, a fuller discussion of a specific application, and aspects of analyses that worked well and didn’t work well.
White and Stritholt (‘‘Forest Conservation Planning’’) describe an EMDS application for spatially explicit conservation planning in forested landscapes. Its application is illustrated in two case studies: a conservation assessment of 1.5 million acres of the northern California Sierra Nevada region that was used to prioritize and expand land protection, and an 18 million acre conservation value assessment of the Alberta Foothills region that was used in multiuse forest planning. These case studies demonstrate how EMDS can be used to model diverse and complex landscape characteristics, using information about mixed precision, to inform conservation decision making across large regions.
The Northwest Forest Plan was implemented in 1994 to protect habitat for species associated with old-growth forests, including Northern Spotted Owls (Strix occidentailis caurina) in Washington, Oregon, and northern California (U.S.A.). Nevertheless, 10-year monitoring data indicate mixed success in meeting the ecological goals of the plan. We used the ecosystem management decision-support model to evaluate terrestrial and aquatic habitats across the landscape on the basis of ecological objectives of the Northwest Forest Plan, which included maintenance of late-successional and old-growth forest, recovery, and maintenance of Pacific salmon (Oncorhynchus spp.), and viability of Northern Spotted Owls. Areas of the landscape that contained habitat characteristics that supported these objectives were considered of high conservation value. We used the model to evaluate ecological condition of each of the 36, 180 township and range sections of the study area. Eighteen percent of the study area was identified as habitat of high conservation value. These areas were mostly on public lands. Many of the sections that contained habitat of exceptional conservation value were on Bureau of Land Management land that has been considered for management-plan revisions to increase timber harvests. The results of our model can be used to guide future land management in the Northwest Forest Plan area, and illustrate how decision-support models can help land managers develop strategies to better meet their goals.
As natural resource management agencies and conservation organizations seek guidance on responding to climate change, myriad potential actions and strategies have been proposed for increasing the long-term viability of some attributes of natural systems. Managers need practical tools for selecting among these actions and strategies to develop a tailored management approach for specific targets at a given location. We developed and present one such tool, the participatory Adaptation for Conservation Targets (ACT) framework, which considers the effects of climate change in the development of management actions for particular species, ecosystems and ecological functions. Our framework is based on the premise that effective adaptation of management to climate change can rely on local knowledge of an ecosystem and does not necessarily require detailed projections of climate change or its effects. We illustrate the ACT framework by applying it to an ecological function in the Greater Yellowstone Ecosystem (Montana, Wyoming, and Idaho, USA)—water flows in the upper Yellowstone River. We suggest that the ACT framework is a practical tool for initiating adaptation planning, and for generating and communicating specific management interventions given an increasingly altered, yet uncertain, climate.
Animals concentrate their activities within areas we call home ranges because information about places increases fitness. Most animals, and certainly all mammals, store information about places in cognitive maps—or neurally encoded representations of the geometric relations among places—and learn to associate objects or events with places on their map. I define the value of information as a time-dependent increment it adds to any appropriate currency of fitness for an informed versus an uninformed forager, and integrate it into simple conceptual models that help explain movements of animals that learn, forget, and use information. Unlike other space-use models, these recognize that movement decisions are based on an individual’s imperfect and ever-changing expectancies about the environment—rather than omniscience or ignorance. Using simple, deterministic models, I demonstrate how the use of such dynamic information explains why animals use home ranges, and can help explain diverse movement patterns, including systematic patrolling or ‘‘traplining,’’ shifting activity or focal areas, extra-home-range exploration, and seemingly random (although goal-directed and spatially contagious) movements. These models also provide insights about interindividual spacing patterns, from exclusive home ranges (whether defended as territories or not) to broadly overlapping or shared ranges. Incorporating this dynamic view of animal expectancies and information value into more-complex and realistic movement models, such as random-walk, Bayesian foraging, and multi-individual movement models, should facilitate a more comprehensive and empirical understanding of animal space-use phenomena. The fitness value of cognitive maps and the selective exploitation of spatial information support a general theory of animal space use, which explains why mammals have home ranges and how they use them.
Recent studies suggest that species distribution models (SDMs) based on fine-scale climate data may provide markedly different estimates of climate-change impacts than coarse-scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse-scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000-fold range of spatial scales (0.008–16 km2). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90 m digital elevation models and deriving bioclimatic predictors from them. As climate-data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine- and coarse-scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species’ range size. On average, SDMs projected onto 4 km climate data predicted 42% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800 m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4 km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net habitat area when predictive maps form the basis of conservation decision making.
Chapter Abstract:
Increasing temperatures have been recorded around the world, leading to changes in precipitation, sea-level rise and extreme events. Climate models are currently in use to simulate the effects of these changes on vegetation cover, which is a strong indicator of ecosystem changes in response to various drivers. Climate change, as well as anthropogenic stressors, is affecting forest dieback and tree-species migration. This chapter addresses the connections between changes in various forest types and the global soil carbon, nitrogen and hydrologic cycles, and related feedbacks between these factors and both natural and anthropogenic environmental changes. We discuss the ways these feedbacks between land use, vegetation changes and global nutrient and water cycles can lead to further climate change and soil degradation, which have profound effects on food security, and we conclude by proposing the use of soil characteristics as tools to inform land managers of challenges they may face in preserving valuable services from forested lands and cropping systems.
Ecosystem services play a crucial role in sustaining human well-being and economic viability. People benefit substantially from the delivery of ecosystem services, for which substitutes usually are costly or unavailable. Climate change will substantially alter or eliminate certain ecosystem services in the future. To better understand the consequences of climate change and to develop effective means of adapting to them, it is critical that we improve our understanding of the links between climate, ecosystem service production, and the economy. This study examines the impact of climate change on the terrestrial distribution and the subsequent production and value of two key ecosystem services in California: (1) carbon sequestration and (2) natural (i.e. nonirrigated) forage production for livestock. Under various scenarios of future climate change we predict that the provision and value of ecosystem services decline under most, but not all, future greenhouse gas trajectories. The predicted changes would result in decreases in the economic output for the state and global economy and illustrate some of the hidden costs of climate change. Since existing information is insufficient to conduct impact analysis across most ecosystem services, a comprehensive research program focused on estimating the impacts of climate change on ecosystem services will be important for understanding, mitigating and adapting to future losses in ecosystem service production and the economic value they provide.
Concern over rapid global changes and the potential for interactions among multiple threats are prompting scientists to combine multiple modelling approaches to understand impacts on biodiversity. A relatively recent development is the combination of species distribution models, land-use change predictions, and dynamic population models to predict the relative and combined impacts of climate change, land-use change, and altered disturbance regimes on species’ extinction risk. Each modelling component introduces its own source of uncertainty through different parameters and assumptions, which, when combined, can result in compounded uncertainty that can have major implications for management. Although some uncertainty analyses have been conducted separately on various model components – such as climate predictions, species distribution models, land-use change predictions, and population models – a unified sensitivity analysis comparing various sources of uncertainty in combined modelling approaches is needed to identify the most influential and problematic assumptions. We estimated the sensitivities of long-run population predictions to different ecological assumptions and parameter settings for a rare and endangered annual plant species (Acanthomintha ilicifolia, or San Diego thornmint). Uncertainty about habitat suitability predictions, due to the choice of species distribution model, contributed most to variation in predictions about long-run populations.
Biodiversity conservation, in an era of global change and scarce funding, benefits from approaches that simultaneously solve multiple problems. Here, we discuss conservation management of the island scrub-jay (Aphelocoma insularis), the only island-endemic passerine species in the continental United States, which is currently restricted to 250-square-kilometer Santa Cruz Island, California. Although the species is not listed as threatened by state or federal agencies, its viability is nonetheless threatened on multiple fronts. We discuss management actions that could reduce extinction risk, including vaccination, captive propagation, biosecurity measures, and establishing a second free-living population on a neighboring island. Establishing a second population on Santa Rosa Island may have the added benefit of accelerating the restoration and enhancing the resilience of that island’s currently highly degraded ecosystem. The proactive management framework for island scrub-jays presented here illustrates how strategies for species protection, ecosystem restoration, and adaptation to and mitigation of climate change can converge into an integrated solution.
Despite the scarcity of sustained funding to promote continuous record collection, scientists and citizens around the world are now generating large volumes of monitoring data that vary in quality, format, supporting documentation, and accessibility. Complex interactions between climate, fauna, flora, and human land use challenge the understanding and forecasting of the mechanisms of change. Diverse models are now being run at various spatial and temporal scales to understand past climate variability and its impacts, generate future climate and land use scenarios, and project potential future impacts to the planet’s inhabitants. Estimates of the uncertainty associated with past observations and climate proxies, and with the results from climate and climate impacts models are often discussed but rarely quantified in a useful way to help land emissions, land use (agriculture, urbanization, industrialization, energy resource acquisition), and conservation efforts. Conservation practitioners and land managers are struggling to synthesize the wealth of available information and heed warnings of the unpredictable human response to edge and information, and translate evolving science results into on-the-ground climate-aware strategies. Many agencies and NGOs are currently involved in synthesizing observations and simulations, developing land management strategies, and implementing those they judge are most likely to succeed or at least cause the least harm. Collaboration and effective information sharing is essential to work effectively towards common goals. This paper includes examples of source of climate change information, a brief summary of the types of models currently used in climate change science projects, and illustrations of collaborative efforts that address climate change issues specifically focused on the Gyrfalcon in panarctic regions.