The challenges of integrating biodiversity and ecosystem services monitoring and evaluation at a landscape-scale wetland restoration project in the UK

There is an increasing emphasis on the restoration of ecosystem services as well as of biodiversity, especially where restoration projects are planned at a landscape scale. This increase in the diversity of restoration aims has a number of conceptual and practical implications for the way that restoration projects are monitored and evaluated. Landscape-scale projects require monitoring of not only ecosystem services and biodiversity but also of ecosystem processes since these can underpin both. Using the experiences gained at a landscape-scale wetland restoration project in the UK, we discuss a number of issues that need to be considered, including the choice of metrics for monitoring ecosystem services and the difficulties of assessing the interactions between ecosystem processes, biodiversity, and ecosystem services. Particular challenges that we identify, using two pilot data sets, include the decoupling of monetary metrics used for monitoring ecosystem services from biophysical change on the ground and the wide range of factors external to a project that influence the monitoring results. We highlight the fact that the wide range of metrics necessary to evaluate the ecosystem service, ecosystem process, and biodiversity outcomes of landscape-scale projects presents a number of practical challenges, including the need for high levels of varied expertise, high costs, incommensurate monitoring outputs, and the need for careful management of monitoring results, especially where they may be used in making decisions about the relative importance of project aims.

Constructing stability landscapes to identify alternative states in coupled social-ecological agent-based models

The resilience of a social-ecological system is measured by its ability to retain core functionality when subjected to perturbation. Resilience is contextually dependent on the state of system components, the complex interactions among these components, and the timing, location, and magnitude of perturbations. The stability landscape concept provides a useful framework for considering resilience within the specified context of a particular social-ecological system but has proven difficult to operationalize. This difficulty stems largely from the complex, multidimensional nature of the systems of interest and uncertainty in system response. Agent-based models are an effective methodology for understanding how cross-scale processes within and across social and ecological domains contribute to overall system resilience. We present the results of a stylized model of agricultural land use in a small watershed that is typical of the Midwestern United States. The spatially explicit model couples land use, biophysical models, and economic drivers with an agent-based model to explore the effects of perturbations and policy adaptations on system outcomes. By applying the coupled modeling approach within the resilience and stability landscape frameworks, we (1) estimate the sensitivity of the system to context-specific perturbations, (2) determine potential outcomes of those perturbations, (3) identify possible alternative states within state space, (4) evaluate the resilience of system states, and (5) characterize changes in system-scale resilience brought on by changes in individual land use decisions.

U.S. wildfire governance as social-ecological problem

There are fundamental spatial and temporal disconnects between the specific policies that have been crafted to address our wildfire challenges. The biophysical changes in fuels, wildfire behavior, and climate have created a new set of conditions for which our wildfire governance system is poorly suited to address. To address these challenges, a reorientation of goals is needed to focus on creating an anticipatory wildfire governance system focused on social and ecological resilience. Key characteristics of this system could include the following: (1) not taking historical patterns as givens; (2) identifying future social and ecological thresholds of concern; (3) embracing diversity/heterogeneity as principles in ecological and social responses; and (4) incorporating learning among different scales of actors to create a scaffolded learning system.