For this project, we combined modern approaches to ecosystem services assessment with structured approaches to decision making (“structured decision making” or SDM) for ecological restoration planning. In the past, ecological restoration decisions utilized physicochemical and biological criteria as proxies for maximizing the ecological functioning of ecosystems. As the ecosystem services concept has evolved, modern viewpoints emphasize the need to make decisions based on the social benefits of ecological restoration, in terms of who benefits and by how much (see Martin 2017). Performing ecological restoration in an urban area, for example, is unlikely to achieve the full functioning of a pristine ecosystem, yet restoration in urban areas is likely to benefit a large number of people, particularly those who may not have access to the direct benefits of ecosystems, including clean air and water, recreation, education, and scenic and wildlife viewing. Our objective with this research is to test whether a social benefits approach to ecological restoration is useful to groups who plan and implement restoration in a real-world decision making context. We worked with the Woonasquatucket River Watershed Council to plan for wetland restoration in the watershed using the SDM approach. The Council participated and co-developed a spreadsheet-based decision support tool for screening 65 candidate restoration sites to help the organization seek that have the most balanced impact on ecosystem services and social equity. In sum, our approach proved valuable for restoration planning in the watershed, and our approach is in early stages of being considered by other restoration, conservation, and green infrastructure groups in Rhode Island, Alabama, Florida, and Puerto Rico.
In the field of environmental management, it is customary for researchers to integrate multiple monetary and non-monetary metrics to reveal tradeoffs in what costs or benefits could be gained or lost by choosing one management alternative over another. The field of multi-criteria decision analysis (MCDA) provides numerous methods that focus on applying mathematical models and preference measures to tradeoffs in outcomes to facilitate the evaluation of management alternatives for decision making purposes. Analysts and their stakeholder constituents should be cautioned that results depend not only on their preferences but the intuitive mathematical assumptions of each method. A critical dimension of transparency that is not often considered in studies using MCDA concerns providing decision makers with implications of the methodological assumptions of the various MCDA techniques. I used a simple hypothetical example to illustrate that many methods yield different results based on scaling and compensation assumptions. These results reinforce an assertion that decision makers should understand and, when possible, specify which methodological assumptions are important to their decision context. Specifically, a determination should be made as to whether management alternatives that have balanced outcomes should be preferred to alternatives that are well-valued on a number of outcomes but worse on others. Doing this could produce results that are most meaningful to decision making. For more information, see Martin & Mazzotta (2018) and real-world case study in Woonasquatucket River watershed, Rhode Island (coming soon).
Several of us at EPA Office of Research and Development and U.S. Geological Survey are developing an approach to evaluate the effectiveness of ecological restoration in urban areas based on social benefits (see Rapid Benefits Indicator Approach). It is important for us to clarify what we mean by the phrase ecological restoration. I researched all of the different definitions and contexts for how ecological restoration has been conceptualized (social, scientific, or both) over the past 40 years. I noticed that the definition has maintained a purely scientific connotation. The majority of past and present definitions indicate what restoration does – it assists in the recovery of natural ecosystem conditions. However, I realized that the conceptualization of ecological restoration has evolved from mainly scientific to social and scientific connotations based in part on why people restore ecosystems – to achieve common values and beliefs. An important time period in that evolution was between 1990-2004 when restoration theorists and practitioners proclaimed that ecological restoration was a process where the means, or value-laden restoration goals and objectives, could not be detached from the ends, or conditions of the restored ecosystem. Today, ecological restoration is a mainstream concept with dual social and scientific roles. In summary, the definition of ecological restoration has not kept up with the evolution and conceptualization of the phrase. So, I wrote an opinion article to inspire change. See Martin 2017.
This word cloud is based on words in The Society for Ecological Restoration definitions of ecological restoration from 1990, 1993, 1994, 1996, and 2002.
Man-made sources of pollution are causing damage to the quality of surface waters, wetlands, and estuaries in coastal New England communities. To protect and conserve valuable goods and services in coastal zones, new engagement tools are needed to communicate how decisions impact these environments and society. The U.S. EPA Atlantic Ecology Division is engaging in a scientist-teacher partnership to develop an educational watershed simulation tool. The simulation tool uses a coupled human and natural systems model and combinatorial simulation to build participants’ skills in evaluating tradeoffs associated with strategies to manage nutrient pollution in coastal water bodies. Concepts and design of the simulation tool were produced to foster question-driven environmental literacy that aligns with STEM concepts and the Next Generation Science Standards for science education. A prototype of the tool is in development. A desired future version of the simulation tool will be a web application with supplementary teaching modules to be used in middle and high school science classrooms.
We developed a method to operationalize the Driver-Pressure-State-Impact-Response (DPSIR) framework so that it may be used to produce qualitative cause-effect ecosystem service relationships in data poor situations. We applied our method on a collaborative case study for coastal water quality management on Cape Cod, Massachusetts. First, we developed DPSIR indicators to aid in a general understanding of how water quality management strategies may interact through human activities and the natural environmental to impacts ecosystem services. We are assigning qualitative measures of the strength of interaction between relevant indicators organized within a DPSIR framework. The measurements are used in a mathematical procedure to model plausible relationships between implementing management strategies and variations in ecosystem services outcome. This modeling exercise will be used in our structured decision making approach to water quality management on Cape Cod. Link to Martin et al. (2018)
Decision makers are unfamiliar with social science methods for preference construction/elicitation and criteria weighting. It is likely that the choice of method is dependent on the degrees of comfort decision facilitators have with certain methods. Therefore, decision makers may be unaware that the choice of method may influence the results of such an analysis. For this project, I conducted a web survey of water resource management groups that examined the context of weighting criteria for multi-criteria decision analysis. In Colorado, USA, eight basin stakeholder groups had previously developed hundreds of projects to address important water resource management challenges in the state (see Colorado’s Water Plan). The groups did not follow a structured and transferable approach with regard to project design that allowed for evaluating the consequences of the projects. To compare projects based on a common metric, I applied four strategies that underlie the primary implementation characteristics of the projects: water security, built infrastructure, river habitat, and cultural resources. The stakeholder groups took a web survey that asked for their preference judgments of the strategies to estimate preference weights. The split survey used two different preference measurement scales, direct rating and pairwise comparison, to investigate whether and how the measurement scales themselves may affect results. My results challenge stakeholders to reconsider what sectors of water management are important for prioritizing time and resources in the coming decades. In addition, researchers and decision analysts must consider the likelihood that results may be sensitive to the method(s) they choose and not necessarily to the value orientations of decision makers.
In accordance with legislation enacted by Colorado’s Water Conservation Board, eight independent stakeholder committees recently published lists of planned and ongoing water management projects to meet future water supply and demand needs for each major water basin in the state (Colorado’s Water Plan). With support from The Nature Conservancy’s Colorado Field Office, I designed a spreadsheet-based financial planning program in Microsoft Excel to investigate the set of environmental water management projects throughout Colorado. The decision support tool classified hundreds of independently described water projects based on establishing criteria common to each project. Preliminary economic costs for each project were estimated based on stakeholder communications and prior economic modeling in the state. This classification was performed to partition estimated project costs into similar categories based on the anticipated project outcomes. Summary statistics based on the results of this prioritization and what they mean to The Nature Conservancy’s strategic planning were investigated.
The ecological limits of hydrologic alteration (ELOHA, N. LeRoy Poff et al. 2010) is a new framework for regional environmental flow assessment. Several collaborative case studies are being carried out around the world. One case study quantified current streamflow-related risk conditions for social and ecological criteria at river segments throughout the Yampa-White Basin, Colorado (USA). To provide a systematic social process conducive to ELOHA, we conducted an interactive decision analysis with members of the stakeholder group who contracted the study and are tasked with making flow management decisions in the basin. This coarse analysis reveals a process by which river segments can be prioritized based on the flow-ecology risk data and user-defined preferences. (Martin et al. 2015)
This project integrated bayesian ecological response modeling, catchment irrigation models, and eWater’s hydrologic modeling software “Source” with theory and methods for decision analysis. In brief, we integrated simulation models of the river system alongside ecological and irrigation models to develop five objective functions in the Goulburn-Broken River catchment (Australia). Multi-objective optimization was applied to develop a set of efficient options to deliver environmental flows for ecological and irrigation needs in the catchment. These options provide trade-off information on the competing catchment needs. We developed an objective method for multi-criteria decision analysis to prioritize the water allocation options using combined statistical ordination and cluster analysis. Our approach is particularly useful for researchers with large multi-dimensional datasets like Pareto frontiers. (Martin et al. 2016)
A systematic river restoration planning approach was developed based on a case study in the upper Bremer River catchment in South East Queensland, Australia (Hermoso et al. 2015). The project integrated sediment load, ecological health, and economic predictive models with multiobjective optimization and decision analysis for catchment scale restoration planning. A sophisticated software was developed to spatially allocate river restoration actions at possible land use parcels throughout the catchment. The response of each restoration action to the multi-disciplinary catchment objectives was routed downstream to the catchment outlet where a single performance value was measured for each objective. An iterative multi-objective simulated annealing algorithm developed a Pareto front of over 500 ‘near-optimal’ restoration plans where each plan is a different spatially distributed set of restoration actions throughout the catchment. We objectively prioritized the near-optimal plans using analytical methods for multi-criteria decision analysis (MCDA) based on measuring geometric distances between the near-optimal plans and an ‘ideal’ but non-feasible reference plan in multi-dimensional coordinate space. The decision analysis achieved a reduction in the number of viable alternatives to a set of ‘better’ alternatives for deliberation and spatial restoration planning by managers. Combining these methods into an integrated conceptual process and application allows for systematic design and formal evaluation of tradeoffs associated with many alternative river restoration options at whole catchment scales. (Martin et al. 2016)
“Environmental flows” is a research discipline that emphasizes freshwater allocation in rivers to sustain desired ecological conditions and human well-being. The basis for environmental flow requirements has traditionally relied on hydrological and ecological data. Contemporary methods focus on detailed hydro-ecological relationships within river ecosystems; however, there is currently no structured approach to systematically incorporate socially relevant data into the environmental flows discipline. To address this limitation we developed a flexible framework that applies a social-ecological systems approach to account for multiple flow-related indicators that reflect both biophysical sustainability and societal preferences. First, we conceptualize the freshwater social-ecological system as a hierarchy of human and environmental domains. Then, we recommend stepwise procedures to assess flow-related vulnerabilities of important system attributes, address their feedbacks, and translate these assessments to a common classification for comparative analyses that guide holistic flow management decisions. (Martin et al. 2014)