Policy learning in collaborative environmental governance processes

ABSTRACT

Collaborative governance processes have become a popular mechanism for addressing complex environmental problems. Their success is premised, in part, on the assumption that they promote learning among diverse participants, who are then better equipped to develop creative, consensus-oriented environmental management actions. Significant gaps remain, however, in our understanding of how collaborative governance processes foster learning and what impact increased learning has on policymaking outputs. To investigate these relationships, this study provides one of the first empirical applications of Heikkila and Gerlak's collective learning framework. Key framework concepts are operationalized via interview data and existing literature and then measured via survey data collected from participants in a collaborative environmental governance process in Colorado, U.S. Findings indicate that both internal and exogenous contextual factors affect how much an individual learns within a collective context. Additionally, participants who report more learning also more strongly agree that the process produced favorable outputs and outcomes. These findings advance theories of learning in collaborative contexts and inform process design to maximize learning.     

Learning in participatory environmental governance – its antecedents and effects. Findings from a case survey meta-analysis

ABSTRACT

Theory on participatory and collaborative governance maintains that learning is essential to achieve good environmental outcomes. Empirical research has mostly produced individual case studies, and reliable evidence on both antecedents and environmental outcomes of learning remains sparse. Given conceptual ambiguities in the literature, we define governance-related learning in a threefold way: learning as deliberation; as knowledge- and capacity-building; and as informing environmental outputs. We develop nine propositions that explain learning through factors characterizing governance process and context, and three propositions explaining environmental outcomes of learning. We test these propositions drawing on the ‘SCAPE’ database of 307 published case studies of environmental decision-making, using multiple regression models. Results show that learning in all three modes is explained to some extent by a combination of process- and context-related factors. Most factors matter for learning, but with stark differences across the three modes of learning, thus demonstrating the relevance of this differentiated approach. Learning modes build on one another: Deliberation is seen to explain both capacity building and informed outputs, while informed outputs are also explained by capacity building. Contrary to our expectations, none of the learning variables was found to significantly affect environmental outcomes when considered alongside the process- and context-related variables.     

A stakeholder dialogue on European vulnerability

A stakeholder dialogue was embedded in the ATEAM project to facilitate the development and dissemination of its European-wide vulnerability assessment of global change impacts. Participating stakeholders were primarily ecosystem managers and policy advisers interested in potential impacts on ‘Agriculture’, ‘Forestry’, ‘Water’, ‘Carbon storage’, ‘Biodiversity’ and ‘Mountain environments’ sectors. First, stakeholder dialogue approaches to integrated assessment are introduced. Methodological considerations on stakeholder selection and dialogue implementation and evaluation follow. The dialogue content and process are evaluated from the perspectives of stakeholders and scientists. Its usefulness in the research process and the relevance of outcomes for stakeholders are particularly considered. The challenging compromises required to perform innovative research, which seeks to achieve both peer scientific credibility and societal relevance, are emphasized. Effective stakeholder dialogues play a substantial role in raising the visibility and meaningfulness of vulnerability assessments as critical means to improve awareness on global change and its potential worrying impacts on society. They further provide scientists with critical information on ecosystem management and sectoral adaptive capacity. These processes of mutual learning and knowledge exchange moreover foster a better understanding of the potential and limits of global change modelling and vulnerability assessment for policy and ecosystem management.

Disciplined Planning,Structured Participation,and Collaborative Modeling — Applying Shared Vision Planning to Water Resources

Participatory planning applied to water resources has sparked significant interest and debate during the last decade. Recognition that models play a significant role in the formulation and implementation of design and management strategies has encouraged the profession to consider how such models can be best implemented. Shared Vision Planning (SVP) is a disciplined planning approach that combines traditional water resources planning methodologies with innovations such as structured public participation and the use of collaborative modeling, resulting in a more complete understanding and an integrative decision support tool. This study reviews these three basic components of SVP and explains how they are incorporated into a unified planning approach. The successful application of SVP is explored in three studies involving planning challenges: the National Drought Study, the Lake Ontario‐St. Lawrence River Study, and the Apalachicola‐Chattahoochee‐Flint/Alabama‐Coosa‐Tallapoosa River Basin Study. The article concludes by summarizing the advantages and limitations of this planning approach.     

Evaluating the Outcomes of Collaborative Modeling for Decision Support

Does collaborative modeling improve water resource management outcomes? How does collaborative modeling improve these outcomes? Does it always work? Under what conditions is collaborative modeling most appropriate? With support from the U.S. Army Corps of Engineers' Institute for Water Resources (IWR), researchers developed an evaluation framework to help address these questions. The framework links the effects of collaborative modeling on decision‐making processes with improvements in the extent to which resource management decisions, practices, and policies balance societal needs. Both practitioners' and participants' experiences suggest that under the right circumstances, collaborative modeling can generate these beneficial outcomes. Researchers developed performance measures and a survey to systematically capture these experiences and evaluate the outcomes of collaborative modeling processes. The survey can provide immediate feedback during a project to determine whether collaborative modeling is having the desired effect and whether course correction is warranted. Over the longer term, the systematic evaluation of collaborative modeling processes will help demonstrate in what ways and under what circumstances collaborative modeling is effective, inform and improve best practices, and raise awareness among water resource planners regarding the use of collaborative modeling for resource management decisions.     

COLLABORATIVE ENVIRONMENTAL DECISION MAKING IN OREGON WATERSHED GROUPS: PERCEPTIONS OF EFFECTIVENESS1

ABSTRACT: Collaborative watershed groups have formed at a significant rate throughout the United States in the last decade. Data on these groups, however, has been largely anecdotal and lacking in rigorous examination of the relationship between group formation, membership, process, and group effectiveness. Using a mail survey, Oregon watershed group participants were asked to identify who initiated the formation of the group, how efficiently the group formed, how the group determines membership, what decision making method the group uses, and how members perceive the group's effectiveness. Findings indicated that a majority believe that, because of their participation in a watershed group, they better understand issues in the watershed and the perspectives of others, but less than half believe that relationships with government decision makers or physical conditions in the watershed have improved. Members of citizen initiated groups rated their groups higher than government initiated groups on addressing difficult or controversial issues. Members of groups that use consensus responded most positively on whether the group gives fair consideration to dissenting opinions. Overall, groups with restricted membership systems rated themselves lowest on involving key decision making groups, timeliness in addressing issues, and overall effectiveness. These results raise concerns about this type of group membership system.     

基于数据同化的太湖叶绿素多模型协同反演

在国内外众多学者的不懈努力下,开发了大量的水质参数遥感估算反演模型,但不同的模型都具有其"局限性",只能从某个层面反映"真值".基于上述考虑,本研究发展了基于数据同化方法的太湖叶绿素a浓度多模型协同反演算法.利用2006~2009年太湖野外实测水体高光谱遥感反射率数据,构建了7个叶绿素a浓度反演模型;通过模型精度对比,最终遴选出6个适宜的叶绿素a浓度反演模型.进而使用不同模型组合,进行多模型协同反演.结果表明:1多模型协同反演算法的反演精度要高于单模型反演的反演精度,最优MAPE仅为22.4%;2随着参与多模型协同反演的模型个数的增加,其反演精度也逐渐提高,MAPE均值从25.6%降低到23.4%,RMSE均值从15.082μg·L-1降低到14.575μg·L-1,相关系数R均值从0.91提升到0.92;3通过对多模型协同反演产品的置信区间进行计算,可以有效地估算产品精度和误差,同时使得获取全湖反演叶绿素a浓度的误差空间分布情况成为可能.     

生物法与化学法协同处理污水技术优化研究

为实现污水厂的高效运行,提出了一种UCT工艺与混凝沉淀工艺的协同运行方式.通过分析处理过程中的不足和影响因素,采取了提高过程污泥浓度的方式.对排泥泵池污泥浓缩方法进行了研究,采取排出排泥泵池上部的上清液,提高了排泥泵池的污泥浓度,减小了排泥体积;对污泥缓冲池的运行过程进行优化研究,采取调整污泥缓冲池的排泥方式和排泥时间,提出了间隔排泥的方法,提高了污泥缓冲池的污泥浓度.这些措施实现了UCT工艺与混凝沉淀工艺的协同高效运行,措施效益明显,可推广应用于类似污水厂的设计与运行.