James J. Kay

Bio: James J. Kay is an academic researcher from University of Waterloo. The author has contributed to research in topics: Ecosystem management & Systems ecology. The author has an hindex of 22, co-authored 24 publications receiving 3440 citations.

Ecological Integrity and the Management of Ecosystems

Abstract: SETTING THE STAGE The Notion of Natural and Cultural Integrity, Henry A Reiger Considerations of Scale and Hierarchy, Anthony W King Applying Notions of Ecological Integrity, Robert Steedman and Wolfgang Haider Choosing Indicators of Ecosystem Integrity: Wetlands as a Model System, Paul A Keddy, Harold T Lee and Irene C Wisheu APPLYING THE CONCEPTS Measuring Biological Integrity: Lessons from Streams, James R Karr Monitoring for Ecosystem Integrity, RE Munn National and Regional Scale Measures of Canada's Ecosystem Health, IB Marshall, H Hirvonen and E Wiken National Environmental Monitoring: A Case Study of the Atlantic Maritime Region, NL Shackell and B Freedman Monitoring and Measuring Ecosystem Integrity in Canadian National Parks, Stephen Woodley An Approach to the Development of Biological Sediment Guidelines, Trevor B Reynoldson and Michael A Zarull On the Nature of Ecological Integrity: Some Closing Comments, James J Kay Index

Embracing Complexity the Challenge of the Ecosystem Approach

Abstract: As environmental degradation and change continues, decision makers and managers feel significant pressure to rectify the situation. Scientists, in turn, find themselves under pressure to set out simple and clear rules for proper ecosystem management. The response has been one of frustration. Michael Soule and Laurence Slobdokin both loudly complain that ecology is an intractable science, immature and not very helpful. Kristin Shrader-Frechette and Robert Peters reproach ecologists for not producing simple testable hypotheses.1 Meanwhile policy makers and managers clamour for a measure of ecosystem integrity whose value in different situations can be predicted by simulation models. The question on everyone’s mind is “what does ecosystem science identify as the main, simple, basic, universal laws which will allow quantitative prediction of ecosystem behaviour and what are the resulting rules for ecosystem management?”

Resilience: the emergence of a perspective for social-ecological systems analyses

Abstract: The resilience perspective is increasingly used as an approach for understanding the dynamics of social–ecological systems. This article presents the origin of the resilience perspective and provides an overview of its development to date. With roots in one branch of ecology and the discovery of multiple basins of attraction in ecosystems in the 1960–1970s, it inspired social and environmental scientists to challenge the dominant stable equilibrium view. The resilience approach emphasizes non-linear dynamics, thresholds, uncertainty and surprise, how periods of gradual change interplay with periods of rapid change and how such dynamics interact across temporal and spatial scales. The history was dominated by empirical observations of ecosystem dynamics interpreted in mathematical models, developing into the adaptive management approach for responding to ecosystem change. Serious attempts to integrate the social dimension is currently taking place in resilience work reflected in the large numbers of sciences involved in explorative studies and new discoveries of linked social–ecological systems. Recent advances include understanding of social processes like, social learning and social memory, mental models and knowledge–system integration, visioning and scenario building, leadership, agents and actor groups, social networks, institutional and organizational inertia and change, adaptive capacity, transformability and systems of adaptive governance that allow for management of essential ecosystem services.

Adaptive governance of social-ecological systems

Abstract: ▪ Abstract We explore the social dimension that enables adaptive ecosystem-based management. The review concentrates on experiences of adaptive governance of social-ecological systems during periods of abrupt change (crisis) and investigates social sources of renewal and reorganization. Such governance connects individuals, organizations, agencies, and institutions at multiple organizational levels. Key persons provide leadership, trust, vision, meaning, and they help transform management organizations toward a learning environment. Adaptive governance systems often self-organize as social networks with teams and actor groups that draw on various knowledge systems and experiences for the development of a common understanding and policies. The emergence of “bridging organizations” seem to lower the costs of collaboration and conflict resolution, and enabling legislation and governmental policies can support self-organization while framing creativity for adaptive comanagement efforts. A resilient social-eco...

Resilience Management in Social-ecological Systems: a Working Hypothesis for a Participatory Approach

Abstract: Approaches to natural resource management are often based on a presumed ability to predict probabilistic responses to management and external drivers such as climate. They also tend to assume that the manager is outside the system being managed. However, where the objectives include long-term sustainability, linked social-ecological systems (SESs) behave as complex adaptive systems, with the managers as integral components of the system. Moreover, uncertainties are large and it may be difficult to reduce them as fast as the system changes. Sustainability involves maintaining the functionality of a system when it is perturbed, or maintaining the elements needed to renew or reorganize if a large perturbation radically alters structure and function. The ability to do this is termed "resilience." This paper presents an evolving approach to analyzing resilience in SESs, as a basis for managing resilience. We propose a framework with four steps, involving close involvement of SES stakeholders. It begins with a stakeholder-led development of a conceptual model of the system, including its historical profile (how it got to be what it is) and preliminary assessments of the drivers of the supply of key ecosystem goods and services. Step 2 deals with identifying the range of unpredictable and uncontrollable drivers, stakeholder visions for the future, and contrasting possible future policies, weaving these three factors into a limited set of future scenarios. Step 3 uses the outputs from steps 1 and 2 to explore the SES for resilience in an iterative way. It generally includes the development of simple models of the system's dynamics for exploring attributes that affect resilience. Step 4 is a stakeholder evaluation of the process and outcomes in terms of policy and management implications. This approach to resilience analysis is illustrated using two stylized examples.

Adaptive co-management for social–ecological complexity

Abstract: Building trust through collaboration, institutional development, and social learning enhances efforts to foster ecosystem management and resolve multi-scale society–environment dilemmas One emerging approach aimed at addressing these dilemmas is adaptive co-management This method draws explicit attention to the learning (experiential and experimental) and collaboration (vertical and horizontal) functions necessary to improve our understanding of, and ability to respond to, complex social–ecological systems Here, we identify and outline the core features of adaptive co-management, which include innovative institutional arrangements and incentives across spatiotemporal scales and levels, learning through complexity and change, monitoring and assessment of interventions, the role of power, and opportunities to link science with policy