A framework for interdisciplinary understanding of rivers as ecosystems

Dollar, Evan S.J.; James, C. S.; Rogers, Kevin H.; Thoms, Martín

doi:10.1016/j.geomorph.2006.07.022

Cited by 153 publications

(128 citation statements)

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“…A time scale is included as a dimension of each spatial scale in some approaches (e.g. Habersack, 2000;Dollar et al, 2007), whereas others incorporate historical analyses that track human interventions or changes in units through time at some spatial scales (e.g. Rosgen, 1994;Montgomery and MacDonald, 2002;Brierley and Fryirs, 2005;Beechie et al, 2010;Rinaldi et al, 2013aRinaldi et al, , 2015.…”

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confidence: 99%

A multi-scale hierarchical framework for developing understanding of river behaviour to support river management

et al. 2015

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Contact CEH NORA team at noraceh@ceh.ac.ukThe NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner. 1The following paper is the final version prior to publication on 22 September 2015. are proposed, the way in which indicators could contribute to classification is discussed. All of the methods described in Table 1 consider a hierarchy of spatial units, but the degree to which they develop the other aspects of the conceptual approach proposed by Frissell et al.(1986) varies widely.2. Many of the frameworks focus entirely on hydromorphological processes and forms that are either directly measured or inferred. This is because interactions between processes and forms control the dynamic morphology or behaviour of rivers and their mosaics of habitats.Hydromorphological processes drive longitudinal and lateral connectivity within river networks and corridors, the assemblage and turnover of physical habitats, and the sedimentary and vegetation structures associated with those habitats.3. Some frameworks are conceptual, providing a way of thinking about or structuring analyses of river systems, and interpreting their processes, morphology and function (e.g. Frissell et al., 1986;Habersack, 2000;Fausch et al., 2002;Thorp et al., 2006;Beechie et al., 2010;McCluney et al., 2014). Some frameworks are more quantitative, generating one or more indices or classifications of spatial units that support assessment of river systems (e.g. Rosgen, 1994;González del Tánago and García de Jalón, 2004;Merovich et al., 2013;Rinaldi et al., 2013Rinaldi et al., , 2015a MacDonald, 2002;Brierley and Fryirs, 2005;Beechie et al., 2010; Rinaldi et al., 2013a Rinaldi et al., , 2015.In some cases, theoretical or historical analyses or consideration of specific future scenarios are used to develop space-time understanding that can support management decisionmaking (e.g. Buffington, 1997, 1998;Montgomery and MacDonald, 2002;Benda et al., 2004;Brierley and Fryirs, 2005;McCluney et al., 2014 , 1997, 1998Montgomery and MacDonald, 2002;Benda et al., 2004;Brierley and Fryirs, 2005;Merovich et al., 2013;Rinaldi et al., 2013Rinaldi et al., , 2015a. Furthermore, some of the frameworks include indicators of human pressures and their impacts (e.g. Merovich et al., 2013;McCluney et al., 2014;Rinaldi et al., 2013Rinaldi et al., , 2015a.6. Finally, although most frameworks could be described as incorporating processes to some degree, some methods are particularly process-based, even when processes are inferred from forms and associations rather than being quantified by direct measurements.Frameworks that consider temporal dynamics and trajectories of historical change (see point 4, above) are particularly effective in developing understanding of processes and the impacts of changed processes cascading through time and across spatial scales.Although the list of frameworks presented in Table 1 is far from comprehensive, ...

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A multi-scale hierarchical framework for developing understanding of river behaviour to support river management

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“…Lower levels within an organization influence those at higher levels through their faster rate flow of information and emerging properties. Hierarchy theory is applicable to systems with natural hierarchical structures and is appropriate for use in natural, Ecology and Society 20(1): 34 http://www.ecologyandsociety.org/vol20/iss1/art34/ public, and societal systems problems (Dollar et al 2007), dealing with complexity.…”

Section: Hierarchy Theorymentioning

confidence: 99%

“…The frameworks of Thoms and Parsons (2002) and Dollar et al (2007) provide examples of how individual disciplinary (or subsystem) hierarchical structures use scale as the currency for linking between disciplines. Recognition of spatial and temporal scales inherent to the levels of organization of a disciplinary hierarchy makes integration of multiple subsystems possible (Dollar et al 2007). Integration of scales allows researchers and managers to ask appropriate questions through recognition that there are causal linkages across different disciplines or organizations.…”

Section: Hierarchy Theorymentioning

confidence: 99%

“…Integration of scales allows researchers and managers to ask appropriate questions through recognition that there are causal linkages across different disciplines or organizations. There are four steps in the application of the frameworks put forward by Thoms and Parsons (2002) and Dollar et al (2007). The first step requires identification of various subsystems and the second focuses on describing the relevant levels of organization that characterize the different subsystems in the context of the issue/ problem being addressed.…”

Section: Hierarchy Theorymentioning

confidence: 99%

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Integrative learning for practicing adaptive resource management

McLoughlin¹,

Thoms²

2015

E&S

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ABSTRACT. Adaptive resource management is a learning-by-doing approach to natural resource management. Its effective practice involves the activation, completion, and regeneration of the "adaptive management cycle" while working toward achieving a flexible set of collaboratively identified objectives. This iterative process requires application of single-, double-, and triple-loop learning, to strategically modify inputs, outputs, assumptions, and hypotheses linked to improving policies, management strategies, and actions, along with transforming governance. Obtaining an appropriate balance between these three modes of learning has been difficult to achieve in practice and building capacity in this area can be achieved through an emphasis on reflexive learning, by employing adaptive feedback systems. A heuristic reflexive learning framework for adaptive resource management is presented in this manuscript. It is built on the conceptual pillars of the following: stakeholder driven adaptive feedback systems; strategic adaptive management (SAM); and hierarchy theory. The SAM Reflexive Learning Framework (SRLF) emphasizes the types, roles, and transfer of information within a reflexive learning context. Its adaptive feedback systems enhance the facilitation of single-, double-, and triple-loop learning. Focus on the reflexive learning process is further fostered by streamlining objectives within and across all governance levels; incorporating multiple interlinked adaptive management cycles; having learning as an ongoing, nested process; recognizing when and where to employ the three-modes of learning; distinguishing initiating conditions for this learning; and contemplating practitioner mandates for this learning across governance levels. The SRLF is a key enabler for implementing the "adaptive management cycle," and thereby translating the theory of adaptive resource management into practice. It promotes the heuristics of adaptive management within a cohesive framework and its deployment guides adaptive resource management within and beyond typical single-loop learning, across all governance levels.

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“…Each issue or system attribute can appear quite different, and interactions have quite different outcomes, under different contexts and at different scales (Levin 1998, Dollar et al 2007). Spatial and historical context are very important, but so too are the different participants' value systems and how they lead to different outcomes.…”

Section: Situational Awareness (See Text Box 2)mentioning

confidence: 99%

Fostering Complexity Thinking in Action Research for Change in Social–Ecological Systems

Rogers¹,

Luton²,

Biggs³

et al. 2013

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103

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ABSTRACT. Complexity thinking is increasingly being embraced by a wide range of academics and professionals as imperative for dealing with today's pressing social-ecological challenges. In this context, action researchers partner directly with stakeholders (communities, governance institutions, and work resource managers, etc.) to embed a complexity frame of reference for decision making. In doing so, both researchers and stakeholders must strive to internalize not only "intellectual complexity" (knowing) but also "lived complexity" (being and practicing). Four common conceptualizations of learning (explicit/tacit knowledge framework; unlearning selective exposure; conscious/competence learning matrix; and model of learning loops) are integrated to provide a new framework that describes how learning takes place in complex systems. Deep reflection leading to transformational learning is required to foster the changes in mindset and behaviors needed to adopt a complexity frame of reference. We then present three broad frames of mind (openness, situational awareness, and a healthy respect for the restraint/ action paradox), which each encompass a set of habits of mind, to create a useful framework that allows one to unlearn reductionist habits while adopting and embedding those more conducive to working in complex systems. Habits of mind provide useful heuristic tools to guide researchers and stakeholders through processes of participative planning and adaptive decision making in complex social-ecological systems.

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A framework for interdisciplinary understanding of rivers as ecosystems

Cited by 153 publications

References 25 publications

A multi-scale hierarchical framework for developing understanding of river behaviour to support river management

A multi-scale hierarchical framework for developing understanding of river behaviour to support river management

Integrative learning for practicing adaptive resource management

Fostering Complexity Thinking in Action Research for Change in Social–Ecological Systems

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A framework for interdisciplinary understanding of rivers as ecosystems

Cited by 153 publications

References 25 publications

A multi-scale hierarchical framework for developing understanding of river behaviour to support river management

A multi-scale hierarchical framework for developing understanding of river behaviour to support river management

Integrative learning for practicing adaptive resource management

Fostering Complexity Thinking in Action Research for Change in Social&#8211;Ecological Systems

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Fostering Complexity Thinking in Action Research for Change in Social–Ecological Systems