River Delta Adaptive Management Strategy/4. Organizing Learning around Critical Dynamics
- Effort References
- Wiki Rules
- Wiki text does not reflect the policy or opinion of any agency or organization
- Please adhere to our Social Contract and Style Guide
- Complain here, and be nice.
Organizing Learning around Critical Dynamics[edit]
Rather than segregating delta ecosystems by scientific disciplines or lists of parameters, we propose a management framework that identifies a short set of critical dynamics to help organize our thinking. Each dynamic contains components, relationships and some compelling system scale phenomena that affect our management.
There are certainly other ways to diagram and define delta ecosystems. There are considerable interactions among proposed ‘critical dynamics’. This framework is based on our repeated consultation with a cross section of the Puget Sound delta research community, and a review of the issues that decision makers and restoration practitioners have identified as important in their work. These dynamics provide a framework for summarizing existing knowledge, defining postulates that drive our current decision making, and ultimately for how we invest resources to improve the predictability of delta dynamics. These critical dynamics are not intended to replace more complex conceptual modelling of delta ecosystems, but to organize the interface between delta science and delta policy.
- Hydrodynamics and Channel Formation – How the work of river flow, interacting with tides, creates and maintains a system of alluvial and tidal channels, and defines the physical and chemical character of the waters.
- Sediment Dynamics and Vegetation – How the delta plain is built by accretion of sediment and debris which is variably colonized by vegetation.
- Biodiversity and Food Webs– How the local biogeochemical environments of the delta develop trophic webs supporting dynamic and interacting populations of organisms.
- Salmonid Rearing Services – How juvenile salmon linger within, and obtain critical services from the delta. This is a highly valued sub-topic within the larger topic of biodiversity and food webs.
- Human Social Dynamics – How different groups of people perceive and gain benefit from the delta, and through attempting to exercise power over decision making and resources, affect the condition of the delta.
- Flood and drainage services – How people living in the delta, cope with living at low elevations near big rivers by keeping sea and river water off the delta plain. This is a critical topic within the broader topic of human social dynamics.
Each of these critical dynamics contains a range of topics of interest to delta restoration practice. To make decision in river deltas, we develop theories, postulates and assumptions about these dynamics. Our challenge here is to synthesize old knowledge, invest in new knowledge, integrate the two, and apply it to decision making.
Learning is a Project[edit]
Integrating research and restoration practice requires that we careful select and design learning projects. We select research objectives by understanding available evidence and theory. We anticipate how decision making may be affected by new knowledge. We consider the duration and the risks of the work needed to acquire new knowledge. We remain responsive to the issues faced by projects, both those completed in the past, and those anticipated in the future.
Monitoring change over time is not necessarily the best tool for all learning. Natural experiments, extensive comparisons among multiple sites, space for time substitution (i.e. chronosequences) or opportunities unique to specific sites may provide the best opportunities to secure new knowledge. We must select tools that suit our purposes, and not prejudice our chances at success by limiting our learning methods.
As we define our learning objectives, and define the best learning tools, we define the human resources that we need to involve in restoration learning. These people may come from institutions not currently involved in restoration, with different goals and behaviors. A restoration learning program must develop a strategy for building and managing the social mechanisms necessary to complete the learning process.
Learning in Capital Programs[edit]
The Estuary and Salmon Restoration Program (ESRP) has made a commitment to integrating learning into project selection and funding. We view this activity as a necessary part of capital budget investment. Capital programs have a public trust obligation to insure that public investments result in the recovery of resilient ecosystems that provide valued ecosystem services. We use the scientific method to evaluate investments and manage risk.
Through the project selection process, negotiation of contractual terms, and review of deliverables, funding programs have a unique and unparalleled opportunity to integrate science and learning into ecosystem restoration on a dynamic and ongoing basis. Because of their scale and complexity, multiple funding sources commonly support each delta restoration effort. While this strategy is being initiated by the Estuary and Salmon Restoration Program, it has the potential to support multiple programs. Coordination with additional funding partners more appropriately distributes what is a shared burden. Additional technical partners outside of ESRP are necessary to implement a fully functioning learning program.
Our implementation goal is to integrate learning into project development, so that we can maximize the opportunities for leveraging project work to improve our ability to restore river deltas. We propose three program elements:
- A Core Monitoring Strategy - where basic observations are consistently documented for all river delta projects.
- Implementation of Learning Projects - which requires definition of an RFP, proposal review, contract negotiation, and technical oversight.
- An Knowledge Synthesis Process - that integrates new evidence into a steadily evolving body of evidence, and provides feedbacks to both capital project decision making, and future learning project development.
Project Duration and Intensity[edit]
Different lines of investigation will require different levels of effort over time. Factors affecting the cost of investigations include how quickly the treatment elicits a response, the degree of variability among observations (both among sites and over time), the scale of sampling necessary to characterize the response, the effort required to obtain a sample, and the number of other factors affecting the subject of study. In some cases investigation may require both intense and prolonged investigation. The cost of a learning project must be compared to the potential value and likelihood of generating decisive results.
The interval of observation under the mitigation model of observing change over time is frequently annual, but is rarely discussed. We assume that since change is rapid immediately following restoration, that we should measure things more frequently. Budgets are often shaped by the scope and duration of effort that an individual grant program will support. A prediction of the duration of effort necessary to obtain new or useful information is commonly lacking. Funding programs are notoriously inconsistent in their support for monitoring, creating a challenge for organizations attempting to maintain the capacity to do the work well.
Only by defining whole project costs and desired outcomes at the onset of a learning project can we begin to overcome these limitations and provide predictable public support for learning projects that maximize public benefits. By providing unpredictable funding for poorly defined investigations, public funders are undermining the very mechanisms for building knowledge, and justifying future investigations.
The Estuary and Salmon Restoration Program defines three levels of investigation. Protracted and intense research efforts are likely to divert more funds than sustainable for a program focused on capital projects. Some level of brief, low intensity investigation is necessary to insure a basic understanding of how projects are performing, and is discussed as part of our Core Monitoring Strategy. Between these two extremes are two classes of learning project being considered. These are 1) projects that are short-lived, but require a relatively high intensity or extent of sampling, and 2) projects that require protracted observation to see effects, but where individual sampling events are relatively low cost. Both of these two classes of learning projects are considered as potential targets for investment.
Selecting Proposals for Investment[edit]
Rigorous and systematic observations are not guaranteed to improve the next restoration action, but there are few replacements for the benefits gained through scientific investigation. The breadth of potential investigations are staggering (for example, see Gelfenbaum et al 2006). Scientists each advocate for the research approach they value, often for very personal reasons. Academic institutions have very different cultural incentives and perspective than capital programs. Even while integration of on-the-ground work and research through adaptive management is near universally lauded, capital programs face a formidable task to integrate restoration and research.
We propose that three criteria describe the likelihood that a scientific study will provide a return on investment:
Importance[edit]
Not all topics directly relate to our ability to increase and sustain delta services. Important topics are anticipated to have a strong impact on the provision of services, where we cannot currently estimate the effect of our choices due to lack of understanding of ecosystem dynamics. This later phrase is important. Just because a dynamic is important part of ecosystem function, does not mean it is important to how we conduct management.
Strong proposals have examined our ability to predict project outcomes, and has identified a lack of ability resulting in a risk of failure to achieve restoration goals.
Viability[edit]
Some investigations are more reliable than others, in that the factors being investigated are relatively simple to isolate and examine, and those factors strongly, consistently, and directly affect system behavior. By contrast some topics are mired in confounding factors, and are likely to require an intense and prolonged series of investigations to generate the evidence to affect decision making. While some of these topics are very important, so that we choose to begin work anyway, these opportunities must be weighed against the likelihood that useful information can be obtained given the limited resources of an individual program.
Strong projects have identified a pathway to obtaining new knowledge that is clear and where confidence can be demonstrated though a strong statistical understanding of the parameters in question, based on previous work in similar situations.
Policy Relevance[edit]
There are three critical junctures of decision making in capital programs: 1) In what locations should project development be supported, 2) how should we design to maximize cost/benefit and minimize risk of those projects, and 3) should the program continue on the same trajectory in the future. We should select learning projects that affect these decisions. Where issues arise infrequently, are exceedingly complex, or are very localized, policy change may be better achieved through political mechanisms, or systematic observation, rather than quantitative study.
Strong projects specifically identify how different study outcomes might directly affect policies and decision that affect future efforts.
The Importance of Defining Working Postulates[edit]
To organize our learning effort, we have identified a set of six critical dynamics. Our understanding of these dynamics is built of a network of axioms and postulates based on a body of evidence and speculation. The postulates represent ideas about how deltas work, around which we have some uncertainty, as compared to axioms, where we are confident in our understanding due to a level of research and refinement (following Ford 2000).
As we examine the dynamics of delta ecosystems, we are looking for specific postulates that fit our selection criteria of importance, viability and policy relevance. We are lookin within our network of theory for where a lack of evidence creates a vulnerability, that is matched with a clear opportunity for learning that will change policy.
This process begins by making explicit, our postulates about how restoration works. These postulates are often unspoken, or are briefly and imprecisely stated in the thick of grant application text. By making our postulates written, public, and explicit we achieve the following goals:
- We define a stable conceptual landscape that can be subjected to critique, countervailing evidence, or alternative explanations.
- We create a written record of propositions and evidence, accessible to a wider audience, that can be revisited and refined over time as new evidence emerges.
- By holding up a set of postulates, at the level of the funding program, we take some responsibility for making predictions in a way that encourages implementers to evaluate, test, and improve understanding without having to defend what are collective assuptions, while at the same time requiring implementers to be responsible to a prevailing understanding of delta ecosystems.
To fully develop this element of the River Delta Adaptive Management Strategy we propose using this wiki to maximize both participation and transparency. The following set of topics, organized by our critical dynamics represents that inital population of topics where we believe a learning opportunity may exist:
| Topics Describing Critical Delta Dynamics | High Uncertainty Topics for Adaptive Management |
|---|---|
| Delta hydrodynamics and channels | |
| Delta sediment dynamics and vegetation | |
| Delta biodiversity and food webs | |
| Delta utilization by salmon | |
| Delta social dynamics | |
| Delta flood and drainage |
No topics are being developed. Drainage and flood effects are evaluated as part of the 'High Risk Project' component of the core monitoring strategy |
