Knowledge - Adaptive Management Strategy
Abstract: Adaptive Management Strategy can be applied to responsibly and sustainably deal with uncertainties, responding to lessons, observations and experiences during the development of the project.
Technology Readiness Level: 9 (strategy effectively used in several projects)
Keywords: Adaptive management, adaptive monitoring, uncertainties, Frame of reference, cyclic
Considering the projected demographic changes in coastal zones and river beds there will be an increasing need for dredging globally. It becomes more important to be able to satisfactorily manage the positive and negative dredging impacts on the environment and their inhabitants. A growing number of uncertainties, degraded environments, (environmental) restrictions, stakeholders and factors increasingly co-determine the programming and execution of dredging projects.
Most execution techniques, support systems and monitoring approaches accompanying infrastructure construction operations include process control and adjustments, and primarily focus on target compliance. Based on fixed knowledge they need clear thresholds to function. There is a severe lack of timely cause-effect knowledge and “business as usual” is not a viable option anymore.
A need for an applicable, structured and true adaptive management approach for the execution of marine infrastructure works has emerged, with the aim of reducing the uncertainty over time via system monitoring: i.e. an approach that aims at closing the gap to what we know and what we should know. This approach is Adaptive Management Strategy. This implies a management of the project that adapts its procedures responding to lessons, observations and experiences during the development of the project, in contrast to adhering to initially set procedures, based on on pre-project assumptions and concepts.
Adaptive management involves not only controlling your system, but also learning from your system. On the control side, which is mostly referred to as responsive management, adaptive management provides options or actions that can be used to influence impact, whereas on the learning side it provides opportunities to incorporate findings (from monitoring, field experience) into the setup of the management system. The often-used adaptive management cycle of Plan, Act, Evaluate & Adjust (Deming, 1986) is reformed in a Frame of Reference approach (Van Koningsveld, 2003) to make it more applicable to the large scale construction of marine infrastructure. A simplified setup of this approach is shown in the figure. Further information can be found in Guidelines on the application of the Framework of Reference for the adaptive execution of low-impact dredging works. This document gives the state of development at the moment of drafting (2102). However, the studies haven't been completed yet and consequently no more clear guidelines can be provided. Development will continue and Guidelines will be updated as results become available.
One of the most important features recognized in Adaptive Management is dealing with uncertainty. Based on objectives and current knowledge levels, the parameters (Quantitative State Concept) that would be usable are identified. Trigger levels or Key Performance Indicators (KPI’s) to benchmark the environmental performance upon are also determined in the beginning of the project in the light of current (system) knowledge. In case of non-compliance responsive management (red arrow) is deployed as an intervention to influence the current state and assure monitored parameters return to values below trigger levels.
However, with the knowledge and insights gained during the works (for instance by validating models, observing patterns in the field, obtaining more reliable biological knowledge), the parameters and their trigger levels might need to be updated, or the selection approach for the responsive management practices might need changes. This process of knowledge improvement (green arrow) delivers a second cyclic activity under the adaptive framework. With this improved knowledge the benchmarks and intervention procedure may be adjusted, leading to a more effective responsive management.
Finally, as for any management systems, the adaptive management includes (management) review. Apart from the well-known feedback loop, in which the fulfilment of objectives strived for is benchmarked, a broader reviewing process is taking place, as on the basis of experience, the views on objectives and target might also be changing. It is therefore better to refer to this process as the system of continuous improvement (blue arrow).
More detail is provided further sections and in Guidelines on the application of the Framework of Reference for the adaptive execution of low-impact dredging works.
Adaptive Monitoring & Management cycles
Monitoring of the ecosystem affected by marine construction works has become an important part of any large-scale development. The use of information obtained during these extensive monitoring campaigns is varying, making the ‘success’ of using these monitoring efforts as a tool to protect the ecosystem variable. To promote sustainable development with an economic use of monitoring and management in marine infrastructure, an ‘adaptive’ approach seems very promising. By using a cyclical and adaptive process, the assessment of impacts is optimized and approved ‘on the go’ and the project can be managed by its quantified monitored impacts.
Generally, the precautionary principle forms the basis for monitoring and management requirements when ecological uncertainties arise in the (pre-) design phases. Implementing the adaptive approach for future dredging works signifies a paradigm shift away from the application of the precautionary principle.
The guideline provides methodologies to structure and help organise an adaptive cyclic approach including monitoring and assessment, ‘learning by doing’.
Plan, act, evaluate and adjust!
The basic strength of the adaptive cycle is that the execution of work can be adjusted during operation in order to reach environmental goals. Since adjustments should be based on the monitoring of effects, a complete cycle of planning, execution of monitoring and evaluation of results is necessary to facilitate adjustment. In this way the well-known management cycle of Plan, Act, Evaluate & Adjust is created (for further reading see Deming, 1986).
When this cycle is applied to the adaptive executive cycle, it follows that within the ‘plan’ phase, the monitoring objectives and information needs are determined, and that the key performance indicators are identified. Finally, a monitoring program is established that can be executed during the ‘act’ phase. Within the ‘evaluate’ phase the status of the performance indicators are compared with the desired state which will either lead to the ‘adjust’
phase within the execution of work or within a review on the overall
When looking at this management cycle it gives a clear indication of the cycle within an adaptive process. However, it is unclear where this cycle is ‘started’ and how the adaptive process should be designed to be successful. In addition, the different steps and needs within the planning phase to get from objective to monitoring program are not clear. For that reason, it was thought that the cycle should be re-adjusted to a framework that consists of the essential components of the complete adaptive approach including the dredging execution management process. For this, use is made of the so-called Frame of Reference (FoR) as introduced by Van Koningsveld (2003) and the figures illustrate how the Adaptive Execution cycle and the Frame of Reference correlate.
Frame of Reference (FoR)
“Gone are the days where environmental considerations were second to economic interest…” (Bray, 2008). These days a thorough inclusion of numerous environmental aspects has become mandatory, complicating previous ways of programming dredging projects. To tackle uncertainties related to the complexity and dynamics related to the systems in which projects take place and associated lack of clarity of (environmental) impacts and restrictions it is necessary to realise that “adjusting” to new circumstances or developments as well as introducing new and clear (environmental) objectives become part of the whole execution process. The “adjusting” also entails new roles for clients and stakeholders and possibly new stakeholders as well (local governments, communities, NGOs, entrepreneurs, etc).
The purpose of the FoR here is to better manage the integration of the conservation of sensitive ecosystems with development of cost-effective construction. Monitoring, benchmarking, evaluation, reporting and improvement are integral components of the FoR. These activities provide approaches to assess the impact, appropriateness, effectiveness, efficiency and legacy of programs and a process to promote accountability.
FoR provides guidance for assessing program performance and the state or change over time in assets, against planned immediate, intermediate and longer-term outcomes. It provides opportunities to improve program and project design and delivery and to reorient construction execution at key decision points throughout the life of the strategy or policy. FoR is designed to make changes transparent so that all parties can learn, through reflection and discussion, which interventions are most appropriate, effective and efficient. Its four components — Quality Status Concept (QSC), benchmarking, intervention and evaluation support a ‘learning by doing’ approach to adaptation.
In order to make improvements in consecutive execution cycles of the adaptive process possible, it is important that all the information gathered within previous cycles is well-defined, correctly designed and documented before being used for adjustments. For instance, within the QSC and the benchmarking, evaluation cycles will update (process) knowledge and databases in such workable way that the earlier defined decisions can be reconsidered based on the new, more complete data set.
The origin of the adaptive management concept can be traced back to the early concepts of scientific management pioneered by Frederick Taylor in the early 1900’s (Haber 1964). The term ‘adaptive management’ evolved in natural resource management workshops through decision makers, managers and scientists focussing on building simulation models to uncover key assumptions and uncertainties (Bormann et al., 1999). Holling (1978) and Walters (1986) further developed the adaptive management practice.
Adaptive management for resource management purposes has probably been most frequently applied in Australia and North America. Initially applied in fishery management, it received more broad application in the 1990s and 2000s (Biodiversity Support Program of the WWF, The Nature Conservancy (TNC), and World Resources Institute).
Adaptive management is foremost an iterative process of optimal decision making in the face of uncertainty, with an aim to structure and reduce uncertainty over time via system monitoring. In this way, decision making simultaneously maximises one or more resource objectives and accrues information needed to improve future management. In short, adaptive management is a tool that should be used not only to change a system, but also to learn about the system (Holling 1978). And because adaptive management is based on a learning process, it improves long-run management outcomes. The challenge in using adaptive approaches lies in finding the correct balance between gaining knowledge to improve management in the future and achieving the best short-term outcome based on current knowledge (Stankey et al., 2005).
Implementing adaptive monitoring for the execution of a lower-impact marine construction project involves the integration of project design, management, and monitoring to systematically test assumptions in order to adapt and learn.
The three principle components of adaptive management in environmental practice are:
- Testing assumptions, which encompass systematically trying different actions to achieve a desired outcome (contrary to random trial-and-error processes). It involves using knowledge about the specific site to select the best known strategy, laying out the assumptions behind how that strategic approach will work, and then collecting monitoring data to determine if the assumptions hold true.
- Adaptation, which involves changing assumptions and interventions to respond to new or different information obtained through monitoring and project experience.
- Learning, which is about explicitly documenting a team’s planning and implementation processes and its successes and failures for internal learning as well as learning across the stakeholder community.
Adaptive execution cycle as Frame of Reference
When applying the FoR for the adaptive monitoring strategy, the FoR is first designed from the “objective phase” onward. Based on a strategic objective, that is usually an aggregate and project-wide, operational objectives for specific project parts can be identified. These objectives in turn require a management recipe based on the quantitative state concept, benchmark, intervention and evaluation. The necessity to come up with a quantitative state concept is to enable objective and reproducible decision making. Based on knowledge on the ecosystem, the appropriate parameters and indicators should be selected to describe this state.
When applying adaptive execution cycles this process knowledge will of course evolve on-the-go, so the appropriate quantitative state concept is not rigid for the full project duration. From the quantitative state concept, a so-called desired (or reference) state, describing an acceptable (quantitative) state of the ecosystem, can be defined. The benchmark then basically compares that desired state with the current state that should be monitored in sufficient detail on the appropriate spatial and temporal scales. Based on this comparison, action might be required. Within the adaptive approach, the action need can be divided in three categories:
- no action needed (as stress levels are still sufficiently low)
- pro-active action needed (as stress levels are rising, but still at acceptable levels), or
- intervention needed (as the stress levels are above acceptable levels).
Interventions should directly influence the current state in order to avoid the risk for over-stressing the ecosystem. After any intervention (or non-intervention) the process should be evaluated not only whether the decision recipe was successful, but also as feedback on the realism of the pre-defined objectives and to see whether the process knowledge has undergone relevant changes. In this way the process contains feedback loops in diverse directions keeping the pre-defined clear realistic objectives in mind. This makes the scheme useful in all stages of a marine infrastructure development and not only strictly applicable to the execution phase.
By describing the adaptive process in the way above, continuity in management is better guaranteed. Not only is the current state continuously evaluated with the desired state to manage the impacts, but also the lessons learned are brought back into the process of defining the quantitative state concept and the management processes to realise the objectives for the project.
In addition, the continuous generation, disclosure and use of new valuable knowledge to address the uncertainties enables the proliferation of several scientific and social processes as vital components of future adaptive management. These are foremost:
- Contractor, Clients and stakeholders may be linked better to appropriate temporal and spatial scales and retain a focus on statistical power and controls.
- Better use of computer models to build synthesis and an embodied ecological consensus
- Workable use of embodied ecological consensus to evaluate strategic alternatives
- Clearer communication of alternatives during negotiation of a selection or intervention
As such, these insights enable the design and management of marine infrastructure projects better and avoid some of the flaws others have encountered, especially in cases where management decisions are repeated (Stankey et al. 2005; Rout et al. 2009).
Mind your (learning) step!
When organisations need to ensure their preparedness for the unexpected change, then adaptive management applied to ecosystems makes sense when considering ever changing environmental conditions. The flexibility and constant learning of an adaptive management approach is a logical application for these organisations seeking sustainability methodologies.
However, in recent times, the term ¨adaptive management¨ has become a rather confusing catchphrase that means many things to many people —as Salafsky et al. (2001) quoted: "Adaptive management is merely an excuse to change your mind."
In fact, there exist many “derivatives” of adaptive monitoring and cyclic management approaches that claim to hold an adaptive approach to resource management operations, intend to comprise a “learning by doing” element, or propose cyclic processes allowing some sort of adjusting.
In the context of guiding operational processes there are e.g., Decision Support System (Common in river basin management), Decision execution cycle (broad application organisational), Adaptive execution cycle (Broad application in resource management), Adaptive management cycle (see Work of Holling, 70’s), Adaptive Environmental monitoring and management planning (Bray, 2008; Doorn-Groen, 2007: CEDA, 2015) and the Adaptive Monitoring Cycle (UN/ECE, 1993; UNESCO, 2005, Verine, 2008).
Seemingly similar, they are easily separated into two types of approaches. The difference lies in the fact that most execution cycles, support systems and monitoring approaches primarily focus on target compliance, responsive management. They are based on fixed knowledge and to function they need a clear demand of thresholds. As such, they mainly include process control and adjustments. For these approaches, no cause-effect knowledge is needed here; it involves no new knowledge-gaining. The “learning” involves adjustment of behaviour (including hardware) based on previously developed knowledge.
On the other hand, Adaptive Monitoring and Management cycles are structured, iterative processes of optimal decision making in the face of uncertainty, with an aim to reducing uncertainty over time via system monitoring. The “learning” aspects here involve adjustment of behaviour based on creative problem-solving resulting in change in the previous knowledge: suited for closing the gap to what we know and what we should know. It aims at achieving information production for the integration of a growing number of different goals. The latter applies to the adaptive character of the FoR.
The purpose of applying adaptive monitoring and management feedbacks within the FoR is to establish a clear and common purpose, make use of system modelling, and develop a management plan that maximises results and learning. This enables the development of monitoring plans that tests pre-defined assumptions, focus the analyses and communication of the results, and finally better use the results to adapt and learn
By applying an adaptive management approach to marine construction, including dredging, it is expected to function as an integrated system, adjusting and learning from a multi-faceted network of influences. These influences are not just environmental but also, economic and social (Bray, 2008; CEDA, 2015). The goal of a sustainable organisation guided by adaptive management must be to engage in active learning. The learning aspects help to direct change in these complex settings towards true sustainability. This “learning to manage by managing to learn” must be at the core of a more sustainable business strategy (Bormann, 1999).
The FoR as presented here aims to:
- make the links between the planning process, monitoring and evaluation activities, and adaptive management of low impact dredging in sensitive areas explicit
- provide a structure to inform the development of clear evaluation questions in relation to the impact, appropriateness, effectiveness, efficiency of FoR policies, programs and initiatives
- inform the development of logical programme execution strategies across scales and across timeframes, including setting achievable targets
- improve capacity to report on FoR performance
- provide tools for progressively developing a picture of progress towards longer-term FoR goals
- improve analysis of the successes and shortcomings of strategies
- improve the performance of programs, initiatives and projects and to enable development of better instruments and policies for sustainable resource.
Two Project pages give examples of practical application of Adaptive Management aspects:
- Adaptive monitoring of sand extraction areas - Maasvlakte 2 extension, NL
- Adaptive Management - Melbourne Port Extension, AUS
The aquatic environment is a complex combination of natural features and phenomena, supporting diverse populations that show rather unpredictable dynamics in resilience and carrying capacity. Because of this complexity, predicting the effects of human-induced changes on these ecosystems is extremely difficult. Even more difficult it is to unravel the relative importance of short-term dredging operations as part of all possible anthropogenic influence.
For example and as quoted before (Kaly, 2000):
“the concept of health in relation to reefs, or any ecosystem, is a slippery one. We have no way of indicating the ideal number of species, community characteristics, energy flows or ecosystem services for even a single reef. Let alone arrive at some guidelines for the range of complex systems we are concerned with across the globe. Despite not really being ready for the challenge, we are forced by necessity to start taking action and learn as we go”.
Partly through the worldwide globalisation and growing international networks, “The Not In My Backyard (NIMBY) syndrome” becomes less applicable. Globally, there is a growing recognition that despite decades of hard work, hundreds of projects, thousands of trained professionals, and billions of dollars, we have not yet substantially slowed the degradation of terrestrial and aquatic ecosystems. It is clear that “business as usual” is not a viable option and that newer, more powerful approaches for sustainable development must be tried.
- Bormann, B.T., J.R. Martin, F.H. Wagner, G. Wood, J. Alegria, P.G. Cunningham, M.H. Brookes, P. Friesema, J. Berg, and J. Henshaw. 1999. Adaptive management. Pp. 505-533 In: Johnson, N.C., A.J. Malk, W. Sexton, and R. Szaro (eds.). Ecological Stewardship: A common reference for ecosystem management. Amsterdam. Elsevier.
- Bray, R. N., 2008. Environmental aspects of dredging, pp 386. ISBN:978-0-415-45080-5 Taylor & Francis, Leiden, The Netherlands.
- CEDA (2015) Integrating Adaptive Environmental Management into Dredging Projects. Position paper.
- Deming, W. E., 1986. Out of the Crisis. MIT Center for Advanced Engineering Study. ISBN 0-911379-01-0.
- Doorn-Groen, S. M., 2007. Environmental monitoring and management of reclamation works close to sensitive habitats.Terra et Aqua (No: 108:3-18).
- Holling, C. S. (ed.), 1978. Adaptive Environmental Assessment and Management. Chichester: Wiley. ISBN 0-471-99632-7.
- Kaly U. and Pratt C., (South Pacific Applied Geoscience Commission) 2000. Environmental Vulnerability Index: Development and provisional indices and profiles for Fiji, Samoa, Tuvalu and Vanuatu. Phase II Report for NZODA. SOPAC Technical Report 306. 89p.; 5 appendixes, 8 figures, 4 tables. ISBN 982-207-010-1
- Rout, T. M., Hauser, C. E., Possingham, H. P., 2009. "Optimal adaptive management for the translocation of threatened species". Ecological Applications 19(2): 515–526.
- Salafsky, N., Margoluis, R. and Redford,. R., 2001. Adaptive management: a tool for conservation practitioners. Washington, D.C. : Biodiversity Support Program, c2001: 100p.
- Stankey, G. H., Clark, R. N. and Bormann, B. T., 2005. Adaptive management of natural resources: theory, concepts, and management institutions. Gen. Tech. Rep. PNW-GTR-654. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. p. 73 p.
- UNCSD. 2001. Indicators of Sustainable Development: Guidelines and Methodologies. United Nations Commission on Sustainable Development, Washington, DC.
- UNESCO, 2005. Water resources systems planning and management– ISBN 92-3-103998-9. monitoring and adaptive management, Appendix B: 559- 579.
- Van Koningsveld, M., 2003, Matching specialist knowledge with end user needs. Bridging the gap between coastal science and coastal management. PhD thesis.
- Verine, L., 2008. "Adaptive Project Management". PM World Today 10(5): 1–9.
- Walters, C.J. (1986). Adaptive Management of Renewable Resources. New York, NY: Mc Graw Hill. ISBN 0029479703
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