Environmental Management and Adaptive

Management

Part I: Structured Decision Making in an Adaptive Management Concept

The concept of structured decision making in adaptive management entails carefully organizing a problem evaluation in order to arrive at a suitable decision that focuses on attaining particular set goals. Over time, the decisions are iterated and the main approach taken in arriving at the decision entails analyzing the risks involved using a simple series of concepts and effective steps. Both the process of making the decision and analyzing the risks place a lot of emphasis on techniques that can improve the quality of the availed options. The main concepts are centered around making decisions that are founded on well – defined fundamental objectives, taking into consideration the risks involved, and also responding openly to legal orders and public preferences, as well as the values that are pertinent to the decision making process.

The objectives of the management are therefore designed to provide guidance and direction in making the right decisions and explicitly assuming any responsibilities with regards to the anticipated result especially in comparison to the actual outcome of the decision. Nevertheless, it is very important to take note of the current decisions undertaken by the management and any assumptions that could be used as an alternative in case of the worst scenario. Any structured decision making process, must be based on a combination of science and policy and as such the process can be said to be derived from subjective opinions that are made with regard to the type of data to include, information sources, the criteria for evaluation, and statistical analysis strategies to be used. Gregory and Keeney (2002) assert that good decision making must be derived from the heart of good science.

The true measure of a good decision however lies in its effectiveness in fulfilling social, environmental, and economic objectives, while simultaneously enhancing scientific knowledge. Consequently, most managers recognize the crucial need to quantify the key concepts, including event probabilities, consequences desirability, and even tradeoffs among competing goals.

There are eight elements that ought to be carefully taken into account when formulating a better and effective choice for tough decisions. The core parts of the process of structured decision making are contained within the first five parts and this entails clarifying problem, identifying key objectives, formulating alternatives, conducting an assessment of various consequences, as well as addressing tradeoff explicitly. Nevertheless, most of the practical situations do not require be analyzed by going through the entire eight elements.

Problem Definition

The scope and nature of the decision is defined. One ought to know whether the decision will be a recurrent one.

Formulating Objectives

Definition of the main objectives and goals that the management intends to achieve. In this case the goals and objectives are defined within the scope of a particular policy, and as such it is necessary for it to be communicated through a legal and regulatory order as well as the point of views of stakeholders. Objectives ought to be quantitative in nature and must be set within specific measurement metrics.

Alternatives

This element defines different practices articulated by the management team and also availed to the main decision makers. It also entails the listing of the different management tasks to select from.

Consequences

This element addresses the different results of the management activities and uses different types of models to offer a prediction ofa set of consequences of the alternative management practice. In this element, the alternative is weighted against each stated goal. It is possible to derive a set of consequences by using specific models based on personal judgment or scientific computer applications.

Tradeoff

This is basically a prediction of the tradeoff of multiple objectives with each other. It entails using available tools that can help to identify the relative weights among the existing conflicting goals in comparison to the available alternatives across a particular set of attributes with the aim of finding the best solution.

Uncertainty

Precise predictions of the effect of management practices on the existing management systems, are difficult to make and as such most of the decisions are made during periods of uncertainty. Such uncertainties complicate decision making process and make it challenging to select one option among many alternatives. Nonetheless, the best decision can only be arrived at if one explicitly addresses and challenges the uncertainties and also assesses the probability of obtaining different outcomes and their potential consequences.

Risk Tolerance

This entails determining and classifying the uncertainties that can impede the process of making decisions. Additionally, the potential risks brought about by the uncertainty brings are assessed by the management. Through better comprehension of risk level and risk response that will be dependent on the organization policy and will

yield a more objective – driven, defensible as well as transparent decision – making process.

Linked Decisions

The important decisions of organizations are often preferred over a given timeframe. In order to effectively handle the related decisions, there is need for the management to separate and resolve the current and near-term concerns and at the same time classify information that may be required for any future management decision.

Benefits of Structured Decision Making

Many organizations utilize different models of decision making with the aim of formulating and organizing their decisions. Through structured decision making, these organizations are able to gain more effective opinions and enhanced advantages. Structured decision making is a means through which the organization managers can divide the complex decisions into simpler decision making elements. Some of the advantages that are related to structured decision making model within the adaptive management include the following:

Organizations can use structured decision making to allocate enough timein order to ensure no quick decisions are made

Managers can easily assess the alternative options through allocation of time

Different alternative solutions can be devised and this will improve innovation

Structured decision making offers quality information which helps to derive quality decision making

Stakeholders will be offer more productive participation Evaluation process by the resource management is more

defensible and can easily be accepted

Part II: Evaluating Quality Structured Environmental Decisions

This study focuses on the hypotheses “that the subjects in the structured values condition as opposed to those assigned to the Unstructured Technical condition, would feel more comfortable with the prospect of providing input to decision makers, more satisfied that their decisions addressed their issue – specific concerns, and more satisfied with their decision overall” (Wilson & Arvai, 2006, p.4834-35)

The findings derived from this research were in support of this hypothesis, and can be virtually matched to the results that were derived from researches that have been previously conducted by other scholars. The findings revealed that the Structured Decision – Making approach was beneficial to the decision making team.

Structured decision – making approach seems to have benefited different stakeholders and other decision makers to take into consideration diverse factors that are available during decision – making processes, and as such they produce choices that are a reflection of particular issues and concerns that are important for their organizations.

Additionally, the study also confirms the fact that whilst majority of the stakeholders can participate in policy – making practices, they lack technical expertise and as such are easily guided by the evaluation of trade off when making decisions that are complex and new. There are certainly those trade offs that give even the most seasoned managers a lot of challenges. These often represent a mean of inclusive incommensurability where the management must come up with the trade offs among attributes that seem to be critically substantial. Different studies of similar nature that have been conducted on the evaluation of objectives and alternatives during decision making have also supported these affirmations. Making decisions in the context of unfamiliar technical data is difficult and thus easily assessed information can assist a manager to develop needed context for a given opinion. Consequently, identifying the essence of making level improvements in environmental health, including making effective

policies on choices that relate to recreation is much easier (Wilson & Arvai, 2006).

Secondly, the structured decision approach can initiatebetter-informed decisions which accurately reflect the objectives of the management and the organization at large, and not justbased on self-reports, but also on the internal consistency in the decision-making behavior. The study was aimed at finding the management of environmental problems which were linked to the population. The primary priority ranked by the subjects included overpopulation, while the wildlife disease came in second, followed by damaged trails as the third. Additionally, the diverse patterns of average allocation of funds of the subjects were also taken into account. Despite this, the subjects were required to account the highest allocations of funding to the challenge of the deer overpopulation with the relatively lower amount being allocated to the other problems regardless of the order. Through the study it was apparent that Structured Decision – Making approach can result in higher quality decisions. It subsequently points out to the concordance between the defined objectives of individuals versus their actual choice behavior.

The results further affirm that the priority of individual management combined with funding allocations directly match with the initial effects of ratings. As such the structured decision making practices have been welcomed as a strategy to enhance environmental quality and even improve the decisions that affect the risk management based on individual behaviors. Wilson & Arvai (2006), assert that the modified approach of structured decision-making can lead to quality informed decisions, which are in line with the set objectives. Therefore, the decision is not only founded on self – report, but also the consistent decision making behavior of each individual.

Nevertheless, some outcomes failed to support this second hypothesis. This can be explained by the fact that participants might have judged the choice task as lacking the assurance of a high accuracy level and

consequently, lowered the effort asserted by them. In addition, it is of significant importance to acknowledge how affective impressions can influence the multiple decision making. The consequential nature of a problem can therefore be used to override the benefits that achieved in decision structuring.

Part III: Benefit or Obstructions that the Adaptive Management Concept Bring to Environmental Management

In the practice of environmental law, adaptive management has become a major theme and according to Williams (2011), it is the sole feasible choice for environmental law. Furthermore, this practice is dependent on the philosophy of “learning by doing”, and as such is often considered and presented in the form of experimentation method. On its own, adaptive Management is not an indication of an end, but instead it is a means to arriving at effective decisions and generating benefits. The dynamic nature of the natural systems has formed the basis and the main rationale for its popularity and acceptance. In order to adopt Adaptive management managers, planners, and stakeholders must be ready to analyze the proposed management practices and take into consideration a set of potential obstruction and results at a high-level details.

The management team must come up with diverse management policies that are applicable for different locations at a time, and can assess any variances in the outcomes over a given period of time. The variances in the results can be of guidance in choosing the management policies that can effectively attain the desired objectives.

As opposed to actively or consciously making variances across various sites with the aim of generating rigorous models on how an environmental system will work, the managers might make their decision based on historical data. In this case, they will utilize these models to identify the single most effective management activity before effecting it. Nevertheless, they might as well employ monitoring

techniques to assess whether the results are from the predicted elements of the model, and use these to modify both the model and the system. Such an approach is referred to as the passive adaptive management because the management team is not adopting active experimentation to control uncertainty (Biber, 2013).

Adaptive Management can entail developing a set of flexible alternatives. This enhances the probability of success across a wide variety of future conditions. It further facilitates an effective and efficient restoration by predicting uncertainty in all the stages of planning, design, implementation, as well as operations.

Adaptive Management facilitates the sustainability of projects and allows them to progress in the face of uncertainty hence accelerating the enforcement of such projects. This raises the probability of success in the restoration project as it is likely to weigh the cost versus the benefits of adopting the Adaptive Management. Nevertheless, it is difficult to quantify the indirect benefits, yet there is still substantial gains from knowledge and vision from adopting the process.

Adaptive Management is beneficial in terms of increasing long – term cost saving as it combines both robustness and flexibility during planning and implementation. By minimizing the undesirable outcomes, the technique promotes the benefits generated from restoration objectives. Managers can use adaptive management, to develop small – scale driver projects that can be employed in the identification and analysis of major uncertainties in the functioning of current system, and simultaneously attempt to minimize uncertainties through experimentation. The manager can also design different methods to conduct adaptive management through dividing sub-units from the larger unit and this way, the managers will effectively address the challenge of undertaking replication for large – scale management of the entire system.

It is easier to comprehend the results from managerial activities as well as other events when Adaptive Management is adopted and this is because it enhances quality decision making that are flexible and adjustable during uncertainties. Such results provide both scientific basis and understanding of a given condition and are still applicable to different policies during the iterative learning process. Since Adaptive Management is an iterative process, it allows room for accommodating continuous performance improvement while taking into account that any novel information collected during monitoring, analysis, assessment, and implementation are used as inputs during the process of decision – making. Moreover, the adaptive management allows the managers to recognize the essence of natural variability in contributing towards ecological resilience and its productivity. Adaptive Management should not be viewed as a “trial and error” practice, but rather one that offers learning opportunities while practicing (Williams, 2011).

Adaptive management is also known as a platform for the concurrent production of information and the management choices by the management team and also a forum through whichmanagers, scientists, and stakeholders can take part in dialogue that is directed at interpreting the evaluation and monitoring of outcomes. This forum can be of assistance to different managers who have an avenue to pursue clarifications on technical and scientific aspects that may distress implementation stages. Adaptive management can also be important inthe formulation of initial management choices. However these choices may be made in a rather “haphazard” manner and without coming up with a rigorous model that accurately predicts the outcomes the management should develop. Managers can use it to monitor various results and adjust them in case they are unable to achieve the management set objectives.

Obstacles of Adaptive Management

Time Requirement

Adaptive management is time consuming. Time demands are necessary during designing adaptive management program, establishing replicates, conducting monitoring, collecting result, and carrying out the analysis of data collected. In converse, there are some environmental crises are much pressing and as such managers might not be able to wait for all this information to be collected and analyzed in the process of adaptive management before making a decision. A quick decision is necessary in such situations.

Immediate management decisions are irreversible and must be made within a short time hence there is no accommodation of the diversity of choices. In such cases, neither active nor passive adaptive management are regarded as feasible.

Information Production Problems

For success in conducting anadaptive management approach, there is need for high – quality monitoring. This demands a lengthy period of time, through which continuous monitoring is conducted during the given time span. Biber (2013) states thatadaptive management entails high – quality monitoring that must be well matched within period and space to the problem scale and more often than not, such exercises are extremely costly and may not be easy for outsiders and non – experts to evaluate the degree of monitoring. Adaptive management further demands the continuous monitoring to the outside supervision, a factor that can make monitoring vulnerable to asymmetric pressures within the political spheres. Organizations which are pursuing multiple goals can be wary to undertake monitoring in case the produced data can raise conflicts with other set objectives. The actual monitoring data can also constrain the freedom of an organization to maneuver and govern itself in the future especially if unpredictable means are involved.

Institutional Continuity Problem

The sustainability or continuity of an institution is crucial for the collection of data and overall maintenance of the adaptive management process. In most cases, the results of different experiments committed to minimizing the uncertainty may require a lengthy period of time to achieve. This is caused by the long time span under which the ecological process operates and may require tremendous patience by the various interest groups and the public, a factor that is often hard to come by.

Problems of Adaption in Dynamic Environment

In many instances, environmental conditions tend to be dynamic and as such change quickly. Where the dynamism of these conditions is high, questions can be raised on the feasibility of even learning and adopting the uncertainty reduction program. The unpredictability of these conditions render the information useless for the purpose of management and regulatory within no time after its collection.

Moreover, in cases where dynamism and complexity of the environment is high and unpredictable, there might be challenges encountered in realizing the effectiveness of any adaptive management practices that can offer guidance to the process of decision making.

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References

Biber, E. (2013). Adaptive Management and the Future of Environmental Law, Akron

Law Review, 46(4), 934-962

Gregory, R.S. & Keeney, R.L. (2002). Making Smarter Environmental Management

Decisions, Journal of the American Water Resources Association, 38(6), 1601-1612

Williams, B.K. (2011). Adaptive Management of Natural Resources — Framework and

Issues, Journal of Environmental Management, 92, 1346-1348

Wilson, R.S. & Arvai, J.L. (2006). Evaluating the Quality of Structured

Environmental Management Decisions, Environmental Science & Technology, 40(16), 4831-4837

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