Sustainable Resource Management: Adaptive management, a method for managing and learning about natural resources and sustainable resource management at the same time, has been around for decades.
Sustainable resource management refers to the management of resources in such a manner that their sources are not depleted, allowing future generations to benefit from them as well. Water, wind, wood, sun, and wave energy are examples of renewable resources that may be utilised again and again, making them more sustainable.
Beverton and Holt (1957), who discussed adaptive decision making in fisheries without naming it adaptive management, were among the first to articulate it in the natural resources literature. A generation later, Holling (1978) and Walters and Hilborn (1978) gave adaptive resources management its name and conceptual framework, while Walters (1986) offered a more thorough technical study of adaptive decision making. By offering a complete presentation of adaptive management’s social and political elements, Lee’s (1993) book extended the framework for it.
These pioneering initiatives prompted a surge in adaptive management and sustainable resource management interest that has lasted to the current day. Many people working in natural resource conservation and sustainable resource management now claim, sometimes incorrectly, that adaptive management is the method they employ to satisfy their resource management obligations.
The adaptive management scenario may be described as resources that are sensitive to management interventions but are susceptible to uncertainty regarding the consequences of such activities.
Concept of adaptive management
Business (Senge, 1990), experimental science (Popper, 1968), systems theory (Ashworth, 1982), and industrial ecology all contributed to the development of adaptive management and sustainable resource management(Allenby and Richards, 1994). Adaptive management and sustainable resource management in natural resources is essentially a systematic method of learning by doing and adjusting based on what is learnt (Walters and Holling, 1990). It is founded on the understanding that resource systems are generally only partially understood, and that recording resource conditions and applying what has been learned as resources are managed has benefit.
Adaptive management and sustainable resource management has been given a number of more formal definitions. Adaptive management is defined by the National Research Council (2004) as “flexible decision making that may be changed in the face of uncertainty when results from management actions and other events become better known.” As part of an iterative learning process, careful monitoring of these results increases scientific understanding while also assisting in the adjustment of policies or operations.
Key Premises of Adaptive Management and Sustainable Resource Management
The fact that knowledge of ecological systems is not only inadequate but also elusive is a fundamental assumption of adaptive management (Walters and Holling 1990). Furthermore, there is a growing consensus that conventional scientific investigation will always be constrained by resources and time. When these limiting constraints are combined with the backdrop of resource scarcity, possible irreversibility, and rising demands, it becomes clear that new forms of understanding and learning are required to not only occur but also to actively inform decision making and policy processes (Bormann et al. 1994b).
Adaptive management and sustainable resource management provides both a scientifically valid course that does not rely on large studies and an implementation method that promotes systematic action assessment (Lee and Lawrence 1986).
Adaptive management has gained popularity as a result of its focus on management experiences as a source of learning. This has resulted in a number of expressions emphasising the concept of adaptive management as learning to manage by managing to learn (Bormann et al. 1994a).
A critic of adaptive management may argue that it is only a variation of Lindblom’s (1959) “disjointed incrementalism” or, as it is more generally known, “muddling through” approach. Natural resource and sustainable resource management has a long history of being able to build on prior actions and outcomes; policies are always being revised in light of previous performance (Kusel et al. 1996). Some learning occurs regardless of the management strategy employed; as Gunderson (1999c: 35) put it, “trial-and-error is a default paradigm for learning.
people will learn and adapt via the basic process of experience.” Adaptive management, on the other hand, differs from Lindblom’s incrementalism in that it is intentional (Dovers 2003); agreed-upon goals and objectives serve as a baseline against which progress and lessons may be assessed. By emphasising uncertainties, defining and assessing hypotheses, and organising activities to verify those hypotheses through field application, adaptive management resembles the scientific process (Gunderson 1999c). Adaptive management, according to Walters (1997), substitutes ad hoc, trial-and-error management learning (an incremental, evolutionary process) with learning through rigorous experiments (a process of directed selection).
Alternative Models of Adaptive Management
Walters and Holling (1990) proposed three different approaches to arrange adaptive systems. The first is an evolutionary or trial-and-error model (Holling 1978; Kusel et al. [1996] called it incremental adaptive management, while Hilborn [1992] called it a reactive method. The outcomes of external decisions and choices are utilised to define subsequent decisions that, hopefully, lead to better outcomes. In many respects, this type of adaptive management resembles muddled through, in which whatever management experience is done ultimately leads to some learning. There is no discernible aim to it, and one just reaps the advantages of previous experiences.
The second idea is passive adaptive management, which Bormann et al. (1999) referred to as sequential learning. It uses past data to construct a single optimal strategy along a linear route that is considered to be accurate (i.e., the underlying assumptions and antecedent circumstances that were relevant before still apply). As a way of framing new options, understanding, or decisions, this approach applies a formal, rigorous, yet post facto examination to secondary facts and experiences.
It’s possible to learn a lot from passive adaptive management. Walters and Holling (1990) reported on research in the Florida Everglades that looked at the impact of different water regime changes. The research was motivated by the sole premise that animals in the region need a natural water supply system.
This resulted in adjustments to waterflow timing and distribution, with the goal of the plan serving as the initial stage in a longer, iterative testing process that might lead to hydrological regime alterations. This might result in significant ecological benefits over time. Alternative hypotheses, according to Walters and Holling (1990), should have been framed, for example, what were the impacts of natural changes in nesting habitat beyond the area? Different assessments and, maybe, new management methods could have resulted from such options.
Adaptive management needs specific assumptions about expected outcomes to evaluate against actual outcomes, as well as defined sustainable resource management objectives to guide decisions about what to do. It is critical to understand the various management alternatives and alternative assumptions in the event that the action taken does not operate as planned. Adaptive management is distinguished from a basic trial and error approach by the connections between management objectives, learning about the system, and altering direction based on what is learnt.