Numeric management
- Variable relationship:
Acheson and Wilson (1996) discuss an approach to fisheries management that they term the "numerical approach" (or also, the "scientific approach"). The numeric management approach emphasizes scientific knowledge, rather than local or traditional knowledge (Governance Knowledge Use; Actor Scientific Knowledge). The management generally relies on simplified models of the target system, and attempts to optimize it for a small number of goals (Metric Diversity). The arguments for this management practice are frequently based on mathematical models and concepts (e.g. maximum sustainable yield, or MSY). As Acheson and Wilson (1996: 580) state: "The central idea of such models is that the longterm abundance or sustainability of a species is strongly linked to the amount of exploitative effort on that stock. The relationship between stock size and fishing effort can be described mathematically." This favors rules that would determine the extent of this exploitative effort (Policy Instrument), such that the commons can be managed optimally and sustainably (Commons Condition Trend).
Numerous types of policies across several sectors are justified by this theory, including: 1) Single-stock, MSY-based management of fisheries, and 2) Elements of the Prior Appropriation-based regime for water management in the Western United States.
- Project
- SESMAD
- Sector(s)
- Scientific Field
- Component Type(s)
- Status
- Public
Variables
| Variable | Role | Role Explanation | Value |
|---|---|---|---|
| Policy instrument | Proximate independent variable | Institutions that are output-based (specifying outcomes in terms of levels of commons use) rather than input-based (specifying the means of use) will be better able to ensure a particular level of use, and that this matches a theoretically optimum level of use. | Outcome-based performance standards |
| Metric diversity | Proximate independent variable | Numeric management focuses on a relatively narrow aspect of the target system in order to optimize the system for the management of this aspect. | Low |
| Governance knowledge use | Proximate independent variable | Numeric management relies primarily on scientific knowledge in order to determine how much of a commons should be used. | Scientific |
| Actor scientific knowledge | Moderating independent variable | A high level of scientific knowledge is needed to set an ecologically appropriate commons use limit. | High |
| Compliance | Moderating independent variable | Numerical standards must be complied with if they are to be effective in sustaining the commons. | Yes |
| External sanctions | Moderating independent variable | Sanctioning of rule-breaking is needed to ensure compliance with numerical standards. | Yes |
| External monitoring | Moderating independent variable | Monitoring for fractions is important to ensure that the numerical standards are complied with. | Yes |
| Commons condition trend | Final outcome | A commons will be sustained if the amount of rights granted equals the overall amount of use specified by the governing policy, and this overall amount is ecological appropriate. | Remained the same or Improved |
Related Theories
| Theory | Relationship | Characterizing Variables |
|---|---|---|
| Individual transferable quotas (ITQs) | nested | |
| Polycentric comanagement | related | |
| Failure of centralized control | contradictory | |
| Technical solutions and shifting the burden | contradictory | |
| Enforcement | contains |
Related Studies
| Study | Relationship |
|---|---|
Acheson, James M, and James A Wilson. 1996. “Order out of Chaos: The Case for Parametric Fisheries Management.” American Anthropologist 98 (3): 1594–1996. | describe |