Information for new directions in fishery research and management

5.1.10 Information for new directions in fishery research and management

Detecting trends and patterns of variation over time to provide a better understanding of the causal relationships among and between physical, economic and sociocultural factors is key to our approaches to fisheries sustainability, and this is crucially dependent on the collection of reliable data over long periods of time (National Research Council 1999). These understandings will lead to higher levels of appreciation about the linkages between human population growth, utilization of natural resources, environmental degradation and climate change. The Large Marine Ecosystem (LME) approach recognizes five interacting com- ponents, comprising ecosystem productivity at all levels, fishery resources and their response to ex- ploitation, ecosystem and habitat health, socio- economic conditions and governance.

The ecosystem approach to fisheries manage- ment recognizes that the chaotic behaviour of marine ecosystems may never allow accurate ecosystem, hence fishery, forecasts more than a few years in advance (Acheson 1995). This is proba- bly doubly true for freshwater ecosystems, given

the added uncertainty of changes in inland hydro- logic cycles and balances. Nevertheless, short- term predictions can enable early responses to, and modifications of, human interventions (Shepherd and Pope, Chapter 7, this volume). This approach requires commitment to long-term observations of the state and dynamics of ecosystem compo- nents; in particular to regime shifts and alternative stable states (Shepherd and Pope, Chapter 8, this volume). Only through the collection of reliable data, from both observations and experimenta- tion, can new and realistic ecosystem models be developed, which can then contribute to longer- term strategic fishery management plans. Invest- ments in better information will not only generate better stock assessments but will also improve understanding and management of aquatic ecosystems.

In addition, new data sources, particularly from satellites, in situ remote sensing and the wider reach of surveys, are improving knowledge of oceanic conditions such as sea-surface characteris- tics, currents, topography and bottom type. These will all assist in the estimation of the biological, chemical and physical factors that influence aquatic ecosystems and fisheries. New techniques are also rapidly developing for the genetic charac- terizations of fish populations, which will enable a better understanding of population structure and diversity, population mixing and migration (see Ward, Chapter 9, Volume 1).

Notwithstanding these advances, it is an unfor- tunate fact that the best scientific evidence may not be made available in the best form to policy makers and even then it will not necessarily be properly used. For example, prior to the formula- tion of the precautionary approach, the uncer- tainty recognized in fishery assessments has often enabled fishers to effectively resist management measures, or allowed fishery managers to resist calls for increased allocation. Human systems monitoring is clearly part of an overall approach, indeed part of the ecosystem approach, to fishery management. Institutional mechanisms are needed (1) to specify the information required, including non-formal or traditional knowledge, and then adequately communicate this to policy

91 makers, managers and the public, and (2) to analyse

Gathering Data for Monitoring and Management

There are three general categories of indicators the responses of communities, both individuals that inform fishery policy: (1) general patterns and and institutions, to economic, environmental and trends such as catch, employment, contributions fisheries factors.

to GDP (gross domestic product), (2) changes in the

In the current debate about community man- infrastructure and institutions that affect fishery agement or comanagement, it is recognized that management outcomes, and (3) indicators, which the key features of the social framework revolve are usually expressed as indices, against some pre- around mutual commitment, understanding of established reference point, in particular in rela- the problems and methods of addressing them and tion to fishing, such as Maximum Sustainable cooperative/collective action, and that this im- Yield (MSY) or Maximum Economic Yield (MEY) plies open and transparent information communi- (see Chapters 6 and 12, this volume). cation. The sociocultural information domain has

The four information domains described above been neglected, but is key to our understanding of are a convenient classification of the general the human dimension of ecosystem stability and groups of data required for integrated fishery analy- sustainability.

sis and decision making. Each domain can be bro- ken down into a number of classes and within each class there may be numerous data types available

5.2 for inclusion within the information cycle, some FISHERIES

permanently included and some temporary or

INFORMATION DATA

transient. What follows is a general description of