Institutionalized Model-Making and ecosystem-based management of exploited resource populations: a comparison with instrument flight

Abstract

Ecosystem-based management of resource populations is not a reality but a vision for the future. We liken it to instrument flight of an aircraft. An aircraft cannot be controlled without visual reference to the ground (VFR—Visual Flight Rules) or a cluster of flight instruments (IFR—Instrument Flight Rules). Instrument pilots are trained to develop a rhythmic scan of the cluster to obtain information about flight path and attitude. The untrained tendency is to fixate on a single gauge. When this occurs, the aircraft deviates from its desired attitude and trajectory, and control may be lost. This is analogous to single-factor management in which variables, like habitat quality, recruitment, predator control, or harvest rates, are singled out for manipulation without regard to the others. Exploited populations are no less complex than an aircraft in flight. They move through time and space, and can only be effectively managed using the multiplicity of instruments nature has provided. These include distal as well as proximate variables because populations are embedded in ecosystems that holistically propagate indirect effects to them. Therefore, whole-ecosystem-based management is needed, giving attention to multiple control variables as in the case of instrument flight. Only modeling can identify a suite of sufficient controls, both direct and indirect, and place them in a coherent, operational framework. “Flying the resource”, then, is what we conceive as modeling-assisted, ecosystem-based management. We advocate that management institutions should employ ecosystem-based modeling as an ongoing organizational activity in which scientists, managers, and others cooperate in framing conceptual models from which further steps in modeling can proceed. We call this Institutionalized Model-Making (IMM), with two purposes: (1) building teams from indigenous expertise, and (2) producing models to serve in the same relation to nature as flight simulators do to actual aircraft. The models mimic responses to control actions, simulating multifactorial management analogous to the instrument scans and control manipulations of instrument flying. We illustrate our ideas with a STELLA simulation model of the North American white-tailed deer ( Odocoileus virginianus Miller) in the Adirondack Mountains of New York State, USA. Sensitivities of control parameters are ranked, and use of the model in the instrument flight sense is demonstrated. The results reflect on current styles and fashions in ecological modeling.