Quo vadis ecosystem?

The description of ecosystems’ evolution is a challenge for many scientists. Several attempts have been made, mostly using compartments and flows, to describe the structure of ecosystems and holistic indicators or goal functions (GF) to describe the state and the trend of their evolution. Under a steady flow of energy from the environment, an ecosystem can increase the biomass by enlarging the number of individuals and/or their body weights until a certain steady state level. In this situation neither the structure (e.g. species composition) nor the pattern of flows linking its compartments vary and both biomass and flow reach an “optimal” level. Benefits compensate the costs of the ecosystem evolution. A question is open: when can an ecosystem be considered to be in an optimal state and how does it reach this state? The answer to this question is also useful to solve the problems related to the concept of reference state as posed in the Water Framework Directive (WFD, EU, 2000/60/EC). In order to answer this question the characteristics of a suitable indicator are discussed and two state indicators are proposed, based on the assumption that costs and benefits of the ecosystem growth have to be in balance. The first one, the benefit/cost indicator (BC), is a function of well known state indicators, that fully satisfies the properties required although is difficult to compute and complex to understand. Nevertheless, from the researcher point of view, this indicator gives interesting insights into system behavior. The second, the supply demand balance (SDB), is an indicator based on two main assumptions, the first one being that an ecosystem can be represented by a network of compartments and flows, the second that the metabolic rates scale across species approximately as the (3/4) power of mass. The SDB indicator summarizes the distance of an ecosystem from an optimal state in a single number. Under these assumptions the SDB indicator can be regarded as a measure of ecosystem state. It is easy to compute and simple to understand. SDB looks like a good indicator both for scientific and practical uses to understand where the ecosystem is going. Finally the applicability of SDB is investigated by computing its values for 33 trophic networks describing the food webs of different aquatic ecosystems.