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Measuring (dis)similarity between ecosystem states is a key theme in ecology. Much of community and ecosystem ecology is devoted to searching for patterns in ecosystem similarity from an external observer's viewpoint, using variables such as species abundances, measures of diversity and complexity. However, from the point of view of organisms in the ecosystem, proportional population growth rates are the only relevant aspect of ecosystem state, because natural selection acts on groups of organisms with different proportional population growth rates. We therefore argue that two ecosystem states are equivalent if and only if, for each species they contain, the proportional population growth rate does not differ between the states. Based on this result, we develop species-level and aggregated summary measures of ecosystem state and discuss their ecological meaning. We illustrate our approach using a long-term dataset on the plankton community from the Central European Lake Constance. We show that the first three principal components of proportional population growth rates describe most of the variation in ecosystem state in Lake Constance. We strongly recommend using proportional population growth rates and the derived equivalence classes for comparative ecosystem studies. This opens up new perspectives on important existing topics such as alternative stable ecosystem states, community assembly, and the processes generating regularities in ecosystems.

International audience

Mechanistic understanding of consumer-resource dynamics is critical to predicting the effects of global change on ecosystem structure, function and services. Such understanding is severely limited by mechanistic models inability to reproduce the dynamics of multiple populations interacting in the field. We surpass this limitation here by extending general consumer-resource network theory to the complex dynamics of a specific ecosystem comprised by the seasonal biomass and production patterns in a pelagic food web of a large, well-studied lake. We parameterised our allometric trophic network model of 24 guilds and 107 feeding relationships using the lakes food web structure, initial spring biomasses and body-masses. Adding activity respiration, the detrital loop, minimal abiotic forcing, prey resistance and several empirically observed rates substantially increased the model's fit to the observed seasonal dynamics and the size-abundance distribution. This process illuminates a promising approach towards improving food-web theory and dynamic models of specific habitats.

1. New patterns and trends in land use are becoming increasingly evident in Europe's heavily modified landscape and else whereas sustainable agriculture and nature restoration are developed as viable long-term alternatives to intensively farmed arable land. The success of these changes depends on how soil biodiversity and processes respond to changes in management. To improve our understanding of the community structure and ecosystem functioning of the soil biota, we analyzed abiotic variables across 200 sites, and biological variables across 170 sites in The Netherlands, one of the most intensively farmed countries. The data were derived from the Dutch Soil Quality Network (DSQN), a long-term monitoring framework designed to obtain ecological insight into soil types (STs) and ecosystem types (ETs). 2. At the outset we describe STs and biota, and we estimate the contribution of various groups to the provision of ecosystem services. We focused on interactive effects of soil properties on community patterns and ecosystem functioning using food web models. Ecologists analyze soil food webs by means of mechanistic and statistical modelling, linking network structure to energy flow and elemental dynamics commonly based on allometric scaling. 3. We also explored how predatory and metabolic processes are constrained by body size, diet and metabolic type, and how these constraints govern the interactions within and between trophic groups. In particular, we focused on how elemental fluxes determine the strengths of ecological interactions, and the resulting ecosystem services, in terms of sustenance of soil fertility. 4. We discuss data mining, food web visualizations, and an appropriate categorical way to capture subtle interrelationships within the DSQN dataset. Sampled metazoans were used to provide an overview of below-ground processes and influences of land use. Unlike most studies to date we used data from the entire size spectrum, across 15 orders of magnitude, using body size as a continuous trait crucial for understanding ecological services. 5. Multimodality in the frequency distributions of body size represents a performance filter that acts as a buffer to environmental change. Large differences in the body-size distributions across ETs and STs were evident. Most observed trends support the hypothesis that the direct influence of ecological stoichiometry on the soil biota as an independent predictor (e.g. in the form of nutrient to carbon ratios), and consequently on the allometric scaling, is more dominant than either ET or ST. This provides opportunities to develop a mechanistic and physiologically oriented model for the distribution of species' body sizes, where responses of invertebrates can be predicted. 6. Our results highlight the different roles that organisms play in a number of key ecosystem services. Such a trait-based research has unique strengths in its rigorous formulation of fundamental scaling rules, as well as in its verifiability by empirical data. Nonetheless, it still has weaknesses that remain to be addressed, like the consequences of intraspecific size variation, the high degree of omnivory, and a possibly inaccurate assignment to trophic groups. 7. Studying the extent to which nutrient levels influence multitrophic interactions and how different land-use regimes affect soil biodiversity is clearly a fruitful area for future research to develop predictive models for soil ecosystem services under different management regimes. No similar efforts have been attempted previously for soil food webs, and our dataset has the potential to test and further verify its usefulness at an unprecedented space scale.