How might we model an ecosystem

Abstract Predicting ecosystem effects is of crucial importance in a world at threat from natural and human-mediated change. Here we propose an ecologically defensible representation of an ecosystem that facilitates predictive modelling. The representation has its roots in the early trophic and energetic theory of ecosystem dynamics and more recent functional ecology and network theory. Using the arable ecosystem of the UK as an example, we show that the representation allows simplification from the many interacting plant and invertebrate species, typically present in arable fields, to a more tractable number of trophic-functional types. Our compound hypothesis is that “trophic-functional types of plants and invertebrates can be used to explain the structure, diversity and dynamics of arable ecosystems”. The trophic-functional types act as containers for individuals, within an individual-based model, sharing similar trophic behaviour and traits of biomass transformation. Biomass, or energy, flows between the types and this allows the key ecological properties of individual abundance and body mass, at each trophic height, to be followed through simulations. Our preliminary simulation results suggest that the model shows great promise. The simulation output for simple ecosystems, populated with realistic parameter values, is consistent with current laboratory observations and provides exciting indications that it could reproduce field scale phenomena. The model also produces output that links the individual, population and community scales, and may be analysed and tested using community, network (food web) and population dynamic theory. We show that we can include management effects, as perturbations to parameter values, for modelling the effects of change and indicating management responses to change. This model will require robust analysis, testing and validation, and we discuss how we will achieve this in the future.

[1]  M. Emmerson,et al.  Predator–prey body size, interaction strength and the stability of a real food web , 2004 .

[2]  L G Firbank,et al.  Crop management and agronomic context of the Farm Scale Evaluations of genetically modified herbicide-tolerant crops. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[3]  J. P. Grime,et al.  Biodiversity and Ecosystem Functioning: Current Knowledge and Future Challenges , 2001, Science.

[4]  R. Axelrod,et al.  The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration , 1998 .

[5]  D. Bohan,et al.  Weed and invertebrate community compositions in arable farmland , 2008, Arthropod-Plant Interactions.

[6]  C. Hawes,et al.  Individuals as the basic accounting unit in studies of ecosystem function: functional diversity in shepherd's purse, Capsella , 2005 .

[7]  Raymond L. Lindeman The trophic-dynamic aspect of ecology , 1942 .

[8]  S. Leather,et al.  Ladybird egg cluster size: relationships between species, oviposition substrate and cannibalism , 2007, Bulletin of Entomological Research.

[9]  E. Slade,et al.  Experimental evidence for the effects of dung beetle functional group richness and composition on ecosystem function in a tropical forest. , 2007, The Journal of animal ecology.

[10]  Cathy Hawes,et al.  Effects on weed and invertebrate abundance and diversity of herbicide management in genetically modified herbicide-tolerant winter-sown oilseed rape , 2005, Proceedings of the Royal Society B: Biological Sciences.

[11]  R. Pakeman Consistency of plant species and trait responses to grazing along a productivity gradient: a multi‐site analysis , 2004 .

[12]  Roy Turkington,et al.  Effects of growing conditions and source habitat on plant traits and functional group definition , 2001 .

[13]  Mike J. May,et al.  An introduction to the Farm‐Scale Evaluations of genetically modified herbicide‐tolerant crops , 2003 .

[14]  Birgit Müller,et al.  A standard protocol for describing individual-based and agent-based models , 2006 .

[15]  A. Tansley The Use and Abuse of Vegetational Concepts and Terms , 1935 .

[16]  S. Carpenter,et al.  The trophic cascade in lakes: Contents , 1993 .

[17]  A. Dixon,et al.  Insect Predator-Prey Dynamics: Ladybird Beetles and Biological Control , 2000 .

[18]  A. P. Schaffers,et al.  Arthropod assemblages are best predicted by plant species composition. , 2008, Ecology.

[19]  David A. Bohan,et al.  Responses of plants and invertebrate trophic groups to contrasting herbicide regimes in the Farm Scale Evaluations of genetically modified herbicide-tolerant crops. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[20]  N. Britton Essential Mathematical Biology , 2004 .

[21]  Neo D. Martinez,et al.  Network structure and biodiversity loss in food webs: robustness increases with connectance , 2002, Ecology Letters.

[22]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[23]  R. Harrington,et al.  Aphids as crop pests , 2007 .

[24]  M. Emmerson,et al.  Global change alters the stability of food webs , 2005 .

[25]  R. Peters The Ecological Implications of Body Size , 1983 .

[26]  R. Dirzo,et al.  Effects of fragmentation on pollinator abundance and fruit set of an abundant understory palm in a Mexican tropical forest , 2008 .

[27]  G. J. Dean Effect of temperature on the cereal aphids Metopolophium dirhodum (Wlk.), Rhopalosiphum padi (L.) and Macrosiphum avenue (F.) (Hem., Aphididae) , 1974 .

[28]  Cathy Hawes,et al.  Asynchronous and synchronous updating in individual-based models , 2008 .

[29]  H. Godfray,et al.  The structure of a leafminer–parasitoid community , 2000 .

[30]  E. Odum Fundamentals of ecology , 1972 .

[31]  D. Reuman,et al.  Trophic links’ length and slope in the Tuesday Lake food web with species’ body mass and numerical abundance , 2004 .

[32]  Cathy Hawes,et al.  Functional approaches for assessing plant and invertebrate abundance patterns in arable systems , 2009 .

[33]  S. Lavorel,et al.  Plant functional classifications: from general groups to specific groups based on response to disturbance. , 1997, Trends in ecology & evolution.

[34]  Debra Bailey,et al.  Plant functional group composition and large-scale species richness in European agricultural landscapes , 2008 .

[35]  G. Nigel Gilbert,et al.  Simulation for the social scientist , 1999 .

[36]  H. C. LONGUET-HIGGINS Models for Biology , 1967, Nature.

[37]  A. Akingbohungbe,et al.  Comparative assessment of feeding damage by pod-sucking bugs (Heteroptera: Coreoidea) associated with cowpea, Vigna unguiculata ssp. unguiculata in Nigeria , 2007, Bulletin of Entomological Research.

[38]  A. J. Willis The ecosystem : an evolving concept viewed historically , 1997 .

[39]  Hauke Reuter,et al.  Individual-based models as tools for ecological theory and application: Understanding the emergence of organisational properties in ecological systems , 2006 .

[40]  B. Enquist,et al.  Rebuilding community ecology from functional traits. , 2006, Trends in ecology & evolution.

[41]  G. Woodward,et al.  Ecosystem functioning in stream assemblages from different regions: contrasting responses to variation in detritivore richness, evenness and density. , 2008, The Journal of animal ecology.

[42]  P. Calow Towards a definition of functional ecology , 1987 .

[43]  L. Rudstam A bioenergetic model for Mysis growth and consumption applied to a Baltic population of Mysis mixta , 1989 .

[44]  Stephen R. Carpenter,et al.  Ecological community description using the food web, species abundance, and body size , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[45]  Stephen R. Carpenter,et al.  Consumer Control of Lake ProductivityLarge-scale experimental manipulations reveal complex interactions among lake organisms , 1988 .

[46]  David A. Bohan,et al.  Invertebrate responses to the management of genetically modified herbicide-tolerant and conventional spring crops. I. Soil-surface-active invertebrates. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[47]  M. Hill,et al.  Weeds in fields with contrasting conventional and genetically modified herbicide-tolerant crops. I. Effects on abundance and diversity. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[48]  David A. Bohan,et al.  Invertebrate responses to the management of genetically modified herbicide-tolerant and conventional spring crops. II. Within-field epigeal and aerial arthropods. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[49]  Jean-Dominique Lebreton,et al.  Functional groups for response to disturbance in Mediterranean old fields , 1999 .

[50]  A. Dixon,et al.  Variations of microbial biomass and hydrolase activities in purple soil under different cropping modes as affected by ginger planting , 1986 .

[51]  L. M. Schoonhoven,et al.  Insect-plant biology , 1998 .

[52]  M. Emmerson,et al.  MEASUREMENT OF INTERACTION STRENGTH IN NATURE , 2005 .

[53]  David A. Bohan,et al.  Statistical models to evaluate invertebrate–plant trophic interactions in arable systems , 2007, Bulletin of Entomological Research.

[54]  J. Rodríguez,et al.  Nutritional ecology of insects, mites, spiders, and related invertebrates , 1988 .

[55]  Jonathan Storkey,et al.  A functional group approach to the management of UK arable weeds to support biological diversity , 2006 .

[56]  R. May,et al.  Stability and Complexity in Model Ecosystems , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[57]  A. Dixon,et al.  Population dynamics of a tree-dwelling aphid: individuals to populations , 1996 .

[58]  Jane Memmott,et al.  Pollinator webs, plant communities and the conservation of rare plants: arable weeds as a case study , 2006 .

[59]  S. Gourlet‐Fleury,et al.  Can functional classification of tropical trees predict population dynamics after disturbance? , 2008 .

[60]  Stefano Tarantola,et al.  Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models , 2004 .

[61]  David A. Bohan,et al.  Weed seed resources for birds in fields with contrasting conventional and genetically modified herbicide-tolerant crops , 2006, Proceedings of the Royal Society B: Biological Sciences.

[62]  Andrew Paul Gutierrez Applied Population Ecology: A Supply-Demand Approach , 1996 .

[63]  Owen L Petchey,et al.  Size, foraging, and food web structure , 2008, Proceedings of the National Academy of Sciences.

[64]  G. Kokkoris,et al.  Complexity does not affect stability in feasible model communities. , 2008, Journal of theoretical biology.

[65]  P. Turchin Quantitative analysis of movement : measuring and modeling population redistribution in animals and plants , 1998 .

[66]  H. Godfray,et al.  Food web structure of three guilds of natural enemies: predators, parasitoids and pathogens of aphids. , 2008, The Journal of animal ecology.

[67]  R. Zang,et al.  Identification of functional groups in an old-growth tropical montane rain forest on Hainan Island, China , 2008 .

[68]  Neo D. Martinez,et al.  Food-web structure and network theory: The role of connectance and size , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[69]  G. Polis,et al.  Complex Trophic Interactions in Deserts: An Empirical Critique of Food-Web Theory , 1991, The American Naturalist.

[70]  Fabien Quétier,et al.  Assessing functional diversity in the field - methodology matters! , 2007 .

[71]  M. J. Townsend,et al.  Estimating the potential role of freshwater shrimp on an aquatic insect assemblage in a tropical headwater stream: a bioenergetics approach , 2000 .

[72]  John Maynard Smith Models in ecology , 1974 .