Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call patternoriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity. What makes James Bond an agent? He has a clear goal, he is autonomous in his decisions about achieving the goal, and he adapts these decisions to his rapidly changing situation. We are surrounded by such autonomous, adaptive agents: cells of the immune system, plants, citizens, stock market investors, businesses, etc. The agent-based complex systems (1) (ACSs) around us are made up of myriad interacting agents. One of the most important challenges confronting modern science is to understand and predict such systems. Bottom-up simulation modeling is one tool for doing so: We compile relevant information about entities at a lower level of the system (in Bagent-based models,[ these are individual agents), formulate theories about their behavior, implement these theories in a computer simulation, and observe the emergence of system-level properties related to particular questions (2, 3).Bottom-up models have been developed for many types of ACSs (4), but the identification of general principles underlying the organization of ACSs has been hampered by the lack of an explicit strategy for coping with the two main challenges of bottom-up modeling: complexity and uncertainty (5, 6). Consequently, model structure often is chosen ad hoc, and the focus is often on how to represent agents without sufficient emphasis on analyzing and validating the applicability of models to real problems (5, 7).A strategy called pattern-oriented modeling (POM) attempts to make bottom-up modeling more rigorous and comprehensive (6,(8)(9)(10). In POM, we explicitly follow the basic research program of science: the explanation of observed patterns (11). Patterns are defining characteristics of a system and often, therefore, indicators of essential underlying processes and structures. Patterns contain information on the internal organization of a system, but in a Bcoded[ form. The purpose of POM is to Bdecode[ this information (10).The motivation for POM is that, for complex systems, a single pattern observed at a specific scale and hierarchical level is not sufficient to reduce uncertainty in model structure and parameters. This has long been known in science. For example, Chargaff_s rule of DNA base pairing was not sufficient to decode the structure of DNA-until combined with patterns from x-ray...

When plants are competing, larger individuals often obtain a disproportionate share of the contested resources and suppress the growth of their smaller neighbors, a phenomenon called size-asymmetric competition. We review what is known about the mechanisms that give rise to and modify the degree of size asymmetry in competition among plants, and attempt to clarify some of the confusion in the literature on size asymmetry. We broadly distinguish between mechanisms determined primarily by characteristics of contested resource from those that are influenced by the growth and behavior of the plants themselves. To generate size asymmetric resource competition, a resource must be "pre-emptable." Because of its directionality, light is the primary, but perhaps not the only, example of a pre-emptable resource. The available data suggest that competition for mineral nutrients is often size symmetric (i.e., contested resources are divided in proportion to competitor sizes), but the potential role of patchily and/or episodically supplied nutrients in causing size asymmetry is largely unexplored. Virtually nothing is known about the size symmetry of competition for water. Plasticity in morphology and physiology acts to reduce the degree of size asymmetry in competition. We argue that an allometric perspective on growth, allocation, resource uptake, and resource utilization can help us understand and quantify the mechanisms through which plants compete.

No abstract

No abstract

No abstract

plant species better competitors than native plant species? Á/ evidence from pair-wise experiments. Á/ Oikos 105: 229 Á/238.Invasive plants often appear to be more competitive than native species, but there have been few tests of this hypothesis. We reviewed published pair-wise experiments between invading and native plant species. Although the designs that have been used allow only limited inferences, the available data suggest that the effect of invasive species on native species is usually stronger than vice versa. Furthermore, mixtures of invasive and native species are generally less productive than monocultures of the native species, but not less than monocultures of the invasive species. However, the selection of invaders and natives for study has not been random, and the data could be biased towards highly competitive invaders and natives that are weaker than average competitors. We attempt to clarify confusion surrounding the concept of competitive superiority in the context of plant invasions, and we discuss the limitations of the methods that have been used to investigate competition between invasive and native species. To rigorously test the generality of the hypothesis that invaders are better competitors than natives we need to compare the effects of closely related native and invasive species on each other. We suggest that the influence of an invading species on total plant community biomass is an important clue in understanding the role of competition in a plant invasion. The role of competition in the establishment and naturalization stages of the invasion process may be very different from its role in the ''outbreak'' stage.

The term "size hierarchy" has been used frequently by plant population biologists but it has not been defined. Positive skewness of the size distribution, which has been used to evaluate size hierarchies, is inappropriate. We suggest that size hierarchy is equivalent to size inequality. Methods developed by economists to evaluate inequalities in wealth and income, the Lorenz curve and Gini Coefficient, provide a useful quantification of inequality and allow us to compare populations. A measure of inequality such as the Gini Coefficient will usually be more appropriate than a measure of skewness for addressing questions concerning plant population structure.

Th~ effect~ of inter-~nd intraspecific interference on size hierarchies (size inequalities) were Investigated m populations of the annual plants Trifolium incarnatum and Latium mu~tijlorum. Va~ables experimentally manipulated included plant density, species proportions, soil fertilit~, and spatial pattern of plantings. Densities were below those for extensive density-dependent mortality.S_ize ine'!-uality ~!ways increased with increasing density. Plants grown individually showed very !ow me~uality, w~Ile plants grown at the highest density had the most developed hierarchies. Size meq~;~ality _usua!IY mcreased with an increase in productivity when interference was occurring. When dom.mant m mixtures, Loliu~ showed les_s size inequality than in monoculture, while the suppressed ~pecies, Trifolium, usually displayed an mcrease in inequality. Spatial pattern appeared to be less Importan~ t~an other factor~ in_ causin? size inequalities; pl~nts sown in a uniform spatial pattern showed Sigmficantl_r l<_>wer Size m~quality than plants sown m a random pattern in only one out of four cases. Inequality m reproductive output of Trifolium, as estimated by dry mass of flower heads was always greater than inequality in plant dry mass.' The results support a model of plant interference in which large plants are able to usurp resources ~nd suppress the growth of smaller individuals more than they themselves are suppressed. While mterferenc~ decreases mean plant mass, it increases both the relative variation in plant mass and the concentratiOn of mass within a small fraction of the population.