The metacommunity concept is an important way to think about linkages between different spatial scales in ecology. Here we review current understanding about this concept. We first investigate issues related to its definition as a set of local communities that are linked by dispersal of multiple potentially interacting species. We then identify four paradigms for metacommunities: the patch-dynamic view, the species-sorting view, the mass effects view and the neutral view, that each emphasizes different processes of potential importance in metacommunities. These have somewhat distinct intellectual histories and we discuss elements related to their potential future synthesis. We then use this framework to discuss why the concept is useful in modifying existing ecological thinking and illustrate this with a number of both theoretical and empirical examples. As ecologists strive to understand increasingly complex mechanisms and strive to work across multiple scales of spatio-temporal organization, concepts like the metacommunity can provide important insights that frequently contrast with those that would be obtained with more conventional approaches based on local communities alone.

In this paper we develop a dynamical theory of coevolution in ecological communities. The derivation explicitly accounts for the stochastic components of evolutionary change and is based on ecological processes at the level of the individual. We show that the coevolutionary dynamic can be envisaged as a directed random walk in the community's trait space. A quantitative description of this stochastic process in terms of a master equation is derived. By determining the first jump moment of this process we abstract the dynamic of the mean evolutionary path. To first order the resulting equation coincides with a dynamic that has frequently been assumed in evolutionary game theory. Apart from recovering this canonical equation we systematically establish the underlying assumptions. We provide higher order corrections and show that these can give rise to new, unexpected evolutionary effects including shifting evolutionary isoclines and evolutionary slowing down of mean paths as they approach evolutionary equilibria. Extensions of the derivation to more general ecological settings are discussed. In particular we allow for multi-trait coevolution and analyze coevolution under nonequilibrium population dynamics.

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Summary 1.This article reviews the application of some summary statistics from current theory of spatial point processes for extracting information from spatial patterns of plants. Theoretical measures and issues connected with their estimation are described. Results are illustrated in the context of specific ecological questions about spatial patterns of trees in two forests. 2. The pair correlation function, related to Ripley's K function, provides a formal measure of the density of neighbouring plants and makes precise the general notion of a 'plant's-eye' view of a community. The pair correlation function can also be used to describe spatial relationships of neighbouring plants with different qualitative properties, such as species identity and size class. 3. The mark correlation function can be used to describe the spatial relationships of quantitative measures (e.g. biomass). We discuss two types of correlation function for quantitative marks. Applying these functions to the distribution of biomass in a temperate forest, it is shown that the spatial pattern of biomass is uncoupled from the spatial pattern of plant locations. 4. The inhomogeneous pair correlation function enables first-order heterogeneity in the environment to be removed from second-order spatial statistics. We illustrate this for a tree species in a forest of high topographic heterogeneity and show that spatial aggregation remains after allowing for spatial variation in density. An alternative method, the master function, takes a weighted average of homogeneous pair correlation functions computed in subareas; when applied to the same data and compared with the former method, the spatial aggregations are smaller in size. 5. Synthesis. These spatial statistics, especially those derived from pair densities, will help ecologists to extract important ecological information from intricate spatially correlated plants in populations and communities.

Concern about the impact of fishing on ecosystems and fisheries production is increasing (1, 2). Strategies to reduce these impacts while addressing the growing need for food security (3) include increasing selectivity (1, 2): capturing species, sexes, and sizes in proportions that differ from their occurrence in the ecosystem. Increasing evidence suggests that more selective fishing neither maximizes production nor minimizes impacts (4-7). Balanced harvesting would more effectively mitigate adverse ecological effects of fishing while supporting sustainable fisheries. This strategy, which challenges present management paradigms, distributes a moderate mortality from fishing across the widest possible range of species, stocks, and sizes in an ecosystem, in proportion to their natural productivity (8), so that the relative size and species composition is maintained.

In this paper we develop a dynamical theory of coevolution in ecological communities. The derivation explicitly accounts for the stochastic components of evolutionary change and is based on ecological processes at the level of the individual. We show that the coevolutionary dynamic can be envisaged as a directed random walk in the community's trait space. A quantitative description of this stochastic process in terms of a master equation is derived. By determining the first jump moment of this process we abstract the dynamic of the mean evolutionary path. To first order the resulting equation coincides with a dynamic that has frequently been assumed in evolutionary game theory. Apart from recovering this canonical equation we systematically establish the underlying assumptions. We provide higher order corrections and show that these can give rise to new, unexpected evolutionary effects including shifting evolutionary isoclines and evolutionary slowing down of mean paths as they approach evolutionary equilibria. Extensions of the derivation to more general ecological settings are discussed. In particular we allow for multi-trait coevolution and analyze coevolution under nonequilibrium population dynamics.

A numerical technique for assembly of ecological communities of Lotka-Volterra form is described. The technique is based upon a global criterion for coexistence of species known as permanence. This provides a relatively fast and accurate method to determine the sequence of communities that develops when species are drawn sequentially and in an arbitrary order from a regional pool of species. Steps in the assembly sequence that cannot be resolved by this method are determined by numerical integration. The results are as follows.( 1) At each step in an assembly sequence, a species that succeeds in invading when rare persists in the resulting community even if one or more of the resident species becomes extinct. (2) Assembly sequences are terminated with a community that is uninvadable by any of the remaining species from the pool. The number of these endpoints is small, even when the species pool is large. (3) In some cases, the final community cannot be reassembled from the species left in it; other species, which are absent at the end, are needed for the endpoint to be reached. (4) Invasion resistance builds up in three stages during an assembly sequence. Over much of the sequence, invasion resistance shows little if any increase; during this period, species composition continues to change until the sequence happens to land on an endpoint. (5) Communities assembled from large species pools are more resistant to invasion than those assembled from small species pools.

with SummaryAge-specific exploitation of a natural population acts as a selective force on genetic variation in life history traits. Evolution arising from this selection may bring about evolutionary changes in the total yield which the population is able to sustain. An analysis of this process is given for a harvested population with densitydependent recruitment, in which selection of life history traits by cropping is independent of density and frequency. Evolution of the total yield depends on an interplay between the yield from an individual over the course of its life and recruitment; whether the total yield increases or decreases depends on the properties of particular populations. Evolution brought about by harvesting does not, in general, lead to the maximization of the total yield. Nonetheless, by appropriate choice of an age-specific harvest pattern, it is possible in principle to select the life history which gives the maximum total yield following evolution; this harvest pattern is called the 'evolutionarily stable optimal harvesting strategy' (ESOHS). Results of the analysis are illustrated with data on the Arcto-Norwegian cod.