Dispersal costs can be classified into energetic, time, risk and opportunity costs and may be levied directly or deferred during departure, transfer and settlement. They may equally be incurred during life stages before the actual dispersal event through investments in special morphologies. Because costs will eventually determine the performance of dispersing individuals and the evolution of dispersal, we here provide an extensive review on the different cost types that occur during dispersal in a wide array of organisms, ranging from micro-organisms to plants, invertebrates and vertebrates. In general, costs of transfer have been more widely documented in actively dispersing organisms, in contrast to a greater focus on costs during departure and settlement in plants and animals with a passive transfer phase. Costs related to the development of specific dispersal attributes appear to be much more prominent than previously accepted. Because costs induce trade-offs, they give rise to covariation between dispersal and other life-history traits at different scales of organismal organisation. The consequences of (i) the presence and magnitude of different costs during different phases of the dispersal process, and (ii) their internal organisation through covariation with other life-history traits, are synthesised with respect to potential consequences for species conservation and the need for development of a new generation of spatial simulation models.

The topology of ecological interaction webs holds important information for theories of coevolution, biodiversity, and ecosystem stability . However, most previous network analyses solely counted the number of links and ignored variation in link strength. Because of this crude resolution, results vary with scale and sampling intensity, thus hampering a comparison of network patterns at different levels . We applied a recently developed quantitative and scale-independent analysis based on information theory to 51 mutualistic plant-animal networks, with interaction frequency as measure of link strength. Most networks were highly structured, deviating significantly from random associations. The degree of specialization was independent of network size. Pollination webs were significantly more specialized than seed-dispersal webs, and obligate symbiotic ant-plant mutualisms were more specialized than nectar-mediated facultative ones. Across networks, the average specialization of animal and plants was correlated, but is constrained by the ratio of plant to animal species involved. In pollination webs, rarely visited plants were on average more specialized than frequently attended ones, whereas specialization of pollinators was positively correlated with their interaction frequency. We conclude that quantitative specialization in ecological communities mirrors evolutionary trade-offs and constraints of web architecture. This approach can be easily expanded to other types of biological interactions.

Based on a marginal value approach, we derive a nonlinear expression for evolutionarily stable (ES) dispersal rates in a metapopulation with global dispersal. For the general case of density-dependent population growth, our analysis shows that individual dispersal rates should decrease with patch capacity and-beyond a certain threshold-increase with population density. We performed a number of spatially explicit, individual-based simulation experiments to test these predictions and to explore further the relevance of variation in the rate of population increase, density dependence, environmental fluctuations and dispersal mortality on the evolution of dispersal rates. They confirm the predictions of our analytical approach. In addition, they show that dispersal rates in metapopulations mostly depend on dispersal mortality and inter-patch variation in population density. The latter is dominantly driven by environmental fluctuations and the rate of population increase. These conclusions are not altered by the introduction of neighbourhood dispersal. With patch capacities in the order of 100 individuals, kin competition seems to be of negligible importance for ES dispersal rates except when overall dispersal rates are low.

Summary 1.Understanding the causes and consequences of dispersal remains a central topic in ecology and evolution. However, a mismatch exists between our empirical understanding of the complexity of dispersal and our representation of dispersal in models. While the empirical literature is replete with examples of condition dependence at the emigration, movement and settlement phases, models rarely incorporate realism or complexity to this degree. Nor do models often include the different costs associated with dispersal, which can themselves be linked to one or more of the three key phases. 2. Here, we propose that by explicitly accounting for emigration, movement and settlement (and the multiple costs associated with each) we can substantially improve our understanding of both the dispersal process itself and how dispersal traits trade off against other life-history characteristics. We explore some of these issues conceptually, before presenting illustrative results gained from a flexible individual-based model which incorporates considerable dispersal complexity. 3. These results emphasise the nonlinear interplay between the different dispersal stages. For example, we find that investment in movement ability (at a cost to fecundity) depends upon the propensity to emigrate (and vice versa). However, owing to selection acting at the metapopulation level as well as at the individual level, the relationship between the two is not straightforward. Importantly, the shape of the trade-off between movement ability and reproductive potential can strongly influence the joint evolution of dispersal parameters controlling the degree of investment in safer movement, the probability of emigration and the straightness of movement. 4. Our results highlight that the joint evolution of dispersal characteristics can have major implications for spatial population dynamics and we argue that, in addition to increasing our fundamental biological understanding, a new generation of dispersal modelling, which exploits recent empirical advances, can substantially improve our ability to predict and manage the response of species to environmental change.

Summary1 Anthropogenic changes in the global climate are shifting the potential ranges of many plant species. 2 Changing climates will allow some species the opportunity to expand their range, others may experience a contraction in their potential range, while the current and future ranges of some species may not overlap. Our capacity to generalize about the threat these range shifts pose to plant diversity is limited by many sources of uncertainty. 3 In this paper we summarize sources of uncertainty for migration forecasts and suggest a research protocol for making forecasts in the context of uncertainty.

Models describing the evolution of dispersal strategies have mostly focused on the evolution of dispersal rates. Taking trees as a model for organisms with undirected, passive dispersal, we have developed an individual-based, spatially explicit simulation tool to investigate the evolution of the dispersal kernel, P(r), and its resulting cumulative seed-density distribution, D(r). Simulations were run on a variety of fractal landscapes di¡ering in the fraction of suitable habitat and the spatial autocorrelation. Starting from a uniform D(r), evolution led to an increase in the fraction of seeds staying in the home cell, a reduction of the dispersal mortality (arrival in unsuitable habitat), and the evolution of`fat-tailed' D(r) in autocorrelated landscapes and approximately uniform D(r) in random landscapes. The evolutionary process was characterized by long periods of stasis with a few bouts of rapid change in the dispersal rate.

Many organisms show polymorphism in dispersal distance strategies. Th is variation is particularly ecological relevant if it encompasses a functional separation of short-(SDD) and long-distance dispersal (LDD). It remains, however, an open question whether both parts of the dispersal kernel are similarly aff ected by landscape related selection pressures.We implemented an individual-based model to analyze the evolution of dispersal traits in fractal landscapes that vary in the proportion of habitat and its spatial confi guration. Individuals are parthenogenetic with dispersal distance determined by two alleles on each individual's genome: one allele coding for the probability of global dispersal and one allele coding for the variance σ of a Gaussian local dispersal with mean value zero.Simulations show that mean distances of local dispersal and the probability of global dispersal, increase with increasing habitat availability, but that changes in the habitat's spatial autocorrelation impose opposing selective pressure: local dispersal distances decrease and global dispersal probabilities increase with decreasing spatial autocorrelation of the available habitat. Local adaptation of local dispersal distance emerges in landscapes with less than 70% of clumped habitat.Th ese results demonstrate that long and short distance dispersal evolve separately according to diff erent properties of the landscape. Th e landscape structure may consequently largely aff ect the evolution of dispersal distance strategies and the level of dispersal polymorphism.

Roughly 40 years after its introduction, the metapopulation concept is central to population ecology. The notion that local populations and their dynamics may be coupled by dispersal is without any doubt of great importance for our understanding of population‐level processes. A metapopulation describes a set of subpopulations linked by (rare) dispersal events in a dynamic equilibrium of extinctions and recolonizations. In the large body of literature that has accumulated, the term “metapopulation” is often used in a very broad sense; most of the time it simply implies spatial heterogeneity. A number of reviews have recently addressed this problem and have pointed out that, despite the large and still growing popularity of the metapopulation concept, there are only very few empirical examples that conform with the strict classical metapopulation (CM) definition. In order to understand this discrepancy between theory and observation, we use an individual‐based modeling approach that allows us to pinpoint the environmental conditions and the life‐history attributes required for the emergence of a CM structure. We find that CM dynamics are restricted to a specific parameter range at the border between spatially structured but completely occupied and globally extinct populations. Considering general life‐history attributes, our simulations suggest that CMs are more likely to occur in arthropod species than in (large) vertebrates. Since the specific type of spatial population structure determines conservation concepts, our findings have important implications for conservation biology. Our model suggests that most spatially structured populations are panmictic, patchy, or of mainland–island type, which makes efforts spent on increasing connectivity (e.g., corridors) questionable. If one does observe a true CM structure, this means that the focal metapopulation is on the brink of extinction and that drastic conservation measures are needed.