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1. We examine causes and consequences of natal dispersal within a metapopulation of house sparrows Passer domesticus in an archipelago in Northern Norway where a large proportion of the individuals is colour-ringed. 2. Less than 10% of the fledglings dispersed, i.e. left their natal island. 3. Dispersal was female biased and almost exclusively performed by juveniles. 4. The probability of natal dispersal was not related either to the body condition or the body mass of the juvenile. Similarly, neither clutch size nor hatching date explained a significant proportion of the variance in the probability of dispersal. 5. The probability of male natal dispersal was related to the rank of the fledgling in the size-hierarchy within the brood. Low ranking individuals that hatched early in the season were more likely to disperse. 6. In both sexes, the survival of dispersers at the island of establishment was higher than among the residents on that island. Similarly, dispersers survived better than adults that remained on their island of birth. 7. These results suggest that dispersal may be an adaptive strategy to avoid poor conditions in the natal area.

Summary 1. Here we review recent advances in characterizing pattern of variation in community structure in space and time based on parametric approaches utilizing the full distribution of abundances of species rather than some summary indices. 2. Assessment of biodiversity based on the structure of rank-abundance plots or simple species diversity indices, which describe properties of the sample of individuals, may reveal limited information about the underlying species abundance distribution of the community because the number of individuals counted are dependent on the sampling intensity. For instance, assuming Poisson sampling and an underlying lognormal species abundance distribution implies that observed abundances (counts) are a sample from a Poisson lognormal distribution. A convenient property of this distribution is that the estimate of r 2 can be used as an inverse measure of species diversity in a community as well as the number of unobserved species can be estimated approximately without bias for unknown sampling intensities. 3. If two communities can be described by a bivariate lognormal species abundance model, then the correlation between the log abundances of species in the two communities is an index of similarity that can be estimated without knowledge of sampling intensities using the bivariate Poisson lognormal distribution. This method is even applicable as an approximation when the abundance distribution deviates from the lognormal. 4. An analysis of the interrelationship between the parameters of the lognormal species abundance distribution in communities of species from a wide variety of taxa shows that the canonical hypothesis of Preston in general, for a given number of species, gives far too large variances in the distribution of log abundances. 5. A general feature in community dynamics is that a large component of the variance in the species abundance distribution is caused by heterogeneity among species in the population dynamics as well as environmental noise. This pattern is in contrast to the assumptions of the neutral theory of community dynamics. 6. The choice of species abundance distribution should be a consequence of specific assumptions about the dynamics of the species. We suggest that such specific assumptions for the choice of species abundance model will facilitate more robust comparisons of changes in community structure in time and space.

1. We develop a Bayesian method for analysing mark-recapture data in continuous habitat using a model in which individuals movement paths are Brownian motions, life spans are exponentially distributed and capture events occur at given instants in time if individuals are within a certain attractive distance of the traps. 2. The joint posterior distribution of the dispersal rate, longevity, trap attraction distances and a number of latent variables representing the unobserved movement paths and time of death of all individuals is computed using Gibbs sampling. 3. An estimate of absolute local population density is obtained simply by dividing the Poisson counts of individuals captured at given points in time by the estimated total attraction area of all traps. Our approach for estimating population density in continuous habitat avoids the need to define an arbitrary effective trapping area that characterized previous mark-recapture methods in continuous habitat. 4. We applied our method to estimate spatial demography parameters in nine species of neotropical butterflies. Path analysis of interspecific variation in demographic parameters and mean wing length revealed a simple network of strong causation. Larger wing length increases dispersal rate, which in turn increases trap attraction distance. However, higher dispersal rate also decreases longevity, thus explaining the surprising observation of a negative correlation between wing length and longevity.

1. Studies of seasonality in ecological diversity rarely extend over more than a few years, and few studies of seasonal diversity have explicitly investigated the influence of environmental factors on seasonal community composition, especially in tropical communities. 2. Our 10 years of monthly sampling in Amazonian Ecuador yielded 20 996 individuals of 137 fruit-feeding butterfly species. Seasonal cycles of rainfall drive annual cycles in species diversity and community similarity. Undetermined processes operating most strongly during the dry season maintain species diversity and high community similarity across years. 3. Seasonal cycles in community diversity and similarity are superimposed on a gradual decline in similarity between community samples on a decadal time-scale because of long-term changes in species abundances. 4. Monitoring and analysis of changes in community composition over a range of time-scales can be used to refine models of community dynamics by incorporating environmental factors necessary to predict the ecological impact of future climate change.

Summary1. Animal movements are the primary behavioural adaptation to spatiotemporal heterogeneityin resource availability. Depending on their spatiotemporal scale, movements have been catego-rized into distinct functional groups (e.g. foraging movements, dispersal, migration), and havebeen studied using different methodologies. We suggest striving towards the development of acoherent framework based on the ultimate function of all movement types, which is to increaseindividual fitness through an optimal exploitation of resources varying in space and time.2. We developed a novel approach to simultaneously study movements at different spatiotem-poral scales based on the following proposed theory: the length and frequency of animalmovements are determined by the interaction between temporal autocorrelation in resourceavailability and spatial autocorrelation in changes in resource availability. We hypothesizedthat for each time interval the spatiotemporal scales of moose Alces alces movements corre-spond to the spatiotemporal scales of variation in the gains derived from resource exploita-tion when taking into account the costs of movements (represented by their proxies, forageavailability NDVI and snow depth respectively). The scales of change in NDVI and snowwere quantified using wave theory, and were related to the scale of moose movement usinglinear mixed models.3. In support of the proposed theory we found that frequent, smaller scale movements weretriggered by fast, small-scale ripples of changes, whereas infrequent, larger scale movementsmatched slow, large-scale waves of change in resource availability. Similarly, moose inhabit-ing ranges characterized by larger scale waves of change in the onset of spring migratedlonger distances.4. We showed that the scales of movements are driven by the scales of changes in the netprofitability of trophic resources. Our approach can be extended to include drivers of move-ments other than trophic resources (e.g. population density, density of related individuals,predation risk) and may facilitate the assessment of the impact of environmental changes oncommunity dynamics and conservation.Key-words: Alces alces, foraging, Fourier transform, GPS, migration, NDVI, phenology,resource, spatiotemporal scales, snowIntroduction

1. Many patterns in macroecology are closely related to the total abundance of a species in a region. Here we show that interspecific differences in the pattern of population fluctuations of British bird species can be predicted from knowledge of their overall abundance and some basic life-history characteristics. 2. We identify a rarity syndrome that arises through an increased stochastic influence on population fluctuations with decreasing population size, mainly resulting from an inverse density-dependent effect of demographic stochasticity. This syndrome involves an increase in the annual changes in population size with increasing rarity in the United Kingdom. 3. The relationship between the magnitude of temporal variation and local mean population size differs between species dependent on their life history, i.e. species with larger clutch size and lower survival tended to have larger annual changes in population size than low-reproducing long-lived species. 4. The probability of local disappearance from a study plot depended on the population size and was hence closely related to the overall abundance of the species in UK. For a given population size, this probability was also related to species-specific life-history characteristics, being higher in species with larger clutch sizes and smaller survival rates. 5. Rareness results in a spatial decoupling of the temporal variation in population size. 6. These patterns show that once a species has become rare, e.g. due to human activities, key population dynamical characteristics will change because of density-dependent stochastic effects, which in turn are dependent on species-specific life-history characteristics.

1. One of the greatest challenges in ecology is to develop tools that can give reliable projections of future population fluctuations as well as to quantity uncertainties. The population prediction interval (PPI), i.e. the stochastic interval that includes a given population size with a certain probability, is affected by changes in expected population size, e.g. due to density regulation, fluctuations in population size because of demographic and environmental stochasticity, uncertainties and biases in parameter estimates, and observation error in estimates of population size. 2. The aim of this study was to examine how PPI can be used to obtain reliable projections of future population fluctuations. Our approach is to split long time series into two parts: the first part is used for parameter estimation and the second part is used for comparing population predictions with actual population sizes after a certain period of time. 3. Here we use the Common Birds Census - data from the UK for several species of passerines. Unbiased predictions will give a uniform distribution of the recorded population sizes across the PPI when transformed to a scale defined by the quantiles of the PPI. However, deviations from a uniform distribution reveal biases in the predictions. For instance, if there is a predominance of recorded population sizes in the upper quantiles of the PPI, this shows that our predictions underestimate future population sizes. 4. Unbiased predictions required models that included both partitioning of stochastic influences into demographic and environmental stochasticity as well as observation error. 5. Precision in the population predictions was improved when including observation error as well as density dependence. 6. We recommend that predictions of future fluctuations of small passerine populations are based on models that include density dependence as well as observation error and estimates of the demographic variance that is obtained from individual-based demographic data or based on species-specific life-history characteristics. 7. These results show that constructing PPI by stochastic simulations may be a useful tool for obtaining reliable population projections.

1. Here we examine how sex ratio variation in house sparrow broods interacts with other demographic traits and parental characteristics to improve the understanding of adaptive significance and demographic effects on variation in sex ratio. 2. The sex ratio in complete broods did not deviate significantly from parity (54.9% males). 3. There was sex-specific seasonal variation in the probability of recruitment. Male nestlings that hatched late in the breeding season had larger probability of surviving than early hatched males. 4. An adaptive adjustment of sex ratio should favour production of an excess of males late in the breeding season. Accordingly, the proportion of male offspring increased throughout the breeding season. 5. A significant nonlinear relationship was present between sex ratio and age of the female. However, there was no relationship between parental phenotype and standardized hatch day that could explain the observed seasonal change in sex ratio. 6. The sex-specific number of offspring recruited by a pair to subsequent generations was closely related to the brood sex ratio. 7. These results indicate an adaptive adjustment of sex ratio to seasonal variation in environmental conditions that affects the offspring fitness of the two sexes differently. Our results also suggest that such a sex ratio variation can strongly influence the demography and structural composition of small passerine populations.

1. A general problem in population ecology is to predict under which conditions stochastic variation in the environment has the stronger effect on ecological processes. By analysing temporal variation in a fitness-related trait, body mass, in 21 Norwegian moose Alces alces (L.) populations, we examined whether the influence of temporal variation in different environmental variables were related to different parameters that were assumed to reflect important characteristics of the fundamental niche space of the moose. 2. Body mass during autumn was positively related to early access to fresh vegetation in spring, and to variables reflecting slow phenological development (low June temperature, a long spring with a slow plant progression during spring). In contrast, variables related to food quantity and winter conditions had only a minor influence on temporal variation in body mass. 3. The magnitude of the effects of environmental variation on body mass was larger in populations with small mean body mass or living at higher densities than in populations with large-sized individuals or living at lower densities. 4. These results indicate that the strongest influence of environmental stochasticity on moose body mass occurs towards the borders of the fundamental niche space, and suggests that populations living under good environmental conditions are partly buffered against fluctuations in environmental conditions.

Summary 1. A central question in ecology is to separate the relative contribution of density dependence and stochastic influences to annual fluctuations in population size. Here we estimate the deterministic and stochastic components of the dynamics of different European populations of white stork Ciconia ciconia . We then examined whether annual changes in population size was related to the climate during the breeding period (the ‘tap hypothesis’ sensu Saether, Sutherland & Engen (2004, Advances in Ecological Research , 35 , 185‐209) or during the nonbreeding period, especially in the winter areas in Africa (the ‘tube hypothesis’). 2. A general characteristic of the population dynamics of this long-distance migrant is small environmental stochasticity and strong density regulation around the carrying capacity with short return times to equilibrium. 3. Annual changes in the size of the eastern European populations were correlated by rainfall in the wintering areas in Africa as well as local weather in the breeding areas just before arrival and in the later part of the breeding season and regional climate variation (North Atlantic Oscillation). This indicates that weather influences the population fluctuations of white storks through losses of sexually mature individuals as well as through an effect on the number of individuals that manages to establish themselves in the breeding population. Thus, both the tap and tube hypothesis explains climate influences on white stork population dynamics. 4. The spatial scale of environmental noise after accounting for the local dynamics was 67 km, suggesting that the strong density dependence reduces the synchronizing effects of climate variation on the population dynamics of white stork. 5. Several climate variables reduced the synchrony of the residual variation in population size after accounting for density dependence and demographic stochasticity, indicating that these climate variables had a synchronizing effect on the population fluctuations. In contrast, other climatic variables acted as desynchronizing agents. 6. Our results illustrate that evaluating the effects of common environmental variables on the spatio-temporal variation in population dynamics require estimates and modelling of their influence on the local dynamics.

Large variation was found in age of onset of reproduction among radio-collared female moose (Alces alces) in a population in northern Norway (69°N). Eight (50%) of the individuals matured at 2.5 years old, whereas age of maturity was 3.5 years or older for eight females. Onset of reproduction was closely correlated with body weight. Both calf and yearling weight was significantly higher for those females that matured as 2.5 years old, compared with the other females. Average calf weight differed significantly among females; however, this variation was not significantly correlated with the mother's body weight. Calf weights were significantly correlated with the biomass of the herb species in the mother's summer home-range