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Different prey species can vary in their significance to a particular predator. In the simplest case, the total available density or biomass of a guild of several prey species might be most relevant to the predator, but behavioural and ecological traits of different prey species can alter the picture. We studied the population dynamics of a predator-prey setting in Finland by fitting first-order log-linear vector autoregressive models to long-term count data from active breeding sites of the northern goshawk (Accipiter gentilis; 1986-2009), and to three of its main prey species (1983-2010): hazel grouse (Bonasa bonasia), black grouse (Tetrao tetrix) and capercaillie (T. urogallus), which belong to the same forest grouse guild and show synchronous fluctuations. Our focus was on modelling the relative significance of prey species and estimating the tightness of predator-prey coupling in order to explain the observed population dynamics, simultaneously accounting for effects of density dependence, winter severity and spatial correlation. We established nine competing candidate models, where different combinations of grouse species affect goshawk dynamics with lags of 1-3 years. Effects of goshawk on grouse were investigated using one model for each grouse species. The most parsimonious model for goshawk indicated separate density effects of hazel grouse and black grouse, and different effects with lags of 1 and 3 years. Capercaillie showed no effects on goshawk populations, while the effect of goshawk on grouse was clearly negative only in capercaillie. Winter severity had significant adverse effects on goshawk and hazel grouse populations. In combination, large-scale goshawk-grouse population dynamics are coupled, but there are no clear mutual effects for any of the individual guild members. In a broader context, our study suggests that pooling data on closely related, synchronously fluctuating prey species can result in the loss of relevant information, rather than increased model parsimony.

We study the dynamics of the capercaillie, black grouse, hazel grouse and willow grouse in Kainuu game management district in northeastern Finland in the years 1989 – 2004. It appears that the 6 – 7 year periodicity that prevailed in this region from 1960s up to 1980s has now vanished in all species. Th e grouse data are modelled using a linear autoregressive model with lag terms for population dynamics including grouse harvest as annual bag and an index of winter severity (winter-time area of Baltic Sea ice cover). We use the Akaike information criterion for selecting the best model for each species; fi rst order lag is forced to the models. It turns out that a term is needed for harvesting (with a negative coeffi cient) in models for all species. For the capercaillie and the hazel grouse second order lag was included, for the black grouse and the willow grouse fi rst order lag suffi ces. Th e willow grouse is the only species where the index of winter strength (with a negative coeffi cient) is needed in the model.

Isolation-by-distance (IBD) is a widely used model explaining population structure and how gene flow decreases with increasing distance. It is biologically intuitive that populations which rarely exchange individuals should drift apart genetically. However, the model is based on the assumptions that populations are large, equal in size and stable over time — conditions that are unlikely to occur in natural conditions. The model has been challenged in the past, for example, in the light of metapopulations or variance in reproductive success. However, an appraisal of the assumption of a large and stable population size per se is lacking. We investigate the robustness of the results concerning IBD patterns when smaller and fluctuating population sizes, or differences in population size are allowed. Through computer simulations we show that allowing for different population sizes and random fluctuations lead to unpredictable patterns regarding the results concerning gene flow and IBD. A pattern of IBD could be the result of high gene flow or no gene flow at all, depending on how populations differ in size and how they fluctuate. Adding environmental noise (white, red and blue noise corresponding to random, positive and negative autocorrelation respectively) gives even more unpredictable results concerning patterns of IBD. Our results have important implications for genetic and conservation research. Interpreting an IBD pattern, or lack thereof, is not as easy as earlier thought and needs to be more thoroughly explored.

Harvest data are commonly used as proxy for count data, especially in studies of long-term temporal and spatial patterns of population fluctuations. However, usually the concurrence of the conclusions based on different types of data is impossible to verify due to the lack of count data. Here, we use annual (1964–2004) harvest and population census data for capercaillie, black grouse and hazel grouse from 14 game management districts covering Finland, and demonstrate some mismatch in the information that these data sets provide. Overall, linear regressions of annual harvest against population count give a reasonable fit, but the slopes are less than 1 in every species. Harvest bags have been proportionally larger in north and eastern Finland than in southwestern Finland, with marked species-specific differences. Considering population variation, the CV% in the census data (30–50%) is consistently smaller than it is in the harvest data (60–70%). Most importantly, conclusions on the spatio-temporal patterns of the population dynamics are different if based on harvest rather than count data. In capercaillie, synchrony decreases faster with distance according to the harvest data, while in black grouse and hazel grouse the census data show the steeper decline. In addition, the autocorrelation coefficients in the census time series are higher in capercaillie and black grouse than in harvest data, but in hazel grouse the opposite is true. Finally, the parameter estimates for a second order autoregressive model using different data sets differ, and these differences are species-specific. Despite the fact that annual harvest is a positive and linear function of annual grouse population density, the pattern of population dynamics derived from the bag data is different from that shown by the census data. This result urges caution in using wildlife bag data as reliable indices of population dynamics. deceased August 2008.

The invasion of alien species and genotypes is an increasing concern in contemporary ecology. A central question is, what life-history traits enable invasion amidst populations of wild species and conventional cultivars? In order to invade, the initially rare species must perform better than their resident competitors. We conducted a mathematical analysis and simulation of a two-species extension of the Maynard Smith and Slatkin model for population dynamics in discrete time to study the role of density dependence as different types of competition in the invasion of new species. The type of density dependence ranged from scramble to contest competition. This led to intrinsic dynamics of the species range from point equilibrium to cycles and chaos. The traits were treated either as free parameters or constrained by a trade-off resulting from a common fixed strength of density dependence or equilibrium density. Resident and intruder traits had up to ten-fold differences in all of the parameters investigated. Higher equilibrium density of the intruder allowed invasion. Under constrained equilibrium density, an intrinsically stable intruder could invade an unstable resident population. Scramble competition made a population more susceptible to invasion than contest competition (e.g., limitation by light or territory availability). This predicts that a population which is mainly limited by food (or nutrients in plants) is more likely to be invaded than a population limited by a hierarchical competition, such as light among plants. The intruder population may have an effect on the resident population’s dynamics, which makes the traditional invasion analysis unable to predict invasion outcome.

Many species from diverse taxa are known to display synchronous fluctuations across vast geographical ranges. It is often thought that climate factors influencing the growth of conspecific populations are correlated over large distances and hence produce the synchronous population dynamics - an effect known as the Moran effect. However, for species embedded in a food web the Moran effect needs not necessarily influence the focal species directly, but can act indirectly through other species. Such an indirect synchronization can also occur in an age-structured population, where the correlated environment of one age-class causes synchronous fluctuations of another. Here, we investigate this indirect Moran effect. We find first of all that synchrony is readily transferred through food webs or between age classes, which complicates the identification of the underlying synchronizing factor. Secondly, we find puzzling cases, where synchrony is enhanced as it is filtered through a food web or between age-classes. Our results also apply to systems of different species, but with closely matching dynamics.

Linkage between environmental variability and population renewal processes is assumed invariable in standard population models. We explored adaptive, density-dependent population dynamics in a setting where population consists of individuals differing in location of their optimum performance relative to a stochastic and autocorrelated environmental variable, such as temperature, humidity or salinity. Relative growth rates of phenotypes are determined by a Gaussian unimodal function of the environmental variable, which also has a unimodal distribution. Adaptive dynamics causes a significant increase in mean population growth performance and decreases its variance. Population growth fluctuates more rapidly, i.e. has a blue-shifted spectrum. This also causes a blue-shift in density-dependent population dynamics in a wide range of population growth rates and autocorrelation of the environment. The blue-shift is most pronounced when the breadth of environmental response is moderately smaller that the breadth of environmental fluctuations. The causes of the blue-shift are discussed. The blue-shift caused by adaptive dynamics is in contrast with views that evolutionary processes redden population time series, i.e. cause slow fluctuations, due to slow changes in population properties. Mean genetic variance is maximised in rapidly fluctuating blue and white noise environments, and when genotype performance breadth is small. In contrast, genotype diversity is maximised in slowly fluctuating red environments and in populations with large performance breadth. Genetic variance and genetic diversity also have marked temporal fluctuations. Temporal variability of genetic variance increases with noise redness and small response breadth. However, genetic diversity is maximised in slightly reddened environments and narrow performance breadth populations. That genetic variance and diversity are affected by the spectrum of environmental noise and also fluctuate temporally, suggest that models assuming constant amount of genetic variability (equilibrium variance) may not be successful in predicting the consequences of environmental changes.

A key question of evolutionary importance is what factors influence who becomes dominant. Individual genetic variation has been found to be associated with several fitness traits, including behaviour. Could it also be a factor influencing social dominance? We investigated the association between social status and the amount of intra-individual genetic variation in juvenile brown trout (Salmo trutta). Genetic variation was estimated using 12 microsatellite loci. Dominant individuals had higher mean heterozygosity than subordinates in populations with the longest hatchery background. Heterozygosity–heterozygosity correlations did not find any evidence of inbreeding; however, single-locus analysis revealed four loci that each individually differed significantly between dominant and subordinate fish, thus giving more support to local than general effect as the mechanism behind the observed association between genetic diversity and a fitness-associated trait. We did not find any significant relation between mean d 2 and social status, or internal relatedness and social status. Our results suggest that individual genetic variation can influence dominance relations, but manifestation of this phenomenon may depend on the genetic background of the population.

Semi-automated fluorescent genotyping of eight polymorphic microsatellite loci was used to assess the level of genetic diversity and population differentiation in Nordic stocks of non-anadromous Arctic charr, Salvelinus alpinus, of both wild and hatchery origin. Highly significant genetic heterogeneity was detected globally across wild and/or hatchery populations and even between populations from lakes separated by as little as six kilometres. The overall level of genetic differentiation among wild populations (FST= 0.360) was substantially higher than that observed between populations of anadromous Arctic charr in Canada using microsatellite data. Cavalli-Sforza and Edward's chord distance was used to construct a neighbour-joining tree and three population clusters were supported with relatively high bootstrap values which included the populations from north-west, north-east and southern Finland respectively. Use of Paetkau et al's individual assignment test further supported the strong differentiation of most populations as well as their classification into the three predicted geographical areas. No significant difference in average allele number or heterozygosity was observed between populations of wild and hatchery origin. However, the effects of hatchery rearing were revealed by a strong increase in the number of deviations from Hardy-Weinberg equilibrium as well as of linkage disequilibrium events in the hatchery stocks compared to natural populations. The population from Lake Saimaa, in south-east Finland, is completely reliant upon aquaculture assistance for its survival. The broodstocks of this population exhibited particularly low levels of genetic variability. Although the hatchery stocks of this population suffer from increased egg and alevin mortality and disease susceptibility, it remains to be determined if this is due directly to a lack of genetic variation as some abundant unstocked natural populations possessed similarly low levels of microsatellite variability.

Non-linearities are commonly observed in the responses of organisms to environment. They potentially modify the qualitative and quantitative properties of population dynamics. We studied how non-linear responses to environment, or “noise filters”, influence population variability and extinction risk by introducing coloured noise to the growth rate in the Hassell single-species model. The consequences of noise filtering were analysed by comparing the model dynamics with linearly filtered and non-linearly filtered noise that have the same mean. Three biologically plausible filters we used: saturating, unimodal optimum type, and sigmoid responses. Filtering can either decrease or increase population variability when compared to linear noise response. The effect of noise filtering on variability is most pronounced with stable population dynamics and the outcome depends on the filter type, population growth rate, and noise colour. Non-linear noise filtering predominantly increases extinction risks when population growth rate is low (R

We assessed how non-linear biological responses to environmental noise, or “noise filtering”, impact the spectra of density-dependent population dynamics, and the correlation between noise and population dynamics. The noise was assumed to affect population growth rate in a discrete-time population model by Hassell [J. Anim. Ecol. 44 (1975) 283–295] where the population growth rate was linked to the environment with an optimum type filter. When compared to unfiltered noise, the filtered noise can distort the stationary distribution of population values. The optimum type filter can make cyclic population dynamics more regular and low population values can become more frequent or rare depending on the strength of density dependence. Filtering can cause blue shifted and red shifted population dynamics and determine the strength of correlation between environmental noise and population size. In most cases, optimum type filtering makes linear correlation between population dynamics and noise weaker. The filter effect on population spectra and noise versus population correlation is sensitive to changes in population model parameters, the location where noise hits the filter, and noise colour.

It has recently been shown that damped endogenous dynamics is a common feature in Finnish grouse species; In this paper, we demonstrate that time-variant harvesting may turn damped dynamics to quasi-periodic fluctuations. Exploited populations, e.g. grouse, may therefore fluctuate more than expected if we do not manage to keep the harvest fraction constant over time. However, the harvest fraction of Finnish grouse varies with the phase of the cycle. Such a harvesting strategy could potentially change the periodicity of the fluctuations, as can a threshold harvest strategy where a constant fraction is harvested above a density threshold. The two non-linear harvesting strategies investigated here can modulate the dynamic properties of the population in a way not predicted by linear models. We argue that the behaviour of exploited populations and the role of harvesting can only be understood if we identify and understand the interplay of endogenous and exogenous components of population dynamics. (Less)

Research on the evolution of life histories addresses the topic of fitness trade-offs between semelparity (reproducing once in a lifetime) and iteroparity (repeated reproductive bouts per lifetime). Bulmer (1994) derived the relationship v+P(A)

Evidence from wildlife and human populations indicates that conditions during early development can have marked effects on the subsequent performance of individuals and cohorts. Likewise, the effects of maternal and, more generally, parental environments can be transferred among individuals between generations. These delayed life-history effects are found consistently and suggestions have been made that they can be one source of both variability and of delayed density dependence in population dynamics. Assessments of several different time series indicate that population variability and delayed density dependence are common and that understanding the mechanisms giving rise to them is crucial for the interpretation and application of such models to basic and applied research. Therefore, it is necessary to assess the different ways in which history in the life history might give rise to variability and delayed density dependence in population dynamics. Here, we build on recent appraisals of the pervasive influence of past environmental conditions on current and future fitness and link the details of these life-history studies to classic features of population dynamics.

Per Lundberg and Jorgen Ripa, Dept of Theoretical Ecology, Lund Univ., Ecology Building, SE-223 62 Lund, Sweden (per.lundberg@teorekol.lu.se). Veijo Kaitala, Dept of Biological and Environmental Science, Univ. of Jyvaskyld, P.O. Box 35, FIN-40351 Jyvaskyll, Finland. Esa Ranta, Integrative Ecology Unit, Div. of Population Biology, Dept of Ecology and Systematics, P.O. Box 17, FIN-00014 University of Helsinki, Finland

Climate change has ignited lively research into its impact on various population–level processes. The research agenda in ecology says that some of the fluctuations in population size are accountable for by the external noise (e.g. weather) modulating the dynamics of populations. We obeyed the agenda by assuming population growth after a resource–limited Leslie matrix model in an age–structured population. The renewal process was disturbed by superimposing noise on the development of numbers in one or several age groups. We constructed models for iteroparous and semelparous breeders so that, for both categories, the population growth rate was matching. We analysed how the modulated population dynamics correlates with the noise signal with different time–lags. No significant correlations were observed for semelparous breeders, whereas for iteroparous breeders high correlations were frequently observed with time–lags of −1 year or longer. However, the latter occurs under red–coloured noise and for low growth rates when the disturbance is on the youngest age group only. It is laborious to find any clear signs of the (red) noise– and age group–specific fluctuations if the disturbance influences older age groups only. These results cast doubts on the possibility of detecting the signature of external disturbance after it has modulated temporal fluctuations in age–structured populations.

The moose Alces alces population in Finland has been managed for sustained harvest since 1970 by regulating annual hunting quotas. However, against all expectations the population size declined in the 1990s. An ecological risk analysis approach was used to build a growth model with annual harvest for the moose population. In the model there is stochasticity in the parameters representing population dynamics. We shall address: 1) whether the population decline could be due to a mismatch between harvest and anticipated population growth rate, and 2) to what extent hunting the moose population down to a much lower target size succeeds. A central element in this is the assumption that the estimate of the pre-hunting population size errs. First, the probability of a population decline due to hunting increases from values close to 0% up to 100% in a very narrow range (15–25%) of harvest rates. Even with high birth rates the risk of a population decline was substantial when the hunting rate exceeded 25% for cows and 37.5% for calves and bulls. The 1974–1994 moose harvest rate was, on average, ca 45% of the population size in autumn. The high rate suggests that the harvest might have been too intense in that period to keep the population stable. Second, we set the target to reduce the moose population drastically (to say 50% of the existing population size). Assuming that the estimates of the population size may err, our analysis shows that the achieved population size after the severe harvest is far below the size we aimed at.

We report an individual-based single-species model producing temporal scale-free, self-similar dynamics in time. Individuals in the population renew in an explicit space with a large number of loci. We show that reproduction, subsequent dispersal of the offspring, and mortality will organise population fluctuations such that the emerging dynamics represent power law and scale-free structures. Further, we show that spatially structured population dynamics may show red frequency spectra, a property that the simple nonlinear population models are generally lacking.

Summary 1. It is widely appreciated that complex population dynamics are more likely in systems where there is a lag in the density dependence. The transmission of maternal environmental conditions to offspring phenotype is a potential cause of such a lag. Maternal effects are increasingly found to be common in a wide range of organisms, and might thus be a frequent cause of nonequilibrium population dynamics. 2. We show that a maternal effects’ lag generally increases population variability. This may result from the lag inducing cycles (or more complex dynamics) in a deterministic environment or, in a stochastic environment, from the lag interacting with environmental noise to produce more variable dynamics than would otherwise occur. This may happen whether the underlying dynamics are equilibrium, periodic or more complex.

We investigate conditions enabling long-term coexistence of semelparity (reproducing only once per lifetime) and iteroparity (repeated spells of reproduction in subsequent breeding seasons). Bulmer (1985, 1994) has transferred the study of the fitness merit of reproducing semelparously vs. iteroparously into a density-dependent system, using an invasion scenario with an abundant resident population of one reproductive strategy and a rare mutant invader population of another reproductive strategy. For stable population dynamics, Bulmer (1994) derived condition v + PA < 1 (PA is adult survival and v is the ratio of offspring number of the iteroparous type over that of the semelparous type) where a semelparous population cannot be invaded by an iteroparous strategy. In order to study the generalisation of Bulmer's results in spatial population dynamics, we generate a population system consisting of a linear string of habitable sub-units. The sub-units are semi-independent, obeying discrete-time Ricker dynamics in renewal, but they are close enough for dispersing individuals to couple them together. At each time step, a random fraction of individuals in each sub-unit disperses into neighbourhood. In this setting, we observe long-term persistence of semelparity and iteroparity when dispersal is stochastic and positively autocorrelated. Stochasticity in dispersal creates fluctuating local dynamics and thus permits long-term persisting coexistence of semelparity and iteroparity even in the parameter region where Ricker dynamics are stable and the Bulmer inequality is true. Positively autocorrelated, in contrast to negatively autocorrelated dispersal time-series, promoted coexistence between semelparity and iteroparity.

Birth and death rates, as so many other biological processes, are usually not linearly related to environmental variation. Common examples of non-linear response forms include unimodal ‘‘optimum-type’’ responses and various saturating responses. These responses filter the signal coming from the environment to a corresponding biological process. We explored how different types of environmental signal may be transformed to a biological process. We were interested in the effect of the filter on modulation of (1) the variance of the signal, on (2) the variance-covariance structure between the signal and the filtered signal, and on (3) the match between the power spectra of the signal and the filtered signal. We found that the filters will change the frequency distribution (mean, variance, modality) of the signal. Especially symmetric filters that have a single peak of optimum will change signal structure so that there either exists or does not exist a correlation between the signal and the filtered signal. When the correlation exists it may be either positive or negative depending on the signal’s mode relative to the filter structure. Also, the power spectrum properties of the signal may be dramatically transformed after passing the filter, e.g., blue noise can turn into red noise. Our results strongly suggest that studies on the influence of external signals on biological processes, such as population dynamics, should explicitly consider how the signal is transferred to biological processes.

We study resource matching – the relationship between resource supply and forager numbers – under conditions of fluctuating population dynamics in a two-patch system. For the inter-patch dispersal we apply the patch-departure rule following the principle of the ideal free distribution: leave the current patch of residence if local conditions are worse than conditions elsewhere on average. We show that such a dispersal rule synchronises cyclic and chaotic local population dynamics, but unlike many other dispersal rules, leaves the underlying population dynamics untouched. We also show that the IFD dispersal rule is not very sensitive to biased information and navigation failures during the dispersal phase. Even under such circumstances we observe a quick process of populations becoming synchronised, even when the population dynamics are chaotic. We conclude that an IFD patch-departure rule represents an ESS dispersal behaviour towards which the dispersal patterns should evolve.

In stark contrast to other species within the Salmonidae family, phylogeographic information on European grayling, Thymallus thymallus, is virtually nonexistent. In this paper, we utilized mitochondrial DNA polymerase chain reaction-restriction fragment length polymorphism (mtDNA PCR-RFLP) and sequence variation to infer the postglacial dispersal routes of T. thymallus into and within northern Europe, and to locate geographically, potential evolutionarily distinct populations. Mitochondrial analyses revealed a total of 27 T. thymallus haplotypes which clustered into three distinct lineages. Average pairwise interlineage divergence was four and nine times higher than average intralineage divergence for RFLP and sequence data, respectively. Two European grayling individuals from the easternmost sample in Russia exhibited haplotypes more genetically diverged from any T. thymallus haplotype than T. arcticus haplotype, and suggested that hybridization/introgression zone of these two sister species may extend much further west than previously thought. Geographic division of the lineages was generally very clear with northern Europe comprising of two genetically differentiated areas: (i) Finland, Estonia and north-western Russia; and (ii) central Germany, Poland and western Fennoscandia. Average interpopulation divergence in North European T. thymallus was 10 times higher than that observed in a recent mtDNA study of North American T. arcticus. We conclude that (i) North European T. thymallus populations have survived dramatic Pleistocene temperature oscillations and originate from ancient eastern and central European refugia; (ii) genetic divergence of population groups within northern Europe is substantial and geographically distinct; and (iii) the remainder of Europe harbours additional differentiated assemblages that likely descend from a Danubian refugium. These findings should provide useful information for developing appropriate conservation strategies for European grayling and exemplify a case with a clear need for multinational co-operation for managing and conserving biodiversity.

According to Fisherian sex allocation theory, parents that can adjust their offspring sex ratio in response to skews in population sex ratio will maximize their fitness over parents lacking this ability. There is good evidence that adaptive sex ratio adjustment occurs in many natural populations, but deviations from theoretical predictions have also been observed. These anomalies may be more apparent than real. When the spatial dimension of sex ratio variation is ignored, then a mismatch between empirical data and theoretical predictions based on panmictic mating is to be expected. We illustrate this with data on human sex ratio variation in 21 preindustrial populations, and with a cellular automaton model built to obey Fisherian sex allocation rules. The results from the model generally match with the data. When information about the ambient sex ratio is limited, then the sex allocation decisions may appear locally maladaptive. In general, the results indicate that Fisher’s sex-ratio theory may have greater explanatory power than previously thought.

We investigated the evolution of monogamy (one male, one female) and polygyny (one male, more than one female). In particular, we studied whether it is possible for a mutant polygynous mating strategy to invade a resident population of monogamous breeders and, alternatively, whether a mutant monogamy can invade resident polygyny. Our population obeys discrete-time Ricker dynamics. The role of males and females in the breeding system is incorporated via the harmonic birth function. The results of the invasability analysis are straightforward. Polygyny is an evolutionarily stable strategy mating system; this holds throughout the examined range of numbers of offspring produced per female. So that the two strategies can coexist, polygyny has to be punished. The coexistence of monogamy and polygyny is achieved by reducing the offspring number for polygyny relative to monogamy. This yields long-term persistence of the strategies for all offspring numbers studied. An alternative punishment is to increase the sensitivity of polygynous breeders to population density. The coexistence is possible only with a limited range of offspring produced. The third way to achieve coexistence of the two mating strategies is to assume that individuals live in a spatially structured population, where dispersal links population subunits to a network. Reducing the dispersal rate of polygynous breeders relative to that of monogamous individuals makes the coexistence feasible. However, for monogamy to persist, the number of offspring produced has to be relatively high.

Spatially synchronous population dynamics have been documented in many taxa. The prevailing view is that the most plausible candidates to explain this pattern are extrinsic disturbances (the Moran effect) and dispersal. In most cases disentangling these factors is difficult. Theoretical studies have shown that dispersal between subpopulations is more likely to produce a negative relationship between population synchrony and distance between the patches than perturbations. As analyses of empirical data frequently show this negative relationship between the level of synchrony and distance between populations, this has emphasized the importance of dispersal as a synchronizing agent. However, several weather patterns show spatial autocorrelation, which could potentially produce patterns in population synchrony similar to those caused by dispersal. By using spatially extended versions of several population dynamic models, we show that this is indeed the case. Our results show that, especially when both factors (spatially autocorrelated perturbations and distance-dependent dispersal) act together, there may exist groups of local populations in synchrony together but fluctuating asynchronously with some other groups of local populations. We also show, by analysing 56 long-term population data sets, that patterns of population synchrony similar to those found in our simulations are found in natural populations as well. This finding highlights the subtlety in the interactions of dispersal and noise in organizing spatial patterns in population fluctuations.

Successful predictions of population fluctuations are valuable in game management, as population estimates are instrumental in increasing the time available for management decisions. However, finding a population model which produces predictions accurate enough to be used for management purposes is often precluded due to scarcity and noisiness of population data. Using two long-term population data sets, 1964-1984 data on Finnish grouse (Tetrao urogallus, T. tetrix and Bonasa bonasia) and 1914-1950 data on coloured fox Vulpes fulva from Canada, we demonstrate the use and power of an artificial neural network in predicting population fluctuations. The performance of an artificial neural network model is compared to two benchmark forecasts: time series mean and the previous data value. Unfortunate as it is, in practise management decisions often have to be made with limited data. Therefore, a notable advantage of neural network modelling is the forecast accuracy even in cases when the time series available are short and noisy, and the processes underlying population fluctuations are not fully understood.

A common ‘rule of thumb' in conservation biology is that populations of more than 100 individuals are not threatened by demographic stochasticity alone. However, the effect of demographic stochasticity on population survival may be strengthened if the population has a non-homogeneous demography. A recently developed measure, the demographic effective population size ND, scales population size by taking the differential contribution of individuals into account. We exemplify the estimation of ND with the current population of the Saimaa ringed seal, comprising about 200 individuals. The estimate of ND is shown to be dependent on how independently individuals can be assumed to reproduce. Completely independent reproduction leads to ND∼ 250, suggesting a safe future for the population. However, when acknowledging the potential of breeding failure due to habitat limitation and difficulties of dispersal among the different subareas of Lake Saimaa, ND lies in an alarming range from six to 30 individuals. The effective means to increase the ND value are limited. Although subdivision itself decreases the value of ND, improving dispersal of individuals is shown to be of limited aid. Instead, the most effective way to enhance future prospects of the Saimaa seal population is to improve pup survival to maturity.

The effect of red, white and blue environmental noise on discrete-time population dynamics is analyzed. The coloured noise is superimposed on Moran-Ricker and Maynard Smith dynamics, the resulting power spectra are less than examined. Time series dominated by short- and long-term fluctuations are said to be blue and red, respectively. In the stable range of the Moran-Ricker dynamics, environmental noise of any colour will make population dynamics red or blue depending the intrinsic growth rate. Thus, telling apart the colour of the noise from the colour of the population dynamics may not be possible. Population dynamics subjected to red and blue environmental noises show, respectively, more red or blue power spectra than those subjected to white noise. The sensitivity to differences in the noise colours decreases with increasing complexity and ultimately disappears in the chaotic range of the population dynamics. These findings are duplicated with the Maynard Smith model for high growth rates when the strength of density dependence changes. However, for low growth rates the power spectra of the population dynamics with noise are red in stable, periodic and aperiodic ranges irrespective of the noise colour. Since chaotic population fluctuations may show blue spectra in the deterministic case, this implies that blue deterministic chaos may become red under any colour of the noise.

Our data are long-term population dynamics of a set of species in different localities in Finland. There is considerable level of species-specific synchrony in population fluctuations among the localities. The degree of synchrony levels off with increasing distance among the populations compared. Climatic perturbations and dispersal have been proposed as pace-making factors for synchrony. According to Moran's theorem, local populations sharing a common structure of density dependence should become synchronized under the influence of a spatially correlated density-independent factor. This predicts synchrony to decay slower with increasing distance between local populations than if the synchrony is caused by dispersal. To explore the significance of the Moran effect and dispersal in explaining the observed regional synchrony, we used a metapopulation system. The Moran effect and dispersal are both capable to synchronize alone local population fluctuations. However, with dispersal the level of synchrony decreases with distance among the populations. Adding Moran's effect does not greatly affect the level of synchrony, nor the negative correlation between synchrony and distance. This finding makes it difficult to tell apart whether an observed negative correlation between the level of synchrony and distance among the compared populations is caused by dispersal alone, or both dispersal and Moran's effect acting together.

Contemporary research has documented a large number of shifts in spring phenology and changes in distribution range although the average spring temperatures have increased by only 0.3–0.6 °C over the past 100 years. Generally, earlier breeding birds have larger clutch sizes, and the advancing spring could thus potentially increase breeding success. Shifts in spring phenology can, however, be crucial for bird reproduction, and mistiming the breeding event may even have negative consequences for population development. Our aim was to explore how weather and prey abundance relates to the breeding performance of a north European top predator, the northern goshawk Accipiter gentilis. Our nationwide dataset from Finland, spanning the period 1989–2004, shows that ambient weather has a greater impact on the timing and success of breeding than the density of grouse Tetraonidae, the main prey of goshawks. Higher early spring temperatures were associated with advancing hatching date of goshawks. Correspondingly, grouse density and temperature during laying and brooding were positively associated with brood size, while precipitation showed a negative connection. Applying our models to a future scenario of climate warming, combined with a 50 % reduction in grouse density, suggests that average breeding dates will advance only 2.5 days and average breeding success would remain the same. Notably, breeding success was not spatially equal throughout Finland, as northern and eastern populations suffered most from declining grouse densities. The observed pattern is thus the opposite to what is expected from a population situated at the northern edge of its distribution range, and thus may help to understand why populations may not increase at the northern edge of their thermal distribution due to climate change.

Using brook (Culaea inconstans) and 10-spined (Pungitius pungitius) sticklebacks we examined body-size related schooling behaviour. Small and large sticklebacks were allowed to choose between two test schools, of small and of large individuals, with and without a piscivorous fish (Oncorhynchus mykiss) visible. Sticklebacks of both species preferred the company of fish of matching body size: small fish associating with a school of small fish, large fish with a school of large fish. While no interspecific differences were found in responses to school selection, body size and predator presence did affect selection of school-type. In both species, small fish tended to show a stronger preference for matching schools. The preference was enhanced in small fish with presence of a predator, but not in large fish. These observations are further evidence for assortative schooling in sticklebacks.

The probability of, and time to, fixation of a mutation in a population has traditionally been studied by the classic Wright-Fisher model where population size is constant. Recent theoretical expansions have covered fluctuating populations in various ways but have not incorporated models of how the environment fluctuates in combination with different levels of density-compensation affecting fecundity. We tested the hypothesis that the probability of, and time to, fixation of neutral, advantageous and deleterious mutations is dependent on how the environment fluctuates over time, and on the level of density-compensation. We found that fixation probabilities and times were dependent on the pattern of autocorrelation of carrying capacity over time and interacted with density-compensation. The pattern found was most pronounced at small population sizes. The patterns differed greatly depending on whether the mutation was neutral, advantageous, or disadvantageous. The results indicate that the degree of mismatch between carrying capacity and population size is a key factor, rather than population size per se, and that effective population sizes can be very low also when the census population size is far above the carrying capacity. This study highlights the need for explicit population dynamic models and models for environmental fluctuations for the understanding of the dynamics of genes in populations.

Using a threshold-triggering framework, we extend the Moran effect to also cover timing of life history events. With two varieties of the model we demonstrate emergence of synchrony in seasonal and annual timing that levels off against distance between sampling sites compared. In the first model we address within-season timing over years. The Finnish data on leafing of European aspen support the model predictions in al detail explored. In the second example the focus is on annual match of seed production in the Finnish Scotch pine and Norway spruce. The model predictions find their match with the data. We show that it is possible to extend Moran’s (1953) idea to encompass events not directly regulated by density-dependent feedback. It is perhaps not too surprising that phenological events can be synchronized in much the same way as population fluctuations.

Background Given the recent changes in climate, there is an urgent need to understand the evolutionary ability of populations to respond to these changes. Methodology/Principal Findings We performed individual-based simulations with different shapes of the fitness curve, different heritabilities, different levels of density compensation, and different autocorrelation of environmental noise imposed on an environmental trend to study the ability of a population to adapt to changing conditions. The main finding is that when there is a positive autocorrelation of environmental noise, the outcome of the evolutionary process is much more unpredictable compared to when the noise has no autocorrelation. In addition, we found that strong selection resulted in a higher load, and more extinctions, and that this was most pronounced when heritability was low. The level of density-compensation was important in determining the variance in load when there was strong selection, and when genetic variance was lower when the level of density-compensation was low. Conclusions The strong effect of the details of the environmental fluctuations makes predictions concerning the evolutionary future of populations very hard to make. In addition, to be able to make good predictions we need information on heritability, fitness functions and levels of density compensation. The results strongly suggest that patterns of environmental noise must be incorporated in future models of environmental change, such as global warming.

The effect of school size on the feeding success of individual three-spined sticklebacks was studied. We found that the proportion of fish feeding on benthic prey increased with school size and that fish in large schools tended to start feeding sooner than fish in small schools. The total number of strikes also increased in larger schools. Despite this evidence for a foraging benefit associated with school membership we propose that improved feeding returns do not alone explain stickleback schooling.

Network topography ranges from regular graphs (linkage between nearest neighbours only) via small-world graphs (some random connections between nodes) to completely random graphs. Small-world linkage is seen as a revolutionary architecture for a wide range of social, physical and biological networks, and has been shown to increase synchrony between oscillating subunits. We study small-world topographies in a novel context: dispersal linkage between spatially structured populations across a range of population models. Regular dispersal between population patches interacting with density-dependent renewal provides one ecological explanation for the large-scale synchrony seen in the temporal fluctuations of many species, for example, lynx populations in North America, voles in Fennoscandia and grouse in the UK. Introducing a small-world dispersal kernel leads to a clear reduction in synchrony with both increasing dispersal rate and small-world dispersal probability across a variety of biological scenarios. Synchrony is also reduced when populations are affected by globally correlated noise. We discuss ecological implications of small-world dispersal in the frame of spatial synchrony in population fluctuations.

Theoretical research into the dynamics of coupled populations has suggested a rich ensemble of spatial structures that are created and maintained either by external disturbances or self-reinforcing interactions among the populations. Long-term data of the Canadian lynx from eight Canadian provinces display large-scale spatial synchrony in population fluctuations. The synchronous dynamics are not time-invariant, however, as pairs of populations that are initially in step may drift out of phase and back into phase. These observations are in agreement with predictions of a spatially-linked population model and support contemporary population ecology theory.

The interface between the evolution of life history traits and population dynamics in temporally and spatially variable environments is the topic of this chapter. Thus, the frame for the life history processes is set by spatial and temporal fluctuations in population density. Here, we will focus primarily on modes of reproduction and we are especially interested in whether alternative reproductive strategies can co-exist in a population. We show that spatially structured populations may allow co-existence of various life history strategies that do not easily co-exist in a nonstructured environment. Also, intrinsic and external temporal fluctuations in the environment tend to enhance polymorphism in certain traits, e.g., iteroparity versus semelparity and whether monogamy or polygamy are favored reproductive strategies. In this chapter, we largely omit genetics, but a short comment on that aspect is found towards the end. All life history problems are related to optimizing reproduction. One central question is how individuals allocate resources to survival and reproduction, and, for example, how offspring number, size, and sex are decided. When we put the evolution of life histories and optimizing behavioral decisions into the context of population dynamics, we will change our focus from optimizing to evolutionary stability. We may introduce, say, different reproductive behavioral patterns in our population models and ask which one of them will be an ESS. Technically, as is the tradition in the ESS literature, we will assume two or more distinct phenotypes competing (Maynard Smith 1982; Bulmer 1994).

Sexually transmitted diseases (STDs) have been shown to increase the costs of multiple mating and therefore favor relatively monogamous mating strategies. We examine another way in which STDs can influence mating systems in species in which female choice is important. Because more popular males are more likely to become infected, STDs can counteract any selective pressure that generates strong mating skews. We build two models to investigate female mate choice when the sexual behavior of females determines the prevalence of infection in the population. The first model has no explicit social structure. The second model considers the spatial distribution of matings under social monogamy, when females mated to unattractive males seek extrapair fertilizations from attractive males. In both cases, the STD has the potential to drastically reduce the mating skew. However, this reduction does not always happen. If the per contact transmission probability is low, the disease dies out and is of no consequence. In contrast, if the transmission probability is very high, males are likely to be infected regardless of their attractiveness, and mating with the most attractive males imposes again no extra cost for the female. We also show that optimal female responses to the risk of STDs can buffer the prevalence of infection to remain constant, or even decrease, with increasing per contact transmission probabilities. In all cases considered, the feedback between mate choice strategies and STD prevalence creates frequency-dependent fitness benefits for the two alternative female phenotypes considered (choosy vs. randomly mating females or faithful vs. unfaithful females). This maintains mixed evolutionarily stable strategies or polymorphisms in female behavior. In this way, a sexually transmitted disease can stabilize the populationwide proportion of females that mate with the most attractive males or that seek extrapair copulations.

We shall examine the impact of Charles S. Elton's 1924 article on periodic fluctuations in animal populations on the development of modern population ecology. We argue that his impact has been substantial and that during the past 75 years of research on multi-annual periodic fluctuations in numbers of voles, lemmings, hares, lynx and game animals he has contributed much to the contemporary understanding of the causes and consequences of population regulation. Elton was convinced that the cause of the regular fluctuations was climatic variation. To support this conclusion, he examined long-term population data then available. Despite his firm belief in a climatic cause of the self-repeating periodic dynamics which many species display, Elton was insightful and far-sighted enough to outline many of the other hypotheses since put forward as an explanation for the enigmatic long-term dynamics of some animal populations. An interesting, but largely neglected aspect in Elton's paper is that it ends with speculation regarding the evolutionary consequences of periodic population fluctuations. The modern understanding of these issues will also be scrutinised here. In population ecology, Elton's 1924 paper has spawned a whole industry of research on populations displaying multi-annual periodicity. Despite the efforts of numerous research teams and individuals focusing on the origins of multi-annual population cycles, and despite the early availability of different explanatory hypotheses, we are still lacking rigorous tests of some of these hypotheses and, consequently, a consensus of the causes of periodic fluctuations in animal populations. Although Elton would have been happy to see so much effort spent on cyclic populations, we also argue that it is unfortunate if this focus on a special case of population dynamics should distract our attention from more general problems in population and community dynamics.

Self-organization and pattern formation represent the emergence of order in temporal and spatial processes. Self-organization in population ecology is gaining attention due to the recent advances concerning temporal fluctuations in the population size of dispersal-linked subunits. We shall report that spatially structured models of population renewal promote the emergence of a complex power law order in spatial population dynamics. We analyse a variety of population models showing that self-organization can be identified as a temporal match in population dynamics among local units, and how the synchrony changes in time. Our theoretical results are concordant with analyses of population data on the Canada lynx.

One of the most ubiquitous phenomena of all natural populations is their variability in numbers in space and time. However, there are notable differences among populations in the way the population size fluctuates. One of the major challenges in population and community ecology is to explain and understand this variety and to find possible underlying rules that might be modified from case-to-case. Population variability also has a spatial component because fluctuations are often synchronized over relatively large distances. Recently, this has led to growing interest in how 'internal' (density-dependent) processes interact with 'external' factors such as environmental variability.

A persistent question in the evolution of life histories is the fitness trade-off between reproducing only once (semelparity) in a lifetime or reproducing repeated times in different seasons (iteroparity). The problem can be formulated into a research agenda by assuming that one reproductive strategy is resident (has already evolved) and by asking whether invasion (evolution) of an alternative reproductive strategy is possible. For a spatially nonstructured system, Bulmer (1994) derived the relationship v + PA1 (PA is adult survival; vbS and bS are offspring numbers for iteroparous and semelparous breeding strategies, respectively) at which semelparous population cannot be invaded by an iteroparous mutant. When the inequality is changed to v + PA1, invasion of a semelparous mutant is not possible. From the inequalities, it is easy to see that possibilities for evolutionary establishment of a novel reproductive strategy are rather narrow. We extended the evolutionary scenario into a spatially structured system with dispersal linkage among the subunits. In this domain, a rare reproductive strategy can easily invade a population dominated by a resident reproductive strategy. The parameter space enabling invasion is far more generous with spatially structured evolutionary scenarios than in a spatially nonstructured system.

Characterizing population fluctuations and their causes is a major theme in population ecology. The debate is on the relative merits of density-dependent and density-independent effects. One paradigm (revived by the research on global warming and its relation to long-term population data) states that fluctuations in population densities can often be accounted for by external noise. Several empirical models have been suggested to support this view. We followed this by assuming a given population skeleton dynamics (Ricker dynamics and second-order autoregressive dynamics) topped off with noise composed of low- and high-frequency components. Our aim was to determine to what extent the modulated population dynamics correlate with the noise signal. High correlations (with time-lag -1) were observed with both model categories in the region of stable dynamics, but not in the region of periodic or complex dynamics. This finding is not very sensitive to low-frequency noise. High correlations throughout the entire range of dynamics are only achievable when the impact of the noise is very high. Fitted parameter values of skeleton dynamics modulated with noise are prone to err substantially. This casts doubt as to what degree the underlying dynamics are any more recognizable after being modulated by the external noise.

Sex, so important in the reproduction of bigametic species, is nonetheless often ignored in explorations of the dynamics of populations. Using a growth model of dispersal-coupled populations we can keep track of fluctuations in numbers of females and males. The sexes may differ from each other in their ability to disperse and their sensitivity to population density. As a further complication, the breeding system is either monogamous or polygamous. We use the harmonic mean birth function to account for sex-ratio-dependent population growth in a Moran–Ricker population renewal process. Incorporating the spatial dimension stabilizes the dynamics of populations with monogamy as the breeding system, but does not stabilize the population dynamics of polygamous species. Most notably, in populations coupled with dispersal, where the sexes differ in their dispersal ability there are rarely stable and equal sex ratios. Rather, a two-point cycle, four-point cycle and eventually complex behaviour of sex-ratio dynamics will emerge with increasing birth rates. Monogamy often leads to less noisy sex-ratio dynamics than polygamy. In our model, the sex-ratio dynamics of coupled populations differ from those of an isolated population system, where a stable 50:50 sex ratio is achievable with equal density-dependence costs for females and males. When sexes match in their dispersal ability, population dynamics and sex-ratio dynamics of coupled populations collapse to those of isolated populations.

We explore extinction rates using a spatially arranged set of subpopulations obeying Ricker dynamics. The population system is subjected to dispersal of individuals among the subpopulations as well as to local and global disturbances. We observe a tight positive correlation between global extinction rate and the level of synchrony in dynamics among thesubpopulations. Global disturbances and to a lesser extent, migration, are capable of synchronizing the temporal dynamics of the subpopulations over a rather wide span of the population growth rate r. Local noise decreases synchrony, as does increasing distance among the subpopulations. Synchrony also levels off with increasing r: in the chaotic region, subpopulations almost invariably behave asynchronously. We conclude that it is asynchrony that reduces the probability of global extinctions, not chaos as such: chaos is a special case only. The relationship between global extinction rate, synchronous dynamics and population growth rate is robust to changes in dispersal rates and ranges.