Effects of local density dependence and temperature on the spatial synchrony of marine fish populations.

Disentangling empirically the many processes affecting spatial population synchrony is a challenge in population ecology. Two processes that could have major effects on the spatial synchrony of wild population dynamics are density dependence and variation in environmental conditions like temperature. Understanding these effects is crucial for predicting the effects of climate change on local and regional population dynamics. We quantified the direct contribution of local temperature and density dependence to spatial synchrony in the population dynamics of nine fish species inhabiting the Barents Sea. First, we estimated the degree to which the annual spatial autocorrelations in density are influenced by temperature. Second, we estimated and mapped the local effects of temperature and strength of density dependence on annual changes in density. Finally, we measured the relative effects of temperature and density dependence on the spatial synchrony in changes in density. Temperature influenced the annual spatial autocorrelation in density more in species with greater affinities to the benthos and to warmer waters. Temperature correlated positively with changes in density in the eastern Barents Sea for most species. Temperature had a weak synchronizing effect on density dynamics, while increasing strength of density dependence consistently desynchronised the dynamics. Quantifying the relative effects of different processes affecting population synchrony is important to better predict how population dynamics might change when environmental conditions change. Here, high degrees of spatial synchrony in the population dynamics remained unexplained by local temperature and density dependence, confirming the presence of additional synchronizing drivers, such as trophic interactions or harvesting.

The role of seasonal migration in spatial population synchrony.

Spatially synchronized population dynamics are common in nature, and understanding their causes is key for predicting species persistence. A main driver of synchrony between populations of the same species is shared environmental conditions, which cause populations closer together in space to be more synchronized than populations further from one another. Most theoretical and empirical understanding of this driver considers resident species. For migratory species, however, the degree of spatial autocorrelation in the environment may change across seasons and vary by their geographic location along the migratory route or on a nonbreeding ground, complicating the synchronizing effect of the environment. Migratory species show a variety of different strategies in how they disperse to and aggregate on nonbreeding grounds, ranging from completely shared nonbreeding grounds to multiple different ones. Depending on the sensitivity to environmental conditions off the breeding grounds, we can expect that migration and overwintering strategies will impact the extent and spatial pattern of population synchrony on the breeding grounds. Here, we use spatial population-dynamic modeling and simulations to investigate the relationship between seasonal environmental autocorrelation and migration characteristics. Our model shows that the effects of environmental autocorrelation experienced off the breeding ground on population synchrony depend on the number and size of nonbreeding grounds, and how populations migrate in relation to neighboring populations. When populations migrated to multiple nonbreeding grounds, spatial population synchrony increased with increasing environmental autocorrelation between nonbreeding grounds. Populations that migrated to the same place as near neighbors had higher synchrony at short distances than populations that migrated randomly. However, synchrony declined less across increasing distances for the random migration strategy. The differences in synchrony between migration strategies were most pronounced when the environmental autocorrelation between nonbreeding grounds was low. These results show the importance of considering migration when studying spatial population synchrony and predicting patterns of synchrony and population viability under global environmental change. Climate change and habitat loss and fragmentation may cause range shifts and changes in migratory strategies, as well as changes in the mean and spatial autocorrelation of the environment, which can alter the scale and patterns observed in spatial population synchrony.

Generation time and seasonal migration explain variation in spatial population synchrony across European bird species.

Spatial population synchrony is common among populations of the same species and is an important predictor of extinction risk. Despite the potential consequences for metapopulation persistence, we still largely lack understanding of what makes one species more likely to be synchronized than another given the same environmental conditions. Generally, environmental conditions in a shared environment or a species' sensitivity to the environment can explain the extent of synchrony. Populations that are closer together experience more similar fluctuations in their environments than those populations that are further apart and are therefore more synchronized. The relative importance of environmental and demographic stochasticity for population dynamics is strongly linked to species' life-history traits, such as pace of life, which may impact population synchrony. For populations that migrate, there may be multiple environmental conditions at different locations driving synchrony. However, the importance of life history and migration tactics in determining patterns of spatial population synchrony have rarely been explored empirically. We therefore hypothesize that increasing generation time, a proxy for pace of life, would decrease spatial population synchrony and that migrants would be less synchronized than resident species. We used population abundance data on breeding birds from four countries to investigate patterns of spatial population synchrony in growth rate and abundance. We calculated the mean spatial population synchrony between log-transformed population growth rates or log-transformed abundances for each species and country separately. We investigated differences in synchrony across generation times in resident (n = 67), short-distance migrant (n = 86) and long-distance migrant (n = 39) bird species. Species with shorter generation times were more synchronized than species with longer generation times. Short-distance migrants were more synchronized than long-distance migrants and resident birds. Our results provide novel empirical links between spatial population synchrony and species traits known to be of key importance for population dynamics, generation time and migration tactics. We show how these different mechanisms can be combined to understand species-specific causes of spatial population synchrony. Understanding these specific drivers of spatial population synchrony is important in the face of increasingly severe threats to biodiversity and could be key for successful future conservation outcomes.

Harvesting can stabilise population fluctuations and buffer the impacts of extreme climatic events.

Harvesting can magnify the destabilising effects of environmental perturbations on population dynamics and, thereby, increase extinction risk. However, population-dynamic theory predicts that impacts of harvesting depend on the type and strength of density-dependent regulation. Here, we used logistic population growth models and an empirical reindeer case study to show that low to moderate harvesting can actually buffer populations against environmental perturbations. This occurs because of density-dependent environmental stochasticity, where negative environmental impacts on vital rates are amplified at high population density due to intra-specific resource competition. Simulations from our population models show that even low levels of harvesting may prevent overabundance, thereby dampening population fluctuations and reducing the risk of population collapse and quasi-extinction following environmental perturbations. Thus, depending on the species' life history and the strength of density-dependent environmental drivers, low to moderate harvesting can improve population resistance to increased climate variability and extreme weather expected under global warming.

Age-dependent patterns of spatial autocorrelation in fish populations.

The degree of spatial autocorrelation in population fluctuations increases with dispersal and geographical covariation in the environment, and decreases with strength of density dependence. Because the effects of these processes can vary throughout an individual's lifespan, we studied how spatial autocorrelation in abundance changed with age in three marine fish species in the Barents Sea. We found large interspecific differences in age-dependent patterns of spatial autocorrelation in density. Spatial autocorrelation increased with age in cod, the reverse trend was found in beaked redfish, while it remained constant among age classes in haddock. We also accounted for the average effect of local cohort dynamics, i.e. the expected local density of an age class given last year's local density of the cohort, with the goal of disentangling spatial autocorrelation patterns acting on an age class from those formed during younger age classes and being carried over. We found that the spatial autocorrelation pattern of older age classes became increasingly determined by the distribution of the cohort during the previous year. Lastly, we found high degrees of autocorrelation over long distances for the three species, suggesting the presence of far-reaching autocorrelating processes on these populations. We discuss how differences in the species' life history strategies could cause the observed differences in age-specific variation in spatial autocorrelation. As spatial autocorrelation can differ among age classes, our study indicates that fluctuations in age structure can influence the spatio-temporal variation in abundance of marine fish populations.

The neglected season: Warmer autumns counteract harsher winters and promote population growth in Arctic reindeer.

Arctic ungulates are experiencing the most rapid climate warming on Earth. While concerns have been raised that more frequent icing events may cause die-offs, and earlier springs may generate a trophic mismatch in phenology, the effects of warming autumns have been largely neglected. We used 25 years of individual-based data from a growing population of wild Svalbard reindeer, to test how warmer autumns enhance population growth. Delayed plant senescence had no effect, but a six-week delay in snow-onset (the observed data range) was estimated to increase late winter body mass by 10%. Because average late winter body mass explains 90% of the variation in population growth rates, such a delay in winter-onset would enable a population growth of r = 0.20, sufficient to counteract all but the most extreme icing events. This study provides novel mechanistic insights into the consequences of climate change for Arctic herbivores, highlighting the positive impact of warming autumns on population viability, offsetting the impacts of harsher winters. Thus, the future for Arctic herbivores facing climate change may be brighter than the prevailing view.

High-Arctic family planning: earlier spring onset advances age at first reproduction in barnacle geese.

Quantifying how key life-history traits respond to climatic change is fundamental in understanding and predicting long-term population prospects. Age at first reproduction (AFR), which affects fitness and population dynamics, may be influenced by environmental stochasticity but has rarely been directly linked to climate change. Here, we use a case study from the highly seasonal and stochastic environment in High-Arctic Svalbard, with strong temporal trends in breeding conditions, to test whether rapid climate warming may induce changes in AFR in barnacle geese, Branta leucopsis. Using long-term mark-recapture and reproductive data (1991-2017), we developed a multi-event model to estimate individual AFR (i.e. when goslings are produced). The annual probability of reproducing for the first time was negatively affected by population density but only for 2 year olds, the earliest age of maturity. Furthermore, advanced spring onset (SO) positively influenced the probability of reproducing and even more strongly the probability of reproducing for the first time. Thus, because climate warming has advanced SO by two weeks, this likely led to an earlier AFR by more than doubling the probability of reproducing at 2 years of age. This may, in turn, impact important life-history trade-offs and long-term population trajectories.

Spatial covariation of competing species in a fluctuating environment.

Understanding how stochastic fluctuations in the environment influence population dynamics is crucial for sustainable management of biological diversity. However, because species do not live in isolation, this requires knowledge of how species interactions influence population dynamics. In addition, spatial processes play an important role in shaping population dynamics. It is therefore important to improve our understanding of how these different factors act together to shape patterns of abundance across space within and among species. Here, we present a new analytical model for understanding patterns of covariation in space between interacting species in a stochastic environment. We show that the correlation between two species in how they experience the same environmental conditions determines how correlated fluctuations in their densities would be in the absence of competition. In other words, without competition, synchrony between the species is driven by the environment, similar to the Moran effect within a species. Competition between the two species causes their abundances to become less positively or more negatively correlated. The same strength of competition has a greater negative effect on the correlation between species when one of them has a more variable growth rate than the other. In addition, dispersal or other movement weakens the effect of competition on the interspecific correlation. Finally, we show that movement increases the distance over which the species are (positively or negatively) correlated, an effect that is stronger when the species are competitors, and that there is a close connection between the spatial scaling of population synchrony within a species and between species. Our results show that the relationships between the different factors influencing interspecific correlations in abundance are not simple linear ones, but this model allows us to disentangle them and predict how they will affect population fluctuations in different situations.

Decomposing demographic contributions to the effective population size with moose as a case study.

Levels of random genetic drift are influenced by demographic factors, such as mating system, sex ratio and age structure. The effective population size (Ne ) is a useful measure for quantifying genetic drift. Evaluating relative contributions of different demographic factors to Ne is therefore important to identify what makes a population vulnerable to loss of genetic variation. Until recently, models for estimating Ne have required many simplifying assumptions, making them unsuitable for this task. Here, using data from a small, harvested moose population, we demonstrate the use of a stochastic demographic framework allowing for fluctuations in both population size and age distribution to estimate and decompose the total demographic variance and hence the ratio of effective to total population size (Ne /N) into components originating from sex, age, survival and reproduction. We not only show which components contribute most to Ne /N currently, but also which components have the greatest potential for changing Ne /N. In this relatively long-lived polygynous system we show that Ne /N is most sensitive to the demographic variance of older males, and that both reproductive autocorrelations (i.e., a tendency for the same individuals to be successful several years in a row) and covariance between survival and reproduction contribute to decreasing Ne /N (increasing genetic drift). These conditions are common in nature and can be caused by common hunting strategies. Thus, the framework presented here has great potential to increase our understanding of the demographic processes that contribute to genetic drift and viability of populations, and to inform management decisions.

Spatial scaling of population synchrony in marine fish depends on their life history.

The synchrony of population dynamics in space has important implications for ecological processes, for example affecting the spread of diseases, spatial distributions and risk of extinction. Here, we studied the relationship between spatial scaling in population dynamics and species position along the slow-fast continuum of life history variation. Specifically, we explored how generation time, growth rate and mortality rate predicted the spatial scaling of abundance and yearly changes in abundance of eight marine fish species. Our results show that population dynamics of species' with 'slow' life histories are synchronised over greater distances than those of species with 'fast' life histories. These findings provide evidence for a relationship between the position of the species along the life history continuum and population dynamics in space, showing that the spatial distribution of abundance may be related to life history characteristics.

More frequent extreme climate events stabilize reindeer population dynamics.

Extreme climate events often cause population crashes but are difficult to account for in population-dynamic studies. Especially in long-lived animals, density dependence and demography may induce lagged impacts of perturbations on population growth. In Arctic ungulates, extreme rain-on-snow and ice-locked pastures have led to severe population crashes, indicating that increasingly frequent rain-on-snow events could destabilize populations. Here, using empirically parameterized, stochastic population models for High-Arctic wild reindeer, we show that more frequent rain-on-snow events actually reduce extinction risk and stabilize population dynamics due to interactions with age structure and density dependence. Extreme rain-on-snow events mainly suppress vital rates of vulnerable ages at high population densities, resulting in a crash and a new population state with resilient ages and reduced population sensitivity to subsequent icy winters. Thus, observed responses to single extreme events are poor predictors of population dynamics and persistence because internal density-dependent feedbacks act as a buffer against more frequent events.

Spatial distribution and optimal harvesting of an age-structured population in a fluctuating environment.

We analyze a spatial age-structured model with density regulation, age specific dispersal, stochasticity in vital rates and proportional harvesting. We include two age classes, juveniles and adults, where juveniles are subject to logistic density dependence. There are environmental stochastic effects with arbitrary spatial scales on all birth and death rates, and individuals of both age classes are subject to density independent dispersal with given rates and specified distributions of dispersal distances. We show how to simulate the joint density fields of the age classes and derive results for the spatial scales of all spatial autocovariance functions for densities. A general result is that the squared scale has an additive term equal to the squared scale of the environmental noise, corresponding to the Moran effect, as well as additive terms proportional to the dispersal rate and variance of dispersal distance for the age classes and approximately inversely proportional to the strength of density regulation. We show that the optimal harvesting strategy in the deterministic case is to harvest only juveniles when their relative value (e.g. financial) is large, and otherwise only adults. With increasing environmental stochasticity there is an interval of increasing length of values of juveniles relative to adults where both age classes should be harvested. Harvesting generally tends to increase all spatial scales of the autocovariances of densities.

Modelling time to population extinction when individual reproduction is autocorrelated.

In nature, individual reproductive success is seldom independent from year to year, due to factors such as reproductive costs and individual heterogeneity. However, population projection models that incorporate temporal autocorrelations in individual reproduction can be difficult to parameterise, particularly when data are sparse. We therefore examine whether such models are necessary to avoid biased estimates of stochastic population growth and extinction risk, by comparing output from a matrix population model that incorporates reproductive autocorrelations to output from a standard age-structured matrix model that does not. We use a range of parameterisations, including a case study using moose data, treating probabilities of switching reproductive class as either fixed or fluctuating. Expected time to extinction from the two models is found to differ by only small amounts (under 10%) for most parameterisations, indicating that explicitly accounting for individual reproductive autocorrelations is in most cases not necessary to avoid bias in extinction estimates.

Modelling effects of nonbreeders on population growth estimates.

Adult individuals that do not breed in a given year occur in a wide range of natural populations. However, such nonbreeders are often ignored in theoretical and empirical population studies, limiting our knowledge of how nonbreeders affect realized and estimated population dynamics and potentially impeding projection of deterministic and stochastic population growth rates. We present and analyse a general modelling framework for systems where breeders and nonbreeders differ in key demographic rates, incorporating different forms of nonbreeding, different life histories and frequency-dependent effects of nonbreeders on demographic rates of breeders. Comparisons of estimates of deterministic population growth rate, λ, and demographic variance, σd2, from models with and without distinct nonbreeder classes show that models that do not explicitly incorporate nonbreeders give upwardly biased estimates of σd2, particularly when the equilibrium ratio of nonbreeders to breeders, Nnb∗/Nb∗, is high. Estimates of λ from empirical observations of breeders only are substantially inflated when individuals frequently re-enter the breeding population after periods of nonbreeding. Sensitivity analyses of diverse parameterizations of our model framework, with and without negative frequency-dependent effects of nonbreeders on breeder demographic rates, show how changes in demographic rates of breeders vs. nonbreeders differentially affect λ. In particular, λ is most sensitive to nonbreeder parameters in long-lived species, when Nnb∗/Nb∗>0, and when individuals are unlikely to breed at several consecutive time steps. Our results demonstrate that failing to account for nonbreeders in population studies can obscure low population growth rates that should cause management concern. Quantifying the size and demography of the nonbreeding section of populations and modelling appropriate demographic structuring is therefore essential to evaluate nonbreeders' influence on deterministic and stochastic population dynamics.

Contrasting effects of summer and winter warming on body mass explain population dynamics in a food-limited Arctic herbivore.

The cumulative effects of climate warming on herbivore vital rates and population dynamics are hard to predict, given that the expected effects differ between seasons. In the Arctic, warmer summers enhance plant growth which should lead to heavier and more fertile individuals in the autumn. Conversely, warm spells in winter with rainfall (rain-on-snow) can cause 'icing', restricting access to forage, resulting in starvation, lower survival and fecundity. As body condition is a 'barometer' of energy demands relative to energy intake, we explored the causes and consequences of variation in body mass of wild female Svalbard reindeer (Rangifer tarandus platyrhynchus) from 1994 to 2015, a period of marked climate warming. Late winter (April) body mass explained 88% of the between-year variation in population growth rate, because it strongly influenced reproductive loss, and hence subsequent fecundity (92%), as well as survival (94%) and recruitment (93%). Autumn (October) body mass affected ovulation rates but did not affect fecundity. April body mass showed no long-term trend (coefficient of variation, CV = 8.8%) and was higher following warm autumn (October) weather, reflecting delays in winter onset, but most strongly, and negatively, related to 'rain-on-snow' events. October body mass (CV = 2.5%) increased over the study due to higher plant productivity in the increasingly warm summers. Density-dependent mass change suggested competition for resources in both winter and summer but was less pronounced in recent years, despite an increasing population size. While continued climate warming is expected to increase the carrying capacity of the high Arctic tundra, it is also likely to cause more frequent icing events. Our analyses suggest that these contrasting effects may cause larger seasonal fluctuations in body mass and vital rates. Overall our findings provide an important 'missing' mechanistic link in the current understanding of the population biology of a keystone species in a rapidly warming Arctic.

Inbreeding parents should invest more resources in fewer offspring.

Inbreeding increases parent-offspring relatedness and commonly reduces offspring viability, shaping selection on reproductive interactions involving relatives and associated parental investment (PI). Nevertheless, theories predicting selection for inbreeding versus inbreeding avoidance and selection for optimal PI have only been considered separately, precluding prediction of optimal PI and associated reproductive strategy given inbreeding. We unify inbreeding and PI theory, demonstrating that optimal PI increases when a female's inbreeding decreases the viability of her offspring. Inbreeding females should therefore produce fewer offspring due to the fundamental trade-off between offspring number and PI. Accordingly, selection for inbreeding versus inbreeding avoidance changes when females can adjust PI with the degree that they inbreed. By contrast, optimal PI does not depend on whether a focal female is herself inbred. However, inbreeding causes optimal PI to increase given strict monogamy and associated biparental investment compared with female-only investment. Our model implies that understanding evolutionary dynamics of inbreeding strategy, inbreeding depression, and PI requires joint consideration of the expression of each in relation to the other. Overall, we demonstrate that existing PI and inbreeding theories represent special cases of a more general theory, implying that intrinsic links between inbreeding and PI affect evolution of behaviour and intrafamilial conflict.

Demographic buffering of life histories? Implications of the choice of measurement scale.

Life-history theory predicts that the vital rates that influence population growth the most should be buffered against environmental fluctuations due to selection for reduced variation. However, it remains unclear whether populations actually are influenced by such "demographic buffering," because variation in vital rates can be compared on different measurement scales, and there has been little attempt to investigate whether the choice of scale influences the chance of detecting demographic buffering. We compared two statistical approaches to examine whether demographic buffering has influenced vital rates in wild Svalbard reindeer (Rangifer tarandus platyrhynchus). To account for statistical variance constraints on vital rates limited between 0 and 1 in analyses of demographic buffering, one approach is to scale observed variation by the maximum possible variation on the arithmetic scale. When applying this approach, the results suggested that demographic buffering was occurring. However, when we applied an alternative approach that identified statistical variance constraints on the logit scale, there was no evidence for demographic buffering. Thus, the choice of measurement scale must be carefully considered before one can fully understand whether demographic buffering influences life histories. Defining the appropriate scale may require an understanding of the mechanisms through which demographic buffering may have evolved.

Evidence of inbreeding depression but not inbreeding avoidance in a natural house sparrow population.

Inbreeding is common in small and threatened populations and often has a negative effect on individual fitness and genetic diversity. Thus, inbreeding can be an important factor affecting the persistence of small populations. In this study, we investigated the effects of inbreeding on fitness in a small, wild population of house sparrows (Passer domesticus) on the island of Aldra, Norway. The population was founded in 1998 by four individuals (one female and three males). After the founder event, the adult population rapidly increased to about 30 individuals in 2001. At the same time, the mean inbreeding coefficient among adults increased from 0 to 0.04 by 2001 and thereafter fluctuated between 0.06 and 0.10, indicating a highly inbred population. We found a negative effect of inbreeding on lifetime reproductive success, which seemed to be mainly due to an effect of inbreeding on annual reproductive success. This resulted in selection against inbred females. However, the negative effect of inbreeding was less strong in males, suggesting that selection against inbred individuals is at least partly sex specific. To examine whether individuals avoided breeding with close relatives, we compared observed inbreeding and kinship coefficients in the population with those obtained from simulations of random mating. We found no significant differences between the two, indicating weak or absent inbreeding avoidance. We conclude that there was inbreeding depression in our population. Despite this, birds did not seem to actively avoid mating with close relatives, perhaps as a consequence of constraints on mating possibilities in such a small population.

Demographic stochasticity, allee effects, and extinction: the influence of mating system and sex ratio.

Demographic stochasticity has a substantial influence on the growth of small populations and consequently on their extinction risk. Mating system is one of several population characteristics that may affect this. We use a stochastic pair-formation model to investigate the combined effects of mating system, sex ratio, and population size on demographic stochasticity and thus on extinction risk. Our model is designed to accommodate a continuous range of mating systems and sex ratios as well as several levels of stochasticity. We show that it is not mating system alone but combinations of mating system and sex ratio that are important in shaping the stochastic dynamics of populations. Specifically, polygyny has the potential to give a high demographic variance and to lower the stochastic population growth rate substantially, thus also shortening the time to extinction, but the outcome is highly dependent on the sex ratio. In addition, population size is shown to be important. We find a stochastic Allee effect that is amplified by polygyny. Our results demonstrate that both mating system and sex ratio must be considered in conservation planning and that appreciating the role of stochasticity is key to understanding their effects.

The influence of persistent individual differences and age at maturity on effective population size.

Ratios of effective populations size, N(e), to census population size, N, are used as a measure of genetic drift in populations. Several life-history parameters have been shown to affect these ratios, including mating system and age at sexual maturation. Using a stochastic matrix model, we examine how different levels of persistent individual differences in mating success among males may affect N(e)/N, and how this relates to generation time. Individual differences of this type are shown to cause a lower N(e)/N ratio than would be expected when mating is independent among seasons. Examining the way in which age at maturity affects N(e)/N, we find that both the direction and magnitude of the effect depends on the survival rate of juveniles in the population. In particular, when maturation is delayed, lowered juvenile survival causes higher levels of genetic drift. In addition, predicted shifts in N(e)/N with changing age at maturity are shown to be dependent on which of the commonly used definitions of census population size, N, is employed. Our results demonstrate that patterns of mating success, as well as juvenile survival probabilities, have substantial effects on rates of genetic drift.