Interspecific population synchrony, or co‐fluctuations in the population dynamics and demographic parameters of different species, is an important ecological phenomenon with major implications for the stability of communities and ecosystems. It is also central in the context of biodiversity loss, as interspecific synchrony can influence how ecological communities are affected by anthropogenic stressors. Studies of interspecific synchrony are therefore important for understanding fundamental mechanisms underlying the biodiversity changes occurring worldwide. Interspecific synchrony has received increased interest in recent years, and studies have focused on synchrony in abundances, growth rates and vital rates at species, community and metacommunity levels. However, there is little cohesiveness in the literature, as studies focused on different levels of biological organization are largely separate from each other. Still, synchrony at these levels of biological organization is likely interconnected in nature. Understanding these connections would greatly benefit our understanding of interspecific synchrony and its implications for populations and communities. Here, we provide an overview of the current status and future perspectives of interspecific synchrony research, highlighting major knowledge gaps. We show how interspecific synchrony at different levels of biological organization is conceptually linked and present an accessible overview of the terminology and methods used to study it. By providing a common understanding of the meaning and applicability of terms and an overview of commonly used methods, this overview will serve as a point of departure for integrating research on interspecific synchrony. Such integration is important to fully understand the impacts of environmental change on species and ecological communities.

Nearby populations often experience shared environmental fluctuations and have stronger population synchrony than distant populations. However, different species often show different levels of synchrony across the same areas and environments, possibly because some traits influence their susceptibility to environmental stochasticity. In this paper, we compiled a pan-European collection of long-term annual abundance data on birds and butterflies from eight countries to identify how species' life history traits can influence the effects of environmental synchrony. We show that in birds and butterflies, the impact of environmental synchrony on population synchrony depended on key life history traits. For birds, which had stronger evidence for synchronizing effects of temperature compared to precipitation, the environmental effects on population synchrony depended on generation time, dietary diversity, and migratory tactic. The positive effects of environmental synchrony were stronger in bird species with short generation times (i.e., faster lived), higher dietary diversity, resident species, and short-distance migrants. In butterflies, which had stronger evidence for synchronizing effects of precipitation compared to temperature, we found that environmental effects on population synchrony depended on voltinism, with stronger effects in multivoltine (i.e., faster lived) species. Thus, life history can interact with environmental synchrony in shaping patterns of spatial population synchrony, with implications for predicting impacts of environmental change on species abundances over larger spatial scales. Further understanding of drivers of spatial population synchrony based on long-term abundance data is important in the face of increasingly severe threats to biodiversity and could be key for successful future conservation outcomes.

Indirect interspecific effects (IIEs) occur when one species affects another through a third intermediary species. Understanding the role of IIEs in population dynamics is key for predicting community-level impacts of environmental change. Yet, empirically teasing apart IIEs from other interactions and population drivers has proven challenging and data-demanding, particularly in species-rich communities. We used stochastic population models parameterized with long-term time series of individual data to simulate population trajectories and examine IIEs in a simple high-arctic vertebrate food chain consisting of the wild Svalbard reindeer, its scavenger (the Arctic fox) and the barnacle goose, a migratory prey of the fox. We used the simulated population trajectories to explore co-fluctuations between the species within the food chain. Additionally, we adjusted the model in two ways: first, to isolate the impact of fluctuations in the abundance of a species by keeping its abundance constant; and second, to isolate the impact of a trophic interaction on the dynamics of other species by setting the abundance of the influencing species to zero. We found that fluctuations in reindeer carcasses shaped fox abundance fluctuations, which subsequently affected goose population dynamics. Reindeer and goose population growth rates were nevertheless only weakly correlated, probably in part due to demographic and environmental stochasticity, density dependence and lagged dynamics in the geese. However, removing the fluctuations in reindeer abundance or setting reindeer abundance to zero indeed demonstrated strong underlying IIEs on goose population dynamics and extinction probability. This study thus highlights the importance of species interactions, including IIEs, on species coexistence and communities in the long-term, that is beyond immediate effects and covariation in short-term fluctuations.

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 on 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, why 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 strategies in determining patterns of spatial population synchrony have rarely been explored empirically. We therefore hypothesize that generation time, a proxy for pace of life, and migration play an important role in determining spatial population synchrony. We used population abundance data on breeding birds from four countries to investigate patterns of spatial population synchrony in growth rate and abundance. We investigated differences in synchrony across a gradient of generation times in resident, short-distance migrant, and long-distance migrant 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 characteristics. 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.

Populations closer together in space are more likely to experience shared environmental fluctuations. This correlation in experienced environmental conditions is the main driver of spatial population synchrony, defined as the tendency for geographically separate populations of the same species to exhibit parallel fluctuations in abundance over time. Moran’s theorem states that spatially distinct populations are expected to show the same synchrony in their population dynamics as the synchrony in their environment. However, this is rarely the case in the wild, and the population synchrony of different species inhabiting the same area is rarely similar. These species-specific differences in how the environment synchronizes populations can be due to life history traits that make some species more susceptible to environmental stochasticity, such as reduced mobility or faster pace of life. In this study, we compiled long-term annual abundance datasets on European birds and insects ( Lepidoptera sp. and Bombus sp.) to identify how environmental synchrony (i.e., positively spatially correlated fluctuations in the environment, also called the Moran effect) affects species population synchrony. As expected, the environment synchronized populations of both birds and insects. Populations experiencing correlated fluctuations in precipitation or temperature had higher synchrony in annual population growth rates. Birds were more strongly synchronized by temperature, while precipitation was a stronger driver of synchrony in insects. In birds, species with short generation times had a stronger synchronizing effect of the environment compared to species with long generation times. Moreover, in birds the effects of synchrony in the environment also depended on movement propensity, with a positive impact for resident and short-distance migration species. In insects, annual population synchrony was affected by species movement propensity and dietary niche breadth, but these traits did not modify the effects of environmental synchrony. Our study provides empirical support for the prediction that spatial correlation in population dynamics is more influenced by environmental stochasticity for life histories with lower mobility and faster pace of life, but only in birds. By quantifying spatial population synchrony across different levels of environmental synchrony and life history traits, our study improves the understanding of the Moran effect as well as factors that drive population persistence in the face of environmental change.

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.

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 sustainable use of natural resources is critical for addressing the global challenges of today. Strategies for sustainable harvesting need to consider not only harvested species, but also other non-harvested species interacting with them in the same ecosystem. In addition, environmental variation needs to be considered, with climate change currently being one of the main sources of this variation. Understanding the consequences of complex interactions between different drivers and processes affecting dynamics of species and ecosystems across spatial scales requires large-scale integrative research projects. The Norwegian research initiative “Sustainable management of renewable resources in a changing environment: an integrated approach across ecosystems” (SUSTAIN) was launched to fill knowledge gaps related to the sustainable management of populations and ecosystems experiencing climate change. SUSTAIN investigated terrestrial, marine and freshwater ecosystems in boreal and Arctic regions, using both theoretical developments and empirical analyses of long-term data. This Climate Research Special contains both synthesis articles and original research exemplifying some of the approaches used in SUSTAIN. In this introduction we highlight 4 key topics addressed by SUSTAIN: (i) population structure, (ii) interactions between species, (iii) spatial processes, and (iv) adaptive management. These topics are fundamental to the understanding of harvested species from an ecosystem perspective, and to ecosystem-based management approaches, which we are striving to work towards.

Achieving sustainable harvesting of natural populations depends on our ability to predict population responses to the combined effects of harvesting and environmental fluctuations while accounting for other internal and external factors that influence population dynamics in time and space. Here, we review recent research showing how spatial patterns and interspecific interactions can influence population responses to harvesting in fluctuating environments. We highlight several pathways through which harvesting can, often inadvertently, influence the dynamics and resilience to environmental fluctuations of both harvested and surrounding non-harvested populations and species. For instance, spatial models have shown that harvesting is expected to influence the spatial synchrony of population fluctuations, both of the harvested species and its competitors, predators and prey, with implications for population extinction risk. Dispersal and interspecific interactions can cause responses to harvesting in areas and species that are not themselves harvested. Harvesting that selectively targets certain groups of individuals, either intentionally or through for example spatially biased harvesting, can amplify environmentally induced population fluctuations by biasing the population structure towards individuals that are more sensitive to environmental variation. On the other hand, harvesting can in some cases buffer populations against the density-dependent effects of harsh climatic conditions, which are probably more common than previously acknowledged. Recent advances in modeling are providing new predictions that are highly relevant under global warming and now need to be tested empirically. We discuss how knowledge of these pathways can be used to increase the sustainability of harvesting.

Harvesting can have a substantial impact on population dynamics and individual performance in wild populations. While the direct consequences of harvest on individual survival and population growth rate are often apparent, harvesting can also have indirect and more subtle demographic consequences. Disentangling these consequences, however, requires in-depth knowledge of individual life histories of both females and males in the population. Here, we summarise demographic research on a population where such data exist: the Vega moose population in northern Norway. In this population, vital rates vary considerably among both females and males, and harvesting increases this variation by generating positive covariation between reproductive performance and survival. The skewed age and sex structure, which is typical of many harvested populations, also has demographic consequences: it reduces the ratio of effective to total population size and influences variation in vital rates in males and females. The moose harvest at Vega is structured by age- and sex-specific quotas, but it is not intentionally selective regarding size or other phenotypic characteristics. Still, harvest selection for earlier birth rates and larger calves was apparent, likely due to habitat-performance relationships and habitat-specific harvest mortality. Together, the bulk of research on this population shows that harvesting impacts population demography through many different pathways, with some being more subtle than others. These complex pathways influence the demographic variance and affect stochastic processes such as population growth, genetic drift, and rates of evolutionary change, and they must therefore be acknowledged in management plans to achieve sustainable harvesting.

Environmental variation in time and space generates complex patterns in the spatial structure of temporally covarying populations. Accounting for spatial population structure is important for sustainable management and harvest, but there is a need for a better understanding of the many mechanisms affecting the spatial structure of populations. In the large-scale research project SUSTAIN, detailed long-term data from several taxa within the boreal and Arctic ecosystems were used to address key research questions about spatial population structure. Here, we synthesise the main findings from these studies. Because nearby populations experience similar environmental variation, populations close to each other show more correlated dynamics than those at greater distances. However, several mechanisms can affect the extent of such spatial population synchrony, and we point to some similarities across systems that can explain the observed discrepancy between the spatial structure of the environment and that of population dynamics. We discuss the consequences of these findings for the practical management of species in a changing environment and the need for further research on how populations and ecosystems are affected by the spatial structure of the environment.

Understanding how population dynamics are influenced by species interactions and the surrounding community is crucial for addressing many ecological questions, but requires modelling of complex systems involving direct, indirect and often asymmetric species interactions. Progress in developing multispecies models that can tackle this task is being made in multiple subfields of ecology, often with varying approaches and end goals but also facing shared challenges. We review some of the main challenges and the ways in which they are being addressed, highlighting a wide variety of methods that can support the development of multispecies models for understanding population dynamics. The main challenges that we examine are estimation of species interactions from limited data, the necessity of simplifications, and handling uncertainty in complex, multispecies models. In addition to reviewing a wide variety of approaches and methods for dealing with these challenges, we discuss future directions and make suggestions for how we believe the development of multispecies models for understanding population dynamics can move forward more efficiently.

Choosing the right harvesting strategy is crucial for sustainable utilization of biological resources but is challenging in real systems with fluctuating environments. This challenge is expected to become even greater with global warming, as environmental variability is predicted to increase. Additionally, harvesting strategies based on single-species models have been shown to carry a severe risk of species extinctions when species interactions are ignored, particularly in systems with more than one harvested species. As the climate continues to warm, we therefore need new reference points for harvesting in an ecosystem context with environmental fluctuations. In this paper, we discuss the development of harvesting strategies and suggest that a proportional threshold harvesting framework could be a useful starting point for developing such reference points and tackling the challenge of sustainable harvesting in the future.

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.

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.

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.

Harvesting can magnify the destabilizing 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 population models for a range of life histories and an empirical reindeer case study to show that 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 proportional harvesting may prevent overabundance, thereby dampening population fluctuations and reducing the risk of population collapse and quasi-extinction induced by environmental perturbations. Thus, depending on the species’ life history and the strength of density-dependent environmental drivers, harvesting can improve population resistance to increased climate variability and extreme weather expected under global warming.

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 old, 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.

The world is spatially autocorrelated. Both abiotic and biotic properties are more similar among neighboring than distant locations, and their temporal co-fluctuations also decrease with distance. P. A. P. Moran realized the ecological importance of such 'spatial synchrony' when he predicted that isolated populations subject to identical log-linear density-dependent processes should have the same correlation in fluctuations of abundance as the correlation in environmental noise. The contribution from correlated weather to synchrony of populations has later been coined the 'Moran effect'. Here, we investigate the potential role of the Moran effect in large-scale ecological outcomes of global warming. Although difficult to disentangle from dispersal and species interaction effects, there is compelling evidence from across taxa and ecosystems that spatial environmental synchrony causes population synchrony. Given this, and the accelerating number of studies reporting climate change effects on local population dynamics, surprisingly little attention has been paid to the implications of global warming for spatial population synchrony. However, a handful of studies of insects, birds, plants, mammals and marine plankton indicate decadal-scale changes in population synchrony due to trends in environmental synchrony. We combine a literature review with modeling to outline potential pathways for how global warming, through changes in the mean, variability and spatial autocorrelation of weather, can impact population synchrony over time. This is particularly likely under a 'generalized Moran effect', i.e. when relaxing Moran's strict assumption of identical log-linear density-dependence, which is highly unrealistic in the wild. Furthermore, climate change can influence spatial population synchrony indirectly, through its effects on dispersal and species interactions. Because changes in population synchrony may cascade through food-webs, we argue that the (generalized) Moran effect is key to understanding and predicting impacts of global warming on large-scale ecological dynamics, with implications for extinctions, conservation and management.

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.