The ‘Moran effect’ predicts that dynamics of populations of a species are synchronized over similar distances as their environmental drivers. Strong population synchrony reduces species viability, ...but spatial heterogeneity in density dependence, the environment, or its ecological responses may decouple dynamics in space, preventing extinctions. How such heterogeneity buffers impacts of global change on large‐scale population dynamics is not well studied. Here, we show that spatially autocorrelated fluctuations in annual winter weather synchronize wild reindeer dynamics across high‐Arctic Svalbard, while, paradoxically, spatial variation in winter climate trends contribute to diverging local population trajectories. Warmer summers have improved the carrying capacity and apparently led to increased total reindeer abundance. However, fluctuations in population size seem mainly driven by negative effects of stochastic winter rain‐on‐snow (ROS) events causing icing, with strongest effects at high densities. Count data for 10 reindeer populations 8–324 km apart suggested that density‐dependent ROS effects contributed to synchrony in population dynamics, mainly through spatially autocorrelated mortality. By comparing one coastal and one ‘continental’ reindeer population over four decades, we show that locally contrasting abundance trends can arise from spatial differences in climate change and responses to weather. The coastal population experienced a larger increase in ROS, and a stronger density‐dependent ROS effect on population growth rates, than the continental population. In contrast, the latter experienced stronger summer warming and showed the strongest positive response to summer temperatures. Accordingly, contrasting net effects of a recent climate regime shift—with increased ROS and harsher winters, yet higher summer temperatures and improved carrying capacity—led to negative and positive abundance trends in the coastal and continental population respectively. Thus, synchronized population fluctuations by climatic drivers can be buffered by spatial heterogeneity in the same drivers, as well as in the ecological responses, averaging out climate change effects at larger spatial scales.
Spatially autocorrelated weather and climate may cause population co‐fluctuations over large distances. We show that increasingly frequent rain‐on‐snow (ROS) and icing events in winter synchronize the annual dynamics of Svalbard reindeer populations, while, paradoxically, spatial variation in ROS trends and density‐dependent weather effects cause diverging local population trajectories in the long run. Such decoupling of population dynamics increases species viability under a rapidly warming high‐Arctic climate.
Our knowledge of the factors affecting species abundances is mainly based on time‐series analyses of a few well‐studied species at single or few localities, but we know little about whether results ...from such analyses can be extrapolated to the community level. We apply a joint species distribution model to long‐term time‐series data on British bird communities to examine the relative contribution of intra‐ and interspecific density dependence at different spatial scales, as well as the influence of environmental stochasticity, to spatiotemporal interspecific variation in abundance. Intraspecific density dependence has the major structuring effect on these bird communities. In addition, environmental fluctuations affect spatiotemporal differences in abundance. In contrast, species interactions had a minor impact on variation in abundance. Thus, important drivers of single‐species dynamics are also strongly affecting dynamics of communities in time and space.
Dispersal has a crucial role determining ecoevolutionary dynamics through both gene flow and population size regulation. However, to study dispersal and its consequences, one must distinguish ...immigrants from residents. Dispersers can be identified using telemetry, capture‐mark‐recapture (CMR) methods, or genetic assignment methods. All of these methods have disadvantages, such as high costs and substantial field efforts needed for telemetry and CMR surveys, and adequate genetic distance required in genetic assignment. In this study, we used genome‐wide 200K Single Nucleotide Polymorphism data and two different genetic assignment approaches (GSI_SIM, Bayesian framework; BONE, network‐based estimation) to identify the dispersers in a house sparrow (Passer domesticus) metapopulation sampled over 16 years. Our results showed higher assignment accuracy with BONE. Hence, we proceeded to diagnose potential sources of errors in the assignment results from the BONE method due to variation in levels of interpopulation genetic differentiation, intrapopulation genetic variation and sample size. We show that assignment accuracy is high even at low levels of genetic differentiation and that it increases with the proportion of a population that has been sampled. Finally, we highlight that dispersal studies integrating both ecological and genetic data provide robust assessments of the dispersal patterns in natural populations.
Stabilizing selection is thought to be common in wild populations and act as one of the main evolutionary mechanisms, which constrain phenotypic variation. When multiple traits interact to create a ...combined phenotype, correlational selection may be an important process driving adaptive evolution. Here, we report on phenotypic selection and evolutionary changes in two natal traits in a semidomestic population of reindeer (Rangifer tarandus) in northern Finland. The population has been closely monitored since 1969, and detailed data have been collected on individuals since they were born. Over the length of the study period (1969–2015), we found directional and stabilizing selection toward a combination of earlier birth date and heavier birth mass with an intermediate optimum along the major axis of the selection surface. In addition, we demonstrate significant changes in mean traits toward earlier birth date and heavier birth mass, with corresponding genetic changes in breeding values during the study period. Our results demonstrate evolutionary changes in a combination of two traits, which agree closely with estimated patterns of phenotypic selection. Knowledge of the selective surface for combinations of genetically correlated traits are vital to predict how population mean phenotypes and fitness are affected when environments change.
Across the Arctic, heavy rain-on-snow (ROS) is an "extreme" climatic event that is expected to become increasingly frequent with global warming. This has potentially large ecosystem implications ...through changes in snowpack properties and ground-icing, which can block the access to herbivores' winter food and thereby suppress their population growth rates. However, the supporting empirical evidence for this is still limited. We monitored late winter snowpack properties to examine the causes and consequences of ground-icing in a Svalbard reindeer (
Rangifer tarandus
platyrhynchus
) metapopulation. In this high-arctic area, heavy ROS occurred annually, and ground-ice covered from 25%% to 96%% of low-altitude habitat in the sampling period (2000-2010). The extent of ground-icing increased with the annual number of days with heavy ROS (≥10 mm) and had a strong negative effect on reindeer population growth rates. Our results have important implications as a downscaled climate projection (2021-2050) suggests a substantial future increase in ROS and icing. The present study is the first to demonstrate empirically that warmer and wetter winter climate influences large herbivore population dynamics by generating ice-locked pastures. This may serve as an early warning of the importance of changes in winter climate and extreme weather events in arctic ecosystems.
Generation time determines the pace of key demographic and evolutionary processes. Quantified as the weighted mean age at reproduction, it can be studied as a life‐history trait that varies within ...and among populations and may evolve in response to ecological conditions. We combined quantitative genetic analyses with age‐ and density‐dependent models to study generation time variation in a bird metapopulation. Generation time was heritable, and males had longer generation times than females. Individuals with longer generation times had greater lifetime reproductive success but not a higher expected population growth rate. Density regulation acted on recruit production, suggesting that longer generation times should be favoured when populations are closer to carrying capacity. Furthermore, generation times were shorter when populations were growing and longer when populations were closer to equilibrium or declining. These results support classic theory predicting that density regulation is an important driver of the pace of life‐history strategies.
We studied spatial and temporal variation in the mean age at reproduction in a house sparrow metapopulation. We find that generation times were shorter when populations were growing and longer when populations were closer to equilibrium or declining. Our study supports the classic density‐dependence theory in explaining variation in fast versus slow pace of life and highlights that competitive regimes can have important consequences for the evolution of life‐history strategies.
Identifying factors shaping variation in resource selection is central for our understanding of the behaviour and distribution of animals. We examined summer habitat selection and space use by 108 ...Global Positioning System (GPS)-collared moose in Norway in relation to sex, reproductive status, habitat quality, and availability. Moose selected habitat types based on a combination of forage quality and availability of suitable habitat types. Selection of protective cover was strongest for reproducing females, likely reflecting the need to protect young. Males showed strong selection for habitat types with high quality forage, possibly due to higher energy requirements. Selection for preferred habitat types providing food and cover was a positive function of their availability within home ranges (i.e. not proportional use) indicating functional response in habitat selection. This relationship was not found for unproductive habitat types. Moreover, home ranges with high cover of unproductive habitat types were larger, and smaller home ranges contained higher proportions of the most preferred habitat type. The distribution of moose within the study area was partly related to the distribution of different habitat types. Our study shows how distribution and availability of habitat types providing cover and high-quality food shape ungulate habitat selection and space use.
Theoretical analyses of single‐species models have revealed that the degree of synchrony in fluctuations of geographically separated populations increases with increasing spatial covariation in ...environmental fluctuations and increased interchange of individuals, but decreases with local strength of density dependence. Here we extend these results to include interspecific competition between two species as well as harvesting. We show that the effects of interspecific competition on the geographical scale of population synchrony are dependent on the pattern of spatial covariation of environmental variables. If the environmental noise is uncorrelated between the competing species, competition generally increases the spatial scale of population synchrony of both species. Otherwise, if the environmental noises are strongly correlated between species, competition generally increases the spatial scale of population synchrony of at least one, but also often of both species. The magnitude of these spatial scaling effects is, however, strongly influenced by the dispersal capacity of the two competing species. If the species are subject to proportional harvesting, this may synchronise population dynamics over large geographical areas, affecting the vulnerability of harvested species to environmental changes. However, the strength of interspecific competition may strongly modify this effect of harvesting on the spatial scale of population synchrony. For example, harvesting of one species may affect the spatial distribution of competing species that are not subject to harvesting. These analytical results provide an important illustration of the importance of applying an ecosystem rather than a single‐species perspective when developing harvest strategies for a sustainable management of exploited species.
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.
We analyze the stochastic demography and evolution of a density-dependent age- (or stage-) structured population in a fluctuating environment. A positive linear combination of age classes (e.g., ...weighted by body mass) is assumed to act as the single variable of population size, N, exerting density dependence on age-specific vital rates through an increasing function of population size. The environment fluctuates in a stationary distribution with no autocorrelation.We show by analysis and simulation of age structure, under assumptions often met by vertebrate populations, that the stochastic dynamics of population size can be accurately approximated by a univariate model governed by three key demographic parameters: the intrinsic rate of increase and carrying capacity in the average environment, r₀ and K, and the environmental variance in population growth rate,
σ
e
2
. Allowing these parameters to be genetically variable and to evolve, but assuming that a fourth parameter, θ, measuring the nonlinearity of density dependence, remains constant, the expected evolution maximizes
E
N
θ
=
1
−
σ
e
2
/
(
2
r
0
)
K
θ
. This shows that the magnitude of environmental stochasticity governs the classical trade-off between selection for higher r₀ versus higher K. However, selection also acts to decrease
σ
e
2
, so the simple life-history trade-off between r- and K-selection may be obscured by additional trade-offs between them and
σ
e
2
. Under the classical logistic model of population growth with linear density dependence (θ = 1), life-history evolution in a fluctuating environment tends to maximize the average population size.
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