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Farmland habitats witness steep declines in biodiversity. One rapidly declining farmland species is the ortolan bunting Emberiza hortulana. In Finland, a staggering 99% of the population has been lost during the past 30 years. Changes in the breeding habitats have been proposed as a reason for the decline, although hazards during migration and wintering may also play a role. We gathered a 19‐year data set of Finnish ortolan buntings and studied which spatial characteristics, habitat features, and climate factors might explain the population growth rate at the singing‐group level. As explanatory variables we used region, density of small‐scale structures, proportion of agricultural area in the landscape, diversity of crop types, proportion of bare ground, and temperature and precipitation of previous breeding season. Higher population growth rates were associated with higher crop type diversity and higher proportion of bare ground. The mosaic of various crop plants and bare ground may provide a wider array of feeding, hiding and nesting places, and an easier access to food. Higher growth rates were also associated with landscapes dominated by interconnected agricultural land, which may reflect the species' sociability and avoidance of forested areas. The North Ostrobothnia region had higher growth rates compared to other regions. We suggest that northern populations of ortolan bunting should be targeted for further studies on feeding and breeding ecology as well as for urgent conservation actions, such as increasing crop type diversity and bare ground. [ABSTRACT FROM AUTHOR]

The Skellam model describes discrete‐time population dynamics of a single species assuming uniform (i.e., random or Poissonian) individual distribution and intraspecific contest competition. Apart from studies on individual‐based models derived from first principles it has been rarely applied in ecological research although in specific situations it may be more appropriate than, for instance, the frequently used Ricker model, which is derived assuming scramble competition among the individuals. In this article, we offer an insight into the first principles underlying the Skellam model and provide an alternative parameterization of the model in terms of two commonly used parameters: intrinsic rate of population increase and carrying capacity. We also provide guidelines and software for fitting the Skellam model to discrete population time series data. In light of these findings, the Skellam model may be a useful alternative for a range of purposes where it has been earlier overlooked. [ABSTRACT FROM AUTHOR]

Wetland habitats are changing under multiple anthropogenic pressures. Nutrient leakage and pollution modify physico‐chemical state of wetlands and affect the ecosystem through bottom‐up processes, while alien predators affect the ecosystems in a top‐down manner. Boreal wetlands are important breeding areas for several waterbird species, the abundances of which potentially reflect both bottom‐up and top‐down ecosystem processes. Here, we use long‐term national monitoring data gathered from c. 130 waterbird breeding sites in Finland from the 1980s to the 2020s. We hypothesised that the physico‐chemical state of the waters and increasing alien predator abundance both play a role in steering the waterbird population trends. We set out to test this hypothesis by relating population changes of 17 waterbird species to changes in water chemistry and to regional alien predator indices while allowing species‐specific effects to vary with foraging niche (dabblers, invertivore divers, piscivorous divers, herbivores), nesting site, female mass and habitat (oligotrophic, eutrophic). We found niche and nesting site‐specific, habitat‐dependent changes in waterbird numbers. While the associations with higher phosphorus levels and browning water were in overall positive at the oligotrophic lakes, the numbers of invertivore and piscivore diving ducks were most strongly negatively associated with higher phosphorus levels and browning water at the eutrophic lakes. Furthermore, increased pH levels benefitted piscivores. Invertivore diving duck species nesting on the wetlands had declined most on sites with high alien predator indices. Large herbivorous species and species preferring oligotrophic lakes seem to be successful. We conclude that the large‐scale breeding waterbird decline in Finland is closely connected to both bottom‐up and top‐down processes, where negative associations are emphasised especially at eutrophic lakes. Niche‐, nest site‐ and habitat‐specific management actions are required to conserve declining waterbird populations. Managing wetlands on catchments level together with alien predator control may provide important approaches to future wetland management. [ABSTRACT FROM AUTHOR]

Aim: Recent evidence has shown changes in body size and shape of individuals, which are suggested to be a result of global warming caused by climate change. Here, we explored the spatiotemporal changes in wing length and body mass of 24 wintering bird species in Northern Europe and how these relate to temperature anomaly. Location: Finland and Sweden, Europe. Time Period: 50 years, 1970 to 2020. Major Taxa Studied: Birds, 24 species. Methods: We used site‐specific, long‐term winter ringing data containing wing length and body mass measurements from across Sweden and Finland for 24 bird species. We modelled wing length and body mass change over time, in relation to the spatioclimatic gradient and as response to temperature anomalies (of [i] the same winter as the ringing took place, [ii] the previous winter and [iii] the previous spring) by accounting for phylogenetic relatedness between species and their species‐specific responses to each predictor of interest. Results: We show that across all species, body size has decreased since the 1970s, with a negative relationship between wing length and temperature anomalies of previous winters, suggesting carry‐over effects likely linked to body size‐related survival or dispersal. Body mass was negatively related to the temperature anomaly of the same winter, indicating more immediate effects related to reduced fat reserves during mild winters. Main Conclusions: Our results highlight a climate‐driven decrease in body size across several species and its association with positive anomalies in winter temperature in the high latitudes. However, the responses are not spatially uniform and there is considerable species‐specific variation, emphasizing the importance of conducting multispecies studies when investigating responses to climate change. The mechanisms of decreasing wing length and body mass seem to differ and underline the immediate and carry‐over effects of temperature warming during the nonbreeding season. [ABSTRACT FROM AUTHOR]

Benthic species and communities are linked to pelagic zooplankton through life‐stages encompassing both benthic and pelagic habitats and through a mutual dependency on primary producers as a food source. Many zooplankton taxa contribute to the sedimentary system as benthic eggs. Our main aim was to investigate the nature of the population level biotic interactions between and within these two seemingly independent communities, both dependent on the pelagic primary production, while simultaneously accounting for environmental drivers (salinity, temperature, and oxygen conditions). To this end, we applied multivariate autoregressive state‐space models to long (1966–2007) time series of annual abundance data, comparing models with and without interspecific interactions, and models with and without environmental variables included. We were not able to detect any direct coupling between sediment‐dwelling benthic taxa and pelagic copepods and cladocerans on the annual scale, but the most parsimonious model indicated that interactions within the benthic community are important. There were also positive residual correlations between the copepods and cladocerans potentially reflecting the availability of a shared resource or similar seasonal dependence, whereas both groups tended to correlate negatively with the zoobenthic taxa. The most notable single interaction within the benthic community was a tendency for a negative effect of Limecola balthica on the amphipods Monoporeia affinis and Pontoporeia femorata which can help explain the observed decrease in amphipods due to increased competitive interference. [ABSTRACT FROM AUTHOR]

Aim: The temporal structure (colour) of environmental variation influences population fluctuations, extinction risk and community stability. However, it is unclear whether environmental covariates linked to population fluctuations are distinguishable from a purely random process (white noise). We aimed to estimate colour coefficients and relative support for three models commonly representing coloured stochastic processes, in environmental series linked to terrestrial animal population fluctuations. Location: North America and Eurasia. Time period: 1901–2002. Major taxa studied: Birds, insects and mammals. Methods: We analysed multiple abiotic environmental covariates, comparing point estimates and confidence intervals of temporal structure in competing models fitted using white noise, autoregressive [AR(1)] and 1/f processes in the time domain and the frequency domain (where time series were analysed after decomposition into different sinusoidal frequencies and their relative powers). All animal time series were sampled annually for ≤ 50 years, potentially inflating type II errors. We also considered 101‐year series of matched environmental covariates, performing a statistical power analysis evaluating our ability to draw robust conclusions. Results: Temperature‐related variables were associated with the largest fraction of population fluctuations. Ninety‐three per cent of shorter environmental series were indistinguishable from white noise, limited by time‐series length and associated with wide confidence intervals. The longer environmental series analysed in the time domain offered sufficiently high statistical power to identify correctly colour estimates ≥ |0.27|, indicating that 20% of series were best described by a slightly reddened noise process. Main conclusions: Focusing on the short time‐scales typically available for ecologists, most environmental variables associated with terrestrial animal population fluctuations are best characterized by white noise processes, although type II errors are common. The correct detection of intermediately coloured noise with power 0.8 requires ≥ 16 data points in the time domain or ≥ 47 points in the frequency domain. Over longer time‐scales, where type II errors are less likely, one‐fifth of populations are associated with coloured (often reddened) variables. [ABSTRACT FROM AUTHOR]

Bird migration phenology shows strong responses to climate change. Studies of trends and patterns in phenology are typically based on annual summarizing metrics, such as means and quantiles calculated from raw daily count data. However, with irregularly sampled data and large day-to-day variation, such metrics can be biased and noisy, and may be analysed using phenological functions fitted to the data. Here we use count data of migration passage from a Finnish bird observatory to compare different models for the phenological distributions of spring migration (27 species) and autumn migration (57 species). We assess parsimony and goodness-of-fit in a set of models, with phenological functions of different complexity, optionally with covariates accounting for day-to-day variability. The covariates describe migration intensities of related species or relative migration intensities the previous day (autocovariates). We found that parametric models are often preferred over the more flexible generalized additive models with constrained degrees of freedom. Models corresponding to a mixture of two distinct passing populations were frequently preferred over simpler ones, but usually no more complex models are needed. Slightly more complex models were favoured in spring compared to autumn. Related species' migration activity effectively improves the model by accounting for the large day-to-day variation. Autocovariates were usually not that relevant, implying that autocorrelation is generally not a major concern if phenology is modelled properly. We suggest that parametric models are relatively good for studying single-population migration phenology, or a mix of two groups with distinct phenologies, especially if daily variation in migration intensity can be controlled for. Generalized additive models may be useful when the migrating population composition is unknown. Despite these guidelines, choosing an appropriate model involves case-by-case assessment or the biological relevance and rationale for modelling phenology. [ABSTRACT FROM AUTHOR]

The application of uniform conservation schemes often fails to account for small-scale spatial variation in the drivers of population decline. Demographic comparisons of imperilled populations across locations are therefore crucial for successful conservation, but progress is hampered by lack of long-term data from more than a single population. The recent large-scale decline of eider ducks ( Somateria mollissima) in the Baltic Sea is ideal for determining to what extent mechanisms underlying population decline can be extrapolated over larger areas. We utilized stochastic demographic methods incorporating both environmental and sampling variation to assess small-scale spatial and temporal variation in the population dynamics of eiders at Söderskär (eastern range-margin) and Tvärminne (core breeding area), situated 130 km apart. The stochastic growth rate models accurately predicted the observed differences in the rate of decline between sites and time periods. At Söderskär, established breeder survival had by far the greatest elasticity, whereas elasticity was more evenly distributed among vital rates at Tvärminne. Although the study sites showed the single largest difference in fecundity, stochastic life table response experiment analyses revealed that reduced adult female survival at Tvärminne mainly determined the observed difference in growth rates between sites. In contrast, reduced fecundity primarily differentiated the past population increase from the present population decline at Söderskär. Our results demonstrate that different mechanisms may be associated with population decline across adjacent geographic locations, and indicate that dispersal of first-time breeders may be important for population dynamics. Safeguarding adult female survival and/or fecundity should be prioritized in management efforts. [ABSTRACT FROM AUTHOR]

Few studies have covered both the effects of climate and land-use change on animal populations under a single framework. Besides, the scarce multi-species studies conducted have focused on breeding data, and there is little information published on changes in wintering populations. Here, we relate the pattern of long-term temporal trends of wintering bird populations in Finland, north Europe, to covariates associated with climate and land-use change. Finnish wintering populations have been monitored using ca 10 km winter bird census routes (> 420 routes counted annually) during 1959-2012. Population trends of 63 species were related to migratory strategy, urbanity, and thermal niche measured as species-specific centre of gravity of the wintering distribution. Waterbird trends have shown a marked increase compared to landbirds. Among landbirds, forest species have suffered severe declines, whereas urban species have considerably increased in their wintering numbers. To follow up these results, we produced three multi-species indices (for waterbirds, forest and urban species, respectively), which can improve our ability to detect and monitor the specific consequences of climate change and changes in land-use, but at the same time act as a feedback to track the conservation status of the species. Our results suggest that waterbirds are responding to climate change, given their dependence on open water and the correlation with early-winter temperature over the last decades. On the other hand, we believe trends of landbirds have been mainly driven by human-induced land-use changes. While urban species have likely benefited from the increase of supplementary feeding, forest species have probably suffered from the loss of native habitats. [ABSTRACT FROM AUTHOR]

Environmental effects on population growth are often quantified by coupling environmental covariates with population time series, using statistical models that make particular assumptions about the shape of density dependence. We hypothesized that faulty assumptions about the shape of density dependence can bias estimated effect sizes of temporally autocorrelated covariates. We investigated the presence of bias using Monte Carlo simulations based on three common per capita growth functions with distinct density dependent forms (θ-Ricker, Ricker and Gompertz), autocorrelated (coloured) 'known' environmental covariates and uncorrelated (white) 'unknown' noise. Faulty assumptions about the shape of density dependence, combined with overcompensatory intrinsic population dynamics, can lead to strongly biased estimated effects of coloured covariates, associated with lower confidence interval coverage. Effects of negatively autocorrelated (blue) environmental covariates are overestimated, while those of positively autocorrelated (red) covariates can be underestimated, generally to a lesser extent. Prewhitening the focal environmental covariate effectively reduces the bias, at the expense of the estimate precision. Fitting models with flexible shapes of density dependence can also reduce bias, but increases model complexity and potentially introduces other problems of parameter identifiability. Model selection is a good option if an appropriate model is included in the set of candidate models. Under the specific and identifiable circumstances with high risk of bias, we recommend prewhitening or careful modelling of the shape of density dependence. [ABSTRACT FROM AUTHOR]

Recent shifts in phenology in response to climate change are well established but often poorly understood. Many animals integrate climate change across a spatially and temporally dispersed annual life cycle, and effects are modulated by ecological interactions, evolutionary change and endogenous control mechanisms. Here we assess and discuss key statements emerging from the rapidly developing study of changing spring phenology in migratory birds. These well-studied organisms have been instrumental for understanding climate-change effects, but research is developing rapidly and there is a need to attack the big issues rather than risking affirmative science. Although we agree poorly on the support for most claims, agreement regarding the knowledge basis enables consensus regarding broad patterns and likely causes. Empirical data needed for disentangling mechanisms are still scarce, and consequences at a population level and on community composition remain unclear. With increasing knowledge, the overall support ('consensus view') for a claim increased and between-researcher variability in support ('expert opinions') decreased, indicating the importance of assessing and communicating the knowledge basis. A proper integration across biological disciplines seems essential for the field's transition from affirming patterns to understanding mechanisms and making robust predictions regarding future consequences of shifting phenologies. [ABSTRACT FROM AUTHOR]

Irruptive migrants are partially migrating species showing pronounced temporal variation in the number of migrants. Occasional irruptions are often explained by increased population density (per area) or lack of food. Similarly to population dynamics, these explanations are not mutually exclusive, but probably act in concert. Here we do a parallel analysis on the migration intensity and population dynamics of an irruptive migratory bird species, the great spotted woodpecker Dendrocopos major, in southern Finland. Both analyses include simultaneous effects of breeding density and cone crops of Scots pine Pinus sylvestris and Norway spruce Picea abies. A novel model for statistical analyses of irruptive migration intensity is developed. Population dynamics are investigated using log-linear state-space models. Woodpecker migration intensity is well explained by lack of spruce cones and increases proportionally to population density. Population dynamics is most successfully described with a density dependent model, where the natural logarithm of spruce cone availability previous autumn has a strong positive effect on population growth. This is likely to be due to lowered winter mortality and lowered emigration rates resulting from plentiful food availability. Although the species uses pine cones as a food resource in winter, the estimated impacts of pine cone crops on migration intensity and population dynamics are low, probably due to low annual variation in crop comparing to spruce cones. Large irruptions also tend to occur earlier in season, often before cones are a crucial food resource for the woodpeckers, suggesting that the woodpeckers use the amount of maturing cones as a cue for upcoming conditions. Our results show that the ecological role of different resources can differ considerably from the expected pattern based on the proportion of the resources in a species' diet. Advantages of examining patterns of bird migration, population density and dynamics in unison are apparent. [ABSTRACT FROM AUTHOR]

Current climate change has been found to advance spring arrival and breeding dates of birds, but the effects on autumn migration and possible responses in the distribution of wintering individuals are poorly known. To thoroughly understand the consequences of climate change for animal life histories and populations, exploration of whole annual cycles are needed. We studied timing of migration (years 1979-2007), breeding phenology (1979-2007) and breeding success (1973-2007) of Eurasian sparrowhawks Accipiter nisus in Finland. We also investigated whether the migration distance of Finnish sparrowhawks has changed since the 1960s, using ringing recovery records. Since the late 1970s Finnish sparrowhawks have advanced their spring arrival, breeding and autumn departure considerably, but the migration distance has not changed. Early migrants, who are the ones with the highest reproductive success, show the strongest advance in the timing of spring migration. In autumn, advanced departure concerns young sparrowhawks. Late autumn migrants, who are mainly adults, have not advanced their migration significantly. The sparrowhawk is the most common bird of prey and the main predator of most passerines in Finland. Therefore, changes in sparrowhawk migration phenology may affect the migration behaviour of many prey species. The breeding success of sparrowhawks has increased significantly over the study period. This is however more likely caused by other factors than climate change, such as reduced exposure to organochlorine pollutants. [ABSTRACT FROM AUTHOR]

Within the paradigm of population dynamics a central task is to identify environmental factors affecting population change and to estimate the strength of these effects. We here investigate the impact of observation errors in measurements of population densities on estimates of environmental effects. Adding observation errors may change the autocorrelation of a population time series with potential consequences for estimates of effects of autocorrelated environmental covariates. Using Monte Carlo simulations, we compare the performance of maximum likelihood estimates from three stochastic versions of the Gompertz model (log–linear first order autoregressive model), assuming 1) process error only, 2) observation error only, and 3) both process and observation error (the linear state–space model on log-scale). We also simulated population dynamics using the Ricker model, and evaluated the corresponding maximum likelihood estimates for process error models. When there is observation error in the data and the considered environmental variable is strongly autocorrelated, its estimated effect is likely to be biased when using process error models. The environmental effect is overestimated when the sign of the autocorrelations of the intrinsic dynamics and the environment are the same and underestimated when the signs differ. With non-autocorrelated environmental covariates, process error models produce fairly exact point estimates as well as reliable confidence intervals for environmental effects. In all scenarios, observation error models produce unbiased estimates with reasonable precision, but confidence intervals derived from the likelihood profiles are far too optimistic if there is process error present. The safest approach is to use state–space models in presence of observation error. These are factors worthwhile to consider when interpreting earlier empirical results on population time series, and in future studies, we recommend choosing carefully the modelling approach with respect to intrinsic population dynamics and covariate autocorrelation. [ABSTRACT FROM AUTHOR]