Climate and spatio-temporal variation in the population dynamics of a long distance migrant, the white stork

1. A central question in ecology is to separate the relative contribution of density dependence and stochastic influences to annual fluctuations in population size. Here we estimate the deterministic and stochastic components of the dynamics of different European populations of white stork Ciconia ciconia. We then examined whether annual changes in population size was related to the climate during the breeding period (the 'tap hypothesis' sensu Saether, Sutherland & Engen (2004, Advances in Ecological Research, 35, 185 209) or during the nonbreeding period, especially in the winter areas in Africa (the 'tube hypothesis'). 2. A general characteristic of the population dynamics of this long-distance migrant is small environmental stochasticity and strong density regulation around the carrying capacity with short return times to equilibrium. 3. Annual changes in the size of the eastern European populations were correlated by rainfall in the wintering areas in Africa as well as local weather in the breeding areas just before arrival and in the later part of the breeding season and regional climate variation (North Atlantic Oscillation). This indicates that weather influences the population fluctuations of white storks through losses of sexually mature individuals as well as through an effect on the number of individuals that manages to establish themselves in the breeding population. Thus, both the tap and tube hypothesis explains climate influences on white stork population dynamics. 4. The spatial scale of environmental noise after accounting for the local dynamics was 67 km, suggesting that the strong density dependence reduces the synchronizing effects of climate variation on the population dynamics of white stork. 5. Several climate variables reduced the synchrony of the residual variation in population size after accounting for density dependence and demographic stochasticity, indicating that these climate variables had a synchronizing effect on the population fluctuations. In contrast, other climatic variables acted as desynchronizing agents. 6. Our results illustrate that evaluating the effects of common environmental variables on the spatio-temporal variation in population dynamics require estimates and modelling of their influence on the local dynamics.     

A chronology of plankton dynamics in silico: how computer models have been used to study marine ecosystems

Research on plankton ecology in the oceans has traditionally been conducted via two scientific approaches: in situ (in the field) and in vitro (in the laboratory). There is, however, a third approach: exploring plankton dynamics in silico, or using computer models as tools to study marine ecosystems. Models have been used for this purpose for over 60 years, and the innovations and implementations of historical studies provide a context for how future model applications can continue to advance our understanding. To that end, this paper presents a chronology of the in silico approach to plankton dynamics, beginning with modeling pioneers who worked in the days before computers. During the first 30 years of automated computation, plankton modeling focused on formulations for biological processes and investigations of community structure. The changing technological context and conceptual paradigms of the late-1970s and 1980s resulted in simulations becoming more widespread research tools for biological oceanographers. This period saw rising use of models as hypothesis-testing tools, and means of exploring the effects of circulation on spatial distributions of organisms. Continued computer advances and increased availability of data in the 1990s allowed old approaches to be applied to old and new problems, and led to developments of new approaches. Much of the modeling in the new millennium so far has incorporated these sophistications, and many cutting-edge applications have come from a new generation of plankton scientists who were trained by modeling gurus of previous eras. The future directions for modeling plankton dynamics are rooted in the historical studies.     

Geographical gradients in the population dynamics of North American prairie ducks

1. Geographic gradients in population dynamics may occur because of spatial variation in resources that affect the deterministic components of the dynamics (i.e. carrying capacity, the specific growth rate at small densities or the strength of density regulation) or because of spatial variation in the effects of environmental stochasticity. To evaluate these, we used a hierarchical Bayesian approach to estimate parameters characterizing deterministic components and stochastic influences on population dynamics of eight species of ducks (mallard, northern pintail, blue-winged teal, gadwall, northern shoveler, American wigeon, canvasback and redhead (Anas platyrhynchos, A. acuta, A. discors, A. strepera, A. clypeata, A. americana, Aythya valisineria and Ay. americana, respectively) breeding in the North American prairies, and then tested whether these parameters varied latitudinally. 2. We also examined the influence of temporal variation in the availability of wetlands, spring temperature and winter precipitation on population dynamics to determine whether geographical gradients in population dynamics were related to large-scale variation in environmental effects. Population variability, as measured by the variance of the population fluctuations around the carrying capacity K, decreased with latitude for all species except canvasback. This decrease in population variability was caused by a combination of latitudinal gradients in the strength of density dependence, carrying capacity and process variance, for which details varied by species. 3. The effects of environmental covariates on population dynamics also varied latitudinally, particularly for mallard, northern pintail and northern shoveler. However, the proportion of the process variance explained by environmental covariates, with the exception of mallard, tended to be small. 4. Thus, geographical gradients in population dynamics of prairie ducks resulted from latitudinal gradients in both deterministic and stochastic components, and were likely influenced by spatial differences in the distribution of wetland types and shapes, agricultural practices and dispersal processes. 5. These results suggest that future management of these species could be improved by implementing harvest models that account explicitly for spatial variation in density effects and environmental stochasticity on population abundance.     

Survival of Svalbard pink-footed geese Anser brachyrhynchus in relation to winter climate, density and land-use

1. Global change may strongly affect population dynamics, but mechanisms remain elusive. Several Arctic goose species have increased considerably during the last decades. Climate, and land-use changes outside the breeding area have been invoked as causes but have not been tested. We analysed the relationships between conditions on wintering and migration staging areas, and survival in Svalbard pink-footed geese Anser brachyrhynchus. Using mark-recapture data from 14 winters (1989-2002) we estimated survival rates and tested for time trends, and effects of climate, goose density and land-use. 2. Resighting rates differed for males and females, were higher for birds recorded during the previous winter and changed smoothly over time. Survival rates did not differ between sexes, varied over time with a nonsignificant negative trend, and were higher for the first interval after marking (0.88-0.97) than afterwards (0.74-0.93). Average survival estimates were 0.967 (SE 0.026) for the first and 0.861 (SE 0.023) for all later survival intervals. 3. We combined 16 winter and spring climate covariates into two principal components axes. F1 was related to warm/wet winters and an early spring on the Norwegian staging areas and F2 to dry/cold winters. We expected that F1 would be positively related to survival and F2 negatively. F1 explained 23% of survival variation (F1,10=3.24; one-sided P=0.051) when alone in a model and 28% (F1,9=4.50; one-sided P=0.031) in a model that assumed a trend for survival. In contrast, neither F2 nor density, land-use, or scaring practices on important Norwegian spring staging areas had discernible effects on survival. 4. Climate change may thus affect goose population dynamics, with warmer winters and earlier springs enhancing survival and fecundity. A possible mechanism is increased food availability on Danish wintering and Norwegian staging areas. As geese are among the main herbivores in Arctic ecosystems, climate change, by increasing goose populations, may have important indirect effects on Arctic vegetation. Our study also highlights the importance of events outside the breeding area for the population dynamics of migrant species.     

The anatomy of predator-prey dynamics in a changing climate

Humans are increasingly influencing global climate and regional predator assemblages, yet a mechanistic understanding of how climate and predation interact to affect fluctuations in prey populations is currently lacking. Here we develop a modelling framework to explore the effects of different predation strategies on the response of age-structured prey populations to a changing climate. We show that predation acts in opposition to temporal correlation in climatic conditions to suppress prey population fluctuations. Ambush predators such as lions are shown to be more effective at suppressing fluctuations in their prey than cursorial predators such as wolves, which chase down prey over long distances, because they are more effective predators on prime-aged adults. We model climate as a Markov process and explore the consequences of future changes in climatic autocorrelation for population dynamics. We show that the presence of healthy predator populations will be particularly important in dampening prey population fluctuations if temporal correlation in climatic conditions increases in the future.     

Environmental forcing and Southern Ocean marine predator populations: effects of climate change and variability

The Southern Ocean is a major component within the global ocean and climate system and potentially the location where the most rapid climate change is most likely to happen, particularly in the high-latitude polar regions. In these regions, even small temperature changes can potentially lead to major environmental perturbations. Climate change is likely to be regional and may be expressed in various ways, including alterations to climate and weather patterns across a variety of time-scales that include changes to the long interdecadal background signals such as the development of the El Niño–Southern Oscillation (ENSO). Oscillating climate signals such as ENSO potentially provide a unique opportunity to explore how biological communities respond to change. This approach is based on the premise that biological responses to shorter-term sub-decadal climate variability signals are potentially the best predictor of biological responses over longer time-scales. Around the Southern Ocean, marine predator populations show periodicity in breeding performance and productivity, with relationships with the environment driven by physical forcing from the ENSO region in the Pacific. Wherever examined, these relationships are congruent with mid-trophic-level processes that are also correlated with environmental variability. The short-term changes to ecosystem structure and function observed during ENSO events herald potential long-term changes that may ensue following regional climate change. For example, in the South Atlantic, failure of Antarctic krill recruitment will inevitably foreshadow recruitment failures in a range of higher trophic-level marine predators. Where predator species are not able to accommodate by switching to other prey species, population-level changes will follow. The Southern Ocean, though oceanographically interconnected, is not a single ecosystem and different areas are dominated by different food webs. Where species occupy different positions in different regional food webs, there is the potential to make predictions about future change scenarios.     

Maternal effects mediated by maternal age: from life histories to population dynamics

1. Maternal effects describe how mothers influence offspring life histories. In many taxa, maternal effects arise by differential resource allocation to young, often identified by variation in propagule size, and which affects individual traits and population dynamics. 2. Using a laboratory model system, the soil mite Sancassania berlesei, we show that, controlling for egg size, older mothers lay eggs that hatch later, develop more slowly, and mature at larger body sizes. 3. Such differences in life histories lead to marked population dynamical effects lasting for multiple generations, as evidenced by an experiment initiated with similarly sized eggs that came from young or old mothers. Differences in maturation from the initial cohort led to differences in population structure and life history that propagated the initial differences over time. 4. Maternal-age effects, which are not related to gross provisioning of the egg and are therefore phenotypically cryptic, can have profound implications for population dynamics, especially if environmental variation can affect the age structure of the adult population.     

Population regulation of brook trout (Salvelinus fontinalis) in Hunt Creek,Michigan: a 50‐year study

1. Fisheries models generally are based on the concept that strong density dependence exists in fish populations. Nonetheless, there are few examples of long‐term density dependence in fish populations. 2. Using an information theoretical approach (AIC) with regression analyses, we examined the explanatory power of density dependence, flow and water temperature on the per capita rate of change and growth (annual mean total length) for the whole population, adults, 1+ and young‐of‐the‐year (YOY) brook trout (Salvelinus fontinalis) in Hunt Creek, Michigan, USA, between 1951 and 2001. This time series represents one of the longest quantitative population data sets for fishes. 3. Our analysis included four data sets: (i) Pooled (1951–2001), (ii) Fished (1951–65), (iii) Unfished (1966–2001) and (iv) Temperature (1982–2001). 4. Principle component analyses of winter flow data identified a gradient between years with high mean daily winter flows, high daily maximum and minimum flows and frequent high flow events, and years with an opposite set of flow characteristics. Flows were lower during the Fished Period than during the Unfished Period. Winter temperature analyses elucidated a gradient between warm mean, warm minimum and maximum daily stream temperatures and a high number of minimum daily temperatures >6.1 °C, and years with the opposite characteristics. Summer temperature analyses contrasted years with warm summer stream temperatures vs years with cool summer stream temperatures. 5. Both YOY and adult densities varied several‐fold during the study. Regression analysis did not detect a significant linear or nonlinear stock–recruitment relationship. AIC analysis indicated that density dependence was present in 15 of 16 cases (four population segments × four data sets) for both per capita rate of increase (w_i values 0.46–1.00) and growth data (w_i values 0.28–0.99). The almost ubiquitous presence of density dependence in both population and growth data is concordant with results from other trout populations and other studies in Michigan.     

Footprints of climate change in the Arctic marine ecosystem

In this article, we review evidence of how climate change has already resulted in clearly discernable changes in marine Arctic ecosystems. After defining the term ‘footprint’ and evaluating the availability of reliable baseline information we review the published literature to synthesize the footprints of climate change impacts in marine Arctic ecosystems reported as of mid‐2009. We found a total of 51 reports of documented changes in Arctic marine biota in response to climate change. Among the responses evaluated were range shifts and changes in abundance, growth/condition, behaviour/phenology and community/regime shifts. Most reports concerned marine mammals, particularly polar bears, and fish. The number of well‐documented changes in planktonic and benthic systems was surprisingly low. Evident losses of endemic species in the Arctic Ocean, and in ice algae production and associated community remained difficult to evaluate due to the lack of quantitative reports of its abundance and distribution. Very few footprints of climate change were reported in the literature from regions such as the wide Siberian shelf and the central Arctic Ocean due to the limited research effort made in these ecosystems. Despite the alarming nature of warming and its strong potential effects in the Arctic Ocean the research effort evaluating the impacts of climate change in this region is rather limited.     

Performance of climate envelope models in retrodicting recent changes in bird population size from observed climatic change

Twenty-five-year population trends of 42 bird species rare as breeders in the UK were examined in relation to changes in climatic suitability simulated using climatic envelope models. The effects of a series of potential 'nuisance' variables were also assessed. A statistically significant positive correlation was found across species between population trend and climate suitability trend. The demonstration that climate envelope models are able to retrodict species' population trends provides a valuable validation of their use in studies of the potential impacts of future climatic changes.     

Density-dependent population dynamics in clonal organisms: a modelling approach

1. Density dependence may act at several stages in an organisms life-cycle (e.g. on mortality, fecundity, etc.), but not all density-dependent processes necessarily regulate population size. In this paper I use a density manipulation experiment to determine the effects of density on the transition rates between different size classes of the clonal zoanthid Palythoa caesia Dana 1846. I then formulate a density-dependent matrix model of population dynamics of Palythoa , and perform a series of sensitivity analyses on the model to determine at what stage in the life-cycle regulation acts.
2. Seven of the 16 transition probabilities decreased with density, most of them being shrinkage (due to loss of tissue or fission) and stasis (the self–self transition) of medium and large colonies. The only probability to increase was for the stasis of large colonies. Recruitment was quadratically dependent on density, peaking at intermediate densities.
3. Equilibrium cover in the model was 84% and was reached in ≈40 years. To determine which density-dependent transitions were involved in population regulation, the strength of density dependence was varied in each independently. This sensitivity analysis showed that only changes in the probabilities of large colonies remaining large and producing medium colonies, were regulating.
4. These results suggest that regulation is primarily acting on fission of large colonies to produce intermediate-sized colonies, in combination with size specific growth rates. Fission rates decrease greatly with density, resulting in a greater proportion of large colonies at high densities and large colonies grow more slowly than small. Overall, this behaviour is very similar to that of clonal plants which have a phalanx type life history.     

Historical and projected interactions between climate change and insect voltinism in a multivoltine species

Climate change can cause major changes to the dynamics of individual species and to those communities in which they interact. One effect of increasing temperatures is on insect voltinism, with the logical assumption that increases in surface temperatures would permit multivoltine species to increase the number of generations per year. Though insect development is primarily driven by temperature, most multivoltine insect species rely on photoperiodic cues, which do not change from year‐to‐year or in response to climate warming, to initiate diapause. Thus, the relationship between climate change and voltinism could be complex. We use a phenology model for grape berry moth, Paralobesia viteana (Clemens), which incorporates temperature‐dependent development and diapause termination, and photoperiod‐dependent diapause induction, to explore historical patterns in year‐to‐year voltinism fluctuations. We then extend this model to predict voltinism under varying scenarios of climate change to show the importance of both the quality and quantity of accumulated heat units. We also illustrate that increases in mean surface temperatures > 2 °C can have dramatic effects on insect voltinism by causing a shift in the ovipositional period that currently is subject to diapause‐inducing photoperiods.