Population dynamics of a South American rodent: seasonal structure interacting with climate,density dependence and predator effects

Understanding the role of interactions between intrinsic feedback loops and external climatic forces is one of the central challenges within the field of population ecology. For rodent dynamics, the seasonal structure of the environment necessitates changes between two stages: reproductive and non-reproductive. Nevertheless, the interactions between seasonality, climate, density dependence and predators have been generally ignored. We demonstrate that direct climate effects, the nonlinear effect of predators and the nonlinear first-order feedback embedded in a seasonal structure are key elements underlying the large and irregular fluctuations in population numbers exhibited by a small rodent in a semi-arid region of central Chile. We found that factors influencing population growth rates clearly differ between breeding and non-breeding seasons. In addition, we detected nonlinear density dependencies as well as nonlinear and differential effects of generalist and specialist predators. Recent climatic changes may account for dramatic perturbations of the rodent's population dynamics. Changes in the predator guild induced by climate are likely to result, through the food web, in a large impact on small rodent demography and population dynamics. Assuming such interactions to be typical of ecological systems, we conclude that appropriate predictions of the ecological consequences of climate change will depend on having an in-depth understanding of the community-weather system.     

Carry-over effects,sequential density dependence and the dynamics of populations in a seasonal environment

Most animal populations have distinct breeding and non-breeding periods, yet the implications of seasonality on population dynamics are not well understood. Here, we introduce an experimental model system to study the population dynamics of two important consequences of seasonality: sequential density dependence and carry-over effects (COEs). Using a replicated seasonal population of Drosophila, we placed individuals at four densities in the non-breeding season and then, among those that survived, placed them to breed at three different densities. We show that COEs arising from variation in non-breeding density negatively impacts individual performance by reducing per capita breeding output by 29–77%, implying that non-lethal COEs can have a strong influence on population abundance. We then parametrized a bi-seasonal population model from the experimental results, and show that both sequential density dependence and COEs can stabilize long-term population dynamics and that COEs can reduce population size at low intrinsic rates of growth. Our results have important implications for predicting the successful colonization of new habitats, and for understanding the long-term persistence of seasonal populations in a wide range of taxa, including migratory organisms.     

Mechanisms of density dependence in fluctuating vole populations: deducing annual density dependence from seasonal processes

Based on recent advances in time-series analyses of ecological dynamics using statistical and mathematical models, we summarise our recent results on the seasonal processes in the annual population dynamics of the grey-sided vole Clethrionomys rufocanus (Sundevall, 1846) in Hokkaido, Japan, and report additional analyses on annual and seasonal density dependence. Annual direct density dependence was strong in almost all populations. In contrast, delayed density dependence was generally weak, although clear delayed density dependence was detected in some of the studied populations. Although seasonal density dependence was observed both in winter and summer, direct density dependence was much more profound during winter; thus, winter density dependence contributed most to the overall annual direct density dependence. We found no correlation between the seasonal components of annual direct density dependence; however, the corresponding seasonal components for annual delayed density dependence were positively correlated. We conclude that winter conditions influence the strength of annual direct density dependence most profoundly. Moreover, we conclude that direct density dependence during summer and winter may be generated by different mechanisms, whereas delayed density dependence seems to be generated by a common mechanism. Candidate mechanisms are discussed in relation to general knowledge of northern rodent populations and to specific insights provided by earlier studies of grey-sided voles in Hokkaido.     

Seasonal forcing on the dynamics ofClethrionomys rufocanus: Modeling geographic gradients in population dynamics

We interpret gradients in population dynamics of the gray-sided vole from the southwestern part of the island of Hokkaido to its northeastern part within the framework of a phenomenological model involving the relative length of summer and winter. In Hokkaido, as in other northern regions, both spring and fall is considered as short transition periods between the two main seasons — summer (the primary breeding season) and winter (the non-reproductive or secondary breeding season). We show that the geographic transition in dynamics may be understood as the combined consequence of different patterns of density-dependence during summer and winter, and geographically varying season lengths. Differences are shown to exist between summer and winter with respect to strength of density-dependence. Direct density-dependence, in particular, is stronger during winter than during summer. A model is presented to show how relative lengths of seasons can induce both stable and periodically fluctuating population dynamics. The results are compared and contrasted with what is otherwise known about the gradient in rodent dynamics in Fennoscandia.     

Patterns of density dependence in measles dynamics.

An important question in metapopulation dynamics is the influence of external perturbations on the population''s long-term dynamic behaviour. In this paper we address the question of how spatiotemporal variations in demographic parameters affect the dynamics of measles populations in England and Wales. Specifically, we use nonparametric statistical methods to analyse how birth rate and population size modulate the negative density dependence between successive epidemics as well as their periodicity. For the observed spatiotemporal data from 60 cities, and for simulated model data, the demographic variables act as bifurcation parameters on the joint density of the trade-off between successive epidemics. For increasing population size, a transition occurs from an irregular unpredictable pattern in small communities towards a regular, predictable endemic pattern in large places. Variations in the birth rate parameter lead to a bifurcation from annual towards biennial cyclicity in both observed data and model data.     

Differences in the ecology of Bartonella infections of Apodemus flavicollis and Myodes glareolus in a boreal forest

The epidemiology of Bartonella species infecting Apodemus flavicollis and Myodes glareolus in a forest in Eastern Poland was followed for 2 years using mark-recapture. Infections could be acquired in any month, but prevalence, and probability of infection, peaked in the summer. There were significant differences in the pattern of infections between the two species. Both hosts were primarily infected as juveniles, but the probability of infection was highest for A. flavicollis, which, evidence suggests, experienced longer-lasting infections with a wider range of Bartonella genotypes. There was no evidence of increased host mortality associated with Bartonella, although the infection did affect the probability of recapture. Animals could become re-infected, generally by different Bartonella genotypes. Several longer lasting, poorly resolved infections of A. flavicollis involved more than 1 genotype, and may have resulted from sequential infections. Of 22 Bartonella gltA genotypes collected, only 2 (both B. grahamii) were shared between mice and voles; all others were specific either to A. flavicollis or to M. glareolus, and had their nearest relatives infecting Microtus species in neighbouring fields. This heterogeneity in the patterns of Bartonella infections in wild rodents emphasizes the need to consider variation between both, host species and Bartonella genotypes in ecological and epidemiological studies.     

Cycles, stochasticity and density dependence in pink salmon population dynamics

Complex dynamics of animal populations often involve deterministic and stochastic components. A fascinating example is the variation in magnitude of 2-year cycles in abundances of pink salmon (Oncorhynchus gorbuscha) stocks along the North Pacific rim. Pink salmon have a 2-year anadromous and semelparous life cycle, resulting in odd- and even-year lineages that occupy the same habitats but are reproductively isolated in time. One lineage is often much more abundant than the other in a given river, and there are phase switches in dominance between odd- and even-year lines. In some regions, the weak line is absent and in others both lines are abundant. Our analysis of 33 stocks indicates that these patterns probably result from stochastic perturbations of damped oscillations owing to density-dependent mortality caused by interactions between lineages. Possible mechanisms are cannibalism, disease transmission, food depletion and habitat degradation by which one lineage affects the other, although no mechanism has been well-studied. Our results provide comprehensive empirical estimates of lagged density-dependent mortality in salmon populations and suggest that a combination of stochasticity and density dependence drives cyclical dynamics of pink salmon stocks.     

Population cycles produced by delayed density dependence in an annual plant

In contrast to insect and animal populations, little attention has been directed to the study of cycles in plant populations. It has been argued on theoretical grounds that plants present stable dynamics. Nevertheless, there are examples where plant populations appear to exhibit oscillatory dynamics, but the oscillatory signal is variable and comes from very short time series data. Using a combination of time series, models, and empirical results, we present evidence of population cycles for Descurania sophia in a 16-year field experiment. Endogenous and exogenous causal mechanisms were studied to identify processes underlying this temporal dynamic. Our results show a 4-year cycle produced by delayed density dependence. We suggest that high nutrient levels might be responsible for the observed dynamics of D. sophia. Our results suggest that although plant population dynamics may be stabilized by direct density dependence, delayed density dependence could destabilize dynamics.     

Spin labelling study of frozen solutions of porcine high density and low density lipoproteins: temperature dependence of the lipid dynamics

Frozen solutions of porcine lipoproteins, spin-labelled with steric acids, were studied as a function of temperature. High and low density lipoproteins and their subclasses were examined to obtain informatin on the relationship between the size, composition and dynamics of their lipid constituents. in low density lipoproteins (LDL) the temperature at which spin-labelled fatty acids responded to increased temperature depended on the position of the nitroxide moiety on the fatty acid chain. In LDL, e.s.r. spectra of 16-doxyl stearic acid I(1/14) with the nitroxide moiety buried depp in the phospholipid interior, responded to moderate increase of temperature even at ?50°C. In high densitylipoproteins (HDL), all spin-labelled fatty acids, I(m/n), remained in the frozen state (on the e.s.r. time scale) up to the melting point of the baffer. These differences in behaviour of the frozen lipoprotein solutions indicated that physicochemical properties of the surface constituents of the lipoprotein particle might be of a different nature in HLD and LDL.     

Hatching fraction and timing of resting stage production in seasonal environments: effects of density dependence and uncertain season length

Many organisms survive unfavourable seasons as resting stages, some of which hatch each favourable season. Hatching fraction and timing of resting stage production are important life history variables. We model life cycles of freshwater invertebrates in temporary pools, with various combinations of uncertain season length and density‐dependent fecundity. In deterministic density‐independent conditions, resting stage production begins suddenly. With uncertain season length and density independence, resting stage production begins earlier and gradually. A high energetic cost of resting stages favours later resting stage production and a lower hatching fraction. Deterministic environments with density dependence allow sets of coexisting strategies, dominated by pairs, each switching suddenly to resting stage production on a different date, usually earlier than without density dependence. Uncertain season length and density dependence allow a single evolutionarily stable strategy, around which we observe many mixed strategies with negatively associated yield (resting stages per initial active stage) and optimal hatching fraction.     

The seasonal dynamics of fleas (Siphonaptera) on bank voles (Clethrionomys glareolus) in the north part of Novgorod region

The twelve flea species were revealed on bank voles. Only four of them (Amalaraeus penicillige, Ctenophthalmus uncinatus, Megabothris turbidus, Peromescopsylla bidentata) were abundant in some seasons of the year. Four other species (Ct. agyrtes, Hystrichopsylla talpae, P. silvatica, Rhadinopsylla integella) are the parasites of bank vole too but their numbers were always low in the study area. The four last species (Amphypsylla rossica, M. walkeri, Doratopsylla dasycnema, Palaeopsylla soricis) are not peculiar to bank vole. They occurs on it occasionally from other animals--the voules of Mucrotus and shrews. The most species diversity of fleas on bank vole was observed at the period from August to October, the least one--in late winter, spring and early summer. The total abundance indices of fleas on the voles (mean number of the insects per host) ranged in different months from 0.17 to 5.65. The time of minimum flea numbers was August-September. The peak abundance was reached in springtime (March-April).     

Population dynamics and morphometries of Gammarus pulex L.: evidence of seasonal food limitation in a freshwater detritivore

SUMMARY. 1. Seasonal changes in population size structure of Gammarus pulex L. in a Cotswold stream appeared to indicate a growth check in late summer.
2. The relationships between dry weight and body length, and between the number of primary flagellar segments on the first antenna and either dry weight or body length provided further evidence of a reduction in growth in mid and late summer.
3. Body fat content was minimal (4% of dry weight) at the end of summer, when large particulate organic detritus was scarce or of poor quality, and maximal in late winter (17.9% dry weight in females; 9.4% in males), after a period of high food availability. In a field experiment, the fat content of animals in summer was raised to levels typical of winter by providing high quality food.
4. Field and experimental evidence together strongly infer that this population of G. pulex was subject to severe food limitation from early summer until leaf fall in autumn.     

Mischaracterising density dependence biases estimated effects of coloured covariates on population dynamics

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.