Population Dynamics In Variable Environments Research Articles

Tuljapurkar and Orzack (1980) and Tuljapurkar (1982a,b): Population dynamics in variable environments

Tuljapurkar and Orzack (1980) and Tuljapurkar (1982a,b): Population dynamics in variable environments

Food quantity–quality co‐limitation: Interactive effects of dietary carbon and essential lipid supply on population growth of a freshwater rotifer

Abstract Food quantity and quality are highly variable in natural systems. Therefore, their interplay and the associated effects on consumer population growth are important for predator–prey interactions and community dynamics. Experiments in which consumers were exposed to elemental nutrient limitations along food quantity gradients suggest that food quality effects on consumer performance are relevant only at high food quantities. However, elemental nutrients act differently on physiological processes than biochemical nutrients. So far, the interactive effects of food quantity and biochemical compounds on consumer performance have been insufficiently studied. We studied interactive effects of food quantity and biochemical food quality on population growth, including fecundity and survival, of the freshwater rotifer Brachionus calyciflorus. We hypothesised that these life history traits are differently affected by the availability of biochemical nutrients and that food quality effects gain importance with increasing food quantity. In a first experiment, we established food quantity and quality gradients by providing rotifers with different concentrations of a low‐quality food, the sterol‐free cyanobacterium Synechococcus elongatus, supplemented with increasing amounts of cholesterol. In a second experiment, food quantity and quality gradients were established by providing different proportions of two prey species differing in biochemical food quality, i.e. S. elongatus and the lipid‐rich alga Nannochloropsis limnetica, at different total food concentrations. We found that the effects of cholesterol supplementation on population growth increased with increasing food quantity. This interactive effect on population growth was mainly due to food quality effects on fecundity, as effects on survival remained constant along the food quantity gradient. In contrast, when feeding on the mixed algal diet, the food quality effect associated with increasing the proportion of the high‐quality alga did not change along the food quantity gradient. The data on survival and fecundity demonstrate the missing interactive effect of food quantity and quality on population growth, as both traits were oppositely affected. Survival was affected by food quality primarily at low food quantity, whereas food quality effects on fecundity were stronger at high food quantity. Our results highlight the significance of essential biochemicals in mediating the interactive effects of food quantity and quality on population growth. The interplay between food quantity and biochemical food quality limitation seems to influence resource allocation patterns in order to optimise survival or reproduction, which may strongly affect population dynamics in variable environments. As opposed to exploring the function of a single nutrient via supplementation, using algae mixtures allowed us to assess food quality effects on consumer performance in a more natural context by taking potential interactive effects of multiple co‐limiting nutrients into account.

Spatial and temporal synchrony in reptile population dynamics in variable environments.

Resources are seldom distributed equally across space, but many species exhibit spatially synchronous population dynamics. Such synchrony suggests the operation of large-scale external drivers, such as rainfall or wildfire, or the influence of oasis sites that provide water, shelter, or other resources. However, testing the generality of these factors is not easy, especially in variable environments. Using a long-term dataset (13-22years) from a large (8000km(2)) study region in arid Central Australia, we tested firstly for regional synchrony in annual rainfall and the dynamics of six reptile species across nine widely separated sites. For species that showed synchronous spatial dynamics, we then used multivariate follow a multivariate auto-regressive state-space (MARSS) models to predict that regional rainfall would be positively associated with their populations. For asynchronous species, we used MARSS models to explore four other possible population structures: (1) populations were asynchronous, (2) differed between oasis and non-oasis sites, (3) differed between burnt and unburnt sites, or (4) differed between three sub-regions with different rainfall gradients. Only one species showed evidence of spatial population synchrony and our results provide little evidence that rainfall synchronizes reptile populations. The oasis or the wildfire hypotheses were the best-fitting models for the other five species. Thus, our six study species appear generally to be structured in space into one or two populations across the study region. Our findings suggest that for arid-dwelling reptile populations, spatial and temporal dynamics are structured by abiotic events, but individual responses to covariates at smaller spatial scales are complex and poorly understood.

Linking demographic responses and life history tactics from longitudinal data in mammals

In stochastic environments, a change in a demographic parameter can influence the population growth rate directly or via a resulting impact on age structure. Stochastic elasticity of the long‐run stochastic growth rate λsto a demographic parameter offers a suitable way to measure the overall demographic response because it includes both the direct effect of changing the demographic parameter and its indirect effect through changes in the age structure. From 25 mammalian populations with contrasting life histories, we investigated how pace of life and population growth rate influence the demographic responses (measured as the relative contributions of the direct and indirect components of stochastic elasticity on λs). We found that in short‐lived species, the change in population structure resulting from an increase in yearling survival leads to an additional increase in λs, whereas in long‐lived species, the same change in population structure leads to a decrease. Short‐lived species thus display a boom‐bust life history strategy contrary to long‐lived species, for which the long lifespan dampens the demographic consequences of changing age structure. Irrespective of the species’ life history strategy, the change in population age structure resulting from an increase in adult survival leads to an additional increase in λsdue to an increase of the proportion of mature individuals in the population. On the contrary, a change in population age structure resulting from an increase of reproductive performance leads to a decrease in λsthat is due to the increase of the proportion of immature individuals in the population. Our comparative analysis of stochastic elasticity patterns in mammals shows the existence of different demographic responses to changes in age structure between short‐ and long‐lived species, which improves our understanding of population dynamics in variable environments in relation to the species‐specific pace of life.

Influence of life-history tactics on transient dynamics: a comparative analysis across mammalian populations.

Most mammalian populations suffer from natural or human-induced disturbances; populations are no longer at the equilibrium (i.e., at stable [st]age distribution) and exhibit transient dynamics. From a literature survey, we studied patterns of transient dynamics for mammalian species spanning a large range of life-history tactics and population growth rates. For each population, we built an age-structured matrix and calculated six metrics of transient dynamics. After controlling for possible confounding effects of the phylogenetic relatedness among species using a phylogenetic principal component analysis and phylogenetic generalized least squares models, we found that short-term demographic responses of mammalian populations to disturbance are shaped by generation time and growth rate. Species with a slow pace of life (i.e., species with a late maturity, a low fecundity, and a long life span) displayed decreases in population size after a disturbance, whereas fast-living species increased in population size. The magnitude of short-term variation in population size increased with asymptotic population growth, being buffered in slow-growing species (i.e., species with a low population growth rate) but large in fast-growing species. By demonstrating direct links between transient dynamics, life history (generation time), and ecology (demographic regime), our comparative analysis of transient dynamics clearly improves our understanding of population dynamics in variable environments and has clear implications for future studies of the interplay between evolutionary and ecological dynamics. As most populations in the wild are not at equilibrium, we recommend that analyses of transient dynamics be performed when studying population dynamics in variable environments.

Population Dynamics in Variable Environments

Population Dynamics in Variable Environments

Population Dynamics in Variable Environments. VII. The Demography and Evolution of Iteroparity

A dynamic analysis is presented of the manner in which survival rates and reproductive schedules evolve in variable environments. This approach accounts for (1) age structure, (2) density-independent fluctuations in vital rates, (3) life histories of arbitrary length, (4) variance and covariance of vital rates, and (5) an incorporation of genotypic differences in life history. The results indicate that there is no general advantage to a more iteroparous life history in a variable environment and that the direction of evolution depends on the absolute amount of environmental variation and the correlation structure of the vital rates. Analysis of indifference curves also indicates that there is considerable potential for neutral evolution with respect to life history, given genotypic differences in environmental sensitivity. We suggest two nonexclusive partial answers to Cole's paradox. One is that the magnitude of environmental variability and the correlation structure of vital rates cause short-lived, e...

Population dynamics in variable environments. VI. Cyclical environments

This paper studies the dynamics of an age-structured population which experiences cyclical variation in vital rates. The principal features of population behavior are found to be contained in an explicitly calculable response function. Three distinct regimes of qualitative behavior are described when cycle period is respectively much less than, of the order of, and much greater than the average generation length. These results make explicit the way in which transient properties corresponding to average vital rates determine population response to cycles.

Population Dynamics in Variable Environments. V. The Genetics of Homeostasis Revisited

A one-locus stochastic environment model in which genotypes differ in homeostatic ability is analyzed. Each genotype is assigned a set of Leslie matrices, the vital rates of which vary between environments to differing degrees depending on genotype. In contrast to the classical assumption and the results of previous theoretical analyses, the least variable genotype does not necessarily have a selective advantage. In particular, the relative advantage of homeostasis is dependent on environmental frequencies and, more significantly, on the environmental autocorrelation. For a given set of environments, changing autocorrelation can change the allele which is ultimately fixed, or allow a polymorphism to be maintained. In addition, for given environmental conditions, the direction of evolution can qualitatively change depending on which part of the life history is subject to selection. Covariances between vital rates can enhance or eliminate the advantage of the least variable genotype. Finally, it is shown, in contradiction to the prediction of the theory of "genetic homeostasis," that overdominance for homeostatic ability does not necessarily lead to maintenance of polymorphism within a population.

Population dynamics in variable environments. IV. Weak ergodicity in the Lotka equation.

The Hilbert projective metric is applied to the continuous-time Lotka equation in demography to establish weak ergodicity: populations with the same time-varying fecundity and mortality schedules ultimately have the same age composition. The analysis displays clearly the dynamic content of Lotka's equation and identifies a contraction operator which forces convergence of birth sequences over time. The relationship between primitivity in the discrete (Leslie) and continuous (Lotka) demographic models is made clear.

Population dynamics in variable environments. II. Correlated environments, sensitivity analysis and dynamics

Mean and mean square number are studied for age-structured populations with serially correlated temporally fluctuating vital rates. Results are that (1) Moments of population number can be used effectively to analyse growth rates of the coefficient of variation and an approximate median population number. (2) Analytical approximations to the growth rates of moments reveal dynamic consequences of covarying phenotypic traits and of temporal correlation along environmental sequences. (3) Dynamic properties can be explicitly related to the static sensitivity of an average vital rate matrix. (4) The use of (1), (2) and (3) allows an extension of many applications of static vital rate theory to dynamics with fluctuating rates.

Population dynamics in variable environments I. Long-run growth rates and extinction

A model of population growth is studied in which the Leslie matrix for each time interval is chosen according to a Markov process. It is shown analytically that the distribution of total population number is lognormal at long times. Measures of population growth are compared and it is shown that a mean logarithmic growth rate and a logarithmic variance effectively describe growth and extinction at long times. Numerical simulations are used to explore the convergence to lognormality and the effects of environmental variance and autocorrelation. The results given apply to other geometric growth models which involve nonnegative growth matrices.