Local environment and density-dependent feedbacks determine population growth in a forest herb

Linking spatial variation in environmental factors to variation in demographic rates is essential for a mechanistic understanding of the dynamics of populations. However, we still know relatively little about such links, partly because feedbacks via intraspecific density make them difficult to observe in natural populations. We conducted a detailed field study and investigated simultaneous effects of environmental factors and the intraspecific density of individuals on the demography of the herb Lathyrus vernus. In regression models of vital rates we identified effects associated with spring shade on survival and growth, while density was negatively correlated with these vital rates. Density was also negatively correlated with average individual size in the study plots, which is consistent with self-thinning. In addition, average plant sizes were larger than predicted by density in plots that were less shaded by the tree canopy, indicating an environmentally determined carrying capacity. A size-structured integral projection model based on the vital rate regressions revealed that the identified effects of shade and density were strong enough to produce differences in stable population sizes similar to those observed in the field. The results illustrate how the local environment can determine dynamics of populations and that intraspecific density may have to be more carefully considered in studies of plant demography and population viability analyses of threatened species. We conclude that demographic approaches incorporating information about both density and key environmental factors are powerful tools for understanding the processes that interact to determine population dynamics and abundances.     

Spatial scaling in a benthic population model with density-dependent disturbance.

This work investigates approaches to simplifying individual-based models in which the rate of disturbance depends on local densities. To this purpose, an individual-based model for a benthic population is developed that is both spatial and stochastic. With this model, three possible ways of approximating the dynamics of mean numbers are examined: a mean-field approximation that ignores space completely, a second-order approximation that represents spatial variation in terms of variances and covariances, and a patch-based approximation that retains information about the age structure of the patch population. Results show that space is important and that a temporal model relying on mean disturbance rates provides a poor approximation to the dynamics of mean numbers. It is possible, however, to represent relevant spatial variation with second-order moments, particularly when recruitment rates are low and/or when disturbances are large and weak. Even better approximations are obtained by retaining patch age information.     

Local and global stability for population models

In general, local stability does not imply global stability. We show that this is true even if one only considers population models.We show that a population model is globally stable if and only if it has no cycle of period 2. We also derive easy to test sufficient conditions for global stability. We demonstrate that these sufficient conditions are useful by showing that for a number of population models from the literature, local and global stability coincide.We suggest that the models from the literature are in some sense simple, and that this simplicity causes local and global stability to coincide.     

Extinction risk of a density-dependent population estimated from a time series of population size

Environmental threats, such as habitat size reduction or environmental pollution, may not cause immediate extinction of a population but shorten the expected time to extinction. We develop a method to estimate the mean time to extinction for a density-dependent population with environmental fluctuation. We first derive a formula for a stochastic differential equation model (canonical model) of a population with logistic growth with environmental and demographic stochasticities. We then study an approximate maximum likelihood (AML) estimate of three parameters (intrinsic growth rate r, carrying capacity K, and environmental stochasticity sigma(2)(e)) from a time series of population size. The AML estimate of r has a significant bias, but by adopting the Monte Carlo method, we can remove the bias very effectively (bias-corrected estimate). We can also determine the confidence interval of the parameter based on the Monte Carlo method. If the length of the time series is moderately long (with 40-50 data points), parameter estimation with the Monte Carlo sampling bias correction has a relatively small variance. However, if the time series is short (less than or equal to 10 data points), the estimate has a large variance and is not reliable. If we know the intrinsic growth rate r, however, the estimate of K and sigma(2)(e)and the mean extinction time T are reliable even if only a short time series is available. We illustrate the method using data for a freshwater fish, Japanese crucian carp (Carassius auratus subsp.) in Lake Biwa, in which the growth rate and environmental noise of crucian carp are estimated using fishery records.     

Interspecific competition among macroparasites in a density-dependent host population

 We analyze the dynamics of a community of macroparasite species that share the same host. Our work extends an earlier framework for a host species that would grow exponentially in the absence of parasitism, to one where an uninfected host population is regulated by factors other than parasites. The model consists of one differential equation for each parasite species and a single density-dependent nonlinear equation for the host. We assume that each parasite species has a negative binomial distribution within the host and there is zero covariance between the species (exploitation competition). New threshold conditions on model parameters for the coexistence and competitive exclusion of parasite species are derived via invadibility and stability analysis of corresponding equilibria. The main finding is that the community of parasite species coexisting at the stable equilibrium is obtained by ranking the species according t! o th e minimum host density H ^* above which a parasite species can grow when rare: the lower H ^* , the higher the competitive ability. We also show that ranking according to the basic reproduction number Q ₀ does not in general coincide with ranking according to H ^* . The second result is that the type of interaction between host and parasites is crucial in determining the competitive success of a parasite species, because frequency-dependent transmission of free-living stages enhances the invading ability of a parasite species while density-dependent transmission makes a parasite very sensitive to other competing species. Finally, we show that density dependence in the host population entails a simplification of the portrait of possible outcomes with respect to previous studies, because all the cases resulting in the exponential growth of host and parasite populations are eliminated.. Received: 24 June 1996 / Revised version: 28 April 1998     

Demographic heterogeneity impacts density-dependent population dynamics

Among-individual variation in vital parameters such as birth and death rates that is unrelated to age, stage, sex, or environmental fluctuations is referred to as demographic heterogeneity. This kind of heterogeneity is prevalent in ecological populations, but is almost always left out of models. Demographic heterogeneity has been shown to affect demographic stochasticity in small populations and to increase growth rates for density-independent populations. The latter is due to ??cohort selection,?? where the most frail individuals die out first, lowering the cohort??s average mortality as it ages. The importance of cohort selection to population dynamics has only recently been recognized. We use a continuous-time model with density dependence, based on the logistic equation, to study the effects of demographic heterogeneity in mortality and reproduction. Reproductive heterogeneity is introduced in three ways: parent fertility, offspring viability, and parent?Coffspring correlation. We find that both the low-density growth rate and the equilibrium population size increase as the magnitude of mortality heterogeneity increases or as parent?Coffspring phenotypic correlation increases. Population dynamics are affected by complex interactions among the different types of heterogeneity, and trade-off scenarios are examined which can sometimes reverse the effect of increased heterogeneity. We show that there are a number of different homogeneous approximations to heterogeneous models, but all fail to capture important parts of the dynamics of the full model.     

Natural selection and density-dependent population growth

Natural selection was studied in the context of density-dependent population growth using a single locus, continuous time model for the rates of change of population size and allele frequency. The maximization principle of density-dependent selection was applied to a class of fitness expressions with explicit recruitment and mortality terms. Three general results were obtained: First, at low population densities, the genetic basis of selection is the difference between the mean recruitment rate and the mean mortality rate. Second, at densities much higher than the equilibrium population size, selection is expected to act to minimize the mean mortality rate. Third, as the population approaches its equilibrium density, selection is predicted to maximize the ratio of the mean recruitment rate to the mean mortality rate.     

Effects of density-dependent migrations on stability of a two-patch predator-prey model

We consider a predator-prey model in a two-patch environment and assume that migration between patches is faster than prey growth, predator mortality and predator-prey interactions. Prey (resp. predator) migration rates are considered to be predator (resp. prey) density-dependent. Prey leave a patch at a migration rate proportional to the local predator density. Predators leave a patch at a migration rate inversely proportional to local prey population density. Taking advantage of the two different time scales, we use aggregation methods to obtain a reduced (aggregated) model governing the total prey and predator densities. First, we show that for a large class of density-dependent migration rules for predators and prey there exists a unique and stable equilibrium for migration. Second, a numerical bifurcation analysis is presented. We show that bifurcation diagrams obtained from the complete and aggregated models are consistent with each other for reasonable values of the ratio between the two time scales, fast for migration and slow for local demography. Our results show that, under some particular conditions, the density dependence of migrations can generate a limit cycle. Also a co-dim two Bautin bifurcation point is observed in some range of migration parameters and this implies that bistability of an equilibrium and limit cycle is possible.     

Strong stability and density-dependent evolutionarily stable strategies

Stability conditions for equilibria of the evolution of population strategies in a single species are developed by comparing frequency and density dependent fitnesses of pairs of strategies. Stability of such equilibria is shown for general haploid frequency and density dynamics. It is also shown that this stability is stronger than that of multispecies population dynamical systems. A biological interpretation of the conditions is provided in terms of the fitness of invading subpopulations.     

The evolution of density-dependent dispersal in a noisy spatial population model

It is well-known that dispersal is advantageous in many different ecological situations, e.g. to survive local catastrophes where populations live in spatially and temporally heterogeneous habitats. However, the key question, what kind of dispersal strategy is optimal in a particular situation, has remained unanswered. We studied the evolution of density-dependent dispersal in a coupled map lattice model, where the population dynamics are perturbed by external environmental noise. We used a very flexible dispersal function to enable evolution to select from practically all possible types of monotonous density-dependent dispersal functions. We treated the parameters of the dispersal function as continuously changing phenotypic traits. The evolutionary stable dispersal strategies were investigated by numerical simulations. We pointed out that irrespective of the cost of dispersal and the strength of environmental noise, this strategy leads to a very weak dispersal below a threshold density, and dispersal rate increases in an accelerating manner above this threshold. Decreasing the cost of dispersal increases the skewness of the population density distribution, while increasing the environmental noise causes more pronounced bimodality in this distribution. In case of positive temporal autocorrelation of the environmental noise, there is no dispersal below the threshold, and only low dispersal below it, on the other hand with negative autocorrelation practically all individual disperses above the threshold. We found our results to be in good concordance with empirical observations.     

Some threshold and stability results for epidemic models with a density-dependent death rate.

Most classical models for infectious diseases assume that the birth and death rates of individuals and the meeting rates between susceptible and infected individuals do not depend on the total number of individuals in the population. While these assumptions are valid in some situations they are less valid in others. For example, for diseases in animal an insects populations competition for scarce resources might well mean that the death rate depends on the number of individuals. The present paper examines two epidemic models where the death rate is density dependent. For each model the possible equilibrium levels of disease incidence are determined and the stability of these equilibrium levels to small perturbations is discussed. The biological interpretation of these results is presented together with the results of some numerical simulations.     

Environmentally-controlled,density-dependent secondary dispersal in a local estuarine crab population

The mechanisms driving the pelagic secondary dispersal of aquatic organisms following initial settlement to benthic habitats are poorly characterized. We examined the physical environmental (wind, diel cycle, tidal phase) and biological (ontogenetic, density-dependent) factors that contribute to the secondary dispersal of a benthic marine invertebrate, the blue crab (Callinectes sapidus) in Pamlico Sound, NC, USA. Field studies conducted in relatively large (0.05 km²) seagrass beds determined that secondary dispersal is primarily undertaken by the earliest juvenile blue crab instar stages (J1 crabs). These crabs emigrated pelagically from seagrass settlement habitats using nighttime flood tides during average wind conditions (speed ~5 m s^–1). Moreover, the secondary dispersal of J1 crabs was density-dependent and regulated by intra-cohort (J1) crab density in seagrass. Our results suggest that dispersal occurs rapidly following settlement, and promotes blue crab metapopulation persistence by redistributing juveniles from high-density settlement habitats to areas characterized by low postlarval supply. Collectively, these data indicate that blue crab secondary dispersal is an active process under behavioral control and can alter initial distribution patterns established during settlement. This study highlights the necessity of considering secondary dispersal in ecological studies to improve our understanding of population dynamics of benthic organisms.     

Matrix population model with density-dependent recruitment for assessment of age-structured wildlife populations

A logistic density-dependent matrix model is developed in which the matrices contain only parameters and recruitment is a function of adult population density. The model was applied to simulate introductions of white-tailed deer into an area; the fitted model predicted a carrying capacity of 215 deer, which was close to the observed carrying capacity of 220 deer. The rate of population increase depends on the dominant eigenvalue of the Leslie matrix, and the age structure of the simulated population approaches a stable age distribution at the carrying capacity, which was similar to that generated by the Leslie matrix. The logistic equation has been applied to study many phenomena, and the matrix model can be applied to these same processes. For example, random variation can be added to life history parameters, and population abundances generated with random effects on fecundity show both the affect of annual variation in fecundity and a longer-term pattern resulting from the age structure.     

Interspecific population regulation and the stability of mutualism: fruit abortion and density-dependent mortality of pollinating seed-eating insects

Two questions central to the population ecology of mutualism include: (1) what mechanisms prevent the inherent positive feedback of mutualism from leading to unbounded population growth; and (2) what mechanisms prevent instability from arising due to overexploitation. Theory and empiricism suggest that preventing such instability requires density‐dependent processes. A recent theory proposes that if benefits and costs to a mutualist vary with the density of its partner, then instability can be prevented if the former species can control demographic rates and regulate (or limit) the population density of its partner. The ecological and evolutionary feasibility of this theory of interspecific population regulation has been demonstrated using quantitative models of mutualism between plants and pollinating seed‐consuming insects. In these models, resource‐limited fruit set and ensuing fruit abortion are mechanisms that can lead to density‐dependent recruitment and population regulation of the insects. Yet, there has been little interplay between these theoretical results and empirical research. A recent study empirically examined the density‐dependent effects of resource‐limited fruit set and fruit abortion in the Yucca/moth mutualism. An analysis of the study led to the conclusion that, even though fruit abortion can account for >95% of moth mortality, it is largely a density‐independent source of mortality that cannot regulate moth population density. Here, we re‐analyze those empirical data and conduct further theoretical analyses to examine the nature of fruit abortion on moth recruitment. We conclude that resource‐limited fruit set and fruit abortion can effectively regulate and limit moth populations, due to its density‐dependent feedback on moth recruitment. Nonetheless, in any given interaction, multiple sources of mortality may contribute to the regulation and limitation of populations, and hence the stability of mutualism, including, larval competition and mortality due to locule damage in the Yucca/moth mutualism.     

An evolutionary maximum principle for density-dependent population dynamics in a fluctuating environment

The evolution of population dynamics in a stochastic environment is analysed under a general form of density-dependence with genetic variation in r and K, the intrinsic rate of increase and carrying capacity in the average environment, and in σ_e², the environmental variance of population growth rate. The continuous-time model assumes a large population size and a stationary distribution of environments with no autocorrelation. For a given population density, N, and genotype frequency, p, the expected selection gradient is always towards an increased population growth rate, and the expected fitness of a genotype is its Malthusian fitness in the average environment minus the covariance of its growth rate with that of the population. Long-term evolution maximizes the expected value of the density-dependence function, averaged over the stationary distribution of N. In the θ-logistic model, where density dependence of population growth is a function of N^θ, long-term evolution maximizes E[N^θ]=[1−σ_e²/(2r)]K^θ. While σ_e² is always selected to decrease, r and K are always selected to increase, implying a genetic trade-off among them. By contrast, given the other parameters, θ has an intermediate optimum between 1.781 and 2 corresponding to the limits of high or low stochasticity.     

Sensitivity analysis of equilibrium in density-dependent matrix population models

We consider the effects of parameter perturbations on a density‐dependent population at equilibrium. Such perturbations change the dominant eigenvalue λ of the projection matrix evaluated at the equilibrium as well as the equilibrium itself. We show that, regardless of the functional form of density dependence, the sensitivity of λ is equal to the sensitivity of an effective equilibrium density , which is a weighted combination of the equilibrium stage densities. The weights measure the contributions of each stage to density dependence and their effects on demography. Thus, is in general more relevant than total density, which simply adds all stages regardless of their ecological properties. As log λ is the invasion exponent, our results show that successful invasion will increase , and that an evolutionary stable strategy will maximize . Our results imply that eigenvalue sensitivity analysis of a population projection matrix that is evaluated near equilibrium can give useful information about the sensitivity of the equilibrium population, even if no data on density dependence are available.     

Properties of some density-dependent integrodifference equation population models.

Integrodifference equations may be used as models of populations with discrete generations inhabiting continuous habitats. In this paper integrodifference equation models are formulated for annual plant populations without a seed bank; these models differ in the stage of the life cycle at which intraspecific competition acts to reduce vital rates. The models exhibit a sequence of period-doubling bifurcations leading to chaotic spatial and temporal behavior. The behavior of the models when modal dispersal distances are at the origin is compared with their behavior when these distances are displaced away from the origin. The models are capable of predicting stable, cyclical, and chaotic asymptotic behavior. They also predict that the variance of dispersal distances is an important indicator of the colonizing ability of a species.     

Host-parasite population dynamics under combined frequency- and density-dependent transmission

Many host‐parasite models assume that transmission increases linearly with host population density (‘density‐dependent transmission’), but various alternative transmission functions have been proposed in an effort to capture the complexity of real biological systems. The most common alternative (usually applied to sexually transmitted parasites) assumes instead that the rate at which hosts contact one another is independent of population density, leading to ‘frequency‐dependent’ transmission. This straight‐forward distinction generates fundamentally different dynamics (e.g. deterministic, parasite‐driven extinction with frequency‐ but not density‐dependence). Here, we consider the situation where transmission occurs through two different types of contact, one of which is density‐dependent (e.g. social contacts), the other density‐independent (e.g. sexual contacts). Drawing on a range of biological examples, we propose that this type of contact structure may be widespread in natural populations. When our model is characterized mainly by density‐dependent transmission, we find that allowing even small amounts of transmission to occur through density‐independent contacts leads to the possibility of deterministic, parasite‐driven extinction (and lowers the threshold for parasite persistence). Contrastingly, allowing some density‐dependent transmission to occur in a model characterized mainly by density‐independent contacts (i.e. by frequency‐dependent transmission) does not affect the extinction threshold, but does increase the likelihood of parasite persistence. The idea that directly transmitted parasites exploit different types of host contact is not new, but here we show that the impact on dynamics can be fundamental even in the simplest cases. For example, in systems where density‐dependent transmission is normally assumed de facto, we show that parasite‐driven extinction can occur if a small amount of transmission occurs through density‐independent contacts. Many empirical studies are still guided by the traditional density/frequency dichotomy, but our combined transmission function may provide a better model for systems in which both types of transmission occur.     

Optimal fishery policy for size-specific,density-dependent population models

Optimal harvest policy is derived for a size-specific population model based on the continuity equation. In this model both growth and recruitment rates can depend on either the number of individuals of specific sizes in the population or the level of food available. Necessary conditions for values of fishing pressure and size limit that maximize the present value of the resource are obtained and are interpreted in economic terms. The general solution obtained here reduces to solutions obtained previously for some special cases: the single age-class model, and the linear age-dependent model. Solutions involving constant fishery policy are sought for several different, specific versions of the general model. In each of these versions a constant policy solution is not optimal. This implies that for a general, realistic model the policy that maximizes present value is a time-varying or pulse fishing policy. The theoretical and practical implications of the results are discussed in the light of existing results.