ECPSES: Estimating Critical Population Size in the Presence of Environmental Stochasticity

1987 ◽  
Vol 41 (4) ◽  
pp. 334
Author(s):  
Charles J. Mode ◽  
Marc D. Cain ◽  
Marc E. Jacobson
2016 ◽  
Vol 283 (1829) ◽  
pp. 20152411 ◽  
Author(s):  
Bernt-Erik Sæther ◽  
Marcel E. Visser ◽  
Vidar Grøtan ◽  
Steinar Engen

Understanding the variation in selection pressure on key life-history traits is crucial in our rapidly changing world. Density is rarely considered as a selective agent. To study its importance, we partition phenotypic selection in fluctuating environments into components representing the population growth rate at low densities and the strength of density dependence, using a new stochastic modelling framework. We analysed the number of eggs laid per season in a small song-bird, the great tit, and found balancing selection favouring large clutch sizes at small population densities and smaller clutches in years with large populations. A significant interaction between clutch size and population size in the regression for the Malthusian fitness reveals that those females producing large clutch sizes at small population sizes also are those that show the strongest reduction in fitness when population size is increased. This provides empirical support for ongoing r - and K -selection in this population, favouring phenotypes with large growth rates r at small population sizes and phenotypes with high competitive skills when populations are close to the carrying capacity K . This selection causes long-term fluctuations around a stable mean clutch size caused by variation in population size, implying that r - and K -selection is an important mechanism influencing phenotypic evolution in fluctuating environments. This provides a general link between ecological dynamics and evolutionary processes, operating through a joint influence of density dependence and environmental stochasticity on fluctuations in population size.


Author(s):  
Bernt-Erik Sæther ◽  
Steinar Engen ◽  
Marlène Gamelon ◽  
Vidar Grøtan

Climate variation strongly influences fluctuations in size of avian populations. In this chapter, we show that it is difficult to predict how the abundance of birds will respond to climate change. A major reason for this is that most available time series of fluctuations in population size are in a statistical sense short, thus often resulting in large uncertainties in parameter estimates. We therefore argue that reliable population predictions must be based on models that capture how climate change will affect vital rates as well as including other processes (e.g. density-dependences) known to affect the population dynamics of the species in question. Our survey of examples of such forecast studies show that reliable predictions necessarily contain a high level of uncertainty. A major reason for this is that avian population dynamics are strongly influenced by environmental stochasticity, which is for most species, irrespective of their life history, the most important driver of fluctuations in population size. Credible population predictions must therefore assess the effects of such uncertainties as well as biases in population estimates.


2017 ◽  
Vol 114 (44) ◽  
pp. 11582-11590 ◽  
Author(s):  
Russell Lande ◽  
Steinar Engen ◽  
Bernt-Erik Sæther

We analyze the stochastic demography and evolution of a density-dependent age- (or stage-) structured population in a fluctuating environment. A positive linear combination of age classes (e.g., weighted by body mass) is assumed to act as the single variable of population size, N, exerting density dependence on age-specific vital rates through an increasing function of population size. The environment fluctuates in a stationary distribution with no autocorrelation. We show by analysis and simulation of age structure, under assumptions often met by vertebrate populations, that the stochastic dynamics of population size can be accurately approximated by a univariate model governed by three key demographic parameters: the intrinsic rate of increase and carrying capacity in the average environment, r0 and K, and the environmental variance in population growth rate, σe2. Allowing these parameters to be genetically variable and to evolve, but assuming that a fourth parameter, θ, measuring the nonlinearity of density dependence, remains constant, the expected evolution maximizes E[Nθ]=[1−σe2/(2r0)]Kθ. This shows that the magnitude of environmental stochasticity governs the classical trade-off between selection for higher r0 versus higher K. However, selection also acts to decrease σe2, so the simple life-history trade-off between r- and K-selection may be obscured by additional trade-offs between them and σe2. Under the classical logistic model of population growth with linear density dependence (θ=1), life-history evolution in a fluctuating environment tends to maximize the average population size.


2021 ◽  
Vol 9 ◽  
Author(s):  
Nao Takashina

Terrestrial and marine protected areas are essential tools in mitigating anthropogenic impacts and promoting population persistence and resource sustainability. Adequately implemented protected areas (PAs) aim to promote conservation by increasing population size and reducing its variability. To resolve how these effects depend on PA features, I develop and analyze new models of stochastic processes that encompass the fluctuations generated by demographic or environmental stochasticity in PAs management. The stochastic model is built upon individual processes. In the model, density-independent mortality, migration between PAs and non-PAs, organism preference for PAs, and size characterize the features of the PA. The effect of PAs size is also examined. The long-term conservation effects are quantified using the coefficient of variation (CV) of population size in PAs, where a lower CV indicates higher robustness in stochastic variations. The results from this study demonstrate that sufficiently reduced density-independent mortality in PAs and high site preference for PAs and immigration rate into PAs are likely to decrease the CV. However, different types of stochasticity induce rather different consequences: under demographic stochasticity, the CV is always reduced because PAs increase the population size therein, but an increased population size by PAs does not always decrease the CV under environmental stochasticity. The deterministic dynamics of the model are investigated, facilitating effective management decisions.


2021 ◽  
Author(s):  
Nao Takashina

AbstractTerrestrial and marine protected areas have been essential tools to mitigate anthropogenic impacts and promote population persistence and resource sustainability. Adequately implemented protected areas promote a long-term conservation benefit. Stochasticity affects its long-term performance, and necessary to understand the general influence. Here, we investigate a long-term conservation benefit via stochastic models that encompass demographic or environmental stochasticity. We quantify a long-term conservation benefit by the coefficient of variation (CV) of population size in protected areas, where a low CV indicates high robustness against stochasticity. We demonstrate that adequately implemented protected areas promote a long-term conservation benefit under stochasticity and decrease otherwise. However, demographic and environmental stochasticity induce rather different consequences, although the former is suppressed with the population size. Multiple parameters in our framework determine the quality of protected areas, and systematic investigations for various scenarios facilitate an effective management decision.


Author(s):  
Juan Antonio Alonso ◽  
Luis Sanz

In this work we deal with a multiregional model in discrete time for an age-structured population which lives in an environment that changes randomly with time and is distributed in different spatial patches. In addition, and as is often the case in applications, we assume that migration is fast with respect to demography. Using approximate aggregation techniques we make use of the existence of different time scales in the model and reduce the dimension of the system obtaining a stochastic Leslie model in which the variables are the total population in each age class. Literature shows that, under reasonable conditions, the distribution of population size in matrix models with environmental stochasticity is asymptotically lognormal, and is characterized by two parameters, stochastic growth rate (s.g.r.) and scaled logarithmic variance (s.l.v.), that, in most practical cases, cannot be computed exactly. We show that the s.g.r. and the s.l.v. of the original multiregional model can be approximated by those corresponding to the reduced stochastic Leslie model, therefore simplifying its analysis. Moreover, we illustrate the usefulness of the reduction procedure by presenting some practical cases in which, although the explicit computation of the s.g.r. and the s.l.v. of the original multiregional model is not feasible, we can calculate its analogues for the reduced model.


2010 ◽  
Vol 277 (1699) ◽  
pp. 3391-3400 ◽  
Author(s):  
Thomas E. Reed ◽  
Robin S. Waples ◽  
Daniel E. Schindler ◽  
Jeffrey J. Hard ◽  
Michael T. Kinnison

Phenotypic plasticity plays a key role in modulating how environmental variation influences population dynamics, but we have only rudimentary understanding of how plasticity interacts with the magnitude and predictability of environmental variation to affect population dynamics and persistence. We developed a stochastic individual-based model, in which phenotypes could respond to a temporally fluctuating environmental cue and fitness depended on the match between the phenotype and a randomly fluctuating trait optimum, to assess the absolute fitness and population dynamic consequences of plasticity under different levels of environmental stochasticity and cue reliability. When cue and optimum were tightly correlated, plasticity buffered absolute fitness from environmental variability, and population size remained high and relatively invariant. In contrast, when this correlation weakened and environmental variability was high, strong plasticity reduced population size, and populations with excessively strong plasticity had substantially greater extinction probability. Given that environments might become more variable and unpredictable in the future owing to anthropogenic influences, reaction norms that evolved under historic selective regimes could imperil populations in novel or changing environmental contexts. We suggest that demographic models (e.g. population viability analyses) would benefit from a more explicit consideration of how phenotypic plasticity influences population responses to environmental change.


2017 ◽  
Author(s):  
José M. Ponciano

AbstractUsing a nonparametric Bayesian approach Palacios and Minin [1] dramatically improved the accuracy, precision of Bayesian inference of population size trajectories from gene genealogies. These authors proposed an extension of a Gaussian Process (GP) nonparametric inferential method for the intensity function of non-homogeneous Poisson processes. They found that not only the statistical properties of the estimators were improved with their method, but also, that key aspects of the demographic histories were recovered. The authors’ work represents the first Bayesian nonparametric solution to this inferential problem because they specify a convenient prior belief without a particular functional form on the population trajectory. Their approach works so well and provides such a profound understanding of the biological process, that the question arises as to how truly “biology-free” their approach really is. Using well-known concepts of stochastic population dynamics, here I demonstrate that in fact, Palacios and Minin’s GP model can be cast as a parametric population growth model with density dependence and environmental stochasticity. Making this link between population genetics and stochastic population dynamics modeling provides novel insights into eliciting biologically meaningful priors for the trajectory of the effective population size. The results presented here also bring novel understanding of GP as models for the evolution of a trait. Thus, the ecological principles foundation of Palacios and Minin [1]’s prior adds to the conceptual and scientific value of these authors’inferential approach. I conclude this note by listing a series of insights brought about by this connection with Ecology.


Author(s):  
Delbert E. Philpott ◽  
W. Sapp ◽  
C. Williams ◽  
T. Fast ◽  
J. Stevenson ◽  
...  

Space Lab 3 (SL-3) was flown on Shuttle Challenger providing an opportunity to measure the effect of spaceflight on rat testes. Cannon developed the idea that organisms react to unfavorable conditions with highly integrated metabolic activities. Selye summarized the manifestations of physiological response to nonspecific stress and he pointed out that atrophy of the gonads always occurred. Many papers have been published showing the effects of social interaction, crowding, peck order and confinement. Flickinger showed delayed testicular development in subordinate roosters influenced by group numbers, social rank and social status. Christian reported increasing population size in mice resulted in adrenal hypertrophy, inhibition of reproductive maturation and loss of reproductive function in adults. Sex organ weights also declined. Two male dogs were flown on Cosmos 110 for 22 days. Fedorova reported an increase of 30 to 70% atypical spermatozoa consisting of tail curling and/or the absence of a tail.


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