The generality of management recommendations across populations of an invasive perennial herb

Demographic models are widely used to produce management recommendations for different species. For invasive plants, current management recommendations to control local population growth are often based on data from a limited number of populations per species, and the assumption of stable population structure (asymptotic dynamics). However, spatial variation in population dynamics and deviation from a stable structure may affect these recommendations, calling into question their generality across populations of an invasive species. Here, I focused on intraspecific variation in population dynamics and investigated management recommendations generated by demographic models across 37 populations of a short-lived, invasive perennial herb (Lupinus polyphyllus). Models that relied on the proportional perturbations of vital rates (asymptotic elasticities) indicated an essential role for plant survival in long-term population dynamics. The rank order of elasticities for different vital rates (survival, growth, retrogression, fecundity) varied little among the 37 study populations regardless of population status (increasing or declining asymptotically). Summed elasticities for fecundity increased, while summed elasticities for survival decreased with increasing long-term population growth rate. Transient dynamics differed from asymptotic dynamics, but were qualitatively similar among populations, that is, depending on the initial size structure, populations tended to either increase or decline in density more rapidly than predicted by asymptotic growth rate. These findings indicate that although populations are likely to exhibit transient dynamics, management recommendations based on asymptotic elasticities for vital rates might be to some extent generalised across established populations of a given short-lived invasive plant species.     

Prediction vs. reality: Can a PVA model predict population persistence 13 years later?

The challenge of conservation biology is to make models that predict population dynamics and have a high probability of accurately tracking population change (increase, decrease, constancy). In this study we tested whether the transition model is accurate enough to predict population persistence and size 13 years down and whether after 13 years populations had achieved a stable stage distribution. We modeled 6 small populations of an epiphytic orchid using a Lefkovitch type analysis to predict population growth pattern based on monthly surveys for approximately 1.5 years. In addition, sensitivity and elasticity analyses were used to identify life stages with high sensitivity or elasticity that have the largest influence on population growth rate. We re-censused the populations 13 years after the first study and compared the structure of the populations to predictions based on the earlier census data. Effective population growth rates were similar to those expected except for one where the population went extinct. The prediction slightly (but not significantly) overestimated the actual population growth rates of some populations. Elasticity analysis revealed that the adult stage is critical in the life cycle. The observed stage distributions of the populations were not stable at the beginning of the survey and neither were they after 13 years. We suggest that this might be caused by external perturbations that result in unequal mortality between life stages and stochastic recruitment events. The ability of the matrices to predict population size approximately eight generations in the future is encouraging and warrants the continued use of these approaches for PVA.     

When maladaptive gene flow does not increase selection

Populations receiving high maladaptive gene flow are expected to experience strong directional selection—because gene flow pulls mean phenotypes away from local fitness peaks. We tested this prediction by means of a large and replicated mark‐recapture study of threespine stickleback (Gasterosteus aculeatus) in two stream populations. One of the populations (outlet) experiences high gene flow from the lake population and its morphology is correspondingly poorly adapted. The other population (inlet) experiences very low gene flow from the lake population and its morphology is correspondingly well adapted. Contrary to the above prediction, selection was not stronger in the outlet than in the inlet, a result that forced us to consider potential reasons for why maladaptive gene flow might not increase selection. Of particular interest, we show by means of a simple population genetic model that maladaptive gene flow can—under reasonable conditions—decrease the strength of directional selection. This outcome occurs when immigrants decrease mean fitness in the resident population, which decreases the strength of selection against maladapted phenotypes. We argue that this previously unrecognized effect of gene flow deserves further attention in theoretical and empirical studies.     

Incorporating spatial variation in density enhances the stability of simple population dynamics models

Simple discrete time models of population growth admit a wide variety of dynamic behaviors, including population cycles and chaos. Yet studies of natural and laboratory populations typically reveal their dynamics to be relatively stable. Many explanations for the apparent rarity of unstable or chaotic behavior in real populations have been developed, including the possible stabilizing roles of migration, refugia, abrupt density-dependence, and genetic variation in sensitivity to density. We develop a theoretical framework for incorporating random spatial variation in density into simple models of population growth, and apply this approach to two commonly used models in ecology: the Ricker and Hassell maps. We show that the incorporation of spatial density variation into both these models has a strong stabilizing influence on their dynamic behavior, and leads to their exhibiting stable point equilibria or stable limit cycles over a relatively much larger range of parameter values. We suggest that one reason why chaotic population dynamics are less common than the simple models indicate is, these models typically neglect the potentially stabilizing role of spatial variation in density.     

The impact of mortality on predator population size and stability in systems with stage-structured prey

The relationships between a predator population's mortality rate and its population size and stability are investigated for several simple predator-prey models with stage-structured prey populations. Several alternative models are considered; these differ in their assumptions about the nature of density dependence in the prey's population growth; the nature of stage-transitions; and the stage-selectivity of the predator. Instability occurs at high, rather than low predator mortality rates in most models with highly stage-selective predation; this is the opposite of the effect of mortality on stability in models with homogeneous prey populations. Stage-selective predation also increases the range of parameters that lead to a stable equilibrium. The results suggest that it may be common for a stable predator population to increase in abundance as its own mortality rate increases in stable systems, provided that the predator has a saturating functional response. Sufficiently strong density dependence in the prey generally reverses this outcome, and results in a decrease in predator population size with increasing predator mortality rate. Stability is decreased when the juvenile stage has a fixed duration, but population increases with increasing mortality are still observed in large areas of stable parameter space. This raises two coupled questions which are as yet unanswered; (1) do such increases in population size with higher mortality actually occur in nature; and (2) if not, what prevents them from occurring? Stage-structured prey and stage-related predation can also reverse the 'paradox of enrichment', leading to stability rather than instability when prey growth is increased.     

Habitat choice in predator-prey systems: spatial instability due to interacting adaptive movements

The role of habitat choice behavior in the dynamics of predator-prey systems is explored using simple mathematical models. The models assume a three-species food chain in which each population is distributed across two or more habitats. The predator and prey adjust their locations dynamically to maximize individual per capita growth, while the prey's resource has a low rate of random movement. The two consumer species have Type II functional responses. For many parameter sets, the populations cycle, with predator and prey "chasing" each other back and forth between habitats. The cycles are driven by the aggregation of prey, which is advantageous because the predator's saturating functional response induces a short-term positive density dependence in prey fitness. The advantage of aggregation in a patch is only temporary because resources are depleted and predators move to or reproduce faster in the habitat with the largest number of prey, perpetuating the cycle. Such spatial cycling can stabilize population densities and qualitatively change the responses of population densities to environmental perturbations. These models show that the coupled processes of moving to habitats with higher fitness in predator and prey may often fail to produce ideal free distributions across habitats.     

Population growth regulated by intraspecific competition for energy or time: Some simple representations

An examination is made of some of the ways populations can grow in response to changes in their own density. Under two different assumptions on birth and death rates, models for single-species population growth that incorporate intraspecific competition by interference but not exploitation are of logistic form. Where an individual's net energy input from feeding is inversely proportional to population size, population growth follows a convex curve, whether interference is included or not. Data of Smith (1963) on Daphnia populations are fit well by this kind of curve. Combination of the two kinds of growth can produce S-shaped curves whose inflection is displaced from that value—half the carrying capacity—given by the logistic; an upward displacement is favored by a high ratio of metabolic and replacement costs to feeding input. Inflection points from real curves are much more often higher than expected from the logistic. Nonmonotonic growth curves can arise when there is instantaneous feedback between consumers and resource availability; certain of these equations are of logistic or convex form at equilibrium. The possible effect of r- and K-selection on the biological parameters, such as feeding efficiency, used to construct the monotonie equations is discussed, and the equations are extended to 2-species competition. Table III characterizes some simple single-species growth curves.     

Wealth as a source of density dependence in human population growth

In modern industrialized countries, human birth rates have been declining persistently for decades. In many cases they have now fallen below the replacement threshold. However, unlike in natural populations where population growth is constrained by limited resources, birth rates in modern industrialized countries are negatively correlated with resource availability. Here, declining birth rates in human populations are shown to be a manifestation of density‐dependent population growth brought on by socioeconomic development. This is demonstrated by combining empirical power law relations between population size, gross domestic product (GDP) per capita, and fertility in a simple theoretical model describing population dynamics in developed countries. For a closed population, the model exhibits growth to a globally stable equilibrium population size, for both national and city populations. A version of the model that is open with respect to immigration and the influence of foreign technology and capital exhibits a good fit to long‐term time series data on population size, GDP per capita, and birth rates for the United States, France and Japan.     

Diversity Waves in Collapse-Driven Population Dynamics

Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe reduction in size of the population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g. by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is characterized by cyclic ‘‘diversity waves’’ triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances have bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies.     

Nutritional folate deficiency in Chinese hamster ovary cells. I. Characterization of the pleiotropic response and its modulation by nucleic acid precursors

Nutritional folate deficiency in Chinese hamster ovary (CHO)-K1 cells inhibited population growth rate and caused growth arrest within 3 days of culture in Fol- medium [without folate, hypoxanthine (Hx), and thymidine (TdR)]. Coincident with impaired population growth was a transient delay in cell cycle progression through S phase and an increase in cell size. The growth-arrested population of predominantly G1 phase cells exhibited an increased adhesion to the culture substratum. There was a time-dependent loss of cell reproductive capacity. All these various perturbations of cellular phenotype induced by folate deficiency were prevented by the addition of folate or a combination of TdR and Hx to the Fol- medium. However, the singular presence of each nucleotide precursor differentially affected the pleiotropic response. The addition of Hx to Fol- medium exacerbated the aforementioned abnormalities, producing a threefold increase in mean cell volume, a 72 hr accumulation of cells in the S phase of the cell cycle, and a rapid demise in cell clonogenicity. Unexpectedly, we found reduced cell adhesion in these cultures. In contrast, folate-deficient cells supplemented with TdR exhibited a general amelioration of cell perturbations with respect to cell size, cell cycle distribution, and reproductive viability. Notably, such populations were not released from growth inhibition or subsequent growth arrest, and the cells became elongated and highly adherent with time. When cell populations from each of the three conditions of folate-deficient culture were released from growth arrest by addition of complete medium, the respective profiles of synchronous cell cycle progression were distinctive.     

Dynamics of natural rotifer populations

New tools for analyzing ecological time series have permitted the construction of rigorous models from relatively short series. We have applied these techniques to abundance data for nine natural rotifer populations to construct realistic models of their dynamics. Species included are Asplanchna girodi, Filinia pejleri, Keratella tropica, Monostyla bulla, Brachionus rotundiformis, and four other Brachionus species. The overall shapes of the time series were similar with an initial peak followed by oscillations of varying amplitude around a mean of lower population density. Auto correlation functions (ACF) for all populations were positive at small time lags and decayed rapidly to zero. This suggest that these are stationary, exponentially damped time series, fluctuating arround a constant mean with constant variance. The rapid decay of the ACFs indicates that the effect of a perturbation on these populations is quickly removed in one or two days. Phase portrait plots of log current population density vs log lagged density indicate that the time series are stable and non-chaotic. One type of model yielded the highest R² for four of the nine species and was designated the consensus model. The mean R² of this model for all nine species was 0.53 with a coefficient of variation of 38%. Lyapanov exponents were strongly negative, indicating that these populations rapidly return to equilibrium after an exogenous perturbation. Rotifer populations appear to be tracking very recent perturbations and their dynamics cannot be predicted from perturbations in the more distant past. We investigated the effects of increasing the level of stochasticity in the consensus model on the length of the growing season and resting egg production. Increasing stochastic variance increased the probability of extremely low population densities, shortening the growing season. In shorter growing seasons, fewer resting eggs were produced, other factors being equal. Counteracting this negative effect, was an increased probability of extremely high populations densities which increased mixis and resting egg production. Constructing models accurately depicting the dynamics of natural zooplankton populations should improve aquatic ecosystem models. This revised version was published online in July 2006 with corrections to the Cover Date.     

A simple model for predicting the effect of hygrothermal conditions on populations of house dust mite Dermatophagoides pteronyssinus (Acari: Pyroglyphidae)

A simple mite population index (MPI) model is presented which predicts the effect on house dust mite populations of any combination of temperature and relative humidity (RH). For each combination, the output is an index, or multiplication factor, such that 1.1 indicates 10% population growth and 0.9 indicates 10% population decline. To provide data for the model, laboratory experiments have been carried out using lab cultures of Dermatophagoides pteronyssinus. The population change was observed for mites held in steady-state conditions at different combinations of temperature and RH over 21 days. From the results, a best-fit equation has been derived which forms the basis of the MPI model. The results also enable a new term to be defined: the Population Equilibrium Humidity, PEH, the RH for a given temperature at which house dust mite populations neither grow nor decline. It is similar to Critical Equilibrium Humidity, the RH below which house dust mites are unable to maintain water balance, but relates to a population of mites (rather than a physiological phenomenon) and is more able to take account of the observed effects of extremes of temperature and RH. Compared with previous population models, the MPI model is potentially more accurate and comprehensive. It can be combined with other simple models (described in previous papers), such as BED, which simulates the average hygrothermal conditions in a bed, given room␣conditions, and Condensation Targeter II, which simulates room conditions given a range of easily obtainable inputs for climate, house type and occupant characteristics. In this way it is now possible, for any individual dwelling, to assess the most effective means of controlling mite populations by environmental means, such as by improving standards of ventilation and insulation, or by modifying the occupant behaviour that affects the hygrothermal environment within a dwelling. Although the MPI model requires further development and validation, it has already proved useful for understanding more clearly how the different hygrothermal conditions found in beds and bedrooms can affect mite populations. It has also demonstrated that there is considerable scope for controlling mites by environmental means in cold winter climates such as the UK.     

唐家河大熊猫种群生存力分析

唐家河大熊猫是一个包括3个亚种群的异质种群,借助于游涡模型（vortex 8.21),对唐家河大熊猫未来100a内的种群动态动物了模拟,并分析了不同因子对该种群命运的影响,结果表明,在不考虑近亲繁殖,灾害等因素的情况下,该种群100a内在总体上保持稳定,并略有增长,但种群基因杂合率下降,累积绝灭率增加,尤以薄衣沟亚种群为最,提高环境容纳量,补充外来个体等措施能在不同程度上有利于该种群的长期存活,而近亲繁殖,灾害等因素则大大加速了种群的灭绝步伐,另外,成功的迁移扩散有利于异质种群的稳定与发展,否则对数量稀少的大熊猫种群有害无益,最后提出了针对性的保护与管理建议。     

Dose-structured population dynamics

Applied population dynamics modeling is relied upon with increasing frequency to quantify how human activities affect human and non-human populations. Current techniques include variously the population's spatial transport, age, size, and physiology, but typically not the life-histories of exposure to other important things occurring in the ambient environment, such as chemicals, heat, or radiation. Consequently, the effects of such 'abiotic' aspects of an ecosystem on populations are only currently addressed through individual-based modeling approaches that despite broad utility are limited in their applicability to realistic ecosystems [V. Grimm, Ten years of individual-based modeling in ecology: what have we learned and what could we learn in the future? Ecol. Model. 115 (1999) 129-148][1]. We describe a new category of population dynamics modeling, wherein population dynamical states of the biotic phases are structured on dose, and apply this framework to demonstrate how chemical species or other ambient aspects can be included in population dynamics in three separate examples involving growth suppression in fish, inactivation of microorganisms with ultraviolet irradiation, and metabolic lag in population growth. Dose-structuring is based on a kinematic approach that is a simple generalization of age-structuring, views the ecosystem as a multi-component mixture with reacting biotic/abiotic components. The resulting model framework accommodates (a) different memories of exposure as in recovery from toxic ambient conditions, (b) differentiation between exogenous and endogenous sources of variation in population response, and (c) quantification of acute or sub-acute effects on populations arising from life-history exposures to abiotic species. Classical models do not easily address the very important fact that organisms differ and have different experiences over their life cycle. The dose structuring is one approach to incorporate some of these elements into the existing structures of the classical models, while retaining many of the features (and other limitations) of classical models.     

Models of growth with density regulation in more than one life stage

Discrete-time models of growth of populations with nonoverlapping generations and density regulation in two life stages are studied. It is assumed that there is no delay in the effects of density. Assigning exponential, linear, or hyperbolic functions to describe the dependence of preadult survival and fecundity on density, nine models are obtained. The dynamics of the model resulting from using the exponential function to describe the density dependence of both preadult survival and fecundity is analyzed: for large values of the intrinsic rate of increase there may exist up to three equilibrium population sizes, two stable. This indicates that a life history with two episodes of density regulation can give origin to alternative stable states. The models are fitted to recruitment data from growth experiments of Drosophila laboratory populations obtained with the Serial Transfer System Type 2 (Ayala et al., 1973. Theor. Pop. Biol. 4, 331-356) and collected by other authors. The results of the fittings suggest that this recruitment data can be adequately described with the models.     

Song characteristics and morphological traits in four populations of the grasshopper Chorthippus biguttulus L.

We investigated four populations of the grasshopper Chorthippus biguttulus with respect to differences in morphological traits and characteristics of their communication signals. A special focus was laid on possible correlations between morphological and song traits of males that could be used by females to infer quality cues of potential mates. We also tested whether females exhibit preferences for males of their own population. Specific song features (onset accentuation, offset, syllable period) of males—but not of females—differed between populations. We observed size differences both in males and females from different populations, but the size ranks of the two sexes were not always correlated. Environmental factors appear to have a strong influence on different size traits, compared to genetic origin. In all populations a specific song feature, the accentuation of syllable onsets, showed a similar correlation with a morphological trait, hind leg size, but its correlation with other size indicators sometimes differed in sign. Females did not prefer songs of males from their own population. The best predictor for song attractiveness was—unexpectedly—not the onset accentuation but the offset depth.     

Structural perturbations to population skeletons: transient dynamics, coexistence of attractors and the rarity of chaos

BACKGROUND: Simple models of insect populations with non-overlapping generations have been instrumental in understanding the mechanisms behind population cycles, including wild (chaotic) fluctuations. The presence of deterministic chaos in natural populations, however, has never been unequivocally accepted. Recently, it has been proposed that the application of chaos control theory can be useful in unravelling the complexity observed in real population data. This approach is based on structural perturbations to simple population models (population skeletons). The mechanism behind such perturbations to control chaotic dynamics thus far is model dependent and constant (in size and direction) through time. In addition, the outcome of such structurally perturbed models is [almost] always equilibrium type, which fails to commensurate with the patterns observed in population data. METHODOLOGY/PRINCIPAL FINDINGS: We present a proportional feedback mechanism that is independent of model formulation and capable of perturbing population skeletons in an evolutionary way, as opposed to requiring constant feedbacks. We observe the same repertoire of patterns, from equilibrium states to non-chaotic aperiodic oscillations to chaotic behaviour, across different population models, in agreement with observations in real population data. Model outputs also indicate the existence of multiple attractors in some parameter regimes and this coexistence is found to depend on initial population densities or the duration of transient dynamics. Our results suggest that such a feedback mechanism may enable a better understanding of the regulatory processes in natural populations.     

种群生存力分析研究进展和趋势

种群生存力分析（PVA）是正在迅速发展的新方法,已成为保护生物学研究的热点。它主要研究随机干扰对小种群绝灭的影响,其目的是制定最小可存活种群（MVP）,把绝灭减少到可接受的水平。随机干扰可分四类;统计随机性,环境随机性,自然灾害和遗传随机性。确定MVP的方法有三种：理论模型,模拟模型,模拟模型和岛屿生物地理学方法。理论模型主要研究理想或特定条件下随机因素对种群的影响;模拟模型是利用计算机模拟种群绝灭过程;岛屿生物地理学方法主要分析岛屿物种的分布和存活,证实分析模型和模拟模型。已有大量的文献研究统计随机性,环境随机性和自然灾害的行为特征,但遗传因素与种群生存力之间的关系还不清楚。建立包括四种随机性的综合性模型,广泛地检验PVA模型,系统地研制目标种的遗传和生态特性以及MVP的实际应用是PVA的发展趋势。     

种群统计随机性和环境随机性对种群绝灭的影响

影响种群绝灭的随机干扰可分为种群统计随机性、环境随机性和随机灾害三大类。在相对稳定的环境条件下和相对较短的时间内,以前两类随机干扰对种群绝灭的影响为生态学家关注的焦点。但是,由于自然种群动态及其影响因子的复杂特征,进一步深入研究随机干扰对种群绝灭的作用在理论上和实践上都必须发展新的技术手段。本文回顾了种群统计随机性与环境随机性的概念起源与发展,系统阐述了其分析方法。归纳了两类随机性在种群绝灭研究中的应用范围、作用方式和特点的异同和区别方法。各类随机作用与种群动态之间关系的理论研究与对种群绝灭机理的实践研究紧密相关。根据理论模型模拟和自然种群实际分析两方面的研究现状,作者提出了进一步深入研究随机作用与种群非线性动态方法的策略。指出了随机干扰影响种群绝灭过程的研究的方向：更多的研究将从单纯的定性分析随机干扰对种群动力学简单性质的作用,转向结合特定的种群非线性动态特征和各类随机力作用特点具体分析绝灭极端动态的成因,以期做出精确的预测。     

EVOLUTIONARY INFERENCES FROM THE ANALYSIS OF EXCHANGEABILITY

Evolutionary inferences are usually based on statistical models that compare mean genotypes or phenotypes (or their frequencies) among populations. An alternative is to use the full distribution of genotypes and phenotypes to infer the “exchangeability” of individuals among populations. We illustrate this approach by using discriminant functions on principal components to classify individuals among paired lake and stream populations of threespine stickleback in each of six independent watersheds. Classification based on neutral and nonneutral microsatellite markers was highest to the population of origin and next highest to populations in the same watershed. These patterns are consistent with the influence of historical contingency (separate colonization of each watershed) and subsequent gene flow (within but not between watersheds). In comparison to this low genetic exchangeability, ecological (diet) and morphological (trophic and armor traits) exchangeability was relatively high—particularly among populations from similar habitats. These patterns reflect the role of natural selection in driving parallel adaptive changes when independent populations colonize similar habitats. Importantly, however, substantial nonparallelism was also evident. Our results show that analyses based on exchangeability can confirm inferences based on statistical analyses of means or frequencies, while also refining insights into the drivers of—and constraints on—evolutionary diversification.