Stochastic Population Fluctuations Research Articles

Time-lagged effects of habitat fragmentation on terrestrial mammals in Madagascar.

Biodiversity is severely threatened by habitat destruction. As a consequence of habitat destruction, the remaining habitat becomes more fragmented. This results in time-lagged population extirpations in remaining fragments when these are too small to support populations in the long term. If these time-lagged effects are ignored, the long-term impacts of habitat loss and fragmentation will be underestimated. We quantified the magnitude of time-lagged effects of habitat fragmentation for 157 nonvolant terrestrial mammal species in Madagascar, one of the biodiversity hotspots with the highest rates of habitat loss and fragmentation. We refined species' geographic ranges based on habitat preferences and elevation limits and then estimated which habitat fragments were too small to support a population for at least 100 years given stochastic population fluctuations. We also evaluated whether time-lagged effects would change the threat status of species according to the International Union for the Conservation of Nature (IUCN) Red List assessment framework. We used allometric relationships to obtain the population parameters required to simulate the population dynamics of each species, and we quantified the consequences of uncertainty in these parameter estimates by repeating the analyses with a range of plausible parameter values. Based on the median outcomes, we found that for 34 species (22% of the 157 species) at least 10% of their current habitat contained unviable populations. Eight species (5%) had a higher threat status when accounting for time-lagged effects. Based on 0.95-quantile values, following a precautionary principle, for 108 species (69%) at least 10% of their habitat contained unviable populations, and 51 species (32%) had a higher threat status. Our results highlight the need to preserve continuous habitat and improve connectivity between habitat fragments. Moreover, our findings may help to identify species for which time-lagged effects are most severe and which may thus benefit the most from conservation actions.

Antibiotic-Induced Mutagenesis: Under the Microscope.

The development of antibiotic resistance poses an increasing threat to global health. Understanding how resistance develops in bacteria is critical for the advancement of new strategies to combat antibiotic resistance. In the 1980s, it was discovered that certain antibiotics induce elevated rates of mutation in bacteria. From this, an “increased evolvability” hypothesis was proposed: antibiotic-induced mutagenesis increases the genetic diversity of bacterial populations, thereby increasing the rate at which bacteria develop antibiotic resistance. However, antibiotic-induced mutagenesis is one of multiple competing factors that act on bacterial populations exposed to antibiotics. Its relative importance in shaping evolutionary outcomes, including the development of antibiotic resistance, is likely to depend strongly on the conditions. Presently, there is no quantitative model that describes the relative contribution of antibiotic-induced mutagenesis to bacterial evolution. A far more complete understanding could be reached if we had access to technology that enabled us to study antibiotic-induced mutagenesis at the molecular-, cellular-, and population-levels simultaneously. Direct observations would, in principle, allow us to directly link molecular-level events with outcomes in individual cells and cell populations. In this review, we highlight microscopy studies which have allowed various aspects of antibiotic-induced mutagenesis to be directly visualized in individual cells for the first time. These studies have revealed new links between error-prone DNA polymerases and recombinational DNA repair, evidence of spatial regulation occurring during the SOS response, and enabled real-time readouts of mismatch and mutation rates. Further, we summarize the recent discovery of stochastic population fluctuations in cultures exposed to sub-inhibitory concentrations of bactericidal antibiotics and discuss the implications of this finding for the study of antibiotic-induced mutagenesis. The studies featured here demonstrate the potential of microscopy to provide direct observation of phenomena relevant to evolution under antibiotic-induced mutagenesis.

A stepwise algorithm to detect significant time lags in ecological time series in terms of autocorrelation functions and ARMA model optimisation of pest population seasonal outbreaks

A central issue in population ecology is to determine the structure of negative feedback-density depend process which regulates population dynamics and seasonal fluctuations. In this work the incidence of population density dependences and seasonality was examined in fruit orchards of three closely related pest species (Adoxophyes orana, Anarsia lineatella and (Grapholita) Grapholitha molesta). Analysis included 13 moth population time series during 2003–2011. Additionally, considering that time lags and seasonality are fundamental characteristics of ecological organisation and pest management, the work aimed to introduce a step wise algorithm to detect significant population feedbacks, moth seasonality and population synchronisation of nearby locations. In the proposed procedure, each population-time series was first analysed on the basis of autocorrelation and partial autocorrelation. Moreover, assuming that each of the ecological variable, observed at successive time points, consist of a stochastic process, autoregressive moving average ARMA(p,q) models and seasonal autoregressive moving average models SARMA(p,q)x(P,Q) S were fitted on data. The Akaike information criteria was further used by the stepwise algorithm for parameter optimization and model improvement. Model construction is accompanied by a presentation of the fitting results and a discussion of the heuristic benchmarks used to assess the forecasting performance of the models. Life cycles of populations belonging to same species appeared to synchronise by terms of their autocorrelation functions. Delayed density dependence and order was in most cases of lag:1 and 2, while lag >3 was not found more frequently as expected by chance. In A. orana and A. lineatella moth species lag = 1 delayed density dependence was significantly more frequent and in particular in nearby locations. However, the structure of the fitted models varied with respect to species and observation region. In some cases, seasonal models were considered to be more accurate in simulating moth population dynamics. Finally, to provide means in forecasting moth emergence and abundance, utile in pest management, the models were trained using 2003–2009 data sets and their forecasting performance were validated for each case using data sets of 2010–2011. In most cases, the constructed stochastic linear autoregressive models simulated the population outbreaks very well. Describing and forecasting stochastic population fluctuations is a basic tenet of theoretical and applied ecology, while detecting the relative roles of exogenous and endogenous mechanisms can partly describe the phenomenological behavior of pest population time series data and improve pest management.

Prey Carrying Capacity Modulates the Effect of Predation on Prey Diversity.

Understanding the role of predation in regulating prey diversity is a major goal in ecology, with profound consequences for community dynamics, ecosystem structure, and conservation practice. Deterministic differential equation models predict that some predation regimes, such as prey-switching predation, should promote prey coexistence and increase prey diversity. However, such models do not capture stochastic population fluctuations that are ubiquitous in empirical study sites and nature reserves. In this article, we examine the effects of prey-switching predation on the species richness of prey communities with demographic noise. We show that in finite, discrete prey populations, the ability of prey-switching predation to promote diversity depends on the carrying capacity of the prey community and the richness of the source pool for prey. Identical predation regimes may have opposite effects on prey diversity depending on the size and productivity of the habitat or the metacommunity richness. Statistical properties of the fluctuations of prey populations determine the effect of stabilizing mechanisms on species richness. We discuss the implications of this result for empirical studies of predation in small study areas and for the management of small nature reserves.

Environmental fluctuations lead to predictability in Sin Nombre hantavirus outbreaks

Predicting outbreaks of zoonotic infections in reservoir hosts that live in highly fluctuating environments, such as Sin Nombre virus (SNV) in deer mice, is particularly challenging because host populations vary widely in response to environmental conditions and the relationship between field infection rates and abundance often appears to contradict conventional theory. Using a stage‐structured host‐pathogen model parameterized and cross‐validated from a unique 15‐year data set, we show how stochastic population fluctuations can lead to predictable dynamics of SNV in deer mice. Significant variation in host abundance and the basic reproductive number of the virus results in intermittent crossing of the critical host population density necessary for SNV endemicity and frequent local extinctions. When environmental conditions favor growth of the host population above the threshold, host–pathogen interactions lead to delayed density dependence in reservoir prevalence. The resultant ecological delay may provide a neglected opportunity for outbreak prediction in zoonoses.

AVOIDING EXTINCTION BY MIGRATION: THE CASE OF THE HEAD LOUSE

The possibility of spreading by migration, colonizing new spatial domains suitable for development and reproduction, can substantially relieve a biological population from the risk of extinction. By means of a realistic computational model based on empirical data, we study this phenomenon for the human head louse, Pediculus humanus capitis. In particular, we show that a lice colony infesting a single isolated host is prone to extinction by stochastic population fluctuations within an interval of several months, while migration over a relatively small group of hosts in contact with each other is enough to insure the prevalence of the infestation for indefinitely long periods. We characterize the interplay of the size of the host group with the host-to-host contagion probability, which controls a transition between extinction of the lice population and a situation where the infestation is endemic.

A machine learning approach to investigate the reasons behind species extinction

Species extinction is one of the most important phenomena in conservation biology. Many factors are involved in the disappearance of species, including stochastic population fluctuations, habitat change, resource depletion, and inbreeding. Due to the complexity of the interactions between these various factors and the lengthy time period required to make empirical observations, studying the phenomenon of species extinction can prove to be very difficult in nature. On the other hand, an investigation of the various features involved in species extinction using individual-based simulation modeling and machine learning techniques can be accomplished in a reasonably short period of time. Thus, the aim of this paper is to investigate multiple factors involved in species extinction using computer simulation modeling. We apply several machine learning techniques to the data generated by EcoSim, a predator–prey ecosystem simulation, in order to select the most prominent features involved in species extinction, along with extracting rules that outline conditions that have the potential to be used for predicting extinction. In particular, we used five feature selection methods resulting in the selection of 25 features followed by a reduction of these to 14 features using correlation analysis. Each of the remaining features was placed in one of three broad categories, viz., genetic, environmental, or demographic. The experimental results suggest that factors such as population fluctuation, reproductive age, and genetic distance are important in the occurrence of species extinction in EcoSim, similar to what is observed in nature. We argue that the study of the behavior of species through Individual-Based Modeling has the potential to give rise to new insights into the central factors involved in extinction for real ecosystems. This approach has the potential to help with the detection of early signals of species extinction that could in turn lead to conservation policies to help prevent extinction.

Monitoring spatiotemporal variation in abundance and dispersal by a pheromone-kairomone system in the threatened saproxylic beetles Osmoderma eremita and Elater ferrugineus

Pheromone monitoring could provide unique spatial and temporal information about rare and threatened insect species for conservation purposes. Pheromone traps may be especially valuable in detecting fluctuations and declines in vulnerable species, if trap catch can be related to population density. We exploited the pheromone-kairomone system of the hermit beetle Osmoderma eremita and its predator, the red click beetle Elater ferrugineus, to monitor variation in their flight activity during 7 years (2001–2002, 2005–2009). Spatial and temporal flight activity of O. eremita and E. ferrugineus were highly correlated over individual trap replicates and trap days. Yearly flight activities of both species were correlated within two core sites included during all years of the study, and positively affected by temperature both within and between years. Flight activity could not be directly translated to variation in abundance in either species, however. Dispersal rate was likely the main factor explaining flight activity in O. eremita. Normalizing the flight activity of E. ferrugineus against that of O. eremita did not eliminate most of the variability, however, suggesting that flight activity of E. ferrugineus was governed both by dispersal rate and by population density. Higher fluctuations in population density of E. ferrugineus likely render it more vulnerable to local extinction, which may explain the greater rarity of this species. We suggest that preserving large assemblies of suitable hollow trees would be absolutely essential for buffering against stochastic population fluctuations and securing the long-term persistence of E. ferrugineus.

Effects of demographic stochasticity on biological community assembly on evolutionary time scales

We study the effects of demographic stochasticity on the long-term dynamics of biological coevolution models of community assembly. The noise is induced in order to check the validity of deterministic population dynamics. While mutualistic communities show little dependence on the stochastic population fluctuations, predator-prey models show strong dependence on the stochasticity, indicating the relevance of the finiteness of the populations. For a predator-prey model, the noise causes drastic decreases in diversity and total population size. The communities that emerge under influence of the noise consist of species strongly coupled with each other and have stronger linear stability around the fixed-point populations than the corresponding noiseless model. The dynamics on evolutionary time scales for the predator-prey model are also altered by the noise. Approximate 1/f fluctuations are observed with noise, while 1/f2 fluctuations are found for the model without demographic noise.

Effects of stochastic population fluctuations in two models of biological macroevolution

Two mathematical models of macroevolution are studied. These models have population dynamics at the species level, and mutations and extinction of species are also included. The population dynamics are updated by difference equations with stochastic noise terms that characterize population fluctuations. The effects of the stochastic population fluctuations on diversity and total population sizes on evolutionary time scales are studied. In one model, species can make either predator–prey, mutualistic, or competitive interactions, while the other model allows only predator–prey interactions. When the noise in the population dynamics is strong enough, both models show intermittent behavior and their power spectral densities show approximate 1/f fluctuations. In the noiseless limit, the two models have different power spectral densities. For the predator–prey model, 1/f2 fluctuations appears, indicating random-walk like behavior, while the other model still shows 1/f noise. These results indicate that stochastic population fluctuations may significantly affect long-time evolutionary dynamics.

Food supplementation: A tool to increase reproductive output? A case study in the threatened Florida Scrub-Jay

The federally threatened Florida Scrub-Jay ( Aphelocoma coerulescens) has suffered dramatic losses in recent years primarily because of overdevelopment of its unique scrub habitat. Ensuring the survival of this species will require not only measures to reduce habitat loss, but also efforts to increase the numbers of birds in small scattered populations to a point at which they are resilient to extinction from stochastic population fluctuations. Here we evaluate the utility of providing supplementary food during the pre-breeding season as a means of increasing the reproductive output of Florida Scrub-Jays. Data collected from 2000 to 2007 at Archbold Biological Station in south-central Florida indicate a marked effect of supplemental feeding on reproductive output. This increased output appeared to result primarily from larger clutch sizes produced by supplemented female breeders as a result of their advanced laying. Supplementation also increased offspring survival probabilities and the early laying permitted more renesting attempts. Furthermore, annual variation in several reproductive measures was dampened in supplemented birds, suggesting that supplemental feeding may reduce environmental or stochastic effects on reproductive output. Although a number of potential problems may be associated with supplemental feeding (e.g., predator entrainment and increased opportunity for disease transmission), it can serve as a valuable tool for management agencies that wish to rapidly increase local carrying capacity. In addition, food supplementation might benefit translocation efforts both by increasing the number of potential translocation candidates from a donor population and then by supplementing the newly established population to promote rapid growth.

Long‐term dynamics of the hemiparasiteRhinanthus angustifoliusand its relationship with vegetation structure

AbstractQuestions:1. How are the long‐term dynamics of the root hemiparasiteRhinanthus angustifoliusrelated to vegetation structure, grassland management and climate? 2. DoesR. angustifoliushave a long‐term impact on standing crop and community composition?Location: A formerly fertilized grassland, part of a larger brook valley system in the nature reserve ‘Drentsche Aa’, near Groningen, The Netherlands.Methods: Vegetation development has been monitored since 1973 in 54 permanent plots in nine management regimes without fertilizer application.Results: 1. The hemiparasite established when standing crop was less than 600 g.m−2and performed best under annual haymaking using machinery. Since its appearance, the population fluctuated stochastically, with two peaks. Coinciding collapses in six adjacent grasslands and comparison with an integrated climatic index suggest that the population collapses are induced by spring drought. 2. We did not find a relationship between total standing crop andR. angustifoliuscover. Cover of grasses was negatively related to the abundance of the hemiparasite in the same and the previous year. Forb cover tended to increase with the parasite.Conclusions:R. angustifoliusshows stochastic population fluctuations, mainly determined by spring drought, to which this species is probably highly vulnerable because of its parasitic and annual life style without a persistent seed bank. The hemiparasite also shows long‐term relationships with grass cover (negative) and forb cover (positive), but it seems to have no lasting impact on standing crop.

Modeling Extinction in Periodic Environments: Everglades Water Levels and Snail Kite Population Viability

The effects of periodic environmental fluctuations on population viability are examined based on the use of environmental states. The approach is applied to the Florida population of the Snail Kite, an endangered wetland hawk that feeds almost solely on one species of snail. A preliminary assessment based on stochastic population fluctuations indicated that populations became viable when initial size surpassed 300 individuals. However, changes in population size between consecutive years, nesting success, and the length of the breeding season were all highly and positively related to water level and rainfall characteristics, which are highly periodic. Low water conditions cause Snail Kites to disperse and result in low recruitment, increased adult mortality, and population declines. The effects of cyclic drought were explored using stage‐based life tables for three different water conditions or environmental states (drought, lag years following drought, and high years). Population sizes predicted by the model were closely associated with actual kite population counts. Deterministic projections indicated that kite populations would increase when intervals between droughts exceeded 3.3 yr, but stochastic simulations found that populations did not become viable unless intervals exceeded 4.3 yr. The model was sensitive to estimates of survivorship. The use of the environmental state approach is compared to standard techniques for population viability analyses (PVA), and the implications of the model for Everglades water management are discussed.

The Effects of Toeclipping on Sprint Performance of the Lizard Cnemidophorus sexlineatus

The ability to recapture marked animals over a long time is important because it allows researchers to examine many aspects of population and community biology. Demography and life history traits can be quantified through many years and across generations. This in turn allows researchers to separate stochastic population fluctuations from fluctuations from environmental or anthropogenic perturbations. Non-invasive marking techniques also are important for the study of species that are subject to either ethical or legal restrictions on killing animals

The Bioeconomics of Resource Rehabilitation: A Commercial-Sport Analysis for a Great Lakes Fishery

We construct a fishery model which simulates: (a) stochastic population fluctuations and (b) harvest shifts between commercial and sport user groups. This model then assesses, for both commercial and sport harvesters, the bioeconomic impact of an ongoing rehabilitation plan for the yellow perch fishery of Green Bay, Lake Michigan. Overall economic gains from this plan are positive, with sport anglers reaping sizeable benefits, while commercial harvesters lose moderately. Using probing exercises which approximate economic optimization, the efficient allocation of harvest between sport and commercial user groups is also explored. Uncertainties about sport effort levels greatly influence this optimal allocation.