Climatically driven synchrony of gerbil populations allows large-scale plague outbreaks

In central Asia, the great gerbil (Rhombomys opimus) is the main host for the bacterium Yersinia pestis, the cause of bubonic plague. In order to prevent plague outbreaks, monitoring of the great gerbil has been carried out in Kazakhstan since the late 1940s. We use the resulting data to demonstrate that climate forcing synchronizes the dynamics of gerbils over large geographical areas. As it is known that gerbil densities need to exceed a threshold level for plague to persist, synchrony in gerbil abundance across large geographical areas is likely to be a condition for plague outbreaks at similar large scales. Here, we substantiate this proposition through autoregressive modelling involving the normalized differentiated vegetation index as a forcing covariate. Based upon predicted climate changes, our study suggests that during the next century, plague epizootics may become more frequent in central Asia.     

Local factors associated with on‐host flea distributions on prairie dog colonies

Outbreaks of plague, a flea‐vectored bacterial disease, occur periodically in prairie dog populations in the western United States. In order to understand the conditions that are conducive to plague outbreaks and potentially predict spatial and temporal variations in risk, it is important to understand the factors associated with flea abundance and distribution that may lead to plague outbreaks. We collected and identified 20,041 fleas from 6,542 individual prairie dogs of four different species over a 4‐year period along a latitudinal gradient from Texas to Montana. We assessed local climate and other factors associated with flea prevalence and abundance, as well as the incidence of plague outbreaks. Oropsylla hirsuta, a prairie dog specialist flea, and Pulex simulans, a generalist flea species, were the most common fleas found on our pairs. High elevation pairs in Wyoming and Utah had distinct flea communities compared with the rest of the study pairs. The incidence of prairie dogs with Yersinia pestis detections in fleas was low (n = 64 prairie dogs with positive fleas out of 5,024 samples from 4,218 individual prairie dogs). The results of our regression models indicate that many factors are associated with the presence of fleas. In general, flea abundance (number of fleas on hosts) is higher during plague outbreaks, lower when prairie dogs are more abundant, and reaches peak levels when climate and weather variables are at intermediate levels. Changing climate conditions will likely affect aspects of both flea and host communities, including population densities and species composition, which may lead to changes in plague dynamics. Our results support the hypothesis that local conditions, including host, vector, and environmental factors, influence the likelihood of plague outbreaks, and that predicting changes to plague dynamics under climate change scenarios will have to consider both host and vector responses to local factors.     

Modeling the epidemiological history of plague in Central Asia: Palaeoclimatic forcing on a disease system over the past millennium

Background

Human cases of plague (Yersinia pestis) infection originate, ultimately, in the bacterium's wildlife host populations. The epidemiological dynamics of the wildlife reservoir therefore determine the abundance, distribution and evolution of the pathogen, which in turn shape the frequency, distribution and virulence of human cases. Earlier studies have shown clear evidence of climatic forcing on contemporary plague abundance in rodents and humans.

Results

We find that high-resolution palaeoclimatic indices correlate with plague prevalence and population density in a major plague host species, the great gerbil (Rhombomys opimus), over 1949-1995. Climate-driven models trained on these data predict independent data on human plague cases in early 20th-century Kazakhstan from 1904-1948, suggesting a consistent impact of climate on large-scale wildlife reservoir dynamics influencing human epidemics. Extending the models further back in time, we also find correspondence between their predictions and qualitative records of plague epidemics over the past 1500 years.

Conclusions

Central Asian climate fluctuations appear to have had significant influences on regional human plague frequency in the first part of the 20th century, and probably over the past 1500 years. This first attempt at ecoepidemiological reconstruction of historical disease activity may shed some light on how long-term plague epidemiology interacts with human activity. As plague activity in Central Asia seems to have followed climate fluctuations over the past centuries, we may expect global warming to have an impact upon future plague epidemiology, probably sustaining or increasing plague activity in the region, at least in the rodent reservoirs, in the coming decades. See commentary: http://www.biomedcentral.com/1741-7007/8/108     

Dynamics of Yersinia pestis and Its Antibody Response in Great Gerbils (Rhombomys opimus) by Subcutaneous Infection

Background

Rhombomys opimus (great gerbil) is a reservoir of Yersinia pestis in the natural plague foci of Central Asia. Great gerbils are highly resistant to Y. pestis infection. The coevolution of great gerbils and Y. pestis is believed to play an important role in the plague epidemics in Central Asia plague foci. However, the dynamics of Y. pestis infection and the corresponding antibody response in great gerbils have not been evaluated. In this report, animal experiments were employed to investigate the bacterial load in both the liver and spleen of infected great gerbils. The dynamics of the antibody response to the F1 capsule antigen of Y. pestis was also determined.

Methodology

Captured great gerbils that tested negative for both anti-F1 antibodies and bacterial isolation were infected subcutaneously with different doses (10⁵ to 10¹¹ CFU) of a Y. pestis strain isolated from a live great gerbil during routine plague surveillance in the Junggar Basin, Xinjiang, China. The clinical manifestations, changes in body weight, anal temperature, and gross anatomy of the infected animals were observed. The blood cell count, bacterial load, and anti-F1 antibody titers were determined at different time points after infection using a blood analyzer, plate counts, and an indirect hemagglutination assay, respectively.

Conclusions/Significance

The dynamics of bacterial load and the anti-F1 antibody concentration in great gerbils are highly variable among individuals. The Y. pestis infection in great gerbils could persist as long as 15 days. They act as an appropriate reservoir for plague in the Junggar Basin, which is part of the natural plague foci in Central Asia. The dynamics of the Y. pestis susceptibility of great gerbil will improve the understanding of its variable resistance, which would facilitate the development of more effective countermeasures for controlling plague epidemics in this focus.     

Can hyperparasitoids cause large‐scale outbreaks of insect herbivores?

Synchronous population fluctuations occur in many species and have large economic impacts, but remain poorly understood. Dispersal, climate and natural enemies have been hypothesized to cause synchronous population fluctuations across large areas. For example, insect herbivores cause extensive forest defoliation and have many natural enemies, such as parasitoids, that may cause landscape‐scale changes in density. Between outbreaks, parasitoid‐caused mortality of hosts/herbivores is high, but it drops substantially during outbreak episodes. Because of their essential role in regulating herbivore populations, we need to include parasitoids in spatial modelling approaches to more effectively manage insect defoliation. However, classic host‐parasitoid population models predict parasitoid density, and parasitoid density is difficult to relate to host‐level observations of parasitoid‐caused mortality. We constructed a novel model to study how parasitoids affect insect outbreaks at the landscape scale. The model represents metacommunity dynamics, in which herbivore regulation, colonisation and extinction are driven by interactions with the forest, primary parasitoids and hyperparasitoids. The model suggests that parasitoid spatial dynamics can produce landscape‐scale outbreaks. Our results propose the testable prediction that hyperparasitoid prevalence should increase just before the onset of an outbreak because of hyperparasitoid overexploitation. If verified empirically, hyperparasitoid distribution could provide a biotic indicator that an outbreak will occur.     

Spatial analysis of gypsy moth populations in Sardinia using geostatistical and climate models

• 1 Spatial fluctuations of the Sardinian population of the gypsy moth Lymantria dispar (L.) (Lepidoptera: Lymantriidae) were characterized using geostatistical and climate models. Data on gypsy moth egg mass abundance recorded at 282 permanent monitoring sites from 1980 to 2004 were incorporated in a geographic information system with the vegetational, geomorphological and pedological features of the sites.
• 2 Statistical analyses revealed that the relative outbreak frequency was related to the predominant host tree, slope and elevation of the monitoring sites, whereas there was no correlation between outbreak frequency and exposure and soil type.
• 3 By using bioclimatic modelling, probability maps of gypsy moth outbreaks were generated. The model identified a probability surface with climatic conditions favourable to gypsy moth outbreaks and thus potentially subject to defoliation. The maps included 92 sites where outbreaks never occurred, suggesting that the Sardinian climate may not be a determinant factor for gypsy moth outbreaks.
• 4 The geostatistical method cokriging with outbreak frequency as a covariate was found to be the most suitable technique to estimate gypsy moth egg mass abundance. Semivariograms showed spatial correlation of egg mass abundance within the range 18.5–53 km. The results obtained were used to create regional gypsy moth distribution maps by cokriging, which demonstrated the outbreak foci and different infestation levels at each monitoring area. These results can help to delimit the treatment areas and develop rational gypsy moth management programmes.

     

Plague epizootic cycles in Central Asia

Infection thresholds, widely used in disease epidemiology, may operate on host abundance and, if present, on vector abundance. For wildlife populations, host and vector abundances often vary greatly across years and consequently the threshold may be crossed regularly, both up- and downward. Moreover, vector and host abundances may be interdependent, which may affect the infection dynamics. Theory predicts that if the relevant abundance, or combination of abundances, is above the threshold, then the infection is able to spread; if not, it is bound to fade out. In practice, though, the observed level of infection may depend more on past than on current abundances. Here, we study the temporal dynamics of plague (Yersinia pestis infection), its vector (flea) and its host (great gerbil) in the PreBalkhash region in Kazakhstan. We describe how host and vector abundances interact over time and how this interaction drives the dynamics of the system around the infection threshold, consequently affecting the proportion of plague-infected sectors. We also explore the importance of the interplay between biological and detectability delays in generating the observed dynamics.     

Resonance effects and outbreaks in ecological time series

Organismal response to environmental variability is an important aspect of ecological processes. We propose new mechanisms whereby environmental variability can cause cyclic population outbreaks due to the nonlinearity of the organismal response. We consider stage-structured populations that respond to variable environments with variable diapause or dormancy, and in which cyclic changes of the environment induce a resonance-like boost in the population size. If there is also a stochastic component of variation in the environment, the population outbreaks are magnified by the phenomenon of "stochastic resonance". The results show that large population fluctuations may not be due to extrinsic or intrinsic factors alone, but to a nonlinear interaction between the external environment and internal population processes. Indeed, in the presence of such nonlinearities even very small environmental fluctuations can cause massive fluctuations in population size. Our theoretical results may help to explain periodic population cycles and outbreak dynamics found in many infectious diseases and pest species. We also discuss the evolution of the response parameters that regulate diapause or dormancy and promote the outbreak dynamics in variable environments.     

炔雌醚对内蒙古农牧交错带长爪沙鼠(Meriones unguiculatus)家群大小和巢域行为的影响

为检验施用炔雌醚对农牧交错带长爪沙鼠家群大小与巢域行为的影响,于2006年5月至9月对内蒙古锡林郭勒盟锡林浩特市农牧交错区域分布的长爪沙鼠家群使用炔雌醚进行种群不育控制实验。分设投药区和对照区两个组别,分别于5月、7月与9月份采用1/4样圆面积有效洞口计数法,随机选取24个长爪沙鼠家群,调查对照区域和投药区内沙鼠的家群洞口数量以及家群大小。另在对照区和投药区,随机测定了30个沙鼠的家群活动范围,对比使用炔雌醚前后长爪沙鼠巢域平均半径和活动面积的影响。结果为:对照区家群平均洞口数58个,投药区仅23个,在炔雌醚投药区长爪沙鼠家群受炔雌醚影响,洞口数仅为23个,表明其对长爪沙鼠家群大小控制效果显著。投药区内长爪沙鼠家群密度在投药后连续下降,最大下降幅度较对照区家群密度低70%,表明炔雌醚对长爪沙鼠的家群密度影响较大,可显著降低长爪沙鼠家群密度(P<0.05)。炔雌醚对长爪沙鼠家群平均半径和活动面积的研究结果显示,施用炔雌醚后家群巢域半径与活动面积均显著缩小(P<0.05),与对照区巢域平均面积相比缩小15%、平均活动半径缩小30%。通过以上结果可得出:单独施用炔雌醚对控制野外长爪沙鼠家群以及降低长爪沙鼠巢域、活动面积效果显著。炔雌醚可有效降低农牧交错带长爪沙鼠种群数量和有效活动范围,这对于农牧交错带的鼠害防控,同时降低鼠源性疾病,包括鼠疫的传播都有一定的意义。     

Temporal autocorrelation in host density increases establishment success of parasitoids in an experimental system

Environmental variation is classically expected to affect negatively population growth and to increase extinction risk, and it has been identified as a major determinant of establishment failures in the field. Yet, recent theoretical investigations have shown that the structure of environmental variation and more precisely the presence of positive temporal autocorrelation might alter this prediction. This is particularly likely to affect the establishment dynamics of biological control agents in the field, as host–parasitoid interactions are expected to induce temporal autocorrelation in host abundance. In the case where parasitoid populations display overcompensatory dynamics, the presence of such positive temporal autocorrelation should increase their establishment success in a variable environment. We tested this prediction in laboratory microcosms by introducing parasitoids to hosts whose abundances were manipulated to simulate uncorrelated or positively autocorrelated variations in carrying capacity. We found that environmental variability decreased population size and increased parasitoid population variance, which is classically expected to extinction risk. However, although exposed to significant environmental variation, we found that parasitoid populations experiencing positive temporal autocorrelation in host abundance were more likely to persist than populations exposed to uncorrelated variation. These results confirm that environmental variation is a key determinant of extinction dynamics that can have counterintuitive effects depending on its autocorrelation structure.     

Large-scale forest fragmentation increases the duration of tent caterpillar outbreak

I examined historical data (1950–1984) on the duration of outbreaks of the forest tent caterpillar (Malacosoma disstria) in northern Ontario, Canada. Outbreak duration was compared to host tree species dominance and forest structure over large areas of boreal forest partially cleared for agriculture. Abundance of the principal host tree species Populus tremuloides had no consistent effect on duration of outbreak within forest districts, and was negatively correlated with duration of outbreaks among the eight forest districts examined. The amount of forest edge per km² was the best, and most consistent, predictor of the duration of tent caterpillar outbreaks both within individual forest districts and among forest districts. Because forest tent caterpillar populations are driven largely by the impact of parasitoids and pathogens, results here suggest that large-scale increase in forest fragmentation affects the interaction between these natural enemies and forest tent caterpillar. Increased clearing and fragmentation of boreal forests, by agriculture and forestry, may be exacerbating outbreaks of this forest defoliator.     

Climate-Based Models for Pulsed Resources Improve Predictability of Consumer Population Dynamics: Outbreaks of House Mice in Forest Ecosystems

Accurate predictions of the timing and magnitude of consumer responses to episodic seeding events (masts) are important for understanding ecosystem dynamics and for managing outbreaks of invasive species generated by masts. While models relating consumer populations to resource fluctuations have been developed successfully for a range of natural and modified ecosystems, a critical gap that needs addressing is better prediction of resource pulses. A recent model used change in summer temperature from one year to the next (ΔT) for predicting masts for forest and grassland plants in New Zealand. We extend this climate-based method in the framework of a model for consumer–resource dynamics to predict invasive house mouse (Mus musculus) outbreaks in forest ecosystems. Compared with previous mast models based on absolute temperature, the ΔT method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ΔT on the likelihood of an outbreak occurring. The improved climate-based method for predicting resource pulses and consumer responses provides a straightforward rule of thumb for determining, with one year’s advance warning, whether management intervention might be required in invaded ecosystems. The approach could be applied to consumer–resource systems worldwide where climatic variables are used to model the size and duration of resource pulses, and may have particular relevance for ecosystems where global change scenarios predict increased variability in climatic events.     

Mechanical-Statistical Modeling in Ecology: From Outbreak Detections to Pest Dynamics

Knowledge about large-scale and long-term dynamics of (natural) populations is required to assess the efficiency of control strategies, the potential for long-term persistence, and the adaptability to global changes such as habitat fragmentation and global warming. For most natural populations, such as pest populations, large-scale and long-term surveys cannot be carried out at a high resolution. For instance, for population dynamics characterized by irregular abundance explosions, i.e., outbreaks, it is common to report detected outbreaks rather than measuring the population density at every location and time event. Here, we propose a mechanical-statistical model for analyzing such outbreak occurrence data and making inference about population dynamics. This spatio-temporal model contains the main mechanisms of the dynamics and describes the observation process. This construction enables us to account for the discrepancy between the phenomenon scale and the sampling scale. We propose the Bayesian method to estimate model parameters, pest densities and hidden factors, i.e., variables involved in the dynamics but not observed. The model was specified and used to learn about the dynamics of the European pine sawfly (Neodiprion sertifer Geoffr., an insect causing major defoliation of pines in northern Europe) based on Finnish sawfly data covering the years 1961–1990. In this application, a dynamical Beverton–Holt model including a hidden regime variable was incorporated into the model to deal with large variations in the population densities. Our results gave support to the idea that pine sawfly dynamics should be studied as metapopulations with alternative equilibria. The results confirmed the importance of extreme minimum winter temperatures for the occurrence of European pine sawfly outbreaks. The strong positive connection between the ratio of lake area over total area and outbreaks was quantified for the first time.     

Prairie dog presence affects occurrence patterns of disease vectors on small mammals

Wildlife disease is recognized as a burgeoning threat to imperiled species and aspects of host and vector community ecology have been shown to have significant effects on disease dynamics. The black‐tailed prairie dog is a species of conservation concern that is highly susceptible to plague, a flea‐transmitted disease. Prairie dogs (Cynomys) alter the grassland communities in which they exist and have been shown to affect populations of small rodents, which are purported disease reservoirs. To explore potential ecological effects of black‐tailed prairie dogs on plague dynamics, we quantified flea occurrence patterns on small mammals in the presence and absence of prairie dogs at 8 study areas across their geographic range. Small mammals sampled from prairie dog colonies showed significantly higher flea prevalence, flea abundance, and relative flea species richness than those sampled from off‐colony sites. Successful plague transmission likely is dependent on high prevalence and abundance of fleas that can serve as competent vectors. Prairie dogs may therefore facilitate the maintenance of plague by increasing flea occurrence on potential plague reservoir species. Our data demonstrate the previously unreported ecological influence of prairie dogs on vector species assemblages, which could influence disease dynamics.     

Testing the Generality of a Trophic-cascade Model for Plague

Climate may affect the dynamics of infectious diseases by shifting pathogen, vector, or host species abundance, population dynamics, or community interactions. Black-tailed prairie dogs (Cynomys ludovicianus) are highly susceptible to plague, yet little is known about factors that influence the dynamics of plague epizootics in prairie dogs. We investigated temporal patterns of plague occurrence in black-tailed prairie dogs to assess the generality of links between climate and plague occurrence found in previous analyses of human plague cases. We examined long-term data on climate and plague occurrence in prairie dog colonies within two study areas. Multiple regression analyses revealed that plague occurrence in prairie dogs was not associated with climatic variables in our Colorado study area. In contrast, plague occurrence was strongly associated with climatic variables in our Montana study area. The models with most support included a positive association with precipitation in April–July of the previous year, in addition to a positive association with the number of “warm” days and a negative association with the number of “hot” days in the same year as reported plague events. We conclude that the timing and magnitude of precipitation and temperature may affect plague occurrence in some geographic areas. The best climatic predictors of plague occurrence in prairie dogs within our Montana study area are quite similar to the best climatic predictors of human plague cases in the southwestern United States. This correspondence across regions and species suggests support for a (temperature-modulated) trophic-cascade model for plague, including climatic effects on rodent abundance, flea abundance, and pathogen transmission, at least in regions that experience strong climatic signals.     

Spatially patterned guild structure in larval parasitoids of cyclically outbreaking winter moth populations

1. Wide temporal fluctuations in host abundance are a potential source of instability and stochasticity in the spatiotemporal population dynamics of associated parasitoid species. Within parasitoid guilds (i.e. parasitoids with similar modes of host utilisation), a conceivable outcome is guild organisation according to a lottery model, in which guild members attain local dominance by colonising previously emptied habitats during increasing host density, before other guild members. In the spatial dimension, an expected manifestation of such dynamics is variable guild structure even across homogeneous habitats. 2. We examined the extent of large‐scale spatial patterning of guild characteristics in larval parasitoid wasps associated with cyclically outbreaking populations of the geometrid moth Operophtera brumata in northern Fennoscandia. The study was performed at the onset of the crash‐phase of the geometrid's outbreak cycle, along a 70‐km transect in costal northern Norway, characterised by largely homogeneous environmental conditions, except for a small climatic gradient. 3. There was a distinct large‐scale spatial turnover in dominance among the major parasitoid groups (i.e. guild structure) in O. brumata along the transect, whereas the total prevalence rate of the guild and its diversity showed no consistent variation. Guild structure was unrelated to host density. 4. Although group‐specific responses to a slight spatial climatic gradient cannot be rejected as a causal mechanism, we conclude that our results are consistent with the expectation from large‐scale stochastic extinction‐recolonisation dynamics among functionally equivalent parasitoids relying on a host with strongly cyclic population fluctuations.     

Anatomy of an outbreak: the biology and population dynamics of a Cardiaspina psyllid species in an endangered woodland ecosystem

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长爪沙鼠种群繁殖的季节性特征

长爪沙鼠是分布于我国北方典型和荒漠草原及农牧交错区的优势鼠种之一。2000 年10 月至2004 年10 月通过标志重捕法研究了栖息于内蒙古农牧交错区草地生境的种群动态。对其不同季节出生群性成熟特征和种群性成熟比率、繁殖个体比例、个体月补充率等繁殖参数的季节特征研究显示:冬季和春季出生的个体性成熟较夏季出生的个体快,尤雌鼠表现突出,其3 个季节出生群的性成熟时间分别为4. 6 ± 0.2、4. 4 ± 0.8 和7.7 ± 0.4月龄。种群性成熟比率、繁殖个体比例和个体补充率月间差异显著,季节消长明显,即春季最高,秋季(9 ～10月间)最低。结果还显示,种群性成熟比率与气温和降水负相关。长爪沙鼠喜栖于植被稀疏、低矮的干燥沙质土壤环境。从初春到夏末,随降水和气温增加其栖息生境的植被由低矮稀疏变得高而稠密,土壤湿度和粘性亦随之提高,地面种子库因发芽贮量减少,适宜生境的减少可能加剧了社群竞争,抑制了种群的繁殖表现。长爪沙鼠种群繁殖的季节变化反映了其生活史对策中适应高纬度气候和食物的季节波动的重要特征。     

Long-term demographic surveys reveal a consistent relationship between average occupancy and abundance within local populations of a butterfly metapopulation

Species distribution models are the tool of choice for large-scale population monitoring, environmental association studies and predictions of range shifts under future environmental conditions. Available data and familiarity of the tools rather than the underlying population dynamics often dictate the choice of specific method – especially for the case of presence–absence data. Yet, for predictive purposes, the relationship between occupancy and abundance embodied in the models should reflect the actual population dynamics of the modelled species. To understand the relationship of occupancy and abundance in a heterogeneous landscape at the scale of local populations, we built a spatio-temporal regression model of populations of the Glanville fritillary butterfly Melitaea cinxia in a Baltic Sea archipelago. Our data comprised nineteen years of habitat surveys and snapshot data of land use in the region. We used variance partitioning to quantify relative contributions of land use, habitat quality and metapopulation covariates. The model revealed a consistent and positive, but noisy relationship between average occupancy and mean abundance in local populations. Patterns of abundance were highly variable across years, with large uncorrelated random variation and strong local population stochasticity. In contrast, the spatio-temporal random effect, habitat quality, population connectivity and patch size explained variation in occupancy, vindicating metapopulation theory as the basis for modelling occupancy patterns in fragmented landscapes. Previous abundance was an important predictor in the occupancy model, which points to a spillover of abundance into occupancy dynamics. While occupancy models can successfully model large-scale population structure and average occupancy, extinction probability estimates for local populations derived from occupancy-only models are overconfident, as extinction risk is dependent on actual, not average, abundance.     

Genotype and sex-based host variation in behaviour and susceptibility drives population disease dynamics

Host heterogeneity in pathogen transmission is widespread and presents a major hurdle to predicting and minimizing disease outbreaks. Using Drosophila melanogaster infected with Drosophila C virus as a model system, we integrated experimental measurements of social aggregation, virus shedding, and disease-induced mortality from different genetic lines and sexes into a disease modelling framework. The experimentally measured host heterogeneity produced substantial differences in simulated disease outbreaks, providing evidence for genetic and sex-specific effects on disease dynamics at a population level. While this was true for homogeneous populations of single sex/genetic line, the genetic background or sex of the index case did not alter outbreak dynamics in simulated, heterogeneous populations. Finally, to explore the relative effects of social aggregation, viral shedding and mortality, we compared simulations where we allowed these traits to vary, as measured experimentally, to simulations where we constrained variation in these traits to the population mean. In this context, variation in infectiousness, followed by social aggregation, was the most influential component of transmission. Overall, we show that host heterogeneity in three host traits dramatically affects population-level transmission, but the relative impact of this variation depends on both the susceptible population diversity and the distribution of population-level variation.