Testing for MacArthur-Wilson Equilibrium with the Arthropods of the Miniature Spartina Archipelago at Oyster Bay, Florida

SYNOPSIS. The unique features of the MacArthur-Wilson modelof equilibrium biogeography are the immigration and extinctioncurves. In the model, the immigration rate for each island isnegatively correlated with species number, and island extinctionrate is positively correlated with species number. Direct tests of the sign and statistical significance of immigrationand extinction curves were done, with data on arthropods oftiny Spartina alterniflora islets, in north Florida. Rey (1981)defaunated six islets in the spring, then censused the recolonizationweekly, for one year. Two control islets and a mainland plotwere also censused. Distinct tendencies in favor of MacArthur-Wilsoncorrelations were present for both immigration and extinction.But sufficient extraneous variation occurs in immigration andextinction rates to make correspondence to MacArthur-Wilsoncurves statistically non-significant, unless probabilities arecombined among islands. Thus, mathematical deductions from theMacArthur-Wilson model, which treat the curves as deterministiclines with no variance, are less appropriate than approachesthat incorporate stochastic variation. The study of community patterns, by models such as the MacArthur-Wilsonmodel, are not a substitute for careful autecological studies.Mechanisms of colonization and co-existence are only dimly hintedat by gross community patterns.     

The Probability of Extinction of Infectious Salmon Anemia Virus in One and Two Patches

Single-type and multitype branching processes have been used to study the dynamics of a variety of stochastic birth–death type phenomena in biology and physics. Their use in epidemiology goes back to Whittle’s study of a susceptible–infected–recovered (SIR) model in the 1950s. In the case of an SIR model, the presence of only one infectious class allows for the use of single-type branching processes. Multitype branching processes allow for multiple infectious classes and have latterly been used to study metapopulation models of disease. In this article, we develop a continuous time Markov chain (CTMC) model of infectious salmon anemia virus in two patches, two CTMC models in one patch and companion multitype branching process (MTBP) models. The CTMC models are related to deterministic models which inform the choice of parameters. The probability of extinction is computed for the CTMC via numerical methods and approximated by the MTBP in the supercritical regime. The stochastic models are treated as toy models, and the parameter choices are made to highlight regions of the parameter space where CTMC and MTBP agree or disagree, without regard to biological significance. Partial extinction events are defined and their relevance discussed. A case is made for calculating the probability of such events, noting that MTBPs are not suitable for making these calculations.     

Assessing the relative importance of neutral stochasticity in ecological communities

A central current debate in community ecology concerns the relative importance of deterministic versus stochastic processes underlying community structure. However, the concept of stochasticity presents several profound philosophical, theoretical and empirical challenges, which we address here. The philosophical argument that nothing in nature is truly stochastic can be met with the following operational concept of neutral stochasticity in community ecology: change in the composition of a community (i.e. community dynamics) is neutrally stochastic to the degree that individual demographic events – birth, death, immigration, emigration – which cause such changes occur at random with respect to species identities. Empirical methods for identifying the stochastic component of community dynamics or structure include null models and multivariate statistics on observational species‐by‐site data (with or without environmental or trait data), and experimental manipulations of ‘stochastic’ species colonization order or relative densities and frequencies of competing species. We identify the fundamental limitations of each method with respect to its ability to allow inferences about stochastic community processes. Critical future needs include greater precision in articulating the link between results and ecological inferences, a comprehensive theoretical assessment of the interpretation of statistical analyses of observational data, and experiments focusing on community size and on natural variation in species colonization order. Synthesis Community structure and dynamics have often been described as being underlain by ‘stochastic’ or ‘neutral’ processes, but there is great confusion as to what exactly this means. We attempt to provide conceptual clarity by specifying precisely what focal ecological variable (e.g. species distributions, community composition, demography) is considered to be stochastic with respect to what other variables (e.g. other species' distributions, traits, environment) when using different empirical methods. We clarify what inferences can be drawn by different observational and experimental approaches, and we suggest future avenues of research to better understand the role of neutral stochasticity in community ecology.     

No genetic variation detected within isolated relict populations of Saxifraga cernua in the Alps using RAPD markers

Genetic variation in seven relict populations of Saxifraga cernua from three regions of the Alps was investigated using RAPD (random amplified polymorphic DNA) markers. No variation, either within the populations or within the regions, could be demonstrated. Nevertheless, each alpine region was characterized by a unique RAPD phenotype. Absence of genetic variation in these relict populations is attributed to population bottlenecks and founder effects during or following the ice ages. Contrasting hypotheses about the history of these populations, either as survivors of the glacial period or as products of postglacial immigration, are discussed in the light of the data presented.     

A unifying theory for genetic epidemiological analysis of binary disease data

Background

Genetic selection for host resistance offers a desirable complement to chemical treatment to control infectious disease in livestock. Quantitative genetics disease data frequently originate from field studies and are often binary. However, current methods to analyse binary disease data fail to take infection dynamics into account. Moreover, genetic analyses tend to focus on host susceptibility, ignoring potential variation in infectiousness, i.e. the ability of a host to transmit the infection. This stands in contrast to epidemiological studies, which reveal that variation in infectiousness plays an important role in the progression and severity of epidemics. In this study, we aim at filling this gap by deriving an expression for the probability of becoming infected that incorporates infection dynamics and is an explicit function of both host susceptibility and infectiousness. We then validate this expression according to epidemiological theory and by simulating epidemiological scenarios, and explore implications of integrating this expression into genetic analyses.

Results

Our simulations show that the derived expression is valid for a range of stochastic genetic-epidemiological scenarios. In the particular case of variation in susceptibility only, the expression can be incorporated into conventional quantitative genetic analyses using a complementary log-log link function (rather than probit or logit). Similarly, if there is moderate variation in both susceptibility and infectiousness, it is possible to use a logarithmic link function, combined with an indirect genetic effects model. However, in the presence of highly infectious individuals, i.e. super-spreaders, the use of any model that is linear in susceptibility and infectiousness causes biased estimates. Thus, in order to identify super-spreaders, novel analytical methods using our derived expression are required.

Conclusions

We have derived a genetic-epidemiological function for quantitative genetic analyses of binary infectious disease data, which, unlike current approaches, takes infection dynamics into account and allows for variation in host susceptibility and infectiousness.     

Evaluating Subcriticality during the Ebola Epidemic in West Africa

The 2014–2015 Ebola outbreak is the largest and most widespread to date. In order to estimate ongoing transmission in the affected countries, we estimated the weekly average number of secondary cases caused by one individual infected with Ebola throughout the infectious period for each affected West African country using a stochastic hidden Markov model fitted to case data from the World Health Organization. If the average number of infections caused by one Ebola infection is less than 1.0, the epidemic is subcritical and cannot sustain itself. The epidemics in Liberia and Sierra Leone have approached subcriticality at some point during the epidemic; the epidemic in Guinea is ongoing with no evidence that it is subcritical. Response efforts to control the epidemic should continue in order to eliminate Ebola cases in West Africa.     

The importance of matrix quality in fragmented landscapes: Understanding ecosystem collapse through a combination of deterministic and stochastic forces

Increasing fragmentation of natural landscapes due to anthropogenic forces are changing the ecological structure of many systems. The corpus of literature has addressed the fact that there are many complex mechanisms that may lead to population and ecosystem collapse. Here, we propose an additional mechanism that combines the deterministic framework of complex oscillatory phenomena with the stochastic framework based on the spatial phenomena of island biogeography and metapopulation theory. Combining these two frameworks, which we believe exist in disturbed natural systems, we construct a situation in which collections of competitors are controlled by specialist natural enemies. Species are isolated in fragmented habitats separated by a matrix of decreasing ecological quality, which will determine immigration potential. In this system, species are exposed to stochastic extinction of spatial immigration potential and deterministic extinction of standard oscillatory frameworks. Through the combination of these extinction events, we see that many natural systems may become increasingly unstable and subject to unexpected consequences with changes to the matrix environment. The combined effect of these two extinctions pathways highlights the need to maintain high immigration rates in order to offset possible ecosystem collapse in fragmented systems. The results highlight the importance of landscape conservation efforts, especially towards maintaining matrix environments with greater ecological integrity.     

2003年稻纵卷叶螟重大迁入过程的大气动力机制分析

为了探明稻纵卷叶螟灾变性迁入的大气动力学机制,本研究在ArcGIS中对2003年我国稻纵卷叶螟的时空分布规律进行了简要的地学分析。在此基础上,选取了有典型意义的重大迁入过程2个,从PCVSATTM接收系统中调取覆盖各迁飞过程的实测气象数据和T213数值预报产品,输入MM5中尺度数值预报模式对迁飞和降落期间的大气动力场进行了数值模拟和客观分析。结果表明：（1）用850 hPa和925 hPa高度风向来分别描述稻纵卷叶螟北迁和南迁主迁飞层种群迁移的方向是比较合适的。北迁时,从源地到迁入地之间有比较一致的偏南气流;南迁时,从源地到迁入地之间则有相对均一的偏北气流。水平风场上的气旋式曲率区有利于害虫的起飞迁出,反气旋式曲率区则有利于其迁入降落。（2）垂直气流场中下沉气流的推动作用是稻纵卷叶螟迁入和降落的最直接大气动力机制,当稻纵卷叶螟迁入某一即将危害的稻区时,其降落前36～12 h以内的850 hPa等压面上常表现为相对强而宽广的下沉气流区。（3）在稻纵卷叶螟迁入与为害前36～12 h内的高空850 hPa和925 hPa散度场上,降虫区上空对应着比较一致的高值正散度区,表明有较强的下沉气流存在,这对降虫十分有利。（4）850 hPa、925 hPa等压面上的水平流场、垂直气流场和散度场的特征分布对预测稻纵卷叶螟的迁入和降落具有很好的指示意义。     

Evaluation of the Kullback-Leibler Discrepancy for Model Selection in Open Population Capture-Recapture Models

The objective of this paper is to introduce the logical basis of AIC-based model selection to persons analyzing capture-recapture data and to explore the key theorettical aspect of AIC based model selection, for open-model capture-recapture, needed for AIC to perform well in this context. Almost all previous work on AIC assumes a Gaussian model; that assumption does not hold for capture-recapture models. Assuming the Cormack-Jolly-Seber model as the true model, we used numerical methods to evaluate the expectation of the log-likelihood relative to Akaike's target predictive log-likelihood. The use of this particular target criterion was motivated by the idea of using the Kullback-Leibler discrepancy for model selection, for which Akaike found the bias of the sample log-likelihood was asymptotically K, where K = the number of estimated (by MLE) parameters. In some sense, then, AIC is a bias-adjusted log-likelihood. For a set of 81 plausible cases, we evaluated this bias almost exactly. The ratio of this bias to the first order theory (bias of K) and to second order theory (K + a sample size adjustment) is essentially 1 for these 81 cases. Thus, AIC should be a suitable basis for model selection in open model capture-recapture.     

Estimating the initial relative infection rate for a stochastic epidemic model

Consider the problem of making inference about the initial relative infection rate of a stochastic epidemic model. A relatively complete analysis of infectious disease data is possible when it is assumed that the latent and infectious periods are non-random. Here two related martingale-based techniques are used to derive estimates and associated standard errors for the initial relative infection rate. The first technique requires complete information on the epidemic, the second only the total number of people who were infected and the population size. Explicit expressions for the estimates are obtained. The estimates of the parameter and its associated standard error are easily computed and compare well with results of other methods in an application to smallpox data. Asymptotic efficiency differences between the two martingale techniques are considered.     

Local population dynamics and the impact of scale and isolation: a study on different little owl populations

The understanding of how variation of demographic rates translates into variation of population growth is a central aim in population ecology. Besides stochastic and deterministic factors, the spatial extent and the isolation of a local population may have an impact on the contribution of the different demographic components. Using long-term demographic data we performed retrospective population analyses of four little owl ( Athene noctua ) populations with differential spatial extent and degree of isolation to assess the contribution of demographic rates to the variation of the growth rate (λ) of each local population and to the difference of λ among populations. In all populations variation of fecundity contributed least to variation of λ, and variation of adult survival contributed most to variation of λ in three of four populations. Between population comparisons revealed that differences mainly stem from differences of immigration and juvenile local survival. The relative importance of immigration to λ tended to decrease with increasing spatial extent and isolation of the local populations. None of the four local populations was self-sustainable. Because the local populations export and import individuals, they can be considered as open recruitment systems in which part of the recruited breeding birds are not produced locally. The spatial extent and the degree of isolation of a local population have an impact on local population dynamics; hence these factors need to be considered in studies about local population dynamics and for deriving conservation measures.     

Temporal dynamics of European bat Lyssavirus type 1 and survival of Myotis myotis bats in natural colonies

Many emerging RNA viruses of public health concern have recently been detected in bats. However, the dynamics of these viruses in natural bat colonies is presently unknown. Consequently, prediction of the spread of these viruses and the establishment of appropriate control measures are hindered by a lack of information. To this aim, we collected epidemiological, virological and ecological data during a twelve-year longitudinal study in two colonies of insectivorous bats (Myotis myotis) located in Spain and infected by the most common bat lyssavirus found in Europe, the European bat lyssavirus subtype 1 (EBLV-1). This active survey demonstrates that cyclic lyssavirus infections occurred with periodic oscillations in the number of susceptible, immune and infected bats. Persistence of immunity for more than one year was detected in some individuals. These data were further used to feed models to analyze the temporal dynamics of EBLV-1 and the survival rate of bats. According to these models, the infection is characterized by a predicted low basic reproductive rate (R(0) = 1.706) and a short infectious period (D = 5.1 days). In contrast to observations in most non-flying animals infected with rabies, the survival model shows no variation in mortality after EBLV-1 infection of M. myotis. These findings have considerable public health implications in terms of management of colonies where lyssavirus-positive bats have been recorded and confirm the potential risk of rabies transmission to humans. A greater understanding of the dynamics of lyssavirus in bat colonies also provides a model to study how bats contribute to the maintenance and transmission of other viruses of public health concern.     

Human vs. Animal Outbreaks of the 2009 Swine-Origin H1N1 Influenza A epidemic

The majority of emerging infectious diseases are zoonotic in origin, including recently emerging influenza viruses such as the 2009 swine-origin H1N1 influenza A epidemic. The epidemic that year affected both human and animal populations as it spread globally. In fact, before the end of 2009, 14 different countries reported H1N1 infected swine. In order to better understand the zoonotic nature of the epidemic and the relationship between human and animal disease surveillance data streams, we compared 2009 reports of H1N1 infection to define the temporal relationship between reported cases in animals and humans. Generally, human cases preceded animal cases at a country-level, supporting the potential of H1N1 infection to be a “reverse zoonosis”, and the value of integrating human and animal disease report data.     

Infectious HIV-1 assembles in late endosomes in primary macrophages

Although human immunodeficiency virus type 1 (HIV-1) is generally thought to assemble at the plasma membrane of infected cells, virions have been observed in intracellular compartments in macrophages. Here, we investigated virus assembly in HIV-1-infected primary human monocyte-derived macrophages (MDM). Electron microscopy of cryosections showed virus particles, identified by their morphology and positive labeling with antibodies to the viral p17, p24, and envelope proteins, in intracellular vacuoles. Immunolabeling demonstrated that these compartments contained the late endosomal marker CD63, which was enriched on vesicles within these structures and incorporated into the envelope of budding virions. The virus-containing vacuoles were also labeled with antibodies against LAMP-1, CD81, and CD82, which were also incorporated into the viral envelope. To assess the cellular source of infectious viruses derived from MDM, virus-containing media from infected cells were precipitated with specific antibodies. Only antibodies against antigens found in late endosomes precipitated infectious virus, whereas antibodies against proteins located primarily on the cell surface did not. Our data indicate that most of the infectious HIV produced by primary macrophages is assembled on late endocytic membranes and acquires antigens characteristic of this compartment. This notion has significant implications for understanding the biology of HIV and its cell-cell transmission.     

Susceptibility of wood ducks to H5N1 highly pathogenic avian influenza virus

Since 2002, H5N1 highly pathogenic avian influenza (HPAI) viruses have caused mortality in numerous species of wild birds; this is atypical for avian influenza virus (AIV) infections in these avian species, especially for species within the order Anseriformes. Although these infections document the susceptibility of wild birds to H5N1 HPAI viruses and the spillover of these viruses from infected domestic birds to wild birds, it is unknown whether H5N1 HPAI viruses can persist in free-living avian populations. In a previous study, we established that wood ducks (Aix sponsa) are highly susceptible to infection with H5N1 HPAI viruses. To quantify this susceptibility and further evaluate the likelihood of H5N1 HPAI viral maintenance in a wild bird population, we determined the concentration of virus required to produce infection in wood ducks. To accomplish this, 25 wood ducks were inoculated intranasally at 12-16 wk of age with decreasing concentrations of a H5N1 HPAI virus (A/Whooper Swan/Mongolia/244/05 [H5N1]). The median infectious dose and the lethal dose of H5N1 HPAI virus in wood ducks were very low (10(0.95) and 10(1.71) median embryo infectious dose [EID(50)]/ml, respectively) and less than that of chickens (10(2.80) and 10(2.80) EID(50)/ml). These results confirm that wood ducks are highly susceptible to infection with H5N1 HPAI virus. The data from this study, combined with what is known experimentally about H5N1 HPAI virus infection in wood ducks and viral persistence in aquatic environments, suggest that the wood duck would represent a sensitive indicator species for H5N1 HPAI. Results also suggest that the potential for decreased transmission efficiency associated with reduced viral shedding (especially from the cloaca) and a loss of environmental fitness (in water), may be offset by the ability of this virus to be transmitted through a very low infectious dose.     

Statistical analysis of synaptic transmission: model discrimination and confidence limits.

Procedures for discriminating between competing statistical models of synaptic transmission, and for providing confidence limits on the parameters of these models, have been developed. These procedures were tested against simulated data and were used to analyze the fluctuations in synaptic currents evoked in hippocampal neurones. All models were fitted to data using the Expectation-Maximization algorithm and a maximum likelihood criterion. Competing models were evaluated using the log-likelihood ratio (Wilks statistic). When the competing models were not nested, Monte Carlo sampling of the model used as the null hypothesis (H0) provided density functions against which H0 and the alternate model (H1) were tested. The statistic for the log-likelihood ratio was determined from the fit of H0 and H1 to these probability densities. This statistic was used to determine the significance level at which H0 could be rejected for the original data. When the competing models were nested, log-likelihood ratios and the chi 2 statistic were used to determine the confidence level for rejection. Once the model that provided the best statistical fit to the data was identified, many estimates for the model parameters were calculated by resampling the original data. Bootstrap techniques were then used to obtain the confidence limits of these parameters.     

Assembly of infectious HIV-1 in human epithelial and T-lymphoblastic cell lines

The canonical view of the ultimate steps of HIV-1 replication is that virus assembly and budding are taking place at the plasma membrane of infected cells. Surprisingly, recent studies revealed that these steps also occur on endosomal membranes in the interior of infected cells, such as macrophages. This prompted us to revisit the site of HIV-1 assembly in human epithelial-like cells and in infected human T-lymphoblastic cells. To address this question, we investigated the intracellular location of the major viral structural components of HIV-1, namely Gag, Env and the genomic RNA. Using a sub-cellular fractionation method, as well as immuno-confocal and electron microscopy, we show that Gag, the Env glycoproteins and the genomic RNA accumulate in late endosomes that contain infectious HIV-1 particles. In epithelial-like 293T cells, HIV-1 assembles and buds both at the plasma membrane and in endosomes, while in chronically infected human T lymphocytes, viral assembly mostly occurs within the cell where large amounts of infectious virions accumulate in endosomal compartments. In addition, HIV-1 release could be enhanced by ionomycin, a drug stimulating calcium-dependent exocytosis. These results favour the view that newly made Gag molecules associate with the genomic RNA in the cytosol, then viral core complexes can be targeted to late endosomes together with Env, where infectious HIV-1 are made and subsequently released by exocytosis.