Models for Trypanosoma evansi (surra), its control and economic impact on small-hold livestock owners in the Philippines

Simple demographic and infectious disease models of buffaloes and other domestic hosts for animal trypanosomosis (surra) caused by Trypanosoma evansi were developed. The animal models contained deterministic and stochastic elements and were linked to simulate the benefit of control regimes for surra in village domestic animal populations in Mindanao, Philippines. The impact of the disease on host fertility and mortality were key factors in determining the economic losses and net-benefit from the control regimes. If using a high (99%) efficacy drug in surra-moderate to high risk areas, then treating all animals twice each year yielded low prevalence in 2 years; targeted treatment of clinically sick animals, constantly monitored (monthly), required 75% fewer treatments but took longer to reach a low prevalence than treating all animals twice each year. At high drug efficacy both of these treatment strategies increased the benefit over untreated animals by 81%. If drug efficacy declined then the benefit obtained from twice yearly treatment of all animals declined rapidly compared with regular monitoring and targeting treatment to clinically sick animals. The current control regimen applied in the Philippines of annual sero-testing for surra and only treating sero-positive animals provided the lowest net-benefit of all the control options simulated and would not be regarded as effective control. The total net-benefit from effective surra control for a typical village in a moderate/high risk area was 7.9 million pesos per annum (US $158,000). The value added to buffaloes, cattle, horses, goats/sheep and pigs as a result of this control was US $88, $84, $151, $7, $114 per animal/year, respectively.     

Individual-based model of spatio-temporal dynamics of mixed forest stands

This research presents the results of constructing and parameterizing an individual-based model of spatiotemporal dynamics of mixed forest stands. The model facilitates computerized experiments with forest stands having different combinations of species and age structures. These forest stands grow on temperate areas where light is the main system-forming factor that shapes and develops forest ecosystems. The model TEMFORM (TEMperate FORests Model) is developed with few equations and parameters, most of which can be estimated using standard forest inventory data. Parameterization of the model used the growth tables of a set of basic forest-forming species in Far East Russia. Simulation results of the development of the natural single- and mixed-species stands and the effects of different types of disturbances on the stand dynamics and compositions are presented.     

Stimulator of interferon genes (STING): A “new chapter” in virus-associated cancer research. Lessons from wild-derived mouse models of innate immunity

Thanks to the numerous studies that have been carried out recently in the field of cytosolic DNA sensing, STING (Stimulator of Interferon Genes) is now recognized as a key mediator of innate immune signaling. A substantial body of evidence derived from in vivo mouse models demonstrates that STING-regulated pathways underlie the pathogenesis of many diseases including infectious diseases and cancers. It has also become evident from these studies that STING is a promising therapeutic target for the treatment of cancer. However, mouse strains commonly used for modelling innate immune response against infections or tumors do not allow investigators to accurately reproduce certain specific characteristics of immune response observed in human cells. In this review, we will discuss recent data demonstrating that the use of wild-derived genetically distinct inbred mice as a model for investigation into the innate immunity signaling networks may provide valuable insight into the STING-regulated pathways specific for human cells. The maximum complexity of STING-mediated mechanisms can probably be seen in case of DNA virus-induced carcinogenesis in which STING may perform unexpected biological activities. Therefore, in another part of this review we will summarize emerging data on the role of STING in human DNA virus-related oncopathologies, with particular attention to HPV-associated cervical cancer, aiming to demonstrate that STING indeed “starts a new chapter” in research on this issue and that wild-derived mouse models of STING-mediated response to infections will probably be helpful in finding out molecular basis for clinical observations.     

Trait plasticity alters the range of possible coexistence conditions in a competition–colonisation trade‐off

Most of the classical theory on species coexistence has been based on species‐level competitive trade‐offs. However, it is becoming apparent that plant species display high levels of trait plasticity. The implications of this plasticity are almost completely unknown for most coexistence theory. Here, we model a competition–colonisation trade‐off and incorporate trait plasticity to evaluate its effects on coexistence. Our simulations show that the classic competition–colonisation trade‐off is highly sensitive to environmental circumstances, and coexistence only occurs in narrow ranges of conditions. The inclusion of plasticity, which allows shifts in competitive hierarchies across the landscape, leads to coexistence across a much broader range of competitive and environmental conditions including disturbance levels, the magnitude of competitive differences between species, and landscape spatial patterning. Plasticity also increases the number of species that persist in simulations of multispecies assemblages. Plasticity may generally increase the robustness of coexistence mechanisms and be an important component of scaling coexistence theory to higher diversity communities.     

Bayesian Quantile Regression for Longitudinal Studies with Nonignorable Missing Data

Summary .  We study quantile regression (QR) for longitudinal measurements with nonignorable intermittent missing data and dropout. Compared to conventional mean regression, quantile regression can characterize the entire conditional distribution of the outcome variable, and is more robust to outliers and misspecification of the error distribution. We account for the within-subject correlation by introducing a   ℓ₂   penalty in the usual QR check function to shrink the subject-specific intercepts and slopes toward the common population values. The informative missing data are assumed to be related to the longitudinal outcome process through the shared latent random effects. We assess the performance of the proposed method using simulation studies, and illustrate it with data from a pediatric AIDS clinical trial.     

Species co‐occurrence patterns and dietary resource competition in primates

Diamond (Assembly of species communities. In: Cody ML, Diamond JM, editors. Ecology and evolution of communities. Cambridge: Belknap. p 342–444 ( 1975 )) argued that interspecific competition between species occupying similar niches results in a nonrandom pattern of species distributions. In particular, some species pairs may never be found in the same community due to competitive exclusion. Rigorous analytical methods have been developed to investigate the possible role that interspecific competition has on the evolution of communities. Many studies that have implemented these methods have shown support for Diamond's assembly rules, yet there are numerous exceptions. We build on this previous research by examining the co‐occurrence patterns of primate species in 109 communities from across the world. We used EcoSim to calculate a checkerboard (C) score for each region. The C score provides a measure of the proportion of species pairs that do not co‐occur in a set of communities. High C scores indicate that species are nonrandomly distributed throughout a region, and interspecific competition may be driving patterns of competitive exclusion. We conducted two sets of analyses. One included all primate species per region, and the second analysis assigned each species to one of four dietary guilds: frugivores, folivores, insectivores, and frugivore‐insectivores. Using all species per region, we found significantly high C scores in 9 of 10 regions examined. For frugivores, we found significantly high‐C scores in more than 50% of regions. In contrast, only 23% of regions exhibited significantly high‐C scores for folivores. Our results suggest that communities are nonrandomly structured and may be the result of greater levels of interspecific competition between frugivores compared to folivores. Am J Phys Anthropol, 2010. © 2010 Wiley‐Liss, Inc.     

A physiological analogy of the niche for projecting the potential distribution of plants

Aim  To develop a physiologically based model of the plant niche for use in species distribution modelling. Location  Europe. Methods  We link the Thornley transport resistance (TTR) model with functions which describe how the TTR’s model parameters are influenced by abiotic environmental factors. The TTR model considers how carbon and nutrient uptake, and the allocation of these assimilates, influence growth. We use indirect statistical methods to estimate the model parameters from a high resolution data set on tree distribution for 22 European tree species. Results  We infer, from distribution data and abiotic forcing data, the physiological niche dimensions of 22 European tree species. We found that the model fits were reasonable (AUC: 0.79–0.964). The projected distributions were characterized by a false positive rate of 0.19 and a false negative rate 0.12. The fitted models are used to generate projections of the environmental factors that limit the range boundaries of the study species. Main conclusions  We show that physiological models can be used to derive physiological niche dimensions from species distribution data. Future work should focus on including prior information on physiological rates into the parameter estimation process. Application of the TTR model to species distribution modelling suggests new avenues for establishing explicit links between distribution and physiology, and for generating hypotheses about how ecophysiological processes influence the distribution of plants.     

Rates of small-scale species mobility in alvar limestone grassland

Abstract. Small-scale species frequency and cumulative species frequency were studied in four plots in limestone grassland of the Veronica spicata-Avenula pratensis association on Stora Alvaret on the Baltic island of Öland, Sweden. Species mobility was expressed as increase in cumulative species frequency in 20 subplots of 100 cm². Observed cumulative frequencies from 1985–1989 in all four plots, and from 1985–1995 in one plot were compared with values following from two null models, a ‘minimal mobility’ model and a random mobility model. In ca. 50 % of the cases the observed cumulative frequency was not significantly different from the random expectation. However, in many such cases the mean annual frequency was either very high or very low. Three ways of calculating the mobility rate are presented though only one is used: (observed cumulative frequency -lowest annual frequency) / expected cumulative frequency. Values × 100 range from 0 to 100. There were slight differences between the four plots which were interpreted in terms of differences in grazing intensity and soil depth. It is stressed that the idea of the Carousel model has never been meant to suggest that all species would show random mobility, which we now quantify, but that species differ in their mobility rate and that the mean rate is much higher than generally realized.