A weight-adjusted Peto’s test when cause of death is not assigned

A new statistical testing approach using a weighted logrank statistic is developed for rodent tumorigenicity assays that have a single terminal sacrifice but not cause-of-death data. Instead of using cause-of-death assignment by pathologists, the number of fatal tumors is estimated by a constrained nonparametric maximum likelihood estimation method. For data lacking cause-of-death information, the Peto test is modified with estimated numbers of fatal tumors and a Fleming–Harrington-type weight, which is based on an estimated tumor survival function. A bootstrap resampling method is used to estimate the weight function. The proposed testing method with the weight adjustment appears to improve the performance in various situations of single-sacrifice animal experiments. A Monte Carlo simulation study for the proposed test is conducted to assess size and power of the test. This testing approach is illustrated using a real data set.     

Investigations into a plankton population model: Mortality and its importance in climate change scenarios

The potential for marine plankton ecosystems to influence climate by the production of dimethylsulphide (DMS) has been an important topic of recent research into climate change. Several General Circulation Models, used to predict climate change, have or are being modified to include interactions of ecosystems with climate. Climate change necessitates that parameters within ecosystem models must change during long-term simulations, especially mortality parameters that increase as organisms are pushed toward the boundaries of their thermal tolerance. Changing mortality parameters can have profound influences on ecosystem model dynamics. There is therefore a pressing need to understand the influence of varying mortality parameters on the long-term behaviour of ecosystem models. This work examines the sensitivity of a model of DMS production by marine ecosystems to variations in three linear mortality coefficients. Significant differences in behaviour are observed, and we note the importance of these results in formulating ecosystem models for application in simulations of climate change.     

Mortality and predation in ecosystem models: is it important how these are expressed?

The effects of the form of the grazing and mortality terms used in plankton models are well known. The same cannot be said for ecosystem models. As ecosystem models become more popular more needs to be known about the effects of model formulation on model behaviour and performance. The impact of the form of the grazing response function and mortality terms used in a biogeochemical ecosystem model are considered here. We show that in the large and inter-linked webs used in ecosystem models, model behaviour is far more sensitive to the form of the grazing term than to that of the mortality terms that close the modelled food web.When using biogeochemical ecosystem models in shallow marine ecosystems, the most dynamic and sophisticated functional responses describing grazing require more parameters and validation than the simpler Holling disk equation, but usually still lead to the same general conclusions about the system state and the effects of changes in forcing functions. Thus, the use of more complex functional responses is not necessarily warranted in many cases. Similarly, the extra effort and data required to explicitly represent the top predators (sharks, mammals and birds) is not necessary if they are not the focus of the study. A quadratic mortality term applied to intermediate predators (such as piscivores) is sufficient to achieve plausible model behaviour. It should be noted, however, that some degree of sophistication is required in the grazing and mortality terms. Use of simple linear functional responses and mortality terms is unsuitable for models used to consider a range of nutrient loading or harvesting scenarios.     

Ecological network analysis: network construction

Ecological network analysis (ENA) is a systems-oriented methodology to analyze within system interactions used to identify holistic properties that are otherwise not evident from the direct observations. Like any analysis technique, the accuracy of the results is as good as the data available, but the additional challenge is that the data need to characterize an entire ecosystem's flows and storages. Thus, data requirements are substantial. As a result, there have, in fact, not been a significant number of network models constructed and development of the network analysis methodology has progressed largely within the purview of a few established models. In this paper, we outline the steps for one approach to construct network models. Lastly, we also provide a brief overview of the algorithmic methods used to construct food web typologies when empirical data are not available. It is our aim that such an effort aids other researchers to consider the construction of such models as well as encourages further refinement of this procedure.     

Re-evaluation and re-classification of erionite series minerals

Governments and industries have introduced regulatory measures requiring safety controls to limit asbestos exposure of the general public and asbestos workers. Although erionite is a more potent health hazard mineral than asbestos, it has received far less attention. Precise definition of erionite, types of these fibrous minerals, and most importantly, characterization requirements still raise questions and often lead to arguments and even legal disputes. Many bulk erionite samples used in animal and cell experiments for carcinogenicity are not mineralogically pure. To test this hypothesis, we characterized two erionite standards from Rome, Oregon, and Pine Valley, Nevada, USA. These standards were characterized quantitatively using modern analytical techniques, and one of them, the erionite standard from Rome, Oregon, passed the required tests for positive identification, but the other, the erionite standard from Pine Valley, Nevada, did not. Furthermore, we observed ambiguous definitions, incorrect identifications, and inaccurate reporting of clinical investigations. To address this problem, we established characterization guidelines for positive identification of erionite using a modified balance error formula, and we re-evaluated and re-classified published erionite data from the literature as erionite-Ca, erionite-Na, and erionite-K. If data did not pass either the E% or Mg-content test, then we propose that reference to them in the literature be disregarded. Erionite requires special attention from the mineralogical community to help establish its true carcinogenetic properties. We believe that the characterization guidelines established in this paper will contribute to setting up rules and regulations for evaluation of erionite by regulatory agencies.     

Inorganic arsenic compounds: are they carcinogenic,mutagenic, teratogenic?

This review examines and evaluates the literature on the ability of inorganic arsenic compounds to cause cancer in humans and laboratory animals. The epidemiological data that supports the position that inorganic arsenical derivatives are carcinogenic in humans is convincing and difficult to deny because of their consistency. These data are from studies of different occupational exposures such as smelter and pesticide workers, as well as from studies of drinking water, wines and medicinal tonics that contained or were contaminated with inorganic compounds of arsenic. Indeed, positive dose-response relationships between cancer incidence or mortality with many inorganic arsenical substances have been shown. Despite the presence of data which confuse the interpretation and evaluation of epidemiological data, associated neoplasms of the lungs, skin and gastrointestinal systems have been observed as a result of exposure to inorganic arsenic compounds.The mechanism of carcinogenicity of inorganic arsenical substances in humans is unknown. Inorganic arsenic compounds are not carcinogenic in laboratory animals by most routes of administration. However, further studies (subchronic, chronic, carcinogenic) using intratracheal and other conventional routes in other animal species would appear to be warranted. Moreso, especially since there is no evidence that organic arsenic compounds are carcinogenic in numerous mammalian species. Inorganic derivatives of arsenic are not mutagenic but may be teraiogenic. This latter conclusion is dependent on the method of administration and size of the dose, as well as on the species of animal used for the study.     

An individual-based stochastic hazard model of eastern king prawn (Melicertus plebejus) migration with spatially and temporally varying fishing effort

This paper describes an individual-based stochastic model of eastern king prawn migration along the eastern Australian coast. Migration is treated as one-dimensional diffusion with drift. Capture of a prawn is seen as a failure event driven by movement through a spatially and temporally variable fishing mortality hazard. This hazard is combined with a uniform natural mortality hazard. We use a Monte Carlo method to estimate parameters by comparing expected numbers of tag-returns predicted from the model with previously published tag-release data. As the previous study used a discrete compartmental model, with compartments corresponding to zones of constant fishing effort, we used the same zones and fishing effort in our comparison. The marginal distribution of yield in each zone per single recruit is determined, providing more information compared with the deterministic approach to yield-per-recruit. Using our model we also derive the constant fishing mortality rate equivalent to a spatially variable fishing mortality rate in its impact on the proportion of prawns surviving the migration to reach spawning grounds. Determination of this proportion could contribute significantly to a sustainability assessment of the fishery. It is demonstrated using the AIC that better fits to the data of the previous study and greater parsimony are obtained using our model than were found in the deterministic compartmental analysis of that study. This improvement results from the ability of our model to account separately for average speed of movement and average dispersal rate, whereas in the previous deterministic compartmental model, movement is governed by just one parameter. Our individual-based model includes a parameter that explicitly accounts for dispersal of prawns in migration, so it can distinguish between speed effects and dispersal effects in the data. It also models both types of mortality as processes distinct from those of movement. This enables it to better separate movement and mortality effects compared to the compartmental approach, in which movement and mortality are treated as similar departure processes from a compartment. This separation reduces confounding of movement and mortality effects when parameters are estimated.     

Dose-response curve modeling of excess mortality caused by two forms of stress

A method is presented for modeling the effect of two stresses on mortality. The model assumes a multiplicative simple two-parameter dose-response curve relationship between mortality and the two factors as well as for the effect of combining the two factors. The dose-response curve is modified in order to model survival probabilities. It is shown that the model adequately describes mortality data of Folsomia candida (Collembola) in a two-stress factor design.     

Mycobacteriosis-associated mortality in wild striped bass (Morone saxatilis) from Chesapeake Bay, U.S.A

The striped bass (Morone saxatilis) is an economically and ecologically important finfish species along the Atlantic seaboard of the United States. Recent stock assessments in Chesapeake Bay (U.S.A.) indicate that non-fishing mortality in striped bass has increased since 1999, concomitant with very high (>50%) prevalence of visceral and dermal disease caused by Mycobacterium spp. Current fishery assessment models do not differentiate between disease and other components of non-fishing mortality (e.g., senescence, predation); therefore, disease impact on the striped bass population has not been established. Specific measurement of mortality associated with mycobacteriosis in wild striped bass is complicated because the disease is chronic and mortality is cryptic. Epidemiological models have been developed to estimate disease-associated mortality from cross-sectional prevalence data and have recently been generalized to represent disease processes more realistically. Here, we used this generalized approach to demonstrate disease-associated mortality in striped bass from Chesapeake Bay. To our knowledge this is the first demonstration of cryptic mortality associated with a chronic infectious disease in a wild finfish. This finding has direct implications for management and stock assessment of striped bass, as it demonstrates population-level negative impacts of a chronic disease. Additionally, this research provides a framework by which disease-associated mortality may be specifically addressed within fisheries models for resource management.     

Density dependence in marine fish populations revealed at small and large spatial scales

Experimental manipulation of population density has frequently been used to demonstrate demographic density dependence. However, such studies are usually small scale and typically provide evidence of spatial (within-generation) density dependence. It is often unclear whether small-scale, experimental tests of spatial density dependence will accurately describe temporal (between-generation) density dependence required for population regulation. Understanding the mechanisms generating density dependence may provide a link between spatial experiments and temporal regulation of populations. In this study, I manipulated the density of recently settled kelp rockfish (Sebastes atrovirens) in both the presence and absence of predators to test for density-dependent mortality and whether predation was the mechanism responsible. I also examined mortality of rockfish cohorts within kelp beds throughout central California to evaluate temporal (between-generation) density dependence in mortality. Experiments suggested that short-term behavioral responses of predators and/or a shortage of prey refuges caused spatial density dependence. Temporal density dependence in mortality was also detected at larger spatial scales for several species of rockfish. It is likely that short-term responses of predators generated both spatial and temporal density dependence in mortality. Spatial experiments that describe the causal mechanisms generating density dependence may therefore be valuable in describing temporal density dependence and population regulation.     

Handling and Survivorship of African Wild Dog (Lycaon pictus) in Five Ecosystems

Populations of the African wild dog, Lycaon pictus have declined throughout their range in sub-Saharan Africa during the last 20 years. It has been hypothesized that handling of wild dogs led to local extinction of a study population in the Serengeti-Masai Mara ecosystem. In this paper we compare rates of mortality and disappearance in handled ( n = 305) versus unhandled ( n = 135) dogs to test the hypothesis that handling leads to increased mortality of Lycaon . We examine data from five ecosystems in which Lycaon have been handled. Our data show that there is no effect of handling on the longevity of Lycaon in any ecosystem studied. Given these data, a more parsimonious explanation of the decimation of the Serengeti-Mara Lycaon population would be that disease alone was responsible for the population collapse and that researcher handling of Lycaon was correlated with, but not causal to, this mortality.     

Impact and Dynamics of Disease in Species Threatened by the Amphibian Chytrid Fungus, Batrachochytrium dendrobatidis

Abstract:  Estimating disease-associated mortality and transmission processes is difficult in free-ranging wildlife but important for understanding disease impacts and dynamics and for informing management decisions. In a capture–mark–recapture study, we used a PCR-based diagnostic test in combination with multistate models to provide the first estimates of disease-associated mortality and detection, infection, and recovery rates for frogs endemically infected with the chytrid fungus Batrachochytrium dendrobatidis (Bd), which causes the pandemic amphibian disease chytridiomycosis. We found that endemic chytridiomycosis was associated with a substantial reduction (approximately 38%) in apparent monthly survival of the threatened rainforest treefrog Litoria pearsoniana despite a long period of coexistence (approximately 30 years); detection rate was not influenced by disease status; improved recovery and reduced infection rates correlated with decreased prevalence, which occurred when temperatures increased; and incorporating changes in individuals' infection status through time with multistate models increased effect size and support (98.6% vs. 71% of total support) for the presence of disease-associated mortality when compared with a Cormack–Jolly–Seber model in which infection status was restricted to the time of first capture. Our results indicate that amphibian populations can face significant ongoing pressure from chytridiomycosis long after epidemics associated with initial Bd invasions subside, an important consideration for the long-term conservation of many amphibian species worldwide. Our findings also improve confidence in estimates of disease prevalence in wild amphibians and provide a general framework for estimating parameters in epidemiological models for chytridiomycosis, an important step toward better understanding and management of this disease.     

Inferential permutation tests for maximum entropy models in ecology

Maximum entropy (maxent) models assign probabilities to states that (1) agree with measured macroscopic constraints on attributes of the states and (2) are otherwise maximally uninformative and are thus as close as possible to a specified prior distribution. Such models have recently become popular in ecology, but classical inferential statistical tests require assumptions of independence during the allocation of entities to states that are rarely fulfilled in ecology. This paper describes a new permutation test for such maxent models that is appropriate for very general prior distributions and for cases in which many states have zero abundance and that can be used to test for conditional relevance of subsets of constraints. Simulations show that the test gives correct probability estimates under the null hypothesis. Power under the alternative hypothesis depends primarily on the number and strength of the constraints and on the number of states in the model; the number of empty states has only a small effect on power. The test is illustrated using two empirical data sets to test the community assembly model of B. Shipley, D. Vile, and E. Garnier and the species abundance distribution models of S. Pueyo, F. He, and T. Zillio.     

邻苯二甲酸酯类增塑剂的体外细胞毒性评价

邻苯二甲酸酯(Phthalate esters, PAEs)是环境介质中的一类典型的有机污染物。已有研究表明,PAEs具有明显的内分泌干扰毒性,并会对动物和人体的生殖发育与神经系统造成损伤。体外细胞评价模型因具有高通量、测试周期短、成本低和毒性效应易于探明等技术优点,被广泛应用到PAEs毒理学效应的研究中。本文从内分泌干扰毒性、胚胎发育毒性、神经毒性、免疫毒性、遗传毒性以及致癌作用等方面,对PAEs的一些体外细胞毒性评价模型进行了分类和总结,并对其相应的研究进展进行了综述。本文旨在为体外细胞毒性评价模型的有效利用提供借鉴,并对PAEs毒性作用机制的深入研究提供思路和依据。     

Empirical Bayes calculations of concordance between endpoints in environmental toxicity experiments

Hierarchical models are considered for estimating the probability of agreement between two outcomes or endpoints from an environmental toxicity experiment. Emphasis is placed on generalized regression models, under which the prior mean is related to a linear combination of explanatory variables via a monotone function. This function defines the scale over which the systematic effects are modelled as additive. Specific illustration is provided for the logistic link function. The hierarchical model employs a conjugate beta prior that leads to parametric empirical Bayes estimators of the individual agreement parameters. An example from environmental carcinogenesis illustrates the methods, with motivation derived from estimation of the concordance between two species carcinogenicity outcomes. Based on a large database of carcinogenicity studies, the inter-species concordance is seen to be reasonably informative, i.e. in the range 67–84%. Stratification into pertinent potency-related sub-groups via the logistic model is seen to improve concordance estimation: for environmental stimuli at the extremes of the potency spectrum, concordance can reach well above 90%.     

Evaluation of the QUIC-URB fast response urban wind model for a cubical building array and wide building street canyon

This paper describes the QUIC-URB fast response urban wind modeling tool and evaluates it against wind tunnel data for a 7 × 11 cubical building array and wide building street canyon. QUIC-URB is based on the Röckle diagnostic wind modeling strategy that rapidly produces spatially resolved wind fields in urban areas and can be used to drive urban dispersion models. Röckle-type models do not solve transport equations for momentum or energy; rather, they rely heavily on empirical parameterizations and mass conservation. In the model-experiment comparisons, we test two empirical building flow parameterizations within the QUIC-URB model: our implementation of the standard Röckle (SR) algorithms and a set of modified Röckle (MR) algorithms. The MR model attempts to build on the strengths of the SR model and introduces additional physically based, but simple parameterizations that significantly improve the results in most regions of the flow for both test cases. The MR model produces vortices in front of buildings, on rooftops and within street canyons that have velocities that compare much more favorably to the experimental results. We expect that these improvements in the wind field will result in improved dispersion calculations in built environments.     

Modeling individual tree mortality for crimean pine plantations

Individual tree mortality model was developed for crimean pine (Pinus nigra subsp. pallasiana) plantations in Turkey. Data came from 5 year remeasurements of the permanent sample plots. The data comprises of 115 sample plots with 5029 individual trees. Parameters of the logistic equation were estimated using weighted nonlinear regression analysis. Approximately 80% of the observations were used for model development and 20% for validation. The explicatory variables in the model were ratio of diameter of the subject tree and basal area mean diameter of the sample plot as measure of competition index for individual trees, basal area and site index. All parameter estimates were found highly significant (p < 0.001) in predicting mortality model. Chi-square statistics indicate that the most important variable is d / d(q), the second most important is site index, and the third most important predictor is stand basal area. Examination of graphs of observed vs. predicted mortality rates reveals that the mortality model is well behaved and match the observed mortality rates quite well. Although the phenomenon of mortality is a stochastic, rare and irregular event, the model fit was fairly good. The logistic mortality model passed a validation test on independent data not used in parameter estimation. The key ingredient for obtaining a good mortality model is a data set that is both large and representative of the population under study and the data satisfy both requirements. The mortality model presented in this paper is considered to have an appropriate level of reliability.     

Modelling the effects of UV radiation on the survival of Antarctic krill (Euphausia superba Dana) in the face of limited data

Antarctic krill, Euphausia superba, is a keystone species of the Antarctic ecosystem. A fishery for krill may compete with land-based predators (penguins and seals), particularly during the breeding season. The Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) is moving towards management in small scale units. The management models specify predation and fishing mortality as space and time dependent but do not yet include non-predation natural mortality. Krill are known to be highly susceptible to ultraviolet radiation (UV) but there are limited empirical data. We develop a model for krill mortality caused by UV and parameterize and assess it by comparison with experimental data. The analysis allows us to identify key parameters that should be measured in future experiments and also leads to suggestions about modification of experimental procedure. We illustrate the method for krill found in the Livingston Island area and show that (a) it is possible to estimate the component of natural mortality due to UV-induced damage and (b) that cohorts born in 1979, 1984, or 1997 have different survival in the first 5 years of life, associated with differential UV exposure. In particular, those born in 1997 may have experienced as much as 10% lower survival than those born in 1979. The method developed here allows a potentially important source of krill mortality to be incorporated into the management models and suggests key experiments and field work in the future.     

A pattern-oriented modelling approach to simulating populations of grey partridge

A number of wildlife species including the grey partridge (Perdix perdix) have shown dramatic post-war population declines. Multiple drivers have been proposed as reasons for the declines, for example agrochemical use and intensification of agricultural practices, climate, predation, and changes in landscape structure. These drivers may interact in non-linear ways and are inherently spatio-temporal in nature. Therefore models used to investigate mechanisms should be spatio-temporal, of proper scale, and have a high degree of biological realism. Here we describe the development and testing of an agent-based model (ABM) of grey partridge using a well documented pre-decline historical data set in conjunction with a pattern-oriented modelling (POM) approach. Model development was an iterative process of defining performance criteria, testing model behaviour, and reformulating as necessary to emulate system properties whilst ensuring that internal mechanisms were biologically realistic. The model was documented using ODdox, a new protocol for describing large agent-based models. Parameter fitting in the model was achieved to within ±2% accuracy for 15 out of 17 field data patterns used, and within 5% for the remaining two. Tests of interactions between input parameters showed that 62% of parameter pairs tested had significant interactions underlining the complex nature of the model structure. Sensitivity analysis identified chick mortality as being the most sensitive factor, followed by adult losses to hunting and adult overwinter mortality, agreeing in general with previous partridge models. However, the ABM used here could separate individual drivers, providing a better understanding of the underlying mechanisms behind population regulation, and allowing factors to be compared directly. The ABM used is rich in output signals allowing detailed testing and refinement of the model. This approach is particularly suited to systems such as the partridge system where data for comparison to model outputs is readily available. Despite the accurate fit between historical data and model output, making use of the predictive power of the approach the model requires further calibration and testing under modern field conditions.