Nickel Carcinogenicity in Relation to the Health Risks from Residual Oil Fly Ash

Epidemiological studies of workers in the nickel industry, animal exposure studies, and reports on the potential mechanisms of nickel-induced toxicity and carcinogenicity indicate that only crystalline sulfidic nickel compounds have been clearly established as carcinogenic or potentially carcinogenic in humans. This observation indicates the need to modify and update regulatory approaches for nickel to reflect noncancer toxicity values for some individual nickel species. Analysis of nickel compounds in residual oil fly ash (ROFA) indicates that sulfidic nickel compounds (e.g., nickel subsulfide, nickel sulfide) are not present. Thus, the potential for emission of carcinogenic nickel compounds from residual oil fly ash appears to be low. Preliminary reference concentrations (RfCs) for a number of nickel compounds, based on non-carcinogenic endpoints, are proposed on the basis of the benchmark dose approach in conjunction with NTP data for nickel species.     

Dose and dose rate extrapolation factors for malignant and non-malignant health endpoints after exposure to gamma and neutron radiation

Murine experiments were conducted at the JANUS reactor in Argonne National Laboratory from 1970 to 1992 to study the effect of acute and protracted radiation dose from gamma rays and fission neutron whole body exposure. The present study reports the reanalysis of the JANUS data on 36,718 mice, of which 16,973 mice were irradiated with neutrons, 13,638 were irradiated with gamma rays, and 6107 were controls. Mice were mostly Mus musculus, but one experiment used Peromyscus leucopus. For both types of radiation exposure, a Cox proportional hazards model was used, using age as timescale, and stratifying on sex and experiment. The optimal model was one with linear and quadratic terms in cumulative lagged dose, with adjustments to both linear and quadratic dose terms for low-dose rate irradiation (<5 mGy/h) and with adjustments to the dose for age at exposure and sex. After gamma ray exposure there is significant non-linearity (generally with upward curvature) for all tumours, lymphoreticular, respiratory, connective tissue and gastrointestinal tumours, also for all non-tumour, other non-tumour, non-malignant pulmonary and non-malignant renal diseases (p < 0.001). Associated with this the low-dose extrapolation factor, measuring the overestimation in low-dose risk resulting from linear extrapolation is significantly elevated for lymphoreticular tumours 1.16 (95% CI 1.06, 1.31), elevated also for a number of non-malignant endpoints, specifically all non-tumour diseases, 1.63 (95% CI 1.43, 2.00), non-malignant pulmonary disease, 1.70 (95% CI 1.17, 2.76) and other non-tumour diseases, 1.47 (95% CI 1.29, 1.82). However, for a rather larger group of malignant endpoints the low-dose extrapolation factor is significantly less than 1 (implying downward curvature), with central estimates generally ranging from 0.2 to 0.8, in particular for tumours of the respiratory system, vasculature, ovary, kidney/urinary bladder and testis. For neutron exposure most endpoints, malignant and non-malignant, show downward curvature in the dose response, and for most endpoints this is statistically significant (p < 0.05). Associated with this, the low-dose extrapolation factor associated with neutron exposure is generally statistically significantly less than 1 for most malignant and non-malignant endpoints, with central estimates mostly in the range 0.1–0.9. In contrast to the situation at higher dose rates, there are statistically non-significant decreases of risk per unit dose at gamma dose rates of less than or equal to 5 mGy/h for most malignant endpoints, and generally non-significant increases in risk per unit dose at gamma dose rates ≤5 mGy/h for most non-malignant endpoints. Associated with this, the dose-rate extrapolation factor, the ratio of high dose-rate to low dose-rate (≤5 mGy/h) gamma dose response slopes, for many tumour sites is in the range 1.2–2.3, albeit not statistically significantly elevated from 1, while for most non-malignant endpoints the gamma dose-rate extrapolation factor is less than 1, with most estimates in the range 0.2–0.8. After neutron exposure there are non-significant indications of lower risk per unit dose at dose rates ≤5 mGy/h compared to higher dose rates for most malignant endpoints, and for all tumours (p = 0.001), and respiratory tumours (p = 0.007) this reduction is conventionally statistically significant; for most non-malignant outcomes risks per unit dose non-significantly increase at lower dose rates. Associated with this, the neutron dose-rate extrapolation factor is less than 1 for most malignant and non-malignant endpoints, in many cases statistically significantly so, with central estimates mostly in the range 0.0–0.2.     

Methods for evaluating variability in human health dose–response characterization

Abstract

The Reference Dose (RfD) and Reference Concentration (RfC) are human health reference values (RfVs) representing exposure concentrations at or below which there is presumed to be little risk of adverse effects in the general human population. The 2009 National Research Council report Science and Decisions recommended redefining RfVs as “a risk-specific dose (for example, the dose associated with a 1 in 100,000 risk of a particular end point).” Distributions representing variability in human response to environmental contaminant exposures are critical for deriving risk-specific doses. Existing distributions estimating the extent of human toxicokinetic and toxicodynamic variability are based largely on controlled human exposure studies of pharmaceuticals. New data and methods have been developed that are designed to improve estimation of the quantitative variability in human response to environmental chemical exposures. Categories of research with potential to provide new data useful for developing updated human variability distributions include controlled human experiments, human epidemiology, animal models of genetic variability, in vitro estimates of toxicodynamic variability, and in vitro-based models of toxicokinetic variability. In vitro approaches, with further development including studies of different cell types and endpoints, and approaches to incorporate non-genetic sources of variability, appear to provide the greatest opportunity for substantial near-term advances.     

Fisher's geometrical model and the mutational patterns of antibiotic resistance across dose gradients

Fisher's geometrical model (FGM) has been widely used to depict the fitness effects of mutations. It is a general model with few underlying assumptions that gives a large and comprehensive view of adaptive processes. It is thus attractive in several situations, for example adaptation to antibiotics, but comes with limitations, so that more mechanistic approaches are often preferred to interpret experimental data. It might be possible however to extend FGM assumptions to better account for mutational data. This is theoretically challenging in the context of antibiotic resistance because resistance mutations are assumed to be rare. In this article, we show with Escherichia coli how the fitness effects of resistance mutations screened at different doses of nalidixic acid vary across a dose‐gradient. We found experimental patterns qualitatively consistent with the basic FGM (rate of resistance across doses, gamma distributed costs) but also unexpected patterns such as a decreasing mean cost of resistance with increasing screen dose. We show how different extensions involving mutational modules and variations in trait covariance across environments, can be discriminated based on these data. Overall, simple extensions of the FGM accounted well for complex mutational effects of resistance mutations across antibiotic doses.     

Pesticide Concentrations in Matrices Collected in the Perinatal Period in a Population of Pregnant Women and Newborns in New Jersey,USA

Gestational exposure to pesticides may adversely affect fetal development and birth outcomes. However, data on fetal exposure and associated health effects in newborns remain sparse. We measured a variety of pesticides and metabolites in maternal urine, maternal serum, cord serum, amniotic fluid, and meconium samples collected at the time of cesarean delivery from 150 women in central New Jersey, USA. Women who used pesticides at home had higher concentrations of pesticides or metabolites in cord serum [e.g., dacthal (p = .007), diethyltoluamide (p = .043), and phthalimide (p = .030)] than those who did not use pesticides, suggesting that residential use of pesticides may contribute to overall exposure as assessed by biomonitoring. Except for orthophenylphenol, the concentrations of most pesticides in biological matrices of this study population were either comparable to or lower than the levels reported in previous studies and in the U.S. general population. The daily exposure estimates of two representative organophosphorus insecticides (chlorpyrifos and diazinon) were lower than most regulatory protection limits (USEPA oral benchmark dose₁₀/100, USEPA reference oral dose, or ATSDR minimal risk levels); however, they were near or at the USEPA's population-adjusted doses for children and women. No abnormal birth outcomes or other clinical endpoints were noted in those newborns who had higher concentrations of orthophenylphenol during the perinatal period.     

Saturation Behavior: a general relationship described by a simple second-order differential equation

Background  

The numerous natural phenomena that exhibit saturation behavior, e.g., ligand binding and enzyme kinetics, have been approached, to date, via empirical and particular analyses. This paper presents a mechanism-free, and assumption-free, second-order differential equation, designed only to describe a typical relationship between the variables governing these phenomena. It develops a mathematical model for this relation, based solely on the analysis of the typical experimental data plot and its saturation characteristics. Its utility complements the traditional empirical approaches.     

Categorical Default Uncertainty Factors-Interspecies Variation and Adequacy of Database

The potential application of categorical (i.e., species, pathway, or group specific) defaults for several components of uncertainty relevant to development of tolerable or reference concentrations/doses is considered-namely, interspecies variation and adequacy of database. For the former, the adequacy of allometric scaling by body surface area as a species-specific default for oral tolerable or reference doses is considered. For the latter, the extent to which data from analyses of subchronic:chronic effect levels, LOAELs/NOAELs, and critical effect levels for complete versus incomplete datasets informs selection of defaults is examined. The relative role of categorical defaults for these aspects is considered in the context of the continuum of increasingly data-informed approaches to characterization of uncertainty and variability that range from default (“presumed protective”) to “biologically based predictive”.     

Deriving Toxicity Values for Organophosphate Nerve Agents: A Position Paper in Support of the Procedures and Rationale for Deriving Oral RfDs for Chemical Warfare Nerve Agents

During the process of deriving oral Reference Dose (RfDs) values for chemical warfare agents, several issues arose regarding the identification of adverse effect levels and the application of uncertainty factors. For those agents that function as cholinesterase inhibitors (e.g., agents VX, GA, GB, and GD), these issues included the following: (1) Is the endpoint of blood cholinesterase inhibition an indicator of toxicity or a biomarker of exposure? (2) Can an experimental animal species be more sensitive than humans, thereby eliminating the need for an animal-to-human uncertainty factor? (3) Can the uncertainty factor that is used to extrapolate from a lowest-observed adverse-effect-level (LOAEL) to a no-observed-adverse-effect-level (NOAEL) be less than the default value of 10? (4) Can an oral RfD be derived from non-oral toxicity data? (5) Can an uncertainty factor of less than 10 be used to extrapolate from subchronic to chronic exposure (e.g., is the critical effect adequately described by the subchronic exposure data)? (6) What constitutes an adequate data base for organophosphate cholinesterase inhibitors, and what uncertainty factor should be used for an incomplete data base? Analysis of relevant data resulted in the following selection and justifications of uncertainty factors. For uncertainty associated with intraspecies extrapolation (UF_H), physiologic and pathologic conditions affecting cholinest-erase activity levels justified maintaining a UF_H of 10 for all of the nerve agents. Because available data indicated that humans tended to be more sensitive than rats regarding anticholinesterase effects, an interspecies variability (UF_A) factor of 10 was retained for agents GA, GB, and GD. For agent VX, however, the available data revealed that the domestic sheep test species exhibited sensitivity equivalent to or greater than that of humans thereby justifying a UF_A of 1. For uncertainties regarding extrapolation from subchronic-to- chronic exposure data, consideration of information on the physiology of cholinergic systems and the available toxicity data for the nerve agents and other cholinest-erase inhibitors indicated that a UF_S of 3 was justified for all four of the nerve agents. For uncertainties regarding LOAEL-to- NOAEL extrapolation (UF_L), the selection of agent GB, GD, and VX doses resulting in cholinesterase inhibition in the absence of clinical signs of toxicity (biomarker of exposure) justified this endpoint as a minimal LOAEL and a UF_L of 3. For agent GA, a NOAEL was used, and therefore no UF_L was required. The uncertainty factor for data base completeness (UF_D), was based upon several considerations. Of primary concern was the fact that chronic toxicity studies are not considered an essential component of the data base requirements for cholinesterase inhibitors because of the unlikelihood that the endpoint will change with an increase in exposure time beyond that defined as a subchronic exposure. Additionally, limited data regarding reproductive and developmental toxicity were not considered to represent critical toxicity endpoints for the nerve agents or cholinesterase inhibitors in general. Although the data base for agents GA, GB, and GD were lacking reproductive and developmental toxicity data to some extent, a UF_D of 3 was justified for the aforementioned reasons. The data base for agent VX was considered complete and a UF_D of 1 was selected for development of the RfD for this agent. A modifying factor (MF) to reflect qualitative assessment of additional uncertainties in the critical study or data base that are not addressed by uncertainty factors was limited to agent GA due to the route-to-route (i.e., intraperitoneal to oral) extrapolation and to insure the equivalent oral NOAEL was not overestimated. This article provides a brief overview of the nerve agents, information on cholinergic systems that is pertinent to deriving toxicity values for nerve agents and other organophosphate cholinesterase inhibitors, and a discussion of key issues regarding the use of uncertainty factors in RfD derivations.     

An Extended Guinier Analysis for Intrinsically Disordered Proteins

Guinier analysis allows model-free determination of the radius of gyration (R_g) of a biomolecule from X-ray or neutron scattering data, in the limit of very small scattering angles. Its range of validity is well understood for globular proteins, but is known to be more restricted for unfolded or intrinsically disordered proteins (IDPs). We have used ensembles of disordered structures from molecular dynamics simulations to investigate which structural properties cause deviations from the Guinier approximation at small scattering angles. We find that the deviation from the Guinier approximation is correlated with the polymer scaling exponent ν describing the unfolded ensemble. We therefore introduce an empirical, ν-dependent, higher-order correction term, to augment the standard Guinier analysis. We test the new fitting scheme using all-atom simulation data for several IDPs and experimental data for both an IDP and a destabilized mutant of a folded protein. In all cases tested, we achieve an accuracy of the inferred R_g within ～ 3% of the true R_g. The method is straightforward to implement and extends the range of validity to a maximum qR_g of ～ 2 versus ～ 1.1 for Guinier analysis. Compared with the Guinier or Debye approaches, our method allows data from wider angles with lower noise to be used to analyze scattering data accurately. In addition to R_g, our fitting scheme also yields estimates of the scaling exponent ν in excellent agreement with the reference ν determined from the underlying molecular ensemble.     

Harmonization: Developing Consistent Guidelines for Applying Mode of Action and Dosimetry Information to Cancer and Noncancer Risk Assessment

The 1983 book, Risk Assessment in the Federal Government: Managing the Process, recommended developing consistent inference guidelines for cancer risk assessment. Over the last 15 years, extensive guidance have been provided for hazard assessment for cancer and other endpoints. However, as noted in several recent reports, much less progress has occurred in developing consistent guidelines for quantitative dose response assessment methodologies. This paper proposes an approach for dose response assessment guided by consideration of mode of action (pharmacodynamics) and tissue dosimetry (pharmacokinetics). As articulated here, this systematic process involves eight steps in which available information is integrated, leading first to quantitative analyses of dose response behaviors in the test species followed by quantitative analyses of relevant human exposures. The process should be equally appropriate for both cancer and noncancer endpoints. The eight steps describe the necessary procedures for incorporating mechanistic data and provide multiple options based upon the mode of action by which the chemical causes the toxicity. Given the range of issues involved in developing such a procedure, we have simply sketched the process, focusing on major approaches for using toxicological data and on major options; many details remain to be filled in. However, consistent with the revised carcinogen risk assessment guidance (USEPA, 1996c), we propose a process that would ultimately utilize biologically based or chemical specific pharmacokinetic and pharmacodynamic models as the backbone of these analyses. In the nearer term, these approaches will be combined with analysis of data using more empirical models including options intended for use in the absence of detailed information. A major emphasis in developing any harmonized process is distinguishing policy decisions from those decisions that are affected by the quality and quantity of toxicological data. Identification of data limitations also identifies areas where further study should reduce uncertainty in the final risk evaluations. A flexible dose response assessment procedure is needed to insure that sound toxicological study results are appropriately used to influence risk management decision-making and to encourage the conduct of toxicological studies oriented toward application for dose response assessments.     

Development of a Physiologically Based Model to Describe the Pharmacokinetics of Methylphenidate in Juvenile and Adult Humans and Nonhuman Primates

The widespread usage of methylphenidate (MPH) in the pediatric population has received considerable attention due to its potential effect on child development. For the first time a physiologically based pharmacokinetic (PBPK) model has been developed in juvenile and adult humans and nonhuman primates to quantitatively evaluate species- and age-dependent enantiomer specific pharmacokinetics of MPH and its primary metabolite ritalinic acid. The PBPK model was first calibrated in adult humans using in vitro enzyme kinetic data of MPH enantiomers, together with plasma and urine pharmacokinetic data with MPH in adult humans. Metabolism of MPH in the small intestine was assumed to account for the low oral bioavailability of MPH. Due to lack of information, model development for children and juvenile and adult nonhuman primates primarily relied on intra- and interspecies extrapolation using allometric scaling. The juvenile monkeys appear to metabolize MPH more rapidly than adult monkeys and humans, both adults and children. Model prediction performance is comparable between juvenile monkeys and children, with average root mean squared error values of 4.1 and 2.1, providing scientific basis for interspecies extrapolation of toxicity findings. Model estimated human equivalent doses in children that achieve similar internal dose metrics to those associated with pubertal delays in juvenile monkeys were found to be close to the therapeutic doses of MPH used in pediatric patients. This computational analysis suggests that continued pharmacovigilance assessment is prudent for the safe use of MPH.     

Cope's Rule and the evolution of long-distance transport in vascular plants: allometric scaling, biomass partitioning and optimization

Recent advances in allometric theory have proposed a novel quantitative framework by which to view the evolution of plant form and function. This general theory has placed strong emphasis on the importance of long‐distance transport in shaping the evolution of many attributes of plant form and function. Specifically, it is hypothesized that with the evolutionary increase in plant size natural selection has also resulted in vascular networks that minimize scaling of total hydrodynamic resistance associated with increasing transport distances. Herein the central features of this theory are reviewed and a broad sampling of supporting but yet preliminary empirical data are analysed. In particular, subtle attributes of the scaling of tracheid and vessel anatomy are hypothesized to be crucial for the evolution of increased plant size. Furthermore, the importance of minimizing hydrodynamic resistance associated with increased transport distances is also hypothesized to be reflected in an isometric scaling relationship between stem mass, M_S and root mass, M_R(i.e. M_S ∝ M_R). Preliminary data from multiple extant and fossil plant taxa provide tantalizing evidence supporting the predicted relationships. Together, these results suggest that selection for the minimization of the scaling of hydrodynamic resistance within plant vascular networks has in turn allowed for the enormous diversification in vascular plant size.     

Precision of allometric scaling equations for trees can be improved by including the effect of ecological interactions

Allometric scaling relationships of the form Y = aX ^b are widely utilized in many types of models and analyses of tree structure. They are often viewed as static relationships where both the scaling exponent (b) and the normalization constant (a) obtain empirical values that are fixed within a single set of data. Among different sets of data, their values can show environmental variability. However, there have been only few attempts to give a mechanistic interpretation for this variability. We used field data to demonstrate how the scaling relationships in trees can be modified by ecological interactions. Moreover, we show how such processes can be incorporated into the scaling models to improve the fit and the information content of the scaling equations. When fixed theoretical scaling exponents were used instead of empirical exponents and when the effect of competitive interactions between trees was described by separate submodels that predicted the value of the normalisation constant in the scaling equations, it was possible to obtain 4–10% improvement in the model fit of three different structural scaling relationships. Our results suggest that unexplained variation in the values of the scaling parameters can be substituted by an identified effect of ecological factors on the value of the normalisation constant. This agrees with recent theoretical suggestions stating that ecological factors can directly influence the value of normalisation constants.     

Systematic review of experimental studies on the relative biological effectiveness of tritium

Tritium (³H) is a radioactive isotope of hydrogen. A number of factors combine to create a good deal of interest in tritium doses, both to workers and to members of the public. Tritium is ubiquitous in environmental and biological systems and is very mobile due to its occurrence as water. In this study we systematically review experimental data relating to tritium exposure with a view to assessing its low dose limiting relative biological effectiveness (RBE_max). Interpretation of published experimental studies is complicated by the fact that the reference radiations varied, and doses and dose rates were frequently much higher than those normally received by humans. The four available animal carcinogenicity studies gave RBE values of about 2.5 with chronically-delivered γ-ray reference, and about 1.2 with chronically-delivered X-ray reference. However, because of problems associated with the design and interpretation of the experiments, we do not consider that these RBE values should be taken to apply to the induction of cancer at low doses (i.e. they should not be interpreted as RBE_max). Combining the six studies with chronic γ-ray reference, with adequate quantitative data that examined endpoints apart from cell survival and related endpoints, yields an aggregate RBE estimate of 2.19 (95% CI 2.04, 2.33); the analogous combined RBE estimate using the three studies with chronic X-ray reference groups is 1.17 (95% CI 0.96, 1.39). Again, problems with the design, in particular the range of doses used in some of these studies, mean that these RBE values should also probably not be interpreted as RBE_max.     

Dose Scaling and Extrapolation Across Age Groups

This paper considers how the logic of cross-species dose scaling applies (or does not apply) when extrapolating among differently sized humans, and specifically, when extrapolating to children. Scaling children's doses by a power of body weight predicts that they would be less sensitive to chemicals than adults, owing to faster clearance. Possible countervailing factors, however, are the role of quicker pharmacodynamic processes, differences between interspecific and ontogenetic allometry, and the complex role of inherent differences in the metabolism and physiological system of immature bodies, the last leading to uncertainty in extrapolation but not necessarily to systematic sensitivity among children. The issue of scale per se does not appear to provide a basis for positing a systematically greater sensitivity of children to toxic substances     

Enhancement of phototropic response to a range of light doses in Triticum aestivum coleoptiles in clinostat-simulated microgravity

The phototropic dose-response relationship has been determined for Triticum aestivum cv. Broom coleoptiles growing on a purpose-built clinostat apparatus providing gravity compensation by rotation about a horizontal axis at 2 rev·min^-1. These data are compared with data sets obtained with the clinostat axis vertical and stationary, as a 1·g control, and rotating vertically to examine clinostat effects other than gravity compensation. Triticum at 1·g follows the wellestablished pattern of other cereal coleoptiles with a first positive curvature at low doses, followed by an indifferent response region, and a second positive response at progressively increasing doses. However, these response regions lie at higher dose levels than reported for Avena. There is no significant difference between the responses observed with the clinostat axis vertical in the rotating and stationary modes, but gravity compensation by horizontal rotation increases the magnitude of first and second positive curvatures some threefold at 100 min after stimulation. The indifferent response is replaced by a significant curvature towards the light source, but remains apparent as a reduced curvature response at these dose levels.     

Reconciling the optimal and empirical approaches to modelling stomatal conductance

Models of vegetation function are widely used to predict the effects of climate change on carbon, water and nutrient cycles of terrestrial ecosystems, and their feedbacks to climate. Stomatal conductance, the process that governs plant water use and carbon uptake, is fundamental to such models. In this paper, we reconcile two long‐standing theories of stomatal conductance. The empirical approach, which is most commonly used in vegetation models, is phenomenological, based on experimental observations of stomatal behaviour in response to environmental conditions. The optimal approach is based on the theoretical argument that stomata should act to minimize the amount of water used per unit carbon gained. We reconcile these two approaches by showing that the theory of optimal stomatal conductance can be used to derive a model of stomatal conductance that is closely analogous to the empirical models. Consequently, we obtain a unified stomatal model which has a similar form to existing empirical models, but which now provides a theoretical interpretation for model parameter values. The key model parameter, g₁, is predicted to increase with growth temperature and with the marginal water cost of carbon gain. The new model is fitted to a range of datasets ranging from tropical to boreal trees. The parameter g₁ is shown to vary with growth temperature, as predicted, and also with plant functional type. The model is shown to correctly capture responses of stomatal conductance to changing atmospheric CO₂, and thus can be used to test for stomatal acclimation to elevated CO₂. The reconciliation of the optimal and empirical approaches to modelling stomatal conductance is important for global change biology because it provides a simple theoretical framework for analyzing, and simulating, the coupling between carbon and water cycles under environmental change.     

Replacing the Default Values of 10 With Data-Derived Values: A Comparison of Two Different Data-Derived Uncertainty Factors for Boron

A “safe” or sub-threshold dose is often estimated for oral toxicity of substances in order to protect humans from adverse health effects. This dose is referred to by several terms: reference dose (RfD), tolerable daily intake (TDI), and acceptable daily intake (ADI). Similarly, tolerable concentration (TC), and reference concentration (RfC) are commonly used terms for a “safe” concentration for inhalation. The process of deriving these doses generally involves identifying a no observed, or lowest observed adverse effect level (NOAEL or LOAEL) in animals, or humans, and application of uncertainty factors to account for the extrapolation from laboratory animals to humans and/or from an average human to a sensitive human. Public health agencies have begun to consider using a data derived approach, which uses available toxicokinetic and toxicodynamic data in the determination of uncertainty factors, rather than relying on the standard default values. Recently two different tolerable daily intake risk values were derived by two different World Health Organization (WHO) work groups. The International Programme on Chemical Safety, and the Working Group on Chemical Substances in Drinking Water both used the approach developed by Renwick (1993); however, the two groups interpreted and used the available data differently. The result was a difference of over twofold in the total uncertainty factor used. This review compares and contrasts the two approaches used by these WHO work groups.     

Spatial Heterogeneity in Habitat Quality and Cross-Scale Interactions in Metapopulations

Abstract Integration of habitat heterogeneity into spatially realistic metapopulation approaches reveals the potential for key cross-scale interactions. Broad-scale environmental gradients and land-use practices can create autocorrelation of habitat quality of suitable patches at intermediate spatial scales. Patch occupancy then depends not only on habitat quality at the patch scale but also on feedbacks from surrounding neighborhoods of autocorrelated patches. Metapopulation dynamics emerge from how demographic and dispersal processes interact with relevant habitat heterogeneity. We provide an empirical example from a metapopulation of round-tailed muskrats (Neofiber alleni) in which habitat quality of suitable patches was spatially autocorrelated most strongly within 1,000 m, which was within the expected dispersal range of the species. After controlling for factors typically considered in metapopulation studies—patch size, local patch quality, patch connectivity—we use a cross-variogram analysis to demonstrate that patch occupancy by muskrats was correlated with habitat quality across scales ≤1,171 m. We also discuss general consequences of spatial heterogeneity of habitat quality for metapopulations related to potential cross-scale interactions. We focus on spatially correlated extinctions and metapopulation persistence, hierarchical scaling of source–sink dynamics, and dispersal decisions by individuals in relation to information constraints.