Pathology effects at radiation doses below those causing increased mortality

Mortality data from experiments conducted at the Argonne National Laboratory (ANL) on the long-term effects of external whole-body irradiation on B6CF(1) mice were used to investigate radiation-induced effects at intermediate doses of (60)Co gamma rays or fission-spectrum neutrons either delivered as a single exposure or protracted over 60 once-weekly exposures. Kaplan-Meier analyses were used to identify the lowest dose in the ANL data (within radiation quality, pattern of exposure, and sex) at which radiation-induced mortality caused by primary tumors could be detected (approximately 1-2 Gy for gamma rays and 10-15 cGy for neutrons). Doses at and below these levels were then examined for radiation-induced shifts in the spectrum of pathology detected at death. To do this, specific pathology events were pooled into larger assemblages based on whether they were cancer, cardiovascular disease or non-neoplastic diseases detected within the lungs and pleura, liver and biliary tract, reproductive organs, or urinary tract. Cancer and cardiovascular disease were further subdivided into categories based on whether they caused death, contributed to death, or were simply observed at death. Counts of how often events falling within each of these combined pathology categories occurred within a mouse were then used as predictor variables in logistic regression to determine whether irradiated mice could be distinguished from control mice. Increased pathology burdens were detected in irradiated mice at doses lower than those causing detectable shifts in mortality-22 cGy for gamma rays and 2 cGy for neutrons. These findings suggest that (1) models based on mortality data alone may underestimate radiation effects, (2) radiation may have adverse health consequences (i.e. elevated health risks) even when mortality risks are not detected, and (3) radiation-induced pathologies other than cancer do occur, and they involve multiple organ systems.     

A two-mutation model of radiation-induced acute myeloid leukemia using historical mouse data

From studies of the atomic bomb survivors, it is well known that ionizing radiation causes several forms of leukemia. However, since the specific mechanism behind this process remains largely unknown, it is difficult to extrapolate carcinogenic effects at acute high-dose exposures to risk estimates for the chronic low-dose exposures that are important for radiation protection purposes. Recently, it has become clear that the induction of acute myeloid leukemia (AML) in CBA/H mice takes place through two key steps, both involving the Sfpi1 gene. A similar mechanism may play a role in human radiation-induced AML. In the present paper, a two-mutation carcinogenesis model is applied to model AML in several data sets of X-ray- and neutron-exposed CBA/H mice. The models obtained provide good fits to the data. A comparison between the predictions for neutron-induced and X-ray-induced AML yields an RBE for neutrons of approximately 3. The model used is considered to be a first step toward a model for human radiation-induced AML, which could be used to estimate risks of exposure to low doses.     

52 Beta-dimethylsulfoniopropionate (Dmsp) as a grazing deterrent in coastal phytoplankton communities

One of the most commonly predicted effects of global ocean warming on marine communities is a poleward shift in the distribution of species with an associated replacement of cold-water species by warm-water species. Such predictions are imprecise and based largely on broad correlations in uncontrolled studies that examine changes in species composition and abundance relative to seawater temperature. Before-After-Control-Impact (BACI) analyses of the effects of a large thermal discharge shows that an induced 3.4 deg. C rise in seawater temperature over 10 years along 2 km of rocky coastline resulted in significant community-wide changes in 150 species of algae and invertebrates relative to controls. Contrary to predictions from biogeographic models, there was no trend towards warm-water species with southern geographic affinities replacing cold-species with northern affinities. Instead, communities were greatly altered in apparently cascading responses to changes in abundance of several habitat-forming taxa, particularly subtidal kelps (e.g. Pterygophora californica ) and intertidal foliose red algae (e.g. Mazzaella flaccida ). Many temperature sensitive algae decreased greatly in abundance, whereas many invertebrate grazers increased. The results indicate that the responses of temperate reef communities to ocean warming can be strongly coupled to direct effects on habitat-forming taxa and indirect effects operating through ecological interactions. Given our understanding of temperate reef ecology and its local variability, the results also suggest that accurate predictions of the effects of global ocean warming will be difficult to make.     

Radioprotection by mangiferin in DBAxC57BL mice: a preliminary study

The radioprotective effects of various concentrations (0, 0.25, 0.5, 1, 2, 5, 10, 17.5, 25, 50, 75 and 100 mg/kg b.wt.) of mangiferin (MGN) was studied in the DBAxC57BL mice whole body exposed to 10 Gy of gamma-irradiation. Treatment of mice with different doses of MGN, one hour before irradiation reduced the symptoms of radiation sickness and delayed the onset of mortality when compared with the non-drug treated irradiated controls. The radioprotective action of MGN increased in a dose dependent manner up to 2mg/kg and declined thereafter. The highest radioprotective effect was observed at 2mg/kg MGN, where greatest number of animals survived against the radiation-induced mortality. The administration of 0.5, 1, 2, 5, 10 and 17.5 mg/kg MGN reduced the radiation-induced gastrointestinal death as evident by a greater number of survivors up to 10 days in this group when compared with the DDW + 10 Gy irradiation group. A similar effect of MGN was observed for the radiation-induced bone marrow deaths also. Our study demonstrates that mangiferin, a gluosylxanthone, present in the Mangifera indica protected mice against the radiation-induced sickness and mortality and the optimum protective dose of 2mg/kg was 1/200 of LD50 dose (400 mg/kg) of MGN. The administration of 400 mg/kg MGN induced 50% mortality, therefore LD50 of the drug was considered to be 400 mg/kg.     

Critical appraisals allow the analytical review of existing knowledge on current topics of significance in ecological entomology. They should assess the worth or quality of the work in the field and suggest areas for investigation.

Summary. Previous studies have synthesized life-table data from herbivore species to identify general trends in the demography of herbivorous insects. Frequency-based analyses were used to ascertain which of five mortality sources (enemies, plant factors, competition, weather, intrinsic developmental failure) and which of five ecological characteristics of herbivores (feeding biology, invasion status of the herbivore, latitude, cultivation, and successional status of the habitat) had important influences on mortality patterns. Here these results are reinforced with a quantitative analysis that relies on actual numbers of herbivores killed at different developmental stages by each of the five mortality sources in different ecological settings. We also examine the relationship between taxonomic category (Coleoptera, Diptera, Lepidoptera, and Hymenoptera) and mortality. The analysis identified developmental changes of herbivores as having an important influence on sources of mortality; feeding biology, latitude, and cultivation status also influenced the distribution of mortality sources. Other aspects of the herbivores’ ecology and taxonomy had limited effects. Natural enemies were identified as the most important mortality source overall, and their importance increased from the early larval stages to the pupal stages. They also kill more exophytic insects than endophytic insects, and kill a higher proportion of insects in cultivated habitats than in natural habitats. Weather kills more temperate-zone immatures than tropical/subtropical immatures. The results of the quantitative analysis generally confirm the earlier frequency-based tests. Several predictions that can serve as the foundation of an empirically-based theory of herbivore demography are offered: (1) natural enemies are the dominant cause of mortality in exophytic herbivore populations and may compete more intensely than on endophytics; (2) plant factors and enemies play a more balanced role in endophytic populations; (3) exophytic species should be particularly susceptible to top-down effects, especially in agroecosystems; (4) plant defences will often have sublethal effects, but when they are lethal they will be most important as the hatchling larva is just getting established on the plant. These predictions should be viewed as a challenge to engage in a broader way of thinking about herbivore demography.     

Predicting cancer rates in astronauts from animal carcinogenesis studies and cellular markers

The radiation space environment includes particles such as protons and multiple species of heavy ions, with much of the exposure to these radiations occurring at extremely low average dose-rates. Limitations in databases needed to predict cancer hazards in human beings from such radiations are significant and currently do not provide confidence that such predictions are acceptably precise or accurate. In this article, we outline the need for animal carcinogenesis data based on a more sophisticated understanding of the dose-response relationship for induction of cancer and correlative cellular endpoints by representative space radiations. We stress the need for a model that can interrelate human and animal carcinogenesis data with cellular mechanisms. Using a broad model for dose-response patterns which we term the "subalpha-alpha-omega (SAO) model", we explore examples in the literature for radiation-induced cancer and for radiation-induced cellular events to illustrate the need for data that define the dose-response patterns more precisely over specific dose ranges, with special attention to low dose, low dose-rate exposure. We present data for multiple endpoints in cells, which vary in their radiosensitivity, that also support the proposed model. We have measured induction of complex chromosome aberrations in multiple cell types by two space radiations, Fe-ions and protons, and compared these to photons delivered at high dose-rate or low dose-rate. Our data demonstrate that at least three factors modulate the relative efficacy of Fe-ions compared to photons: (i) intrinsic radiosensitivity of irradiated cells; (ii) dose-rate; and (iii) another unspecified effect perhaps related to reparability of DNA lesions. These factors can produce respectively up to at least 7-, 6- and 3-fold variability. These data demonstrate the need to understand better the role of intrinsic radiosensitivity and dose-rate effects in mammalian cell response to ionizing radiation. Such understanding is critical in extrapolating databases between cellular response, animal carcinogenesis and human carcinogenesis, and we suggest that the SAO model is a useful tool for such extrapolation.     

51 Characterization of the northwestern gulf of Mexico macroalgae

One of the most commonly predicted effects of global ocean warming on marine communities is a poleward shift in the distribution of species with an associated replacement of cold‐water species by warm‐water species. Such predictions are imprecise and based largely on broad correlations in uncontrolled studies that examine changes in species composition and abundance relative to seawater temperature. Before‐After‐Control‐Impact (BACI) analyses of the effects of a large thermal discharge shows that an induced 3.4 deg. C rise in seawater temperature over 10 years along 2 km of rocky coastline resulted in significant community‐wide changes in 150 species of algae and invertebrates relative to controls. Contrary to predictions from biogeographic models, there was no trend towards warm‐water species with southern geographic affinities replacing cold‐species with northern affinities. Instead, communities were greatly altered in apparently cascading responses to changes in abundance of several habitat‐forming taxa, particularly subtidal kelps (e.g. Pterygophora californica) and intertidal foliose red algae (e.g. Mazzaella flaccida). Many temperature sensitive algae decreased greatly in abundance, whereas many invertebrate grazers increased. The results indicate that the responses of temperate reef communities to ocean warming can be strongly coupled to direct effects on habitat‐forming taxa and indirect effects operating through ecological interactions. Given our understanding of temperate reef ecology and its local variability, the results also suggest that accurate predictions of the effects of global ocean warming will be difficult to make.     

The International Mouse Phenotyping Consortium (IMPC): a functional catalogue of the mammalian genome that informs conservation

The International Mouse Phenotyping Consortium (IMPC) is building a catalogue of mammalian gene function by producing and phenotyping a knockout mouse line for every protein-coding gene. To date, the IMPC has generated and characterised 5186 mutant lines. One-third of the lines have been found to be non-viable and over 300 new mouse models of human disease have been identified thus far. While current bioinformatics efforts are focused on translating results to better understand human disease processes, IMPC data also aids understanding genetic function and processes in other species. Here we show, using gorilla genomic data, how genes essential to development in mice can be used to help assess the potentially deleterious impact of gene variants in other species. This type of analyses could be used to select optimal breeders in endangered species to maintain or increase fitness and avoid variants associated to impaired-health phenotypes or loss-of-function mutations in genes of critical importance. We also show, using selected examples from various mammal species, how IMPC data can aid in the identification of candidate genes for studying a condition of interest, deliver information about the mechanisms involved, or support predictions for the function of genes that may play a role in adaptation. With genotyping costs decreasing and the continued improvements of bioinformatics tools, the analyses we demonstrate can be routinely applied.     

A manganese porphyrin complex is a novel radiation protector

Exposure of cells to ionizing radiation leads to formation of reactive oxygen species, which are associated with radiation-induced cytotoxicity. Therefore, compounds that scavenge reactive oxygen species may confer radioprotective effects. Superoxide dismutase (SOD) mimetics have been shown to be protective against cell injury caused by reactive oxygen species. The objective of this study was to investigate the effects of manganese(III) tetrakis(N-methyl-2-pyridyl)porphyrin (MnTMPyP), a cell-permeable SOD mimetic, on radiation-dependent toxicity. We investigated the protective role of MnTMPyP against ionizing radiation in U937 cells and mice. On exposure to ionizing radiation, there was a distinct difference between control cells and cells pretreated with MnTMPyP with respect to viability, cellular redox status, and oxidative damage to cells. Lipid peroxidation, oxidative DNA damage, and protein oxidation were significantly lower in the cells treated with MnTMPyP when the cells were exposed to ionizing radiation. The [GSSG]/[GSH + GSSG] ratio and the generation of intracellular reactive oxygen species were higher and the [NADPH]/[NADP+ + NADPH] ratio was lower in control cells compared with MnTMPyP-treated cells. Ionizing radiation-induced mitochondrial damage, as reflected by the altered mitochondrial permeability transition, increase in accumulation of reactive oxygen species, reduction of ATP production, and morphological change, was significantly higher in control cells than in MnTMPyP-treated cells. MnTMPyP administration for 14 days at a daily dosage of 5 mg/kg provided substantial protection against killing and oxidative damage in mice exposed to whole-body irradiation. These data indicate that MnTMPyP may have great application potential as a new class of in vivo, non-sulfur-containing radiation protectors.     

Biotic interactions boost spatial models of species richness

Biotic interactions are known to affect the composition of species assemblages via several mechanisms, such as competition and facilitation. However, most spatial models of species richness do not explicitly consider inter‐specific interactions. Here, we test whether incorporating biotic interactions into high‐resolution models alters predictions of species richness as hypothesised. We included key biotic variables (cover of three dominant arctic‐alpine plant species) into two methodologically divergent species richness modelling frameworks – stacked species distribution models (SSDM) and macroecological models (MEM) – for three ecologically and evolutionary distinct taxonomic groups (vascular plants, bryophytes and lichens). Predictions from models including biotic interactions were compared to the predictions of models based on climatic and abiotic data only. Including plant–plant interactions consistently and significantly lowered bias in species richness predictions and increased predictive power for independent evaluation data when compared to the conventional climatic and abiotic data based models. Improvements in predictions were constant irrespective of the modelling framework or taxonomic group used. The global biodiversity crisis necessitates accurate predictions of how changes in biotic and abiotic conditions will potentially affect species richness patterns. Here, we demonstrate that models of the spatial distribution of species richness can be improved by incorporating biotic interactions, and thus that these key predictor factors must be accounted for in biodiversity forecasts.     

Model-based uncertainty in species range prediction

Aim Many attempts to predict the potential range of species rely on environmental niche (or ‘bioclimate envelope’) modelling, yet the effects of using different niche‐based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions, identify key reasons why model output may differ and discuss the implications that model uncertainty has for policy‐guiding applications. Location The Western Cape of South Africa. Methods We applied nine of the most widely used modelling techniques to model potential distributions under current and predicted future climate for four species (including two subspecies) of Proteaceae. Each model was built using an identical set of five input variables and distribution data for 3996 sampled sites. We compare model predictions by testing agreement between observed and simulated distributions for the present day (using the area under the receiver operating characteristic curve (AUC) and kappa statistics) and by assessing consistency in predictions of range size changes under future climate (using cluster analysis). Results Our analyses show significant differences between predictions from different models, with predicted changes in range size by 2030 differing in both magnitude and direction (e.g. from 92% loss to 322% gain). We explain differences with reference to two characteristics of the modelling techniques: data input requirements (presence/absence vs. presence‐only approaches) and assumptions made by each algorithm when extrapolating beyond the range of data used to build the model. The effects of these factors should be carefully considered when using this modelling approach to predict species ranges. Main conclusions We highlight an important source of uncertainty in assessments of the impacts of climate change on biodiversity and emphasize that model predictions should be interpreted in policy‐guiding applications along with a full appreciation of uncertainty.     

Why georeferencing matters: Introducing a practical protocol to prepare species occurrence records for spatial analysis

Species Distribution Models (SDMs) are widely used to understand environmental controls on species’ ranges and to forecast species range shifts in response to climatic changes. The quality of input data is crucial determinant of the model's accuracy. While museum records can be useful sources of presence data for many species, they do not always include accurate geographic coordinates. Therefore, actual locations must be verified through the process of georeferencing. We present a practical, standardized manual georeferencing method (the Spatial Analysis Georeferencing Accuracy (SAGA) protocol) to classify the spatial resolution of museum records specifically for building improved SDMs. We used the high‐elevation plant Saxifraga austromontana Wiegand (Saxifragaceae) as a case study to test the effect of using this protocol when developing an SDM. In MAXENT, we generated and compared SDMs using a comprehensive occurrence dataset that had undergone three different levels of georeferencing: (1) trained using all publicly available herbarium records of the species, minus outliers (2) trained using herbarium records claimed to be previously georeferenced, and (3) trained using herbarium records that we have manually georeferenced to a ≤ 1‐km resolution using the SAGA protocol. Model predictions of suitable habitat for S. austromontana differed greatly depending on georeferencing level. The SDMs fitted with presence locations georeferenced using SAGA outperformed all others. Differences among models were exacerbated for future distribution predictions. Under rapid climate change, accurately forecasting the response of species becomes increasingly important. Failure to georeference location data and cull inaccurate samples leads to erroneous model output, limiting the utility of spatial analyses. We present a simple, standardized georeferencing method to be adopted by curators, ecologists, and modelers to improve the geographic accuracy of museum records and SDM predictions.     

Nicaraven Attenuates Radiation-Induced Injury in Hematopoietic Stem/Progenitor Cells in Mice

Nicaraven, a chemically synthesized hydroxyl radical-specific scavenger, has been demonstrated to protect against ischemia-reperfusion injury in various organs. We investigated whether nicaraven can attenuate radiation-induced injury in hematopoietic stem/progenitor cells, which is the conmen complication of radiotherapy and one of the major causes of death in sub-acute phase after accidental exposure to high dose radiation. C57BL/6 mice were exposed to 1 Gy γ-ray radiation daily for 5 days in succession (a total of 5 Gy), and given nicaraven or a placebo after each exposure. The mice were sacrificed 2 days after the last radiation treatment, and the protective effects and relevant mechanisms of nicaraven in hematopoietic stem/progenitor cells with radiation-induced damage were investigated by ex vivo examination. We found that post-radiation administration of nicaraven significantly increased the number, improved the colony-forming capacity, and decreased the DNA damage of hematopoietic stem/progenitor cells. The urinary levels of 8-oxo-2′-deoxyguanosine, a marker of DNA oxidation, were significantly lower in mice that were given nicaraven compared with those that received a placebo treatment, although the levels of intracellular and mitochondrial reactive oxygen species in the bone marrow cells did not differ significantly between the two groups. Interestingly, compared with the placebo treatment, the administration of nicaraven significantly decreased the levels of the inflammatory cytokines IL-6 and TNF-α in the plasma of mice. Our data suggest that nicaraven effectively diminished the effects of radiation-induced injury in hematopoietic stem/progenitor cells, which is likely associated with the anti-oxidative and anti-inflammatory properties of this compound.     

The importance of assessing parameter sensitivity when using biophysical models: a case study using plethodontid salamanders

Landscapes are continually changing due to numerous assaults, including habitat alteration, anthropogenic disturbances, and climate change. Understanding how species will respond to these changes is of critical importance for conservation and management. Mechanistic models, such as biophysical models (BPMs), are an increasingly popular tool to predict how local population dynamics or species’ distributions may be altered in response to environmental and climate changes. By mechanistically modeling relationships between environmental conditions, physiology and behavior, it is possible to make accurate predictions about how species may respond. However, BPMs are often difficult to implement due to lack of appropriate, species-specific data that is biologically realistic or relevant. In this study, we present a BPM for the salamander Plethodon jordani and assess how adding more biological realism has potential to alter model predictions about annual energy budgets. Additionally, we conducted local and global sensitivity analyses to evaluate the importance of accurately specifying model parameter values and functional relationships. We found that the addition of biological realism resulted in greater model complexity as well as substantially different estimates of energy balance. Correct parameterization of biophysical models is also critical, as small changes in parameter values can result in disproportionately large changes in downstream model estimates. Our model highlights the overall importance of using ecologically relevant and specific data for input parameters, as well as careful assessment of parameter sensitivity. We encourage researchers to be aware of the data they are using to parameterize BPMs, and urge the collection of system-specific data that is relevant in spatial and temporal scale. We also recommend greater and more transparent use of sensitivity analyses to provide a better understanding of the model, as well as greater confidence in model predictions.     

Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model

Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species‐based Dynamic Bioclimate Envelope Model (DBEM) with a size‐based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness‐of‐fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter‐specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment.     

Back-casting sociality in extinct species: new perspectives using mass death assemblages and sex ratios

Despite 150 years of interest in the ecology of dinosaurs, mammoths, proto-hominids and other extinct vertebrates, a general framework to recreate patterns of sociality has been elusive. Based on our recent discovery of a contemporary heterospecific mass death assemblage in the Gobi Desert (Mongolia), we fit predictions about gender-specific associations and group living in extant ungulates to extinct ones. We relied on comparative data on sex-ratio variation and body-size dimorphism, basing analyses on 38 additional mass mortality sites from Asia, Africa, Europe and North America that span 50 million years. Both extant and extinct species died in aggregations with biased adult sex ratios, but the skew (from 1:1) was greater for extinct dimorphic taxa, suggesting that sociality in these extinct species can be predicted from spatial and demographic traits of extant ones. However, extinct rhinos, horses and zebras were inconsistent with predictions about adult sex ratios, which underscores the inherent difficulty in backcasting historic patterns to some monomorphic taxa. These findings shed light not only on the sociality of extinct species but provide a sound, although limited, footing for interpretation of modern death assemblages within the context of the emerging science of taphonomy and palaeobehaviour.     

Highly incomplete taxa can rescue phylogenetic analyses from the negative impacts of limited taxon sampling

Background

Phylogenies are essential to many areas of biology, but phylogenetic methods may give incorrect estimates under some conditions. A potentially common scenario of this type is when few taxa are sampled and terminal branches for the sampled taxa are relatively long. However, the best solution in such cases (i.e., sampling more taxa versus more characters) has been highly controversial. A widespread assumption in this debate is that added taxa must be complete (no missing data) in order to save analyses from the negative impacts of limited taxon sampling. Here, we evaluate whether incomplete taxa can also rescue analyses under these conditions (empirically testing predictions from an earlier simulation study).

Methodology/Principal Findings

We utilize DNA sequence data from 16 vertebrate species with well-established phylogenetic relationships. In each replicate, we randomly sample 4 species, estimate their phylogeny (using Bayesian, likelihood, and parsimony methods), and then evaluate whether adding in the remaining 12 species (which have 50, 75, or 90% of their data replaced with missing data cells) can improve phylogenetic accuracy relative to analyzing the 4 complete taxa alone. We find that in those cases where sampling few taxa yields an incorrect estimate, adding taxa with 50% or 75% missing data can frequently (>75% of relevant replicates) rescue Bayesian and likelihood analyses, recovering accurate phylogenies for the original 4 taxa. Even taxa with 90% missing data can sometimes be beneficial.

Conclusions

We show that adding taxa that are highly incomplete can improve phylogenetic accuracy in cases where analyses are misled by limited taxon sampling. These surprising empirical results confirm those from simulations, and show that the benefits of adding taxa may be obtained with unexpectedly small amounts of data. These findings have important implications for the debate on sampling taxa versus characters, and for studies attempting to resolve difficult phylogenetic problems.     

Bone cancer risk of (239)pu in humans derived from animal models

Two-mutation model fits to bone cancer mortality data from mice, rats and beagle dogs injected with (239)Pu or (226)Ra show that (1) it is possible to fit the radiation-related parameters for animals from different strains of the same species together; (2) for every species the same significant parameters are found in the models for (239)Pu and in the models for (226)Ra, and the only difference is in the value of the linear mutation coefficient; and (3) the toxicity ratio, when defined as the ratio of the linear mutation coefficients for (239)Pu over (226)Ra, has a relatively uniform value of approximately 8 for the species considered. This relatively constant ratio enables the development of a (239)Pu model for humans that is based on the radium dial painters and the toxicity ratio for beagles. The model predictions agree well with published risk estimates based on other data and derived using alternative approaches. This has two important implications: (1) The two-mutation model appears to be a useful tool in translating from animal models to humans in a meaningful way; and (2) once a two-mutation model for humans has been derived, radiation risks can be calculated that depend on doses, dose rates and ages at exposure. Such a model therefore supplements published risk estimates that often lack such dependences.     

Wolf population dynamics in the U.S. Northern Rocky Mountains are affected by recruitment and human-caused mortality

Reliable analyses can help wildlife managers make good decisions, which are particularly critical for controversial decisions such as wolf (Canis lupus) harvest. Creel and Rotella (2010) recently predicted substantial population declines in Montana wolf populations due to harvest, in contrast to predictions made by Montana Fish, Wildlife and Parks (MFWP). We replicated their analyses considering only those years in which field monitoring was consistent, and we considered the effect of annual variation in recruitment on wolf population growth. Rather than assuming constant rates, we used model selection methods to evaluate and incorporate models of factors driving recruitment and human-caused mortality rates in wolf populations in the Northern Rocky Mountains. Using data from 27 area-years of intensive wolf monitoring, we show that variation in both recruitment and human-caused mortality affect annual wolf population growth rates and that human-caused mortality rates have increased with the sizes of wolf populations. We document that recruitment rates have decreased over time, and we speculate that rates have decreased with increasing population sizes and/or that the ability of current field resources to document recruitment rates has recently become less successful as the number of wolves in the region has increased. Estimates of positive wolf population growth in Montana from our top models are consistent with field observations and estimates previously made by MFWP for 2008–2010, whereas the predictions for declining wolf populations of Creel and Rotella (2010) are not. Familiarity with limitations of raw data, obtained first-hand or through consultation with scientists who collected the data, helps generate more reliable inferences and conclusions in analyses of publicly available datasets. Additionally, development of efficient monitoring methods for wolves is a pressing need, so that analyses such as ours will be possible in future years when fewer resources will be available for monitoring. © 2011 The Wildlife Society.