Estimating distemper virus dynamics among wolves and grizzly bears using serology and Bayesian state‐space models

Many parasites infect multiple hosts, but estimating the transmission across host species remains a key challenge in disease ecology. We investigated the within and across host species dynamics of canine distemper virus (CDV) in grizzly bears (Ursus arctos) and wolves (Canis lupus) of the Greater Yellowstone Ecosystem (GYE). We hypothesized that grizzly bears may be more likely to be exposed to CDV during outbreaks in the wolf population because grizzly bears often displace wolves while scavenging carcasses. We used serological data collected from 1984 to 2014 in conjunction with Bayesian state‐space models to infer the temporal dynamics of CDV. These models accounted for the unknown timing of pathogen exposure, and we assessed how different testing thresholds and the potential for testing errors affected our conclusions. We identified three main CDV outbreaks (1999, 2005, and 2008) in wolves, which were more obvious when we used higher diagnostic thresholds to qualify as seropositive. There was some evidence for increased exposure rates in grizzly bears in 2005, but the magnitude of the wolf effect on bear exposures was poorly estimated and depended upon our prior distributions. Grizzly bears were exposed to CDV prior to wolf reintroduction and during time periods outside of known wolf outbreaks, thus wolves are only one of several potential routes for grizzly bear exposures. Our modeling approach accounts for several of the shortcomings of serological data and is applicable to many wildlife disease systems, but is most informative when testing intervals are short. CDV circulates in a wide range of carnivore species, but it remains unclear whether the disease persists locally within the GYE carnivore community or is periodically reintroduced from distant regions with larger host populations.     

The role of recruitment and dispersal limitation in tree community assembly in Amazonian forests

Background: Species composition of plant communities is shaped by the interplay between dispersal limitation, environmental filters and stochastic events.

Aims: The aim of this work was to investigate the effects of dispersal limitation and environmental filtering on tree recruitment. To accomplish this, we employed the unified neutral theory of biodiversity and biogeography to examine migration within the metacommunity, defined as a set of interacting local communities linked by the dispersal of multiple potentially interacting species.

Methods: We sampled 12,975 individuals with dbh ≥ 1 cm in 26 1-ha permanent plots, including habitats of terra firme, transitional forests, várzea and campinarana, on the upper Madeira River, Brazilian Amazon.

Results: Campinarana drew individuals from outside the metacommunity species pool at a mean probability of recruitment of 0.06, a much lower probability than terra firme (0.31), transitional (0.21) and várzea forests (0.22). Environmental variables, such as water table depth, soil texture and fertility, were related to differences in community assembly.

Conclusions: Species abundance distribution and diversity patterns of plant assemblages in a large river landscape in the Amazon highlight the importance of environmental heterogeneity that conditions beta-diversity. The high variation in recruitment probabilities from the metacommunity species pool to local communities suggests high habitat variability in the process of maintaining patterns of local diversity.     

一例母及其亲子DNA指纹与血清蛋白、酯酶遗传的研究

采用ＤＮＡ指纹分析和聚丙烯酰胺凝胶电泳法,对一例与公驴交配生育了后代的母后代进行了亲缘鉴定和血清蛋白、酯酶遗传的分析。结果可以认定其亲子关系并证实母骡生育的事实。虽然本例母的后代在Ｐｒ、Ａｌ、Ｐａ和Ｈｂ、Ｅｓ等基因座位上的基因表达倾向于驴,但其外貌仍明显地带有种间杂种的特征。因此,尚不能简单地认为其已“回归”为纯种的驴。     

Placing empirical limits on metapopulation models for terrestrial plants

Both island-biogeographic (dynamic) and niche-based (static) metapopulation models make predictions about the distribution and abundance of species assemblages. We tested the utility of these models concerning such predictions for terrestrial vascular plants using data from 74 landscapes across the globe. We examined correlations between species frequency and local abundance and shapes of the species frequency distribution. No data set met all of the predictions of any single island-biogeographic metapopulation model. In contrast, all data sets met the predictions of the niche-based model. We conclude that in predicting the distribution of species assemblages of plants over scales greater than 10–1 km, niche-based models are robust while current metapopulation models are insufficient. We discuss limitations in the assumptions of the various models and the types of empirical observations that they will each have to deal with in further developments.     

Modelling and simulation of the architecture and development of the oil-palm (Elaeis guineensis Jacq.) root system

A stochastic model of oil-palm (Elaeis guineensis Jacq.) root system architecture and development has been developed. This model enabled us to create 3-D numerical models of complete root systems by simulation. The application of a postprocessor software, called RACINES, to these 3-D numerical models, provided an estimation of some parameters of plant root systems. The objective of this paper is to present oil-palm root characteristics as possible outputs of the application of this RACINES software. The outputs described in this article cover (i) spatial distribution of roots under plantation conditions, (ii) the estimation and distribution of total root biomass, per root type or per soil horizon and (iii) the location and quantification of absorbent surfaces. The computing techniques used were based on voxellization of space and creation of 3-D virtual sceneries exactly reproducing observed planting designs. By comparing the results of observations and simulations for spatial distribution (by trench wall density maps) and root biomasses (by real and virtual sampling) we were able to carry out additional numerical validations of the model.     

Saltatory search: a theoretical analysis

Many animal search in a saltatory fashion: they move forward,pause briefly, and move forward again. Although many optimal-foragingmodels have been developed, most do not address how an animalsearches for food. We view search strategies as "time-distance"functions to allow not only for the possibility of oscillationsin body speed, as implied by saltatory search, but other movementpatterns as well, including cruise search. The key feature ofour models is distinguishing between the body position and thescan position (where the forager is looking). We see the varyingmovement of saltatory search as a consequence of the curvaturein the functions that relate body speed to benefits (Jensen'sinequality)     

Do U.S. county data disprove linear no‐threshold predictions of lung cancer risk for residential radon?‐A preliminary assessment of biological plausibility

Lung‐cancer mortality (LCM) is elevated in underground miners who chronically inhaled the mutagenic, cytotoxic α‐decay products of radon gas. Epidemiologie studies of LCM rates vs. residential‐radon concentration levels are generally considered inconclusive. However, Cohen (Health Physics 68, 157–174, 1995) has hypothesized that data on LCM vs. residential radon concentrations at the U.S. county level are clearly inconsistent with a linear no‐threshold (LN) dose‐response model, and rather are consistent with threshold or hormesis model. Cohen's hypothesis has been criticized as “ecological fallacy,”; particularly because LN (but not threshold or hormesis) models are generally considered biologically plausible for agents like α radiation that damage DNA in linear proportion to dose. To assess the biological plausibility of Cohen's hypothesis, a preliminary study was made of whether a biologically realistic, cytodynamic 2‐stage (CD2) cancer model can provide a good, joint fit to Cohen's set of U.S. county data as well as to underground‐miner data. The CD2 model used adapts a widely applied, mechanistic, 2‐stage stochastic model of carcinogenesis to realistically account for interrelated cell killing and mutation (both assumed to have a LN dose‐response), cell turnover, and incomplete exposure of stem cells. A CD2 fit was obtained to combined summary data on LCM vs. radon‐exposure in white males in 1, 601 U.S. counties (from Cohen) and in white male Colorado Plateau (CP) uranium miners (from the National Research Council's “BEIRIV”; report). The CD2 fit is shown to: (i) be consistent with the combined data; (ii) have parameter values all consistent with biological data; and (iii) predict inverse dose‐rate‐effects data for CP and other radon‐exposed miners, despite the fact that optimization had not involved any of these dose‐rate data. The latter data were not predicted by a simplified CD2 model in which all stem cells were presumed to be exposed. It is concluded that this study provides preliminary evidence that Cohen's hypothesis is biologically plausible.     

BIOVOLUME CALCULATION FOR PELAGIC AND BENTHIC MICROALGAE

Microalgal biovolume is commonly calculated to assess the relative abundance (as biomass or carbon) of co-occurring algae varying in shape and/or size. However, a standardized set of equations for biovolume calculations from microscopically measured linear dimensions that includes the entire range of microalgal shapes is not available yet. In comparison with automated methods, the use of microscopical measurements allows high taxonomic resolution, up to the species level, and has fewer sources of error. We present a set of geometric shapes and mathematical equations for calculating biovolumes of >850 pelagic and benthic marine and freshwater microalgal genera. The equations are designed to minimize the effort of microscopic measurement. The similarities and differences between our proposal for standardization and previously published proposals are discussed and recommendations for quality standards given.     

LAKE SEDIMENT CHRYSOPHYTE SCALES FROM THE NORTHEASTERN U.S.A. AND THEIR RELATIONSHIP TO ENVIRONMENTAL VARIABLES

Chrysophyte scale assemblages were analyzed in the surface sediments (0–1 cm) of 146 lakes sampled in the U.S. Environmental Protection Agency's (EPA) Environmental Monitoring and Assessment Program–Surface Waters (EMAP-SW) in the northeastern U.S.A. Chrysophyte data from the EMAP lakes were combined with a previous study of 71 Adirondack PIRLA (Paleoecological Investigation of Recent Lake Acidification) lakes and collectively analyzed to examine the indicator potential of scaled chrysophytes in the northeastern U.S.A. with respect to several environmental variables. Canonical correspondence analysis (CCA) was used to determine which environmental variables influenced the distributions of species. Forward selection and Monte Carlo permutation tests showed that 51% of the variance in the chrysophyte assemblages was related to pH. The other six significant variables (conductivity, chloride, total phosphorus [TP], elevation, lake depth, and watershed area) contributed an additional 31% of the total (82%) variance explained by the seven forward-selected variables. Similar to previous studies, many taxa showed distinct distribution patterns with respect to pH. Partial and constrained CCAs indicated that, although all seven variables explained significant proportions of variation in the species data, a reliable inference model could be developed only for lake-water pH. The strength of this model ( R ²= 0.78, RMSE_boot= 0.47 of a pH unit) is comparable to a recently constructed diatom-based model for the EMAP lakes. The use of both models in paleolimnological and biomonitoring studies would be advantageous because they would provide two independent lines of evidence of environmental change.