Spatial models of carbon, nitrogen, and sulfur stable isotope distributions (isoscapes) across a shelf sea: an INLA approach

Spatial models of variation in the isotopic composition of structural nutrients across habitats (isoscapes) offer information on physical, biogeochemical and anthropogenic processes occurring across space, and provide a tool for retrospective assignment of animals or animal products to their foraging area or geographic origin. The isotopic differences among reference samples used to construct isoscapes may vary spatially and according to non‐spatial terms (e.g. sampling date, or among individual or species effects). Partitioning variance between spatially dependent and spatially independent terms is a critical but overlooked aspect of isoscape creation with important consequences for the design of studies collecting reference data for isoscape creation and the accuracy and precision of isoscape models. We introduce the use of integrated nested Laplace approximation (INLA) to construct isoscape models. Integrated nested Laplace approximation provides a computationally efficient framework to construct spatial models of isotopic variability explicitly addressing additional variation introduced by including multiple reference species (or other recognized sources of variance). We present carbon, nitrogen and sulphur isoscape models extending over c. 1 million km2 of the UK shelf seas. Models were built using seven different species of jellyfish as spatial reference data and a suite of environmental correlates. Compared to alternative isoscape prediction methods, INLA‐spatial isotope models show high spatial precision and reduced variance. We briefly discuss the likely biogeochemical explanations for the observed spatial isotope distributions. We show for the first time that sulphur isotopes display systematic spatial variation across open marine shelf seas and may therefore be a useful additional tool for marine spatial ecology. The INLA technique provides a promising tool for generating isoscape models and associated uncertainty surfaces where reference data are accompanied by multiple, quantifiable sources of uncertainty

Impact of Scottish smoke-free legislation on smoking quit attempts and prevalence

<p><b>Objectives:</b> In Scotland, legislation was implemented in March 2006 prohibiting smoking in all wholly or partially enclosed public spaces. We investigated the impact on attempts to quit smoking and smoking prevalence.</p> <p><b>Methods:</b> We performed time series models using Box-Jenkins autoregressive integrated moving averages (ARIMA) on monthly data on the gross ingredient cost of all nicotine replacement therapy (NRT) prescribed in Scotland in 2003–2009, and quarterly data on self-reported smoking prevalence between January 1999 and September 2010 from the Scottish Household Survey.</p> <p><b>Results:</b> NRT prescription costs were significantly higher than expected over the three months prior to implementation of the legislation. Prescription costs peaked at £1.3 million in March 2006; £292,005.9 (95% CI £260,402.3, £323,609, p<0.001) higher than the monthly norm. Following implementation of the legislation, costs fell exponentially by around 26% per month (95% CI 17%, 35%, p<0.001). Twelve months following implementation, the costs were not significantly different to monthly norms. Smoking prevalence fell by 8.0% overall, from 31.3% in January 1999 to 23.7% in July–September 2010. In the quarter prior to implementation of the legislation, smoking prevalence fell by 1.7% (95% CI 2.4%, 1.0%, p<0.001) more than expected from the underlying trend.</p> <p><b>Conclusions:</b> Quit attempts increased in the three months leading up to Scotland's smoke-free legislation, resulting in a fall in smoking prevalence. However, neither has been sustained suggesting the need for additional tobacco control measures and ongoing support.</p&gt

A nonlinear mixed-effects modeling approach for ecological data: Using temporal dynamics of vegetation moisture as an example

Increasingly, often ecologist collects data with nonlinear trends, heterogeneous variances, temporal correlation, and hierarchical structure. Nonlinear mixed-effects models offer a flexible approach to such data, but the estimation and interpretation of these models present challenges, partly associated with the lack of worked examples in the ecological literature. We illustrate the nonlinear mixed-effects modeling approach using temporal dynamics of vegetation moisture with field data from northwestern Patagonia. This is a Mediterranean-type climate region where modeling temporal changes in live fuel moisture content are conceptually relevant (ecological theory) and have practical implications (fire management). We used this approach to answer whether moisture dynamics varies among functional groups and aridity conditions, and compared it with other simpler statistical models. The modeling process is set out “step-by-step”: We start translating the ideas about the system dynamics to a statistical model, which is made increasingly complex in order to include different sources of variability and correlation structures. We provide guidelines and R scripts (including a new self-starting function) that make data analyses reproducible. We also explain how to extract the parameter estimates from the R output. Our modeling approach suggests moisture dynamic to vary between grasses and shrubs, and between grasses facing different aridity conditions. Compared to more classical models, the nonlinear mixed-effects model showed greater goodness of fit and met statistical assumptions. While the mixed-effects approach accounts for spatial nesting, temporal dependence, and variance heterogeneity; the nonlinear function allowed to model the seasonal pattern. Parameters of the nonlinear mixed-effects model reflected relevant ecological processes. From an applied perspective, the model could forecast the time when fuel moisture becomes critical to fire occurrence. Due to the lack of worked examples for nonlinear mixed-effects models in the literature, our modeling approach could be useful to diverse ecologists dealing with complex data.Fil: Oddi, Facundo José. Universidad Nacional de Río Negro. Sede Andina. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Miguez, Fernando E.. University of Iowa; Estados UnidosFil: Ghermandi, Luciana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Bianchi, Lucas Osvaldo. Universidad Nacional de Río Negro. Sede Andina. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Garibaldi, Lucas Alejandro. Universidad Nacional de Río Negro. Sede Andina. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Targeting Antibiotics to Households for Trachoma Control

Repeated ocular infection with the bacterium Chlamydia trachomatis leads to the development of trachoma, a major cause of infectious blindness worldwide. Mass distribution of antibiotics, a component of the current trachoma control strategy, has had success in reducing infection in some areas, but results in a large number of uninfected people receiving antibiotics. We have previously shown that transmission of the bacteria between people in the same household is very efficient. Here, we investigated the effectiveness and cost-effectiveness of targeting antibiotics to households with active trachoma (inflammatory disease) compared to mass distribution, using data from four trachoma-endemic populations and a mathematical model of transmission. We found a high correspondence between households with active trachoma and infected households. In all populations the household targeted approach was predicted to be as effective as mass distribution, but it reduced the number of uninfected individuals receiving antibiotics, making the targeted strategy more cost-effective when antibiotics are not donated. Assuming antibiotics are donated, we predicted the targeted strategy to be more cost effective if it increases the proportion of infected individuals receiving treatment. Further work to address the feasibility and the cost variability in implementing the targeted approach in different settings is now required

Age and sex influence marmot antipredator behavior during periods of heightened risk

Animals adjust their antipredator behavior according to environmental variation in risk, and to account for their ability to respond to threats. Intrinsic factors that influence an animal’s ability to respond to predators (e.g., age, body condition) should explain variation in antipredator behavior. For example, a juvenile might allocate more time to vigilance than an adult because mortality as a result of predation is often high for this age class; however, the relationship between age/vulnerability and antipredator behavior is not always clear or as predicted. We explored the influence of intrinsic factors on yellow-bellied marmot (Marmota flaviventris) antipredator behavior using data pooled from 4 years of experiments. We hypothesized that inherently vulnerable animals (e.g., young, males, and individuals in poor condition) would exhibit more antipredator behavior prior to and immediately following conspecific alarm calls. As expected, males and yearlings suppressed foraging more than females and adults following alarm call playbacks. In contrast to predictions, animals in better condition respond more than animals in below average condition. Interestingly, these intrinsic properties did not influence baseline time budgets; animals of all ages, sexes, and condition levels devoted comparable amounts of time to foraging prior to alarm calls. Our results support the hypothesis that inherent differences in vulnerability influence antipredator behavior; furthermore, it appears that a crucial, but poorly acknowledged, interaction exists between risk and state-dependence. Elevated risk may be required to reveal the workings of state-dependent behavior, and studies of antipredator behavior in a single context may draw incomplete conclusions about age- or sex-specific strategies

Modeling the distribution of a wide-ranging invasive species using the sampling efforts of expert and citizen scientists

1- Results for the models calibrated with <i>Weigted Pts</i> pseudo-absences for the paper 'Modelling the distribution of a wide-ranging invasive species using the sampling efforts of expert and citizen scientists'.<div>2- Final figure of the probability of distribution of rabbits in black and white.</div><div>3- Final figure of the probability of distribution of rabbits in ASC format.<br></div

Social dynamics in nonbreeding flocks of a cooperatively breeding bird: causes and consequences of kin associations

Kin selection is regarded as a key process in the evolution of avian cooperative breeding, and kinship influences helper decisions in many species. However, the effect of kinship on nonbreeding social organization is still poorly understood despite its potential fitness implications. Here, we investigated the origins and consequences of kin associations in nonbreeding flocks of long-tailed tits, Aegithalos caudatus, an atypical cooperative breeder where helpers are failed breeders that redirect care towards relatives living in kin neighbourhoods. We found that kinship is an important factor in initial grouping decisions; all members of a nuclear family initially joined the same flock and failed breeders chose to flock with their relatives. Flocks that merged during the nonbreeding season also contained relatives. In contrast to these findings of positive kin association, when long-tailed tits switched flocks they tended to disperse into flocks with fewer relatives, although such switches often occurred with kin. In a playback experiment, we found no evidence that aggression shown towards members of other flocks was affected by kinship, indicating that kin associations result from a preference to flock with relatives rather than a constraint on flocking with nonrelatives. Finally, using social network analysis, we show that fine-scale nonbreeding associations among individuals were positively related to kinship, and that these nonbreeding associations were reflected in helping decisions in the subsequent breeding season, in addition to the previously reported effects of kinship and proximity. We conclude that long-tailed tits prefer to associate with kin when not breeding, and suggest that by doing so they gain either nepotistic benefits within flocks or future indirect benefits during breeding