Preliminary observations on the reproductive cycle of female Tegu lizards (Tupinambis teguizin)

The black tegu lizard, Tupinambis teguixin (Linnaeus 1758) is a common element in the wild all throughout Southamerica except for Chile. This teiid lizard was outstood by earlier travellers such as Sir Charles Waterton who reported for the first time about the delicate food, resembling chicken flesh and frequently consumed by local natives. Despite its relative abundance and both the intense economical and social importance of tegus, as well as its situation in the food web, the reproductive biology of tegus was, until recently, largely unknown.Asociación Herpetológica Argentin

The snake fauna of El Bagual Ecological Reserve, Formosa: abundance, habitat utilization and situational state.

From records made during eight months consisting of direct observations and some captures, the snake fauna was analyzed to know specific composition, abundance and states of conservation. Each species was associated to the habitat where was found. Although bibliographical record cites 60 species, 19 were found within the protected area. Five were categorized to be very abundant, nine abundant, three common and two scarce. The snake fauna was also analyzed to describe functional guilds according to specific habits and an index of community similarity was considered. High and low grasslands together with the forests supported the highest number of species and in a finally situational states of wild fauna, two potential management problems are expected. One of them with venemous snake fauna which would require a future regulation management, and the other with boids requiring a conservation management technique.Asociación Herpetológica Argentin

The snake fauna of El Bagual Ecological Reserve, Formosa: abundance, habitat utilization and situational state.

From records made during eight months consisting of direct observations and some captures, the snake fauna was analyzed to know specific composition, abundance and states of conservation. Each species was associated to the habitat where was found. Although bibliographical record cites 60 species, 19 were found within the protected area. Five were categorized to be very abundant, nine abundant, three common and two scarce. The snake fauna was also analyzed to describe functional guilds according to specific habits and an index of community similarity was considered. High and low grasslands together with the forests supported the highest number of species and in a finally situational states of wild fauna, two potential management problems are expected. One of them with venemous snake fauna which would require a future regulation management, and the other with boids requiring a conservation management technique.Asociación Herpetológica Argentin

Biodiversity-friendly Agricultural Practices in the Indigenous Agricultural Systems in the Biodiversity Corridor of the Alto Paraná Atlantic Forest (Paraguay)

Agricultural systems result of the coevolution between social and natural systems, where biodiversity and natural resources play an important role, emerging interactions between crops and the natural environment that allow the development of ecological processes which interact with external inputs. This research aims to describe the agricultural practices developed by the Guarani Indigenous people in the agricultural systems located within the biodiversity corridor of the Upper Parana Atlantic Forest. This exploratory study is focused on multiple cases, with a qualitative approach and from data collected during 2017 and 2018 in eleven indigenous communities. The main practices developed for the management of biodiversity are polyculture, rotation, and embroideries; they also practice agroforestry and livestock-raising. The main difficulty they face is the reduction of the surrounding biodiversity, which affects the sustainability of the system. This study shows ways for nature-based solutions and ecosystem-based adaptation according to current needs for greening the economy

Preliminary observations on the reproductive cycle of female Tegu lizards (Tupinambis teguizin)

The black tegu lizard, Tupinambis teguixin (Linnaeus 1758) is a common element in the wild all throughout Southamerica except for Chile. This teiid lizard was outstood by earlier travellers such as Sir Charles Waterton who reported for the first time about the delicate food, resembling chicken flesh and frequently consumed by local natives. Despite its relative abundance and both the intense economical and social importance of tegus, as well as its situation in the food web, the reproductive biology of tegus was, until recently, largely unknown.Asociación Herpetológica Argentin

Combining spatial information sources while accounting for systematic errors in proxies

Environmental research increasingly uses high-dimensional remote sensing and numerical model output to help fill space-time gaps between traditional observations. Such output is often a noisy proxy for the process of interest. Thus one needs to separate and assess the signal and noise (often called discrepancy) in the proxy given complicated spatio-temporal dependencies. Here I extend a popular two-likelihood hierarchical model using a more flexible representation for the discrepancy. I employ the little-used Markov random field approximation to a thin plate spline, which can capture small-scale discrepancy in a computationally efficient manner while better modeling smooth processes than standard conditional auto-regressive models. The increased flexibility reduces identifiability, but the lack of identifiability is inherent in the scientific context. I model particulate matter air pollution using satellite aerosol and atmospheric model output proxies. The estimated discrepancies occur at a variety of spatial scales, with small-scale discrepancy particularly important. The examples indicate little predictive improvement over modeling the observations alone. Similarly, in simulations with an informative proxy, the presence of discrepancy and resulting identifiability issues prevent improvement in prediction. The results highlight but do not resolve the critical question of how best to use proxy information while minimizing the potential for proxy-induced error.Comment: 5 figures, 2 table

Practical large-scale spatio-temporal modeling of particulate matter concentrations

The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during 1988--2002 in a large spatial domain for use in studying health effects in the Nurses' Health Study. We develop a conceptually simple spatio-temporal model that uses a rich set of covariates. The model is used to estimate concentrations of $PM_{10}$ for the full time period and $PM_{2.5}$ for a subset of the period. For the earlier part of the period, 1988--1998, few $PM_{2.5}$ monitors were operating, so we develop a simple extension to the model that represents $PM_{2.5}$ conditionally on $PM_{10}$ model predictions. In the epidemiological analysis, model predictions of $PM_{10}$ are more strongly associated with health effects than when using simpler approaches to estimate exposure. Our modeling approach supports the application in estimating both fine-scale and large-scale spatial heterogeneity and capturing space--time interaction through the use of monthly-varying spatial surfaces. At the same time, the model is computationally feasible, implementable with standard software, and readily understandable to the scientific audience. Despite simplifying assumptions, the model has good predictive performance and uncertainty characterization.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS204 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Spatio-temporal modeling of particulate air pollution in the conterminous United States using geographic and meteorological predictors

Background: Exposure to atmospheric particulate matter (PM) remains an important public health concern, although it remains difficult to quantify accurately across large geographic areas with sufficiently high spatial resolution. Recent epidemiologic analyses have demonstrated the importance of spatially- and temporally-resolved exposure estimates, which show larger PM-mediated health effects as compared to nearest monitor or county-specific ambient concentrations. Methods: We developed generalized additive mixed models that describe regional and small-scale spatial and temporal gradients (and corresponding uncertainties) in monthly mass concentrations of fine (PM2.5), inhalable (PM10), and coarse mode particle mass (PM2.5–10) for the conterminous United States (U.S.). These models expand our previously developed models for the Northeastern and Midwestern U.S. by virtue of their larger spatial domain, their inclusion of an additional 5 years of PM data to develop predictions through 2007, and their use of refined geographic covariates for population density and point-source PM emissions. Covariate selection and model validation were performed using 10-fold cross-validation (CV). Results: The PM2.5 models had high predictive accuracy (CV R2=0.77 for both 1988–1998 and 1999–2007). While model performance remained strong, the predictive ability of models for PM10 (CV R2=0.58 for both 1988–1998 and 1999–2007) and PM2.5–10 (CV R2=0.46 and 0.52 for 1988–1998 and 1999–2007, respectively) was somewhat lower. Regional variation was found in the effects of geographic and meteorological covariates. Models generally performed well in both urban and rural areas and across seasons, though predictive performance varied somewhat by region (CV R2=0.81, 0.81, 0.83, 0.72, 0.69, 0.50, and 0.60 for the Northeast, Midwest, Southeast, Southcentral, Southwest, Northwest, and Central Plains regions, respectively, for PM2.5 from 1999–2007). Conclusions: Our models provide estimates of monthly-average outdoor concentrations of PM2.5, PM10, and PM2.5–10 with high spatial resolution and low bias. Thus, these models are suitable for estimating chronic exposures of populations living in the conterminous U.S. from 1988 to 2007

Traffic particles and occurrence of acute myocardial infarction: a case–control analysis

OBJECTIVES: We modelled exposure to traffic particles using a latent variable approach and investigated whether long-term exposure to traffic particles is associated with an increase in the occurrence of acute myocardial infarction (AMI) using data from a population-based coronary disease registry. METHODS: Cases of individually validated AMI were identified between 1995 and 2003 as part of the Worcester Heart Attack Study. Population controls were selected from Massachusetts, USA, resident lists. NO(2) and PM(2.5) filter absorbance were measured at 36 locations throughout the study area. The air pollution data were used to estimate exposure to traffic particles using a semiparametric latent variable regression model. Conditional logistic models were used to estimate the association between exposure to traffic particles and occurrence of AMI. RESULTS: Modelled exposure to traffic particles was highest near the city of Worcester. Cases of AMI were more exposed to traffic and traffic particles compared to controls. An interquartile range increase in modelled traffic particles was associated with a 10% (95% CI 4% to 16%) increase in the odds of AMI. Accounting for spatial dependence at the census tract, but not block group, scale substantially attenuated this association. CONCLUSIONS: These results provide some support for an association between long-term exposure to traffic particles and risk of AMI. The results were sensitive to the scale selected for the analysis of spatial dependence, an issue that requires further investigation. The latent variable model captured variation in exposure, although on a relatively large spatial scale