Roma e la storia del Canada francese sino alla guerra dei Sette Anni

Presentation of the documents concerning New France and Canada in the Vatican Archive

Precipitation regionalization, anomalies and drought occurrence in the Yucatan Peninsula, Mexico

© 2020 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. Climate change projections have identified the Yucatan Peninsula as being vulnerable to increasing drought. Understanding spatial and temporal precipitation variability and drought occurrence are therefore important. Drought monitoring in Mexico has been carried out only relatively recently and often without considering the long-term variability in both droughts and precipitation. This research explores the spatio-temporal variability of precipitation and occurrence of droughts at a much finer spatial resolution and over a longer temporal period than previous studies. Using statistical (cluster analysis and standardized precipitation index) and geostatistical (kriging) techniques, maps of precipitation and droughts are generated for the period 1980–2011. These show that whilst many previous studies have regarded the Yucatan Peninsula as a homogenous region with respect to precipitation, there are actually four distinctive clusters of precipitation amount, showing climatic variability across the Peninsula. The analyses also show that droughts in the Peninsula are regionalised. Twelve-month Standardized Precipitation Indices (SPI), calculated for individual stations and for precipitation surfaces, reveal distinct patterns of spatial and temporal variability. SPI surfaces indicate the occurrence of major droughts in 1981, 1986–1987, 1994, 1996, 2003, 2004 and 2009, but these rarely affect the whole Yucatan Peninsula uniformly. Wetter years, such as 1983, 1984, 1988, 1992, 1995, 2002 and 2005 sometimes reflect the impact of individual extreme events, such as hurricane Isidore in 2002. Our results show that drought can be regionalised, thus enhancing the quality of information about droughts in the area and providing evidence and support for future drought mitigation and environmental protection. These methods could usefully be applied elsewhere

Precipitation Constrains Amphibian Chytrid Fungus Infection Rates in a Terrestrial Frog Assemblage in Jamaica, West Indies

We model Batrachochytrium dendrobatidis (Bd) infection rates in Jamaican frogs—one of the most threatened amphibian fauna in the world. The majority of species we surveyed were terrestrial direct‐developing frogs or frogs that breed in tank bromeliads, rather than those that use permanent water bodies to breed. Thus, we were able to investigate the climatic correlates of Bd infection in a frog assemblage that does not rely on permanent water bodies. We sampled frogs for Bd across all of the major habitat types on the island, used machine learning algorithms to identify climatic variables that are correlated with infection rates, and extrapolated infection rates across the island. We compared the effectiveness of the machine learning algorithms for species distribution modeling in the context of our study, and found that infection rate rose quickly with precipitation in the driest month. Infection rates also increased with mean temperature in the warmest quarter until 22 °C, and remained relatively level thereafter. Both of these results are in accordance with previous studies of the physiology of Bd . Based on our environmental results, we suggest that frogs occupying high‐precipitation habitats with cool rainy‐season temperatures, though zcurrently experiencing low frequencies of infection, may experience an increase in infection rates as global warming increases temperatures in their habitat.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106115/1/btp12093.pd

Modeling the vacuolar storage of malate shed lights on pre- and post-harvest fruit acidity

Background: Malate is one of the most important organic acids in many fruits and its concentration plays a critical role in organoleptic properties. Several studies suggest that malate accumulation in fruit cells is controlled at the level of vacuolar storage. However, the regulation of vacuolar malate storage throughout fruit development, and the origins of the phenotypic variability of the malate concentration within fruit species remain to be clarified. In the present study, we adapted the mechanistic model of vacuolar storage proposed by Lobit et al. in order to study the accumulation of malate in pre and postharvest fruits. The main adaptation concerned the variation of the free energy of ATP hydrolysis during fruit development. Banana fruit was taken as a reference because it has the particularity of having separate growth and post-harvest ripening stages, during which malate concentration undergoes substantial changes. Moreover, the concentration of malate in banana pulp varies greatly among cultivars which make possible to use the model as a tool to analyze the genotypic variability. The model was calibrated and validated using data sets from three cultivars with contrasting malate accumulation, grown under different fruit loads and potassium supplies, and harvested at different stages. Results: The model predicted the pre and post-harvest dynamics of malate concentration with fairly good accuracy for the three cultivars (mean RRMSE = 0.25-0.42). The sensitivity of the model to parameters and input variables was analyzed. According to the model, vacuolar composition, in particular potassium and organic acid concentrations, had an important effect on malate accumulation. The model suggested that rising temperatures depressed malate accumulation. The model also helped distinguish differences in malate concentration among the three cultivars and between the pre and post-harvest stages by highlighting the probable importance of proton pump activity and particularly of the free energy of ATP hydrolysis and vacuolar pH. Conclusions: This model appears to be an interesting tool to study malate accumulation in pre and postharvest fruits and to get insights into the ecophysiological determinants of fruit acidity, and thus may be useful for fruit quality improvement. (Résumé d'auteur

Prediction of weight and percentage of salable meat from Brazilian market lambs by subjective conformation and fatness scores

ABSTRACT This study assessed the use of conformation and fatness scores of the EUROP sheep carcass grading system to predict weight and percentage of salable meat from Brazilian market lambs. Data were collected from in vivo, carcass, and retail production from 252 uncastrated lambs. Evaluated models included single regressions, two multivariate models, and one determined by the stepwise procedure. Conformation was moderately correlated with weight of salable meat. Fatness scores were correlated with rump perimeter, carcass width, and thoracic depth with coefficients of −0.33, −0.32, and −0.23, respectively. Body weight was the best single predictor for weight of salable meat and cold carcass yield for percentage of salable meat. All multivariate models for weight of salable meat prediction were significant. Stepwise regression with body weight, leg perimeter, thoracic depth, rump perimeter, and fatness scores predicted 98% of weight of salable meat variation. For percentage of salable meat prediction, stepwise regression with cold carcass yield, leg perimeter, and conformation score was significant. The EUROP conformation and fatness scores can be used in Brazil for the prediction of lamb meat production