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

Identifying streamgage networks for maximizing the effectiveness of regional water balance modeling

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98795/1/wrcr20233.pd

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

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

Panta Rhei benchmark dataset: socio-hydrological data of paired events of floods and droughts

As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions, and feedbacks in complex human–water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed and in the quantity of socio-hydrological data. The benchmark dataset comprises (1) detailed review-style reports about the events and key processes between the two events of a pair; (2) the key data table containing variables that assess the indicators which characterize management shortcomings, hazard, exposure, vulnerability, and impacts of all events; and (3) a table of the indicators of change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators of change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses, e.g. focused on causal links between risk management; changes in hazard, exposure and vulnerability; and flood or drought impacts. The data can also be used for the development, calibration, and validation of sociohydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al., 2023, https://doi.org/10.5880/GFZ.4.4.2023.001)

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

The challenge of unprecedented floods and droughts in risk management

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3

Assessing the role of uncertain precipitation estimates on the robustness of hydrological model parameters under highly variable climate conditions

Study region: Four headwaters in Southern Africa. Study focus: The streamflow regimes in Southern Africa are amongst the most variable in the world. The corresponding differences in streamflow bias and variability allowed us to analyze the behavior and robustness of the LISFLOOD hydrological model parameters. A differential split-sample test is used for calibration using seven satellite-based rainfall estimates, in order to assess the robustness of model parameters. Robust model parameters are of high importance when they have to be transferred both in time and space. For calibration, the modified Kling-Gupta statistic was used, which allowed us to differentiate the contribution of the correlation, bias and variability between the simulated and observed streamflow. New hydrological insights: Results indicate large discrepancies in terms of the linear correlation (r), bias (β) and variability (γ) between the observed and simulated streamflows when using different precipitation estimates as model input. The best model performance was obtained with products which ingest gauge data for bias correction. However, catchment behavior was difficult to be captured using a single parameter set and to obtain a single robust parameter set for each catchment, which indicate that transposing model parameters should be carried out with caution. Model parameters depend on the precipitation characteristics of the calibration period and should therefore only be used in target periods with similar precipitation characteristics (wet/dry)