Effects of mantle upwelling in a compressional setting: the Atlas Mountains of Morocco

We discuss the implications of a lithospheric model of the Moroccan Atlas Mountains based on topography, heat flow, gravity and geoid anomalies, taking into account the regional geology. The NW African cratonic lithosphere, some 160–180 km thick, thins to c. 80 km beneath the Atlas fold-thrust belts, in contrast with the shortening regime prevailing there since the early Cenozoic. This fact explains several geological and geophysical features as high topography with modest tectonic shortening, the occurrence of alkaline magmatism contemporaneous to compression, the absence of large crustal roots to support elevation, the scarce development of foreland basins, and a marked geoid high. The modelled lithosphere thinning is related to a thermal upwelling constrained between the Iberia–Africa convergent plate boundary and the Saharan craton.     

High-resolution vertical profiles of groundwater electrical conductivity (EC) and chloride from direct-push EC logs

Elevated groundwater salinity associated with produced water, leaching from landfills or secondary salinity can degrade arable soils and potable water resources. Direct-push electrical conductivity (EC) profiling enables rapid, relatively inexpensive, high-resolution in-situ measurements of subsurface salinity, without requiring core collection or installation of groundwater wells. However, because the direct-push tool measures the bulk EC of both solid and liquid phases (EC_a), incorporation of EC_a data into regional or historical groundwater data sets requires the prediction of pore water EC (EC_w) or chloride (Cl^?) concentrations from measured EC_a. Statistical linear regression and physically based models for predicting EC_w and Cl^? from EC_a profiles were tested on a brine plume in central Saskatchewan, Canada. A linear relationship between EC_a/EC_w and porosity was more accurate for predicting EC_w and Cl^? concentrations than a power-law relationship (Archie’s Law). Despite clay contents of up to 96%, the addition of terms to account for electrical conductance in the solid phase did not improve model predictions. In the absence of porosity data, statistical linear regression models adequately predicted EC_w and Cl^? concentrations from direct-push EC_a profiles (EC_w = 5.48 EC_a + 0.78, R ² = 0.87; Cl^? = 1,978 EC_a – 1,398, R ² = 0.73). These statistical models can be used to predict EC_w in the absence of lithologic data and will be particularly useful for initial site assessments. The more accurate linear physically based model can be used to predict EC_w and Cl^? as porosity data become available and the site-specific EC_w–Cl^? relationship is determined.     

Trading more food: Implications for land use,greenhouse gas emissions,and the food system

The volume of agricultural trade increased by more than ten times throughout the past six decades and is likely to continue with high rates in the future. Thereby, it largely affects environment and climate. We analyse future trade scenarios covering the period of 2005–2045 by evaluating economic and environmental effects using the global land-use model MAgPIE (“Model of Agricultural Production and its Impact on the Environment”). This is the first trade study using spatially explicit mapping of land use patterns and greenhouse gas emissions. We focus on three scenarios: the reference scenario fixes current trade patterns, the policy scenario follows a historically derived liberalisation pathway, and the liberalisation scenario assumes a path, which ends with full trade liberalisation in 2045.Further trade liberalisation leads to lower global costs of food. Regions with comparative advantages like Latin America for cereals and oil crops and China for livestock products will export more. In contrast, regions like the Middle East, North Africa, and South Asia face the highest increases of imports. Deforestation, mainly in Latin America, leads to significant amounts of additional carbon emissions due to trade liberalisation. Non-CO₂ emissions will mostly shift to China due to comparative advantages in livestock production and rising livestock demand in the region. Overall, further trade liberalisation leads to higher economic benefits at the expense of environment and climate, if no other regulations are put in place.