Water quality in agriculture: Risks and risk mitigation

Edited by: Pay Drechsel, Sara Marjani Zadeh, and Francisco Pedrero SalcedoWater quality is of paramount importance for human lives, food production, and nature, and of concern where agricultural pollution, salinization, or lack of adequate wastewater treatment transform water from a resource into a potential hazard. This is in particular the case in many low- and middle-income countries water treatment is not keeping pace with population growth and urbanization resulting in about 30 million hectares of agricultural land, home to over 800 million residents, irrigated with polluted water. In addition to irrigated crop production, animal husbandry and aquaculture may be greatly affected by poor water quality, and can also contribute significantly to water quality degradation. These challenges prompted the Food and Agriculture Organization of the United Nations (FAO) to publish in 1976 a benchmark publication entitled Water Quality for Agriculture, followed in 1992 by Wastewater Treatment and Use in Agriculture. Over the ensuing 30 years, water quality challenges have grown resulting in a plethora of new research on water pollution, risk assessments and risk mitigation, as well as various sets of new water reuse guidelines. Based on this premise, FAO, in partnership with the International Water Management Institute (IWMI), began production of a review of current water quality guidelines, resulting in this one-volume handbook for evaluating the suitability of water for crop irrigation, livestock and fish production. The publication emphasizes good agricultural practices, including risk mitigation measures suitable for the contexts of differently resourced countries and institutions. With a focus on the sustainability of the overall system, it also covers possible downstream impacts of farm-level decisions. Water Quality in Agriculture: Risks and Risk Mitigation is intended for use by farm and project managers, extension officers, consultants and engineers to evaluate water quality data and identify potential problems and solutions related to water quality, but will also be of value to the scientific research community and studentsThis work started in 2020 under the CGIAR Research Programme on Water, Land and Ecosystems (WLE), and was further supported by the CGIAR initiative on “Resilient Cities through Sustainable Urban and Peri-urban Agrifood Systems” and the CGIAR Fund DonorsPeer reviewe

Stratigraphic and Isotopic Evolution of the Martian Polar Caps from Paleo‐Climate Models.

International audienceExposed scarps images and ice-penetrating radar measurements in the North Polar Layered Deposits (NPLD) of Mars show alternating layers that provide an archive of past climate oscillations, that are thought to be linked to orbital variations, akin to Milankovitch cycles on Earth. We use the Laboratoire de Météorologie Dynamique (LMD) Martian Global Climate Model (GCM) to study paleoclimate states to enable a better interpretation of the NPLD physical and chemical stratigraphy. When a tropical ice reservoir is present, water vapor transport from the tropics to the poles at low obliquity is modulated by the intensity of summer. At times of low and relatively constant obliquity, the flux still varies due to other orbital elements, promoting polar layer formation. Ice migrates from the tropics towards the poles in two stages. First, when surface ice is present in the tropics, and second, when the equatorial deposit is exhausted, from ice that was previously deposited in mid-high latitudes. The polar accumulation rate is significantly higher when tropical ice is available, forming thicker layers per orbital cycle. However, the majority of the NPLD is sourced from ice that temporary resided in the mid-high latitudes and the layers become thinner as the source location moves poleward. The migration stages imprint different D/H ratios in different sections in the PLDs. The NPLD is isotopically depleted compared to the SPLD in all simulations. Thus we predict the D/H ratio of the atmosphere in contact with NPLD upper layers is biased relative to the average global ice reservoirs

Climatological controls on the chemical stratigraphy of the martian polar layer deposits

International audienc

Climatological controls on the chemical stratigraphy of the martian polar layer deposits

International audienc

Climatological controls on the chemical stratigraphy of the martian polar layer deposits

International audienc

Climatological controls on the chemical stratigraphy of the martian polar layer deposits

International audienc

Recent ice ages on Mars by destabilization of the Northern Polar Cap at 35° obliquity

International audienc

Readily available biomarkers predict poor survival in metastatic pancreatic cancer

Background: Identification of metastatic pancreatic cancer (mPC) patients with the worst prognosis could help to tailor therapy. We evaluated readily available biomarkers for the prediction of 90-day mortality in a nationwide cohort of mPC patients. Methods: Patients with synchronous mPC were included from the Netherlands Cancer Registry (2015–2017). Baseline CA19-9, albumin, CRP, LDH, CRP/albumin ratio, and (modified) Glasgow Prognostic Score ((m)GPS composed of albumin and CRP) were evaluated. Multivariable logistic regression analyses were performed to identify predictors of 90-day mortality. Prognostic value per predictor was quantified by Nagelkerke’s partial R2. Results: Overall, 4248 patients were included. Median overall survival was 2.2 months and 90-day mortality was 59.4% (n = 1629). All biomarkers predicted 90-day mortality in univariable analysis, and remained statistically significant after adjustment for clinically relevant factors and all other biomarkers (all p < 0.001). The prognostic value of the biomarkers combined was similar to WHO performance status. Patients who received chemotherapy had better outcomes than those who did not, regardless of biomarker levels. Conclusions: In mPC patients, albumin, CA19-9, CRP, LDH, CRP/albumin ratio, and (m)GPS are prognostic for poor survival. Biomarkers did not predict response to chemotherapy. These readily available biomarkers can be used to better inform patients and to stratify in clinical trials