PEST-CHEMGRIDS, global gridded maps of the top 20 crop-specific pesticide application rates from 2015 to 2025

Available georeferenced environmental layers are facilitating new insights into global environmental assets and their vulnerability to anthropogenic inputs. Geographically gridded data of agricultural pesticides are crucial to assess human and ecosystem exposure to potential and recognised toxicants. However, pesticides inventories are often sparse over time and by region, mostly report aggregated classes of active ingredients, and are generally fragmented across local or government authorities, thus hampering an integrated global analysis of pesticide risk. Here, we introduce PEST-CHEMGRIDS, a comprehensive database of the 20 most used pesticide active ingredients on 6 dominant crops and 4 aggregated crop classes at 5 arc-min resolution (about 10km at the equator) projected from 2015 to 2025. To estimate the global application rates of specifc active ingredients we use spatial statistical methods to re-analyse the USGS/PNSP and FAOSTAT pesticide databases along with other public inventories including global gridded data of soil physical properties, hydroclimatic variables, agricultural quantities, and socio-economic indices. PEST-CHEMGRIDS can be used in global environmental modelling, assessment of agrichemical contamination, and risk analysis

POLARIS: A 30-meter probabilistic soil series map of the contiguous United States

A newcomplete map of soil series probabilities has been produced for the contiguous United States at a 30mspatial resolution. This innovative database, named POLARIS, is constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm (DSMART-HPC) to remap the Soil Survey Geographic (SSURGO) database. This 9 billion grid cell database is possible using available high performance computing resources. POLARIS provides a spatially continuous, internally consistent, quantitative prediction of soil series. It offers potential solutions to the primary weaknesses in SSURGO: 1) unmapped areas are gap-filled using survey data from the surrounding regions, 2) the artificial discontinuities at political boundaries are removed, and 3) the use of high resolution environmental covariate data leads to a spatial disaggregation of the coarse polygons. The geospatial environmental covariates that have the largest role in assembling POLARIS over the contiguous United States (CONUS) are fine-scale (30 m) elevation data and coarse-scale (~2 km) estimates of the geographic distribution of uranium, thorium, and potassium. A preliminary validation of POLARIS using the NRCS National Soil Information System (NASIS) database shows variable performance over CONUS. In general, the best performance is obtained at grid cells where DSMART-HPC is most able to reduce the chance of misclassification. The important role of environmental covariates in limiting prediction uncertainty suggests including additional covariates is pivotal to improving POLARIS\u27 accuracy. This database has the potential to improve the modeling of biogeochemical, water, and energy cycles in environmental models; enhance availability of data for precision agriculture; and assist hydrologic monitoring and forecasting to ensure food and water security

Me, My Girls, and the Ideal Hotel: Segmenting Motivations of the Girlfriend Getaway Market Using Fuzzy C-Medoids for Fuzzy Data.

Segmenting the motivation of travelers using the push and pull framework remains ubiquitous in tourism. This study segments the girlfriend getaway (GGA) market on motivation (push) and accommodation (pull) attributes and identifies relationships between these factors. Using a relatively novel clustering algorithm, the Fuzzy C-Medoids clustering for fuzzy data (FCM-FD), on a sample of 749 women travelers, three segments (Socializers, Enjoyers, and Rejoicers) are uncovered. The results of a multinomial fractional model show relationships between the clusters of motivation and accommodation attributes as well as sociodemographic characteristics. The research highlights the importance of using a gendered perspective in applying well established motivation models such as the push and pull framework. The findings have implications for both destination and accommodation management

Digital Soil Assessments: Beyond DSM

The scope of digital soil mapping is described but it is not seen as an end in itself. It provides data and information for a new framework for soil assessment which we call digital soil assessment. Although still somewhat fluid, a procedural framework for digital soil mapping and assessment with its links and feedbacks are set out diagrammatically and discussed. Theoretically, the main advantage of DSM over conventional methods is the intended provision of estimates of predictor uncertainties. DSA comprises three main processes: (1) a soil attribute space inference system, (2) evaluation of the soil functions and the threats to soils, and (3) risk assessment and the development of strategies for soil protection. Digital risk assessment consists of integrating political, social, economical parameters and general environmental threats for building, modelling and testing some scenarios about environmental perspectives. The procedure as a whole is illustrated by considering how to address potential question, ‘are we able to provide soil data parameters for climate-change modelling at 200-m resolution?;JRC.H.7-Land management and natural hazard

Digital Soil Assessment: Beyond DSM

The scope of digital soil mapping is described, but it is not seen as an end in itself. It provides data and information for a new framework for soil assessment which we call digital soil assessment. Although still somewhat fluid, a procedural framework for digital soil mapping and assessment with its links and feedbacks are set out diagrammatically and discussed. Theoretically, the principal, but not the sole, advantage of DSM over conventional methods is the intended provision of estimates of predictor uncertainties. DSA comprises three main processes: (1) a soil attribute space inference system, (2) evaluation of soil functions and the threats to soils, and (3) risk assessment and the development of strategies for soil protection. Digital risk assessment consists of integrating political, social, economical parameters and general environmental threats for building, modelling and testing some scenarios about environmental perspectives. The procedure as a whole is illustrated by considering how to address potential questions such as, ‘are we able to provide all the soil data parameters for climate-change modelling at 200-m resolution?’JRC.H.7-Land management and natural hazard

Risk of pesticide pollution at the global scale

Pesticides are widely used to protect food production and meet global food demand but are also ubiquitous environmental pollutants, causing adverse effects on water quality, biodiversity and human health. Here we use a global database of pesticide applications and a spatially explicit environmental model to estimate the world geography of environmental pollution risk caused by 92 active ingredients in 168 countries. We considered a region to be at risk of pollution if pesticide residues in the environment exceeded the no-effect concentrations, and to be at high risk if residues exceeded this by three orders of magnitude. We find that 64% of global agricultural land (approximately 24.5 million km2) is at risk of pesticide pollution by more than one active ingredient, and 31% is at high risk. Among the high-risk areas, about 34% are in high-biodiversity regions, 5% in water-scarce areas and 19% in low- and lower-middle-income nations. We identify watersheds in South Africa, China, India, Australia and Argentina as high-concern regions because they have high pesticide pollution risk, bear high biodiversity and suffer from water scarcity. Our study expands earlier pesticide risk assessments as it accounts for multiple active ingredients and integrates risks in different environmental compartments at a global scale

The global environmental hazard of glyphosate use

Agricultural pesticides can become persistent environmental pollutants. Among many, glyphosate (GLP) is under particular scrutiny because of its extensive use and its alleged threats to the ecosystem and human health. Here, we introduce the first global environmental contamination analysis of GLP and its metabolite, AMPA, conducted with a mechanistic dynamic model at 0.5 × 0.5° spatial resolution (about 55 km at the equator) fed with geographically-distributed agricultural quantities, soil and biogeochemical properties, and hydroclimatic variables. Our analyses reveal that about 1% of croplands worldwide (385,000 km2) are susceptible to mid to high contamination hazard and less than 0.1% has a high hazard. Hotspots found in South America, Europe, and East and South Asia were mostly correlated to widespread GLP use in pastures, soybean, and corn; diffuse contributing processes were mainly biodegradation recalcitrance and persistence, while soil residue accumulation and leaching below the root zone contributed locally to the hazard in hotspots. Hydroclimatic and soil variables were major controlling factors of contamination hotspots. The relatively low risk of environmental exposure highlighted in our work for a single active substance does not rule out a greater recognition of environmental pollution by pesticides and calls for worldwide cooperation to develop timely standards and implement regulated strategies to prevent excess global environmental pollution

Yeast Eap1p, an eIF4E-associated protein, has a separate function involving genetic stability

AbstractA rate-limiting step during translation initiation in eukaryotic cells involves binding of the initiation factor eIF4E to the 7-methylguanosine-containing cap of mRNAs. Overexpression of eIF4E leads to malignant transformation [1–3], and eIF4E is elevated in many human cancers [4–7]. In mammalian cells, three eIF4E-binding proteins each interact with eIF4E and inhibit its function [8–10]. In yeast, EAP1 encodes a protein that binds eIF4E and inhibits cap-dependent translation in vitro[11]. A point mutation in the canonical eIF4E-binding motif of Eap1p blocks its interaction with eIF4E [11]. Here, we characterized the genetic interactions between EAP1 and NDC1, a gene whose function is required for duplication of the spindle pole body (SPB) [12], the centrosome-equivalent organelle in yeast that functions as the centrosome. We found that the deletion of EAP1 is lethal when combined with the ndc1-1 mutation. Mutations in NDC1 or altered NDC1 gene dosage lead to genetic instability [13,14]. Yeast strains lacking EAP1 also exhibit genetic instability. We tested whether these phenotypes are due to loss of EAP1 function in regulating translation. We found that both the synthetic lethal phenotype and the genetic instability phenotypes are rescued by a mutant allele of EAP1 that is unable to bind eIF4E. Our findings suggest that Eap1p carries out an eIF4E-independent function to maintain genetic stability, most likely involving SPBs

The pesticide health risk index - An application to the world's countries

While the use of pesticides continues to rise worldwide, our understanding of the pervasiveness of associated contamination and the health risks humans may be exposed to remain limited to small samples size, and based on small geographic scales, the exposed population, or the pesticide types. Using our recent mapping of global pesticide use, we quantify three complementary health risk metrics for 92 active ingredients: (i) the pesticide hazard load (PHL); (ii) the population exposure (PE); and (iii) the human intake relative to the acceptable dose (INTR). We integrated these metrics into the pesticide health risk index (PHRI) to assess the standing of 133 nations against the global averages of PHL and PE and the acceptable levels of INTR using data of 2015 (PHRI > 1 indicates a concern). We found that some low-toxicity ingredients have PHL values equivalent to high-toxicity ones, and hence neglecting low-toxicity ingredients may cause biases in risk assessments. The geography of PHL, PE, and INTR show hotspots across the Americas, East and South Asia, and Europe, but with the EU27 countries generally showing lower PHL than other countries possibly due to strict governance on pesticide use. By our measure, about 1.7 billion people (24% of the world population) reside in close proximity to where pesticide applications are greater than 100 kg-a.i. km 1 indicates a concern). We found that some low-toxicity ingredients have PHL values equivalent to high-toxicity ones, and hence neglecting low-toxicity ingredients may cause biases in risk assessments. The geography of PHL, PE, and INTR show hotspots across the Americas, East and South Asia, and Europe, but with the EU27 countries generally showing lower PHL than other countries possibly due to strict governance on pesticide use. By our measure, about 1.7 billion people (24% of the world population) reside in close proximity to where pesticide applications are greater than 100 kg-a.i. km-2 year-1; about 2.3 billion people (32% of the world population) may exceed the acceptable pesticide intake and about 1.1 billion (15% of the world population) may exceed this by 10 fold. We identified 36 countries with PHRI > 1 and 6 countries with PHRI > 5; of these countries, 10 belong to lower-middle and low income economies. Our analyses show that proximity exposure to pesticides may be more widespread than revealed in occupational studies, and therefore assessments of potential health effects over wider scales may be needed. 1 and 6 countries with PHRI > 5; of these countries, 10 belong to lower-middle and low income economies. Our analyses show that proximity exposure to pesticides may be more widespread than revealed in occupational studies, and therefore assessments of potential health effects over wider scales may be needed. 5; of these countries, 10 belong to lower-middle and low income economies. Our analyses show that proximity exposure to pesticides may be more widespread than revealed in occupational studies, and therefore assessments of potential health effects over wider scales may be needed

Investigating local relationships between trace elements in soils and cancer data

Medical geology research has recognised a number of potentially toxic elements (PTEs), such as arsenic, cobalt, chromium, copper, nickel, lead, vanadium, uranium and zinc, known to influence human disease by their respective deficiency or toxicity. As the impact of infectious diseases has decreased and the population ages, so cancer has become the most common cause of death in developed countries including Northern Ireland. This research explores the relationship between environmental exposure to PTEs in soil and cancer disease data across Northern Ireland. The incidence of twelve different cancer types (lung, stomach, leukaemia, oesophagus, colorectal, bladder, kidney, breast, mesothelioma, melanoma and non melanoma (NM) both basal and squamous, were examined in the form of twenty-five coded datasets comprising aggregates over the 12 year period from 1993 to 2006. A local modelling technique, geographically weighted regression (GWR) is used to explore the relationship between environmental exposure and cancer disease data. The results show comparisons of the geographical incidence of certain cancers (stomach and NM squamous skin cancer) in relation to concentrations of certain PTEs (arsenic levels in soils and radon were identified). Findings from the research have implications for regional human health risk assessments