Arresting gully formation in the Ethiopian highlands

Over the past five decades, gullying has been widespread and has become more severe in the Ethiopian highlands. Only in very few cases, rehabilitation of gullies has been successful in Ethiopia due to the high costs. The objective of this paper is to introduce cost effective measures to arrest gully formation. The research was conducted in the Debre-Mewi watershed located at 30 km south of Bahir Dar, Ethiopia. Gullying started in the 1980s following the clearance of indigenous vegetation and intensive agricultural cultivation, leading to an increase of surface and subsurface runoff from the hillside to the valley bottoms. Gully erosion rates were 10–20 times the measured upland soil losses. Water levels, measured with piezometers, showed that in the actively eroding sections, the water table was in general above the gully bottom and below it in the stabilized sections. In order to develop effective gully stabilizing measures, we tested and then applied the BSTEM and CONCEPT models for their applicability for Ethiopian conditions where active gully formation has been occurring. We found that the model predicted the location of slips and slumps well with the observed groundwater depth and vegetation characteristics. The validated models indicated that any gully rehabilitation project should first stabilize the head cuts. This can be achieved by regrading these head cuts to slope of 40 degrees and armoring it with rock. Head cuts will otherwise move uphill in time and destroy any improvements. To stabilize side walls in areas with seeps, grass will be effective in shallow gullies, while deeper gullies require reshaping of the gullies walls, then planting the gully with grasses, eucalyptus or fruit trees that can be used for income generation. Only then there is an incentive for local farmers to maintain the structures

Ecological resilience indicators for salt marsh ecosystems

Salt marshes are coastal ecosystems within the intertidal zone, characterized by hypoxic, saline, soil conditions and low biodiversity. Low diversity arises from frequent disturbance and stressful conditions (i.e., high salinity and hypoxia), where vegetative reproduction and low competition result in mostly monotypic stands, with some differences in plant community influenced by flooding regime (described below). While there are several types of salt marshes in the Northern Gulf of Mexico (NGoM), ranging from low to high salt marshes and salt flats (Tiner, 2013), Spartina alterniflora–dominated salt marshes in the Coastal and Marine Ecological Classification Standard (CMECS) Low and Intermediate Salt Marsh Biotic Group (FGDC, 2012) are the most extensive and are the focus of this project. These salt marshes are classified as “Gulf Coast Cordgrass Salt Marsh” (CEGL004190; USNVC, 2016). Within the NGoM region, some salt marsh areas are dominated by other species such as Spartina patens and Juncus roemerianus, which both occupy higher elevations in high-precipitation zones (e.g., Louisiana, Alabama, Mississippi, and Florida). In lower precipitation regions (southern Texas), hypersaline conditions often develop yielding communities of succulent salt marsh plants (Batis and Salicornia spp.). In climatic zones with warmer winter temperatures, temperate salt marshes naturally transition to mangrove (generally in the southern Gulf of Mexico range) or, in areas with lower precipitation, to salt flats (generally in western part of the study area)

Understanding mass fluvial erosion along a bank profile: using PEEP technology for quantifying retreat lengths and identifying event timing

This study provides fundamental examination of mass fluvial erosion along a stream bank by identifying event timing, quantifying retreat lengths, and providing ranges of incipient shear stress for hydraulically driven erosion. Mass fluvial erosion is defined here as the detachment of thin soil layers or conglomerates from the bank face under higher hydraulic shear stresses relative to surface fluvial erosion, or the entrainment of individual grains or aggregates under lower hydraulic shear stresses. We explore the relationship between the two regimes in a representative, US Midwestern stream with semi-cohesive bank soils, namely Clear Creek, IA. Photo-Electronic Erosion Pins (PEEPs) provide, for the first time, in situ measurements of mass fluvial erosion retreat lengths during a season. The PEEPs were installed at identical locations where surface fluvial erosion measurements exist for identifying the transition point between the two regimes. This transition is postulated to occur when the applied shear stress surpasses a second threshold, namely the critical shear stress for mass fluvial erosion. We hypothesize that the regimes are intricately related and surface fluvial erosion can facilitate mass fluvial erosion. Selective entrainment of unbound/exposed, mostly silt-sized particles at low shear stresses over sand-sized sediment can armor the bank surface, limiting the removal of the underlying soil. The armoring here is enhanced by cementation from the presence of optimal levels of sand and clay. Select studies show that fluvial erosion strength can increase several-fold when appropriate amounts of sand and clay are mixed and cement together. Hence, soil layers or conglomerates are entrained with higher flows. The critical shear stress for mass fluvial erosion was found to be an order of magnitude higher than that of surface fluvial erosion, and proceeded with higher (approximately 2–4 times) erodibility. The results were well represented by a mechanistic detachment model that captures the two regimes. Copyright © 2017 John Wiley & Sons, Ltd

Some considerations concerning the challenge of incorporating social variables into epidemiological models of infectious disease transmission

Incorporation of ‘social’ variables into epidemiological models remains a challenge. Too much detail and models cease to be useful; too little and the very notion of infection —a highly social process in human populations—may be considered with little reference to the social. The French sociologist Emile Durkheim proposed that the scientific study of society required identification and study of ‘social currents.’ Such ‘currents’ are what we might today describe as ‘emergent properties,’ specifiable variables appertaining to individuals and groups, which represent the perspectives of social actors as they experience the environment in which they live their lives. Here we review the ways in which one particular emergent property, hope, relevant to a range of epidemiological situations, might be used in epidemiological modelling of infectious diseases in human populations. We also indicate how such an approach might be extended to include a range of other potential emergent properties to repre

Global distribution and bioclimatic characterization of alpine biomes

Although there is a general consensus on the distribution and ecological features of terrestrial biomes, the allocation of alpine ecosystems in the global biogeographic system is still unclear. Here, we delineate a global map of alpine areas above the treeline by modelling regional treeline elevation at 30 m resolution, using global forest cover data and quantile regression. We then used global datasets to 1) assess the climatic characteristics of alpine ecosystems using principal component analysis, 2) define bioclimatic groups by an optimized cluster analysis and 3) evaluate patterns of primary productivity based on the normalized difference vegetation index. As defined here, alpine biomes cover 3.56 Mkm(2) or 2.64% of land outside Antarctica. Despite temperature differences across latitude, these ecosystems converge below a sharp threshold of 5.9 degrees C and towards the colder end of the global climatic space. Below that temperature threshold, alpine ecosystems are influenced by a latitudinal gradient of mean annual temperature and they are climatically differentiated by seasonality and continentality. This gradient delineates a climatic envelope of global alpine biomes around temperate, boreal and tundra biomes as defined in Whittaker's scheme. Although alpine biomes are similarly dominated by poorly vegetated areas, world ecoregions show strong differences in the productivity of their alpine belt irrespectively of major climate zones. These results suggest that vegetation structure and function of alpine ecosystems are driven by regional and local contingencies in addition to macroclimatic factors

Modeling sediment mobilization using a distributed hydrological model coupled with a bank stability model

In addition to surface erosion, stream bank erosion and failure contributes significant sediment and sediment-bound nutrients to receiving waters during high flow events. However, distributed and mechanistic simulation of stream bank sediment contribution to sediment loads in a watershed has not been achieved. Here we present a full coupling of existing distributed watershed and bank stability models and apply the resulting model to the Mad River in central Vermont. We fully coupled the Bank Stability and Toe Erosion Model (BSTEM) with the Distributed Hydrology Soil Vegetation Model (DHSVM) to allow the simulation of stream bank erosion and potential failure in a spatially explicit environment. We demonstrate the model\u27s ability to simulate the impacts of unstable streams on sediment mobilization and transport within a watershed and discuss the model\u27s capability to simulate watershed sediment loading under climate change. The calibrated model simulates total suspended sediment loads and reproduces variability in suspended sediment concentrations at watershed and subbasin outlets. In addition, characteristics such as land use and road-to-stream ratio of subbasins are shown to impact the relative proportions of sediment mobilized by overland erosion, erosion of roads, and stream bank erosion and failure in the subbasins and watershed. This coupled model will advance mechanistic simulation of suspended sediment mobilization and transport from watersheds, which will be particularly valuable for investigating the potential impacts of climate and land use changes, as well as extreme events

Resolving the infinitude controversy

A simple inductive argument shows natural languages to have infinitly many sentences, but workers in the field have uncovered clear evidence of a diverse group of ‘exceptional’ languages from Proto-Uralic to Dyirbal and most recently, Pirahã, that appear to lack recursive devices entirely. We argue that in an information-theoretic setting non-recursive natural languages appear neither exceptional nor functionally inferior to the recursive majority

Performance of prediction models for nephropathy in people with type 2 diabetes:systematic review and external validation study

OBJECTIVES To identify and assess the quality and accuracy of prognostic models for nephropathy and to validate these models in external cohorts of people with type 2 diabetes. DESIGN Systematic review and external validation. DATA SOURCES PubMed and Embase. ELIGIBILITY CRITERIA Studies describing the development of a model to predict the risk of nephropathy, applicable to people with type 2 diabetes. METHODS Screening, data extraction, and risk of bias assessment were done in duplicate. Eligible models were externally validated in the Hoorn Diabetes Care System (DCS) cohort (n=11 450) for the same outcomes for which they were developed. Risks of nephropathy were calculated and compared with observed risk over 2, 5, and 10 years of follow-up. Model performance was assessed based on intercept adjusted calibration and discrimination (Harrell's C statistic). RESULTS 41 studies included in the systematic review reported 64 models, 46 of which were developed in a population with diabetes and 18 in the general population including diabetes as a predictor. The predicted outcomes included albuminuria, diabetic kidney disease, chronic kidney disease (general population), and end stage renal disease. The reported apparent discrimination of the 46 models varied considerably across the different predicted outcomes, from 0.60 (95% confidence interval 0.56 to 0.64) to 0.99 (not available) for the models developed in a diabetes population and from 0.59 (not available) to 0.96 (0.95 to 0.97) for the models developed in the general population. Calibration was reported in 31 of the 41 studies, and the models were generally well calibrated. 21 of the 64 retrieved models were externally validated in the Hoorn DCS cohort for predicting risk of albuminuria, diabetic kidney disease, and chronic kidney disease, with considerable variation in performance across prediction horizons and models. For all three outcomes, however, at least two models had C statistics >0.8, indicating excellent discrimination. In a secondary external validation in GoDARTS (Genetics of Diabetes Audit and Research in Tayside Scotland), models developed for diabetic kidney disease outperformed those for chronic kidney disease. Models were generally well calibrated across all three prediction horizons. CONCLUSIONS This study identified multiple prediction models to predict albuminuria, diabetic kidney disease, chronic kidney disease, and end stage renal disease. In the external validation, discrimination and calibration for albuminuria, diabetic kidney disease, and chronic kidney disease varied considerably across prediction horizons and models. For each outcome, however, specific models showed good discrimination and calibration across the three prediction horizons, with clinically accessible predictors, making them applicable in a clinical setting. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42020192831.Molecular Epidemiolog