How effective are on-farm conservation land management strategies for preserving ecosystem services in developing countries? A systematic map protocol

Background An extensive body of literature in the field of agro-ecology claims to show the positive effects that maintenance of ecosystem services can have on sustainably meeting future food demand, by making farms more productive and resilient, and contributing to better nutrition and livelihoods of farmers. In Africa alone, some research has estimated a two-fold yield increase if food producers capitalize on new and existing knowledge from science and technology. Site-specific strategies adopted with the aim of improving ecosystem services may incorporate principles of multifunctional agriculture, sustainable intensification and conservation agriculture. However, a coherent synthesis and review of the evidence of these claims is largely absent, and the quality of much of this literature is questionable. Moreover, inconsistent effects have commonly been reported, while empirical evidence to support assumed improvements is largely lacking. Objectives This systematic map is stimulated by an interest to (1) collate evidence on the effectiveness of on-farm conservation land management for preserving and enhancing ecosystem services in agricultural landscapes, by drawing together the currently fragmented and multidisciplinary literature base, and (2) geographically map what indicators have been used to assess on-farm conservation land management. For both questions, we will focus on 74 low-income and developing countries, where much of the world’s agricultural expansion is occurring, yet 80% of arable land is already used and croplands are yielding well below their potential. Methods/Design To this end, reviewers will systematically search bibliographic databases for peer-reviewed research from Web of Science, SCOPUS, AGRICOLA, AGRIS databases and CAB abstracts, and grey literature from Google Scholar, and 22 subject-specific or institutional websites. Boolean search operators will be used to create search strings where applicable. Ecosystem services included in the study are pollination services; pest-, carbon-, soil-, and water-regulation; nutrient cycling; medicinal and aromatic plants; fuel wood and cultural services. Outputs of the systematic map will include a database, technical report and an online interactive map, searchable by topic. The results of this map are expected to provide clarity about synergistic outcomes of conservation land management, which will help support local decision-making

A Theoretical Analysis of the Geography of Schistosomiasis in Burkina Faso Highlights the Roles of Human Mobility and Water Resources Development in Disease Transmission

We study the geography of schistosomiasis across Burkina Faso by means of a spatially explicit model of water-based disease dynamics. The model quantitatively addresses the geographic stratification of disease burden in a novel framework by explicitly accounting for drivers and controls of the disease, including spatial information on the distributions of population and infrastructure, jointly with a general description of human mobility and climatic/ecological drivers. Spatial patterns of disease are analysed by the extraction and the mapping of suitable eigenvectors of the Jacobian matrix subsuming the stability of the disease-free equilibrium. The relevance of the work lies in the novel mapping of disease burden, a byproduct of the parametrization induced by regional upscaling, by model-guided field validations and in the predictive scenarios allowed by exploiting the range of possible parameters and processes. Human mobility is found to be a primary control at regional scales both for pathogen invasion success and the overall distribution of disease burden. The effects of water resources development highlighted by systematic reviews are accounted for by the average distances of human settlements from water bodies that are habitats for the parasite's intermediate host. Our results confirm the empirical findings about the role of water resources development on disease spread into regions previously nearly disease-free also by inspection of empirical prevalence patterns. We conclude that while the model still needs refinements based on field and epidemiological evidence, the proposed framework provides a powerful tool for large-scale public health planning and schistosomiasis management

Analysis of the uncertainty in flood predictions of GloFAS forecasts for Piura in the Pacific region of Peru

GloFAS is a global flood awareness system based on a distributed hydrological model forced with numerical ensemble weather predictions (Alfieri et al. 2013). Results are published on a password-protected website. Forecasts from the GloFAS are currently limited in resolution and quality, but are nonetheless being used by humanitarian and aid organisations and a small number of forecasting agencies. One such agency is SENHAMI in Peru. To get around the limited accuracy issue, SENHAMI are applying a simple bias correction to the initial conditions of the GloFAS forecasts. This process is reliant on in situ measurements being available and reliable, therefore limiting the locations which can be corrected. Also, the uncertainties of the initials conditions are reduced but the remaining uncertainties will continue limiting the predictability of the forecasts. This research aims to understand and quantify the inaccuracy and uncertainties in the GloFAS forecasts for the Pacific region of Peru. The work will explore ways of improving the predictability of the forecasts within the GloFAS framework. The research will start with looking at the performance of the three main components of the GloFAS forecasting system: the forcing data, the runoff component and the flow routing component. The forcing data, consisting of the ERA-Intrim (Dee et al. 2011) and Variable Resolution Ensemble Prediction System (Miller et al. 2010),will be validated. The starting point will be finding if the weak rainfall along the Pacific coast caused by the large-scale mid tropospheric subsidence over the southeaster subtropical Pacific Ocean and enhanced by the coastal upwelling of cold air (Garreaud, Rutliant, and Fuenzalida 2002), is present in the forcing data. The representation of the hydrological processes, as done by HTESSEL, will be analysed focussing on the surface runoff, subsurface runoff and soil moisture. The results of the flow routing model, LisFlood-Global, will be validated, focussing on the channel and subsurface flow components. Performance of the model will be quantified with as a starting point using the performance indicators available in the Ensemble Verification System (Brown 2010). The uncertainty will be quantified and alternatives to the bias correction methods reliant on in situ measurements will be trialled, starting with the nonparametric data-based approach (Van Steenbergen, Ronsyn, andWillems 2012). The increased understanding of the flow predictability in the Pacific region of Peru will allow a widening of the use of forecasts to catchments which do not contain in situ measurements and potentially to catchments without any measurements at all

Future Flows Climate: an ensemble of 1-km climate change projections for hydrological application in Great Britain

The dataset Future Flows Climate was developed as part of the project ''Future Flows and Groundwater Levels'' to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications, and to enable climate change uncertainty and climate variability to be accounted for in the assessment of their possible impacts on the environment. <br><br> Future Flows Climate is derived from the Hadley Centre's ensemble projection HadRM3-PPE that is part of the basis of UKCP09 and includes projections in available precipitation (water available to hydrological processes after snow and ice storages have been accounted for) and potential evapotranspiration. It corresponds to an 11-member ensemble of transient projections from January 1950 to December 2098, each a single realisation from a different variant of HadRM3. Data are provided on a 1-km grid over the HadRM3 land areas at a daily (available precipitation) and monthly (PE) time step as netCDF files. <br><br> Because systematic biases in temperature and precipitation were found between HadRM3-PPE and gridded temperature and precipitation observations for the 1962–1991 period, a monthly bias correction procedure was undertaken, based on a linear correction for temperature and a quantile-mapping correction (using the gamma distribution) for precipitation followed by a spatial downscaling. Available precipitation was derived from the bias-corrected precipitation and temperature time series using a simple elevation-dependant snow-melt model. Potential evapotranspiration time series were calculated for each month using the FAO-56 Penman-Monteith equations and bias-corrected temperature, cloud cover, relative humidity and wind speed from HadRM3-PPE along with latitude of the grid and the day of the year. <br><br> Future Flows Climate is freely available for non-commercial use under certain licensing conditions. It is the dataset used to generate Future Flows Hydrology, an ensemble of transient projections of daily river flow and monthly groundwater time series for representative river basins and boreholes in Great Britain. <br><br> <a href="http://dx.doi.org/10.5285/bad1514f-119e-44a4-8e1e-442735bb9797"target="_blank">doi:10.5285/bad1514f-119e-44a4-8e1e-442735bb9797</a>

Future Flows: a dataset of climate, river flow and groundwater levels for climate change impact studies in Great Britain

Science understanding suggests that anthropogenic greenhouse gas emissions will result in a changed climate that will in turn modify patterns of river flow and groundwater recharge, affecting the availability of water and changing the aquatic environment. While many studies have investigated the impact of climate change on river flows in Great Britain, their coverage is uneven and methods vary, and it is very difficult to compare results from different locations and different sectors and to identify appropriate adaptation responses. Future Flows is a set of nationally consistent projections of climate (1-km gridded daily precipitation and 5-km monthly potential evapotranspiration), river flow (for 282 catchments) and groundwater level (at 24 boreholes) for Great Britain at space and time resolutions for hydrological applications. It is based on the Hadley Centre’s 11-member ensemble projections HadRM3-PPE run under the Medium emission scenario SRES A1B. The 11 plausible realisations (all equally likely) of nearly 150 years (from 1951 to 2098), described by Future Flows, enable the role of climate variability on river flow and groundwater levels nationally to be investigated and how this may change in the future. Some climate change uncertainty is accounted for by considering all ensemble members together. In addition to the time series, Future Flows contains information on modelling errors in the river flow and groundwater level projections in the form of catchment fact sheets. These fact sheets contain performance measures for hydrological statistics including monthly flow, flow percentiles and for some catchments flood peaks, and separately the hydro(geo)logical modelling errors from the fuller chain of climate-to-hydrology modelling. This information enables any potential user to have a clear view of the modelling uncertainty before they use the data. Future Flows Climate and Future Flows Hydrology are each associated with a Digital Object Identifier and are available to the research community free of charge for non commercial work

A rainfall threshold-based approach to early warnings in urban data-scarce regions: A case study of pluvial flooding in Alexandria, Egypt

Rapidly expanding cities in the Middle Eastern and North African (MENA) region are at risk of flooding due to heavy rainfall, insufficient drainage capacity, a lack of preparedness and insufficient data to conduct required studies. A low regret Early Warning Systems (EWS) using rainfall thresholds is proposed as a cost-effective short-term solution. This study aims to utilise a probabilistic approach to characterise and predict urban floods by assessing critical rainfall thresholds likely to cause flooding combined with ensemble precipitation forecast in Alexandria, Egypt. Rainfall thresholds were inferred by associating observed rainfall and historical flood information sourced from social media and newspapers. Floods were classified in a colour-coded hazard matrix as no flood (green), minor flood (yellow), significant flood (orange), and severe flood (red). Probability of occurrence of hazard classes was derived by incorporating ensemble rainfall into the hazard matrix to jointly evaluate likelihood and hazard severity. Results from this study showed that three of four severe events analysed could have been predicted with a high likelihood up to 24 hr before. The presented approach supports decision making to issue warnings and flood control actions with limited data and is a model for other data scare regions.Hydraulic Structures and Flood Ris