Use Cases for EIS Databases

An overview of use cases supporting the development of an online database of environmental impact statements

Using satellite data to develop environmental indicators

Environmental indicators are increasingly being used in policy and management contexts, yet serious data deficiencies exist for many parameters of interest to environmental decision making. With its global synoptic coverage and the wide range of instruments available, satellite remote sensing has the potential to fill a number of these gaps, yet their potential contribution to indicator development has largely remained untested. In this paper we present results of a pilot effort to develop satellite-derived indicators in three major issue areas: ambient air pollution, coastal eutrophication, and biomass burning. A primary focus is on the vetting of indicators by an advisory group composed of remote sensing scientists and policy makers

Malaria Stratification, Climate, and Epidemic Early Warning in Eritrea

Eritrea has a successful malaria control program, but it is still susceptible to devastating malaria epidemics. Monthly data on clinical malaria cases from 242 health facilities in 58 subzobas (districts) of Eritrea from 1996 to 2003 were used in a novel stratification process using principal component analysis and nonhierarchical clustering to define five areas with distinct malaria intensity and seasonality patterns, to guide future interventions and development of an epidemic early warning system. Relationships between monthly clinical malaria incidence by subzoba and monthly climate data from several sources, and with seasonal climate forecasts, were investigated. Remotely sensed climate data were averaged over the same subzoba geographic administrative units as the malaria cases. Although correlation was good between malaria anomalies and actual rainfall from ground stations (lagged by 2 months), the stations did not have sufficiently even coverage to be widely useful. Satellite derived rainfall from the Climate Prediction Center Merged Analysis of Precipitation was correlated with malaria incidence anomalies, with a lead time of 2–3 months. NDVI anomalies were highly correlated with malaria incidence anomalies, particularly in the semi-arid north of the country and along the northern Red Sea coast, which is a highly epidemic-prone area. Eritrea has 2 distinct rainy seasons in different parts of the country. The seasonal forecasting skill from Global Circulation Models for the June/July/August season was low except for the Eastern border. For the coastal October/November/December season, forecasting skill was good only during the 1997–1998 El Niño event. For epidemic control, shorter-range warning based on remotely sensed rainfall estimates and an enhanced epidemic early-detection system based on data derived for this study are needed

Assessment of Select Climate Change Impacts on U.S. National Security

This report examines climate change impacts to U.S. national security by quantifying select impacts globally at the national level and identifying countries that are both at high risk from projected climate change and possess risk factors associated with political instability. Exposure to global sea‐level rise risk exposure is quantified by identifying low‐elevation coastal zones (LECZ), at 1, 3, 5, 7, 9, 10 and 12 meters of elevation. Countries with high risk factors for instability that also have the most people exposed to sea‐level rise include China, Philippines, India, and Indonesia. Those with the greatest percentage of population so exposed include Philippines, Egypt, and Indonesia. Within these countries, Egypt has especially high rates of population growth within the LECZ. Aggregate climate change vulnerability is quantified by using an index that takes into account both projected temperature change and adaptive capacity. For countries with high risk factors for instability, the most vulnerable countries are South Africa, Nepal, Morocco, Bangladesh, Tunisia, Paraguay, Yemen, Sudan and Côte d’Ivoire. Water scarcity is examined by comparing numbers of people living under conditions of water in the present with three future scenarios – one in which the climate remains unchanged but population changes; one in which population changes but the climate remains static; and one in which both population and climate change. Countries with high risk factors for instability that are projected to have the biggest increases in water scarcity are Mozambique, Côte d’Ivoire, Nigeria, Iraq, Guatemala, Zimbabwe, Ethiopia, Somalia, China, Syria and Algeria

Use Cases for EIS Databases

An overview of use cases supporting the development of an online database of environmental impact statements

Data Integration for Climate Vulnerability Mapping in West Africa

Vulnerability mapping reveals areas that are likely to be at greater risk of climate-related disasters in the future. Through integration of climate, biophysical, and socioeconomic data in an overall vulnerability framework, so-called “hotspots” of vulnerability can be identified. These maps can be used as an aid to targeting adaptation and disaster risk management interventions. This paper reviews vulnerability mapping efforts in West Africa conducted under the USAID-funded African and Latin American Resilience to Climate Change (ARCC) project. The focus is on the integration of remotely sensed and socioeconomic data. Data inputs included a range of sensor data (e.g., MODIS NDVI, Landsat, SRTM elevation, DMSP-OLS night-time lights) as well as high-resolution poverty, conflict, and infrastructure data. Two basic methods were used, one in which each layer was transformed into standardized indicators in an additive approach, and another in which remote sensing data were used to contextualize the results of composite indicators. We assess the benefits and challenges of data integration, and the lessons learned from these mapping exercises

A Framework for Monitoring Ecosystems-Based Adaptation to Climate Change: Experience from The Gambia

Implementing ecosystems-based adaptation (EbA) to climate change is challenged by the need to monitor biophysical, socio-cultural, and economic impacts which are usually context-specific. Therefore, robust frameworks are required that integrate impacts to better understand EbA effectiveness. Monitoring frameworks that are universally applicable to EbA are desirable, however their universal application is problematic as they should reflect a community-driven design that accommodates both donor reporting functions and the generation of local-level data and information to support management actions and community initiatives. Initial products from this research include a generic, five-step process for developing and testing adaptation indicators, a robust framework consisting of (i) the indicators, data and information used to design the framework, (ii) the operational EbA platform that houses and computes the adaptation indicators, and (iii) the participating institutions, and initial, community-level applications to guide water management, replenishment of the vegetation cover, and business development. Immediate benefits to rural communities include the re-orientation of performance indicators mapped to their needs as opposed to donor reporting alone. The framework contributes to the set of tools currently in use for EbA monitoring by offering an umbrella within which existing tools can be applied. Near-term future research will focus on improving the utility of the framework and its platform beyond reporting on key performance indicators (KPIs) by adapting the EbA platform to support changing management needs. Future research will be needed to understand the extent to which the environmental changes in The Gambia compared to changes across the Sahel and Sudano-Sahel regions of West Africa and whether the lessons learned from The Gambia could be extrapolated to the subregion

Does socio-economic status explain the differentials in malaria parasite prevalence? Evidence from The Gambia

Malaria is commonly associated with poverty. Macro-level estimates show strong links between malaria and poverty, and increasing evidence suggests that the causal link between malaria and poverty runs in both directions. However, micro-level (household and population) analyses on the linkages between malaria and poverty have often produced mixed results. The Gambia Malaria Indicator Survey (MIS) 2010/11 was carried out between November 2010 and January 2011. Laboratory-confirmed malaria and wealth quintiles were used to assess the association of socio-economic status and malaria infection in children and the general population. Simple and multiple logistic regressions and survey data analysis procedures, including linearized standard errors to account for cluster sampling and unequal selection probabilities were applied. Children (six to 59 months) from the second, third, fourth and richest quintiles were significantly less likely to have malaria compared to children from the poorest quintiles. Children (five to 14 years) from the fourth and richest quintiles were also significantly less likely to have malaria compared to those from the poorest quintiles. The malaria burden has shifted from the under-five children (six to 59 months) to children aged five to 14 years. Malaria prevalence was significantly higher in the Central River Region compared to the Upper River Region; and males bear the malaria brunt more than females. Children (six to 59 months) and children (five to 14 years) living in houses with poor walls, floors, roofs and windows were significant associated with higher prevalence of malaria. However, in the general population, only poor wall housing materials were associated with higher prevalence of malaria. Investments in strategies that address socio-economic disparities and improvements in the quality of housing could, in the long term, significantly reduce the malaria burden in the poorest communities

Edge influence on forest structure and composition in fragmented landscapes

Although forest edges have been studied extensively as an important consequence of fragmentation, a unifying theory of edge influence has yet to be developed. Our objective was to take steps toward the development of such a theory by (1) synthesizing the current knowledge of patterns of forest structure and composition at anthropogenically created forest edges, (2) developing hypotheses about the magnitude and distance of edge influence that consider the ecological processes influencing these patterns, and (3) identifying needs for future research. We compiled data from 44 published studies on edge influence on forest structure and composition in boreal, temperate, and tropical forests. Abiotic and biotic gradients near created forest edges generate a set of primary responses to edge creation. Indirect effects from these primary responses and the original edge gradient perpetuate edge influence, leading to secondary responses. Further changes in vegetation affect the edge environment, resulting in ongoing edge dynamics. We suggest that the magnitude and distance of edge influence are a direct function of the contrast in structure and composition between adjacent communities on either side of the edge. Local factors such as climate, edge characteristics, stand attributes, and biotic factors affect patch contrast. Regional factors define the context within which to assess the ecological significance of edge influence (the degree to which the edge habitat differs from interior forest habitat). Our hypotheses will help predict edge influence on structure and composition in forested ecosystems, an important consideration for conservation. For future research on forest edges in fragmented landscapes, we encourage the testing of our hypotheses, the use of standardized methodology, complete descriptions of study sites, studies on other types of edges, synthesis of edge influence on different components of the ecosystem, and investigations of edges in a landscape context