This paper applies methods of multiple resolution map comparison to quantify characteristics for 13 applications of 9 different popular peer-reviewed land change models. Each modeling application simulates change of land categories in raster maps from an initial time to a subsequent time. For each modeling application, the statistical methods compare: (1) a reference map of the initial time, (2) ence map of the subsequent time, and (3) a prediction map of the subsequent time. The three possible two-map comparisons for each application characterize: (1) the dynamics of the landscape, (2) the behavior of the model, and (3) the accuracy of the prediction. The three-map comparison for each application specifies the amount of the prediction's accuracy that is attributable to land persistence versus land change. Results show that the amount of error is larger than the amount of correctly predicted change for 12 of the 13 applications at the resolution of the raw data. The applications are summarized and compared using two statistics: the null resolution and the figure of merit. According to the figure of merit, the more accurate applications are the 123Comparing the input, output, and validation maps for several models of land change 13 ones where the amount of observed net change in the reference maps is larger. This paper facilitates communication among land change modelers, because it illustrates the range of results for a variety of models using scientifically rigorous, generally applicable, and intellectually accessible statistical techniques. JEL Classification
Climate change is likely to affect the infectious disease burden from exposure to pathogens in water used for drinking and recreation. Effective intervention measures require quantification of impacts of climate change on the distribution of pathogens in the environment and their potential effects on human health. Objectives of this systematic review were to summarize current knowledge available to estimate how climate change may directly and indirectly affect infection risks due to Campylobacter, Cryptosporidium, norovirus, and Vibrio. Secondary objectives were to prioritize natural processes and interactions that are susceptible to climate change and to identify knowledge gaps. Search strategies were determined based on a conceptual model and scenarios with the main emphasis on The Netherlands. The literature search resulted in a large quantity of publications on climate variables affecting pathogen input and behavior in aquatic environments. However, not all processes and pathogens are evenly covered by the literature, and in many cases, the direction of change is still unclear. To make useful predictions of climate change, it is necessary to combine both negative and positive effects. This review provides an overview of the most important effects of climate change on human health and shows the importance of QMRA to quantify the net effects.
Faeces originating from wildlife, domestic animals or manure-fertilized fields, is considered an important source of zoonotic pathogens to which people may be exposed by, for instance, bathing or drinking-water consumption. An increase in runoff, and associated wash-off of animal faeces from fields, is assumed to contribute to the increase of disease outbreaks during periods of high precipitation. Climate change is expected to increase winter precipitation and extreme precipitation events during summer, but has simultaneously also other effects such as temperature rise and changes in evapotranspiration. The question is to what extent the combination of these effects influence the input of zoonotic pathogens to the surface waters. To quantitatively analyse the impacts of climate change on pathogen runoff, pathogen concentrations reaching surface waters through runoff were calculated by combining an input model for catchment pathogen loads with the Wageningen Lowland Runoff Simulator (WALRUS). Runoff of Cryptosporidium and Campylobacter was evaluated under different climate change scenarios and by applying different scenarios for sources of faecal pollution in the catchments, namely dairy cows and geese and manure fertilization. Model evaluation of these scenarios shows that climate change has little overall impact on runoff of Campylobacter and Cryptosporidium from land to the surface waters. Even though individual processes like runoff fluxes, pathogen release and dilution are affected, either positively or negatively, the net effect on the pathogen concentration in surface waters and consequently also on infection risks through recreation seems limited.
Environment Explorer is a system developed to support spatial scientists, planners and decision makers at the regional and national level in the Netherlands to analyse a wide range of social, economic and environmental policies and their associated spatial patterns. The core of this system consists of linked dynamic spatial models operating at both the micro-and the macro-geographical scales. At the macro scale, the modelling framework integrates several component sub-models, representing the natural, social, and economic subsystems. At the micro level, cellular automata based models determine the faith of individual parcels of land based on institutional, physical and environmental factors as well as on the type of activities in their neighbourhoods. The approach enables the straightforward integration of detailed physical, environmental, and institutional variables as well as the particulars of the transportation infrastructure, and permits a very detailed and integral representation of the evolving spatial system. In the policy support system the models are supplemented with dedicated tools for interactive design, analysis and evaluation of policy interventions and scenarios. This system covers the entire territory of the Netherlands and represents processes at the national, the regional (40 administrative regions), and the cellular (25 ha cells) levels. It runs on top of detailed GIS information and generates future land use and land cover for the period 2000 till 2030. The quality of the alternatives tried out is expressed in some 40 economic, social and environmental indicators available in the model as dynamic maps. The application has been developed over the past 5 years. It has been used at the national and the provincial level for the preparation of spatial policy documents. Some conclusions relative to the development and the use of the system are presented.
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