Two foundational questions about sustainability are "How are ecosystems and the services they provide going to change in the future?" and "How do human decisions affect these trajectories?" Answering these questions requires an ability to forecast ecological processes Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure Effective forecasting will also require changes in scientific training, culture, and institutions The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward

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Iterative near-term ecological forecasting: Needs, opportunities, and challenges

Nanomaterials are developed for and applied in food, food additives, supplements and food contact materials. In an inventory of internet databases 140 products in the food and food-related sectors were identified that claim to contain nanomaterials. A great diversity of nanomaterials is applied, ranging from inorganic metal and metal oxides to organic nanomaterials that carry bioactive ingredients. Here we present an overview of nanomaterial applications that are currently available, discuss state of the art analytical chemical characterization and toxicological assessment methods, as well as categorization methods to support the safety evaluation of the application of nanomaterials throughout food production.

State of the safety assessment and current use of nanomaterials in food and food production

Remote sensing offers an increasingly wide array of imagery with a broad variety of spectral and spatial resolution, but there are relatively few comparisons of how different sources of data impact the accuracy, cost, and utility of analyses. We evaluated the impact of satellite image spatial resolution (1 m from Digital Globe; 30 m from Landsat) on land use classification via ArcGIS Feature Analyst, and on total suspended solids (TSS) load estimates from the Soil and Water Assessment Tool (SWAT) for the Camboriu watershed in Southeastern Brazil. We independently calibrated SWAT models, using both land use map resolutions and short-term daily streamflow (discharge) and TSS load data from local gauge stations. We then compared the predicted TSS loads with monitoring data outside the model training period. We also estimated the cost difference for land use classification and SWAT model construction and calibration at these two resolutions. Finally, we assessed the value of information (VOI) of the higher-resolution imagery in estimating the cost-effectiveness of watershed conservation in reducing TSS at the municipal water supply intake. Land use classification accuracy was 82.3% for 1 m data and 75.1% for 30 m data. We found that models using 1 m data better predicted both annual and peak TSS loads in the full study area, though the 30 m model did better in a sub-watershed. However, the 1 m data incurred considerably higher costs relative to the 30 m data ($7000 for imagery, plus additional analyst time). Importantly, the choice of spatial resolution affected the estimated return on investment (ROI) in watershed conservation for the municipal water company that finances much of this conservation, although it is unlikely that this would have affected the company's decision to invest in the program. We conclude by identifying key criteria to assist in choosing an appropriate spatial resolution for different contexts.

Impact of satellite imagery spatial resolution on land use classification accuracy and modeled water quality

Preface 1. Introduction 2. Statistical models and methods 3. Decision analysis 4. Spatial modeling 5. Value of information in spatial decision situations 6. Earth sciences applications 7. Problems and projects Appendix. Selected statistical models and sampling methods References Index.

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Value of Information in the Earth Sciences: Integrating Spatial Modeling and Decision Analysis

A growing international human population and rising living standards are increasing the demand for agricultural products. Under higher pressure over natural resources, environmental concerns are increasing as well, challenging current water use decision-making processes in irrigated agriculture. Higher agricultural productivity means water should be applied more efficiently, which requires instant information on weather, soil, and plant conditions throughout the growing season. An information-based irrigation scheduling application tightened to the spatiotemporal variability of the fields is critical for enhancing the current irrigation system and making better irrigation scheduling decisions. The aim of this study is to review current irrigation scheduling methodologies based on two case studies (woody and field crops) located in semi-arid areas of Southeast Spain. We realize that optimal irrigation programming requires consistent investment in equipment, expenditure on operation and maintenance, and qualified technical and maintenance services. These technological approaches will be worthwhile in farms with low water availability, high profitability, and significant technical-economic capacity.

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Trends and Challenges in Irrigation Scheduling in the Semi-Arid Area of Spain

The value of information (VoI) is a decision analytic method for quantifying the potential benefit of additional information in the face of uncertainty. This paper reviews the prevalence of VoI applications reported in the peer-reviewed literature from the years 1990–2011. We categorize papers’ applications across the types of uncertainties considered, modeling choices, and contexts of social importance (such as health care and environmental science). We obtain and analyze statistics on the range of applications and identify trends and patterns in them, and conclude with an interpretation of what these mean for researchers and practitioners as they pursue new efforts. Key results include a substantial increase over the last 20 years in published papers utilizing VoI, particularly in the medical field. Nineteen trends in VoI applications from the period of 1990–2000 to 2001–2011 were found to be at least weakly significant. Beyond simple trends, some characteristics of VoI usage depend on the area of application, and in some cases, certain sets of characteristics tend to be found together.

Value of information analysis: the state of application

The value of information (VoI) is a decision analytic method for quantifying the potential benefit of additional information in the face of uncertainty. This paper reviews the prevalence of VoI applications reported in the peer-reviewed literature from the years 1990–2011. We categorize papers’ applications across the types of uncertainties considered, modeling choices, and contexts of social importance (such as health care and environmental science). We obtain and analyze statistics on the range of applications and identify trends and patterns in them, and conclude with an interpretation of what these mean for researchers and practitioners as they pursue new efforts. Key results include a substantial increase over the last 20 years in published papers utilizing VoI, particularly in the medical field. Nineteen trends in VoI applications from the period of 1990–2000 to 2001–2011 were found to be at least weakly significant. Beyond simple trends, some characteristics of VoI usage depend on the area of application, and in some cases, certain sets of characteristics tend to be found together.

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Eric Chu

Papers

Value of information analysis: the state of application

Value of information analysis: The state of application. Environment Systems & Decisions