Implications of Spatially Variable Costs and Habitat Conversion Risk in Landscape-Scale Conservation Planning

‘‘Strategic habitat conservation’’ refers to a process used by the U.S. Fish and Wildlife Service to develop cost-efficient strategies for conserving wildlife populations and their habitats. Strategic habitat conservation focuses on resolving uncertainties surrounding habitat conservation to meet specific wildlife population objectives (i.e., targets) and developing tools to guide where conservation actions should be focused on the landscape. Although there are examples of using optimization models to highlight where conservation should be delivered, such methods often do not explicitly account for spatial variation in the costs of conservation actions. Furthermore, many planning approaches assume that habitat protection is a preferred option, but they do not assess its value relative to other actions, such as restoration. We developed a case study to assess the implications of accounting for and ignoring spatial variation in conservation costs in optimizing conservation targets. We included assumptions about habitat loss to determine the extent to which protection or restoration would be necessary to meet an established population target. Our case study focused on optimal placement of grassland protection or restoration actions to influence bobolink Dolichonyx oryzivorus populations in the tallgrass prairie ecoregion of the north central United States. Our results show that not accounting for spatially variable costs doubled or tripled the cost of meeting the population target. Furthermore, our results suggest that one should not assume that protecting existing habitat is always a preferred option. Rather, our results show that the balance between protection and restoration can be influenced by a combination of desired targets, assumptions about habitat loss, and the relative cost of the two actions. Our analysis also points out how difficult it may be to reach targets, given the expense to meet them. We suggest that a full accounting of expected costs and benefits will help to guide development of viable management actions and meaningful conservation plans

Temporal characteristics of the influence of punishment on perceptual decision making in the human brain

Perceptual decision making is the process by which information from sensory systems is combined and used to influence our behavior. In addition to the sensory input, this process can be affected by other factors, such as reward and punishment for correct and incorrect responses. To investigate the temporal dynamics of how monetary punishment influences perceptual decision making in humans, we collected electroencephalography (EEG) data during a perceptual categorization task whereby the punishment level for incorrect responses was parametrically manipulated across blocks of trials. Behaviorally, we observed improved accuracy for high relative to low punishment levels. Using multivariate linear discriminant analysis of the EEG, we identified multiple punishment-induced discriminating components with spatially distinct scalp topographies. Compared with components related to sensory evidence, components discriminating punishment levels appeared later in the trial, suggesting that punishment affects primarily late postsensory, decision-related processing. Crucially, the amplitude of these punishment components across participants was predictive of the size of the behavioral improvements induced by punishment. Finally, trial-by-trial changes in prestimulus oscillatory activity in the alpha and gamma bands were good predictors of the amplitude of these components. We discuss these findings in the context of increased motivation/attention, resulting from increases in punishment, which in turn yields improved decision-related processing

Advances and visions in large-scale hydrological modelling: findings from the 11th Workshop on Large-Scale Hydrological Modelling

Large-scale hydrological modelling has become increasingly wide-spread during the last decade. An annual workshop series on large-scale hydrological modelling has provided, since 1997, a forum to the German-speaking community for discussing recent developments and achievements in this research area. In this paper we present the findings from the 2007 workshop which focused on advances and visions in large-scale hydrological modelling. We identify the state of the art, difficulties and research perspectives with respect to the themes "sensitivity of model results", "integrated modelling" and "coupling of processes in hydrosphere, atmosphere and biosphere". Some achievements in large-scale hydrological modelling during the last ten years are presented together with a selection of remaining challenges for the future

Risk, wealth and agrarian change in India: household-level hazards vs. late-modern global risks at different points along the risk transition

The global poor often prioritise immediate hazards of food insecurity over temporally more distant risks like global warming. Yet the influence of socio-economic factors, temporal and spatial distance on risk perception remains under-researched. Data on risk perception and response were collected from two sets of Indian villages. Participatory approaches were used to investigate variations by socio-economic status, food security, age and gender. Villagers’ risk priorities reflected clear spatial and temporal patterns depending on land ownership, community group and education levels. Poorer groups prioritised household-level risks to health and food security while global environmental risks were mentioned by only three of the wealthiest respondents. The paper concludes that household risk perceptions and responses vary greatly with socio-economic status, age, gender and the spatial or temporal distance of the risk. These factors need to be better understood if the most significant contributors to the global burden of disease are to be reduced

Decision Support System for Soybean Rust (Phakopsora pachyrhizi) Management using QnD

The objective of this project is to design a decision support system for soybean rust management using gaming software that incorporates farmer's decision making in the face of risks from soybean rust. Learning from past actions and neighbor's actions are also incorporated. Farmers observe rust outbreak in the current and past periods and decide over how much of land to allocate between soybean, corn and other crops. This decision is influenced by maximization of expected profits criterion which entails crop rotation choices that are based upon perceived risks, yield drags and input costs from altering optimum rotation patterns. Adoption of new technology in terms of selecting better rust management practices is also analyzed in an adaptive management framework. The software meets the need of guiding policy formulation besides training stakeholders in making economically sound choices in the absence of empirical data over pest infestation.Research Methods/ Statistical Methods,

FROM DATA TO INFORMATION: THE VALUE OF SAMPLING VS. SENSING SOIL DATA

A conceptual model is developed to measure the value of information from in-field soil sensing technologies as compared with grid and other soil sampling methods. Soil sensing offers greater spatial accuracy and the potential to apply inputs such as nitrogen fertilizer immediately, avoiding changes in nutrient status that occur with delays between soil sampling and fertilizer application. By contrast, soil sampling offers greater measurement accuracy, because it does not rely on proxy variables such as electrical conductivity to infer nutrient status. The average profitability and relative riskiness of soil sensing versus sampling depend upon 1) the trade-off between, on the one hand, the spatial and temporal accuracy of sensing and, on the other hand, the measurement accuracy of sampling, 2) the cost of data collection, and 3) input and product prices. Similar trade-offs govern the relative riskiness of sensing versus sampling.Farm Management,

National Aeronautics and Space Administration fundamental research program. Information utilization and evaluation

In the second half of the 1980's NASA can expect to face difficult choices among alternative fundamental and applied research, and development projects that could potentially lead to improvements in the information systems used to manage renewable resources. The working group on information utilization and evaluation believes that effective choices cannot be made without a better understanding of the current and prospective problems and opportunities involved in the application of remote sensing to improve renewable research information systems. A renewable resources information system is defined in a broad context to include a flow of data/information from: acquisition through processing, storage, integration with other data, analysis, graphic presentation, decision making, and assessment of the affects of those decisions