The Terrestrial Carbon (Terra C) Information System to facilitate carbon synthesis across heterogeneous landscapes.

There are urgent needs to better synthesize knowledge and data across large regions and time periods to address global climate change, conduct soil/terrestrial carbon accounting, model carbon dynamics, assess carbon sequestration, and develop strategies for mitigation and adaptation. To address these needs we developed the Terrestrial Carbon (TerraC) Information System dedicated to advance soil/terrestrial carbon science. TerraC offers user-friendly tools to upload, store, manage, query, analyze, and download lab and field data characterizing carbon in soils, plants/biomass, atmosphere, water, and whole ecosystems. The purpose of TerraC is three-fold to: (i) advance carbon science through sharing of carbon and ancillary environmental data; (ii) facilitate environmental synthesis; and (iii) enhance collaboration among students, faculty, scientists, and extension specialists through shared resources. Data and metadata stored in TerraC can be shared privately among selected users (groups) or publicly with any user. We integrated various spatially-explicit soil carbon and ancillary environmental data collected in Florida representing different time periods, and conducted a synthesis analysis on soil carbon that will be presented as a case study. Detailed information about TerraC and data sharing options are available at: http://TerraC.ifas.ufl.edu

Great SCO2T! Rapid tool for carbon sequestration science, engineering, and economics

CO2 capture and storage (CCS) technology is likely to be widely deployed in coming decades in response to major climate and economics drivers: CCS is part of every clean energy pathway that limits global warming to 2C or less and receives significant CO2 tax credits in the United States. These drivers are likely to stimulate capture, transport, and storage of hundreds of millions or billions of tonnes of CO2 annually. A key part of the CCS puzzle will be identifying and characterizing suitable storage sites for vast amounts of CO2. We introduce a new software tool called SCO2T (Sequestration of CO2 Tool, pronounced "Scott") to rapidly characterizing saline storage reservoirs. The tool is designed to rapidly screen hundreds of thousands of reservoirs, perform sensitivity and uncertainty analyses, and link sequestration engineering (injection rates, reservoir capacities, plume dimensions) to sequestration economics (costs constructed from around 70 separate economic inputs). We describe the novel science developments supporting SCO2T including a new approach to estimating CO2 injection rates and CO2 plume dimensions as well as key advances linking sequestration engineering with economics. Next, we perform a sensitivity and uncertainty analysis of geology combinations (including formation depth, thickness, permeability, porosity, and temperature) to understand the impact on carbon sequestration. Through the sensitivity analysis we show that increasing depth and permeability both can lead to increased CO2 injection rates, increased storage potential, and reduced costs, while increasing porosity reduces costs without impacting the injection rate (CO2 is injected at a constant pressure in all cases) by increasing the reservoir capacity.Comment: CO2 capture and storage; carbon sequestration; reduced-order modeling; climate change; economic

The Web as an Adaptive Network: Coevolution of Web Behavior and Web Structure

Much is known about the complex network structure of the Web, and about behavioral dynamics on the Web. A number of studies address how behaviors on the Web are affected by different network topologies, whilst others address how the behavior of users on the Web alters network topology. These represent complementary directions of influence, but they are generally not combined within any one study. In network science, the study of the coupled interaction between topology and behavior, or state-topology coevolution, is known as 'adaptive networks', and is a rapidly developing area of research. In this paper, we review the case for considering the Web as an adaptive network and several examples of state-topology coevolution on the Web. We also review some abstract results from recent literature in adaptive networks and discuss their implications for Web Science. We conclude that adaptive networks provide a formal framework for characterizing processes acting 'on' and 'of' the Web, and offers potential for identifying general organizing principles that seem otherwise illusive in Web Scienc

City networks in cyberspace and time : using Google hyperlinks to measure global economic and environmental crises

Geographers and social scientists have long been interested in ranking and classifying the cities of the world. The cutting edge of this research is characterized by a recognition of the crucial importance of information and, specifically, ICTs to cities’ positions in the current Knowledge Economy. This chapter builds on recent “cyberspace” analyses of the global urban system by arguing for, and demonstrating empirically, the value of Web search engine data as a means of understanding cities as situated within, and constituted by, flows of digital information. To this end, we show how the Google search engine can be used to specify a dynamic, informational classification of North American cities based on both the production and the consumption of Web information about two prominent current issues global in scope: the global financial crisis, and global climate change