Variable crustal structure along the Juan de Fuca Ridge : influence of on-axis hot spots and absolute plate motions

Author Posting. © American Geophysical Union, 2008. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geochemistry Geophysics Geosystems 9 (2008): Q08001, doi:10.1029/2007GC001922.Multichannel seismic and bathymetric data from the Juan de Fuca Ridge (JDFR) provide constraints on axial and ridge flank structure for the past 4–8 Ma within three spreading corridors crossing Cleft, Northern Symmetric, and Endeavour segments. Along-axis data reveal south-to-north gradients in seafloor relief and presence and depth of the crustal magma lens, which indicate a warmer axial regime to the south, both on a regional scale and within individual segments. For young crust, cross-axis lines reveal differences between segments in Moho two-way traveltimes of 200–300 ms which indicate 0.5–1 km thicker crust at Endeavour and Cleft compared to Northern Symmetric. Moho traveltime anomalies extend beyond the 5–15 km wide axial high and coincide with distinct plateaus, 32 and 40 km wide and 200–400 m high, found at both segments. On older crust, Moho traveltimes are similar for all three segments (∼2100 ± 100 ms), indicating little difference in average crustal production prior to ∼0.6 and 0.7 Ma. The presence of broad axis-centered bathymetric plateau with thickened crust at Cleft and Endeavour segments is attributed to recent initiation of ridge axis-centered melt anomalies associated with the Cobb hot spot and the Heckle melt anomaly. Increased melt supply at Cleft segment upon initiation of Axial Volcano and southward propagation of Endeavour segment during the Brunhes point to rapid southward directed along-axis channeling of melt anomalies linked to these hot spots. Preferential southward flow of the Cobb and Heckle melt anomalies and the regional-scale south-to-north gradients in ridge structure along the JDFR may reflect influence of the northwesterly absolute motion of the ridge axis on subaxial melt distribution.This work was supported by U.S. National Science Foundation grants OCE00-02488 to S.M.C., OCE06-48303 to S.M.C. and M.R.N., OCE-0648923 to J.P.C., and OCE00-02600 to G.M.K. and A.J.H

Post-Disaster Supply Chain Interdependent Critical Infrastructure System Restoration: A Review of Data Necessary and Available for Modeling

The majority of restoration strategies in the wake of large-scale disasters have focused on short-term emergency response solutions. Few consider medium- to long-term restoration strategies to reconnect urban areas to national 'supply chain interdependent critical infrastructure systems' (SCICI). These SCICI promote the effective flow of goods, services, and information vital to the economic vitality of an urban environment. To re-establish the connectivity that has been broken during a disaster between the different SCICI, relationships between these systems must be identified, formulated, and added to a common framework to form a system-level restoration plan. To accomplish this goal, a considerable collection of SCICI data is necessary. The aim of this paper is to review what data are required for model construction, the accessibility of these data, and their integration with each other. While a review of publically available data reveals a dearth of real-time data to assist modeling long-term recovery following an extreme event, a significant amount of static data does exist and these data can be used to model the complex interdependencies needed. For the sake of illustration, a particular SCICI (transportation) is used to highlight the challenges of determining the interdependencies and creating models capable of describing the complexity of an urban environment with the data publically available. Integration of such data as is derived from public domain sources is readily achieved in a geospatial environment, after all geospatial infrastructure data are the most abundant data source and while significant quantities of data can be acquired through public sources, a significant effort is still required to gather, develop, and integrate these data from multiple sources to build a complete model. Therefore, while continued availability of high quality, public information is essential for modeling efforts in academic as well as government communities, a more streamlined approach to a real-time acquisition and integration of these data is essential