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Torregrosa A.,Western Geographic Science Center | Taylor M.D.,Western Geographic Science Center | Flint L.E.,California Water Science Center | Flint A.L.,California Water Science Center
PLoS ONE | Year: 2013

Bioclimates are syntheses of climatic variables into biologically relevant categories that facilitate comparative studies of biotic responses to climate conditions. Isobioclimates, unique combinations of bioclimatic indices (continentality, ombrotype, and thermotype), were constructed for northern California coastal ranges based on the Rivas-Martinez worldwide bioclimatic classification system for the end of the 20th century climatology (1971-2000) and end of the 21st century climatology (2070-2099) using two models, Geophysical Fluid Dynamics Laboratory (GFDL) model and the Parallel Climate Model (PCM), under the medium-high A2 emission scenario. The digitally mapped results were used to 1) assess the relative redistribution of isobioclimates and their magnitude of change, 2) quantify the loss of isobioclimates into the future, 3) identify and locate novel isobioclimates projected to appear, and 4) explore compositional change in vegetation types among analog isobioclimate patches. This study used downscaled climate variables to map the isobioclimates at a fine spatial resolution -270 m grid cells. Common to both models of future climate was a large change in thermotype. Changes in ombrotype differed among the two models. The end of 20th century climatology has 83 isobioclimates covering the 63,000 km2 study area. In both future projections 51 of those isobioclimates disappear over 40,000 km2. The ordination of vegetation-bioclimate relationships shows very strong correlation of Rivas-Martinez indices with vegetation distribution and composition. Comparisons of vegetation composition among analog patches suggest that vegetation change will be a local rearrangement of species already in place rather than one requiring long distance dispersal. The digitally mapped results facilitate comparison with other Mediterranean regions. Major remaining challenges include predicting vegetation composition of novel isobioclimates and developing metrics to compare differences in climate space.


Apatu E.J.I.,University of North Florida | Gregg C.E.,East Tennessee State University | Wood N.J.,Western Geographic Science Center | Wang L.,East Tennessee State University
Disasters | Year: 2016

Tsunamis represent significant threats to human life and development in coastal communities. This quantitative study examines the influence of household characteristics on evacuation actions taken by 211 respondents in American Samoa who were at their homes during the 29 September 2009 Mw 8.1 Samoa Islands earthquake and tsunami disaster. Multiple logistic regression analysis of survey data was used to examine the association between evacuation and various household factors. Findings show that increases in distance to shoreline were associated with a slightly decreased likelihood of evacuation, whereas households reporting higher income had an increased probability of evacuation. The response in American Samoa was an effective one, with only 34 fatalities in a tsunami that reached shore in as little as 15 minutes. Consequently, future research should implement more qualitative study designs to identify event and cultural specific determinants of household evacuation behaviour to local tsunamis. © 2016 The Author(s). Disasters © Overseas Development Institute, 2016


Peters J.,Western Geographic Science Center | Wood N.,Western Geographic Science Center | Wilson R.,California Geological Survey | Miller K.,California Governor's Office of Emergency Services
Natural Hazards | Year: 2016

Tsunami-evacuation planning in coastal communities is typically based on maximum evacuation zones for a single scenario or a composite of sources; however, this approach may over-evacuate a community and overly disrupt the local economy and strain emergency-service resources. To minimize the potential for future over-evacuations, multiple evacuation zones based on arrival time and inundation extent are being developed for California coastal communities. We use the coastal city of Alameda, California (USA), as a case study to explore population and evacuation implications associated with multiple tsunami-evacuation zones. We use geospatial analyses to estimate the number and type of people in each tsunami-evacuation zone and anisotropic pedestrian evacuation models to estimate pedestrian travel time out of each zone. Results demonstrate that there are tens of thousands of individuals in tsunami-evacuation zones on the two main islands of Alameda, but they will likely have sufficient time to evacuate before wave arrival. Quality of life could be impacted by the high number of government offices, schools, day-care centers, and medical offices in certain evacuation zones and by potentially high population density at one identified safe area after an evacuation. Multi-jurisdictional evacuation planning may be warranted, given that many at-risk individuals may need to evacuate to neighboring jurisdictions. The use of maximum evacuation zones for local tsunami sources may be warranted given the limited amount of available time to confidently recommend smaller zones which would result in fewer evacuees; however, this approach may also result in over-evacuation and the incorrect perception that successful evacuations are unlikely. © 2016 The Author(s)


Wood N.,Western Geographic Science Center | Jones J.,Western Geographic Science Center | Schmidtlein M.,California State University, Sacramento | Schelling J.,Building | Frazier T.,Binghamton University State University of New York
International Journal of Disaster Risk Reduction | Year: 2016

Successful evacuations are critical to saving lives from future tsunamis. Pedestrian-evacuation modeling related to tsunami hazards primarily has focused on identifying areas and the number of people in these areas where successful evacuations are unlikely. Less attention has been paid to identifying evacuation pathways and population demand at assembly areas for at-risk individuals that may have sufficient time to evacuate. We use the neighboring coastal communities of Hoquiam, Aberdeen, and Cosmopolis (Washington, USA) and the local tsunami threat posed by Cascadia subduction zone earthquakes as a case study to explore the use of geospatial, least-cost-distance evacuation modeling for supporting evacuation outreach, response, and relief planning. We demonstrate an approach that uses geospatial evacuation modeling to (a) map the minimum pedestrian travel speeds to safety, the most efficient paths, and collective evacuation basins, (b) estimate the total number and demographic description of evacuees at predetermined assembly areas, and (c) determine which paths may be compromised due to earthquake-induced ground failure. Results suggest a wide range in the magnitude and type of evacuees at predetermined assembly areas and highlight parts of the communities with no readily accessible assembly area. Earthquake-induced ground failures could obstruct access to some assembly areas, cause evacuees to reroute to get to other assembly areas, and isolate some evacuees from relief personnel. Evacuation-modeling methods and results discussed here have implications and application to tsunami-evacuation outreach, training, response procedures, mitigation, and long-term land use planning to increase community resilience. © 2016.


Wood N.,Western Geographic Science Center | Jones J.,Western Geographic Science Center | Schelling J.,Building | Schmidtlein M.,California State University, Sacramento
International Journal of Disaster Risk Reduction | Year: 2014

Tsunami vertical-evacuation (TVE) refuges can be effective risk-reduction options for coastal communities with local tsunami threats but no accessible high ground for evacuations. Deciding where to locate TVE refuges is a complex risk-management question, given the potential for conflicting stakeholder priorities and multiple, suitable sites. We use the coastal community of Ocean Shores (Washington, USA) and the local tsunami threat posed by Cascadia subduction zone earthquakes as a case study to explore the use of geospatial, multi-criteria decision analysis for framing the locational problem of TVE siting. We demonstrate a mixed-methods approach that uses potential TVE sites identified at community workshops, geospatial analysis to model changes in pedestrian evacuation times for TVE options, and statistical analysis to develop metrics for comparing population tradeoffs and to examine influences in decision making. Results demonstrate that no one TVE site can save all at-risk individuals in the community and each site provides varying benefits to residents, employees, customers at local stores, tourists at public venues, children at schools, and other vulnerable populations. The benefit of some proposed sites varies depending on whether or not nearby bridges will be functioning after the preceding earthquake. Relative rankings of the TVE sites are fairly stable under various criteria-weighting scenarios but do vary considerably when comparing strategies to exclusively protect tourists or residents. The proposed geospatial framework can serve as an analytical foundation for future TVE siting discussions. © 2014.


Schmidtlein M.C.,California State University, Sacramento | Wood N.J.,Western Geographic Science Center
Applied Geography | Year: 2015

Although anisotropic least-cost-distance (LCD) modeling is becoming a common tool for estimating pedestrian-evacuation travel times out of tsunami hazard zones, there has been insufficient attention paid to understanding model sensitivity behind the estimates. To support tsunami risk-reduction planning, we explore two aspects of LCD modeling as it applies to pedestrian evacuations and use the coastal community of Seward, Alaska, as our case study. First, we explore the sensitivity of modeling to the direction of movement by comparing standard safety-to-hazard evacuation times to hazard-to-safety evacuation times for a sample of 3985 points in Seward's tsunami-hazard zone. Safety-to-hazard evacuation times slightly overestimated hazard-to-safety evacuation times but the strong relationship to the hazard-to-safety evacuation times, slightly conservative bias, and shorter processing times of the safety-to-hazard approach make it the preferred approach. Second, we explore how variations in land cover speed conservation values (SCVs) influence model performance using a Monte Carlo approach with one thousand sets of land cover SCVs. The LCD model was relatively robust to changes in land cover SCVs with the magnitude of local model sensitivity greatest in areas with higher evacuation times or with wetland or shore land cover types, where model results may slightly underestimate travel times. This study demonstrates that emergency managers should be concerned not only with populations in locations with evacuation times greater than wave arrival times, but also with populations with evacuation times lower than but close to expected wave arrival times, particularly if they are required to cross wetlands or beaches. © 2014 The Authors.


Byrd K.B.,Western Geographic Science Center | O'Connell J.L.,University of California at Berkeley | Di Tommaso S.,University of California at Berkeley | Kelly M.,University of California at Berkeley
Remote Sensing of Environment | Year: 2014

There is a need to quantify large-scale plant productivity in coastal marshes to understand marsh resilience to sea level rise, to help define eligibility for carbon offset credits, and to monitor impacts from land use, eutrophication and contamination. Remote monitoring of aboveground biomass of emergent wetland vegetation will help address this need. Differences in sensor spatial resolution, bandwidth, temporal frequency and cost constrain the accuracy of biomass maps produced for management applications. In addition the use of vegetation indices to map biomass may not be effective in wetlands due to confounding effects of water inundation on spectral reflectance. To address these challenges, we used partial least squares regression to select optimal spectral features in situ and with satellite reflectance data to develop predictive models of aboveground biomass for common emergent freshwater marsh species, Typha spp. and Schoenoplectus acutus, at two restored marshes in the Sacramento-San Joaquin River Delta, California, USA. We used field spectrometer data to test model errors associated with hyperspectral narrowbands and multispectral broadbands, the influence of water inundation on prediction accuracy, and the ability to develop species specific models. We used Hyperion data, Digital Globe World View-2 (WV-2) data, and Landsat 7 data to scale up the best statistical models of biomass. Field spectrometer-based models of the full dataset showed that narrowband reflectance data predicted biomass somewhat, though not significantly better than broadband reflectance data [R2=0.46 and percent normalized RMSE (%RMSE)=16% for narrowband models]. However hyperspectral first derivative reflectance spectra best predicted biomass for plots where water levels were less than 15cm (R2=0.69, %RMSE=12.6%). In species-specific models, error rates differed by species (Typha spp.: %RMSE=18.5%; S. acutus: %RMSE=24.9%), likely due to the more vertical structure and deeper water habitat of S. acutus. The Landsat 7 dataset (7 images) predicted biomass slightly better than the WV-2 dataset (6 images) (R2=0.56, %RMSE=20.9%, compared to R2=0.45, RMSE=21.5%). The Hyperion dataset (one image) was least successful in predicting biomass (R2=0.27, %RMSE=33.5%). Shortwave infrared bands on 30m-resolution Hyperion and Landsat 7 sensors aided biomass estimation; however managers need to weigh tradeoffs between cost, additional spectral information, and high spatial resolution that will identify variability in small, fragmented marshes common to the Sacramento-San Joaquin River Delta and elsewhere in the Western U.S. © 2014 .

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