Description:    This study aims to examine how future climate, temperature and precipitation specifically, are expected to change under the A2, A1B, and B1 emission scenarios over the six states that make up the Southern Climate Impacts Planning Program (SCIPP): Oklahoma, Texas, Arkansas, Louisiana, Tennessee, and Mississippi. SCIPP is a member of the National Oceanic and Atmospheric Administration-funded Regional Integrated Sciences and Assessments network, a program which aims to better connect climate-related scientific research with in-the-field decision-making processes. The results of the study found that the average temperature over the study area is anticipated to increase by 1.7°C to 2.4°C in the twenty-first century based on the different emission scenarios with a rate of change that is more pronounced during the second half of the century. Summer and fall seasons are projected to have more significant temperature increases, while the northwestern portions of the region are projected to experience more significant increases than the Gulf coast region. Precipitation projections, conversely, do not exhibit a discernible upward or downward trend. Late twenty-first century exhibits slightly more precipitation than the early century, based on the A1B and B1 scenario, and fall and winter are projected to become wetter than the late twentieth century as a whole. Climate changes on the city level show that greater warming will happened in inland cities such as Oklahoma City and El Paso, and heavier precipitation in Nashville. These changes have profound implications for local water resources management as well as broader regional decision making. These results represent an initial phase of a broader study that is being undertaken to assist SCIPP regional and local water planning efforts in an effort to more closely link climate modeling to longer-term water resources management and to continue assessing climate change impacts on regional hazards management in the South. Content Type Journal Article Category Original Paper Pages 1-16 DOI 10.1007/s00704-011-0567-9 Authors Lu Liu, School of Civil Engineering and Environmental Science, University of Oklahoma, 120 David L. Boren Blvd., National Weather Center ARRC 4610 Suite, Norman, OK 73072, USA Yang Hong, School of Civil Engineering and Environmental Science, University of Oklahoma, 120 David L. Boren Blvd., National Weather Center ARRC 4610 Suite, Norman, OK 73072, USA James E. Hocker, Southern Climate Impacts Planning Program, Oklahoma Climate Survey, University of Oklahoma, Norman, OK, USA Mark A. Shafer, Southern Climate Impacts Planning Program, Oklahoma Climate Survey, University of Oklahoma, Norman, OK, USA Lynne M. Carter, Southern Climate Impacts Planning Program, Louisiana State University, Baton Rouge, LA, USA Jonathan J. Gourley, NOAA/National Severe Storms Laboratory, Norman, OK 73072, USA Christopher N. Bednarczyk, School of Civil Engineering and Environmental Science, University of Oklahoma, 120 David L. Boren Blvd., National Weather Center ARRC 4610 Suite, Norman, OK 73072, USA Bin Yong, State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098 China Pradeep Adhikari, School of Civil Engineering and Environmental Science, University of Oklahoma, 120 David L. Boren Blvd., National Weather Center ARRC 4610 Suite, Norman, OK 73072, USA Journal Theoretical and Applied Climatology Online ISSN 1434-4483 Print ISSN 0177-798X

Description: Wigand, L. A., Klinger, T., and Logsdon, M. G. 2013. Patterns in groundfish abundance along the Eastern Bering Sea outer continental margin. – ICES Journal of Marine Science, 70: 1181–1197. Place-based management approaches require understanding the spatial arrangement and interaction of elements. To address this need, we explored the utility of spatial-pattern analysis to understand the distribution of groundfish in the Eastern Bering Sea outer continental margin. We divided this region into discrete geomorphological units to explore spatial pattern on a range of scales. We used groundfish catch per unit effort (cpue) trawl survey data collected in four years to quantify spatial autocorrelation. Global statistics indicated that groundfish cpue was dominated by clusters of low values in all years. Local statistics showed that clusters of low values in groundfish cpue were confined to the southern portion of the study area, while clusters of high values varied across the study area. Outliers were most commonly found in close proximity to the shelf–slope break. Our results reveal the existence of spatial dependency in groundfish abundance and demonstrate that spatial analysis can be used to better understand spatial arrangements of these and other living marine resources, and to quantify and validate the local ecological knowledge of resource users. Our results indicate the feasibility of using spatially explicit tools to improve integration and visualization of marine environmental data for purposes of management and conservation.