Hales Burke

No Thumbnail Available
Last Name
Hales
First Name
Burke
ORCID

Filters

2013 - 2019 2
1 1
2
Reset filters

Settings

Search Results

Now showing 1 - 2 of 2
  • Preprint
    Hierarchical and dynamic seascapes : a quantitative framework for scaling pelagic biogeochemistry and ecology
    ( 2013-10-07) Kavanaugh, Maria T. ; Hales, Burke ; Saraceno, Martin ; Spitz, Yvette H. ; White, Angelicque E. ; Letelier, Ricardo M.
    Comparative analyses of oceanic ecosystems require an objective framework to define coherent study regions and scale the patterns and processes observed within them. We applied the hierarchical patch mosaic paradigm of landscape ecology to the study of the seasonal variability of the North Pacific to facilitate comparative analysis between pelagic ecosystems and provide spatiotemporal context for Eulerian time-series studies. Using 13-year climatologies of sea surface temperature (SST), photosynthetically active radiation (PAR), and chlorophyll a (chl-a), we classified seascapes in environmental space that were monthly-resolved, dynamic and nested in space and time. To test the assumption that seascapes represent coherent regions with unique biogeochemical function and to determine the hierarchical scale that best characterized variance in biogeochemical parameters, independent data sets were analyzed across seascapes using analysis of variance (ANOVA), nested-ANOVA and multiple linear regression (MLR) analyses. We also compared the classification efficiency (as defined by the ANOVA F-statistic) of resultant dynamic seascapes to a commonly-used static classification system. Variance of nutrients and net primary productivity (NPP) were well characterized in the first two levels of hierarchy of eight seascapes nested within three superseascapes (R2 = 0.5-0.7). Dynamic boundaries at this level resulted in a nearly 2-fold increase in classification efficiency over static boundaries. MLR analyses revealed differential forcing on pCO2 across seascapes and hierarchical levels and a 33 % reduction in mean model error with increased partitioning (from 18.5 μatm to 12.0 μatm pCO2). Importantly, the empirical influence of seasonality was minor across seascapes at all hierarchical levels, suggesting that seascape partitioning minimizes the effect of non-hydrographic variables. As part of the emerging field of pelagic seascape ecology, this effort provides an improved means of monitoring and comparing oceanographic biophysical dynamics and an objective, quantitative basis by which to scale data from local experiments and observations to regional and global biogeochemical cycles.
  • Article
    Autonomous seawater pCO2 and pH time series from 40 surface buoys and the emergence of anthropogenic trends
    (Copernicus Publications, 2019-03-26) Sutton, Adrienne J. ; Feely, Richard A. ; Maenner-Jones, Stacy ; Musielwicz, Sylvia ; Osborne, John ; Dietrich, Colin ; Monacci, Natalie ; Cross, Jessica N. ; Bott, Randy ; Kozyr, Alex ; Andersson, Andreas J. ; Bates, Nicholas R. ; Cai, Wei-Jun ; Cronin, Meghan F. ; De Carlo, Eric H. ; Hales, Burke ; Howden, Stephan D. ; Lee, Charity M. ; Manzello, Derek P. ; McPhaden, Michael J. ; Meléndez, Melissa ; Mickett, John B. ; Newton, Jan A. ; Noakes, Scott ; Noh, Jae Hoon ; Olafsdottir, Solveig R. ; Salisbury, Joseph E. ; Send, Uwe ; Trull, Thomas W. ; Vandemark, Douglas ; Weller, Robert A.
    Ship-based time series, some now approaching over 3 decades long, are critical climate records that have dramatically improved our ability to characterize natural and anthropogenic drivers of ocean carbon dioxide (CO2) uptake and biogeochemical processes. Advancements in autonomous marine carbon sensors and technologies over the last 2 decades have led to the expansion of observations at fixed time series sites, thereby improving the capability of characterizing sub-seasonal variability in the ocean. Here, we present a data product of 40 individual autonomous moored surface ocean pCO2 (partial pressure of CO2) time series established between 2004 and 2013, 17 also include autonomous pH measurements. These time series characterize a wide range of surface ocean carbonate conditions in different oceanic (17 sites), coastal (13 sites), and coral reef (10 sites) regimes. A time of trend emergence (ToE) methodology applied to the time series that exhibit well-constrained daily to interannual variability and an estimate of decadal variability indicates that the length of sustained observations necessary to detect statistically significant anthropogenic trends varies by marine environment. The ToE estimates for seawater pCO2 and pH range from 8 to 15 years at the open ocean sites, 16 to 41 years at the coastal sites, and 9 to 22 years at the coral reef sites. Only two open ocean pCO2 time series, Woods Hole Oceanographic Institution Hawaii Ocean Time-series Station (WHOTS) in the subtropical North Pacific and Stratus in the South Pacific gyre, have been deployed longer than the estimated trend detection time and, for these, deseasoned monthly means show estimated anthropogenic trends of 1.9±0.3 and 1.6±0.3 µatm yr−1, respectively. In the future, it is possible that updates to this product will allow for the estimation of anthropogenic trends at more sites; however, the product currently provides a valuable tool in an accessible format for evaluating climatology and natural variability of surface ocean carbonate chemistry in a variety of regions. Data are available at https://doi.org/10.7289/V5DB8043 and https://www.nodc.noaa.gov/ocads/oceans/Moorings/ndp097.html (Sutton et al., 2018).