Water budget parameters are estimated for Shark River Slough (SRS), the main drainage within Everglades National Park (ENP) from 2002 to 2008. Inputs to the water budget include surface water inflows and precipitation while outputs consist of evapotranspiration, discharge to the Gulf of Mexico and seepage losses due to municipal wellfield extraction. The daily change in volume of SRS is equated to the difference between input and outputs yielding a residual term consisting of component errors and net groundwater exchange. Results predict significant net groundwater discharge to the SRS peaking in June and positively correlated with surface water salinity at the mangrove ecotone, lagging by 1 month. Precipitation, the largest input to the SRS, is offset by ET (the largest output); thereby highlighting the importance of increasing fresh water inflows into ENP for maintaining conditions in terrestrial, estuarine, and marine ecosystems of South Florida.

Clinicians face difficult treatment decisions in contexts that are not well addressed by available evidence as formulated based on research. The digitization of medicine provides an opportunity for clinicians to collaborate with researchers and data scientists on solutions to previously ambiguous and seemingly insolvable questions. But these groups tend to work in isolated environments, and do not communicate or interact effectively. Clinicians are typically buried in the weeds and exigencies of daily practice such that they do not recognize or act on ways to improve knowledge discovery. Researchers may not be able to identify the gaps in clinical knowledge. For data scientists, the main challenge is discerning what is relevant in a domain that is both unfamiliar and complex. Each type of domain expert can contribute skills unavailable to the other groups. “Health hackathons” and “data marathons”, in which diverse participants work together, can leverage the current ready availability of digital data to discover new knowledge. Utilizing the complementary skills and expertise of these talented, but functionally divided groups, innovations are formulated at the systems level. As a result, the knowledge discovery process is simultaneously democratized and improved, real problems are solved, cross-disciplinary collaboration is supported, and innovations are enabled.

Using imagery at 30 m spatial resolution from the most recent Landsat satellite, the Landsat 7 Enhanced Thematic Mapper Plus (ETM+), we scale up reef metabolic productivity and calcification from local habitat-scale (10 -1 to 10 0 km 2 ) measurements to regional scales (10 3 to 10 4 km 2 ). Distribution and spatial extent of the North Florida Reef Tract (NFRT) habitats come from supervised classification of the Landsat imagery within independent Landsat-derived Millennium Coral Reef Map geomorphologic classes. This system minimizes the depth range and variability of benthic habitat characteristics found in the area of supervised classification and limits misclassification. Classification of Landsat imagery into 5 biotopes (sand, dense live cover, sparse live cover, seagrass, and sparse seagrass) by geomorphologic class is > 73% accurate at regional scales. Based on recently published habitat-scale in situ metabolic measurements, gross production (P = 3.01 × 10 9 kg C yr -1 ), excess production (E = -5.70 × 10 8 kg C yr -1 ), and calcification (G = -1.68 × 10 6 kg CaCO 3 yr -1 ) are estimated over 2711 km 2 of the NFRT. Simple models suggest sensitivity of these values to ocean acidification, which will increase local dissolution of carbonate sediments. Similar approaches could be applied over large areas with poorly constrained bathymetry or water column properties and minimal metabolic sampling. This tool has potential applications for modeling and monitoring large-scale environmental impacts on reef productivity, such as the influence of ocean acidification on coral reef environments. KEY WORDS: Remote sensing · Corals · Carbon cycle · Millennium Coral Reef MapResale or republication not permitted without written consent of the publisher Editorial responsibility: Alain Vézina,

[1] Geochemical proxies in the skeletons of corals used for the purpose of reconstructing environmental records have typically been obtained from relatively fast-growing corals (usually >8 mm yr À1) and from only a few key genera (most commonly Porites and Montastraea). In many areas, however, there are no suitable fast-growing corals available for such reconstructions. Here, we investigate the potential of Siderastrea radians, a slow-growing Atlantic and Caribbean zooxanthellate coral, as an archive of sea surface temperature (SST) and salinity over the period from 1891 to 2002. Sampling the skeleton of three corals from the Cape Verde Islands, we were able to reproduce a clear seasonal signal, but with limited correlation to monthly SST, arising from inadequate chronologic constraint of the individual samples. The O calibration slopes for different sampling scales on several cores can range from about À9°C % À1 to +2°C % À1 (compared to other published values of around À5 to À4°C % À1 ). Careful treatment produced a 18 O-SST calibration equation where SST(°C) = 12.56(±1.20) À 3.86(±0.39)*( c -w ). The recognition of the limitations of calibration at such small growth rates due to skeletal complexity and suspicion of environmental interferences suggests the need for careful consideration in the interpretation of climate proxy results from S. radians and other slow-growing corals.

No abstract