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.

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Satellite-derived sea surface temperature (SST) images have had limited applications in near-shore and coastal environments due to inadequate spatial resolution, incorrect geocorrection, or cloud contamination. We have developed a practical approach to remove these errors using Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS) 1-km resolution data. The objective was to improve the accuracy of SST anomaly estimates in the Florida Keys and to provide the best quality (in particular, high temporal and spatial resolutions) SST data products for this region. After manual navigation of over 47 000 AVHRR images (1993-2005), we implemented a cloud-filtering technique that differs from previously published image processing methods. The filter used a 12-year climatology and ±3-day running SST statistics to flag cloud-contaminated pixels. Comparison with concurrent (±0.5 h) data from the SEAKEYS in situ stations in the Florida Keys showed near-zero bias errors (< 0.05 • C) in the weekly anomaly for SST anomalies between −3 • C and 3 • C, with standard deviations < 0.5 • C. The cloud filter was implemented using Interactive Data Language for near-real-time processing of AVHRR and MODIS data. The improved SST products were used to detect SST anomalies and to estimate degree-heating weeks (DHWs) to assess the potential for coral reef stress. The mean and anomaly products are updated weekly, with periodic updates of the DHW products, on a Web site. The SST data at specific

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[1] Ocean circulation and global climate are strongly influenced by seawater density, which is itself controlled by salinity and temperature. Although adequate instrumental sea surface temperature (SST) records exist for most of the surface oceans over the past 100-150 years, records of salinity really only exist for the last 40-50 years. Here we show that longer proxy records from corals (Siderastrea radians) in the eastern tropical North Atlantic are dominated by multidecadal variations in salinity which are correlated with the relationship between SST and the North Atlantic Oscillation (NAO) over the course of the 20th century. The data reveal an increase in eastern tropical North Atlantic salinity of +0.5 practical salinity units (psu) between about 1950 and 1990. Rather than a monotonic secular increase, as indicated by some instrumental records, the preinstrumental coral proxy records presented here suggest that salinity in the tropical North Atlantic is periodic on a decadal to multidecadal scale.