Alexander W. Karlsen

Climatic variability in the eastern United States over the past millennium from Chesapeake Bay sediments

Salinity oscillations caused by multidecadal climatic variability had major impacts on the Chesapeake Bay estuarine ecosystem during the past 1000 yr. Microfossils from sediments dated by radiometry ( 14 C, 137 Cs, 210 Pb) and pollen stratigraphy indicate that salinity in mesohaline regions oscillated 10‐15 ppt during periods of extreme drought (low fresh-water discharge) and wet climate (high discharge). During the past 500 yr, 14 wet-dry cycles occurred, including sixteenth and early seventeenth century megadroughts that exceeded twentieth century droughts in their severity. These droughts correspond to extremely dry climate also recorded in North American tree-ring records and by early colonists. Wet periods occurred every ~60‐70 yr, began abruptly, lasted <20 yr, and had mean annual rainfall ~25%‐30% and fresh-water discharge ~40%‐50% greater than during droughts. A shift toward wetter regional climate occurred in the early nineteenth century, lowering salinity and compounding the effects of agricultural land clearance on bay ecosystems.

Historical trends in Chesapeake Bay dissolved oxygen based on benthic foraminifera from sediment cores

Environmentally sensitive benthic foraminifera (protists) from Chesapeake Bay were used as bioindicators to estimate the timing and degree of changes in dissolved oxygen (DO) over the past five centuries. Living foraminifers from 19 surface samples and fossil assemblages from 11 sediment cores dated by210Pb,137Cs,14C, and pollen stratigraphy were analyzed from the tidal portions of the Patuxent, Potomac, and Choptank Rivers and the main channel of the Chesapeake Bay.Ammonia parkinsoniana, a facultative anaerobe tolerant of periodic anoxic conditions, comprises an average of 74% of modern Chesapeake foraminiferal assemblages (DO-0.47 and 1.72 ml l−1) compared to 0% to 15% of assemblages collected in the 1960s. Paleoecological analyses show thatA. parkinsoniana was absent prior to the late 17th century, increased to 10–25% relative frequency between approximately 1670–1720 and 1810–1900, and became the dominant (60–90%) benthic formaniferal species in channel environments beginning in the early 1970s. Since the 1970s, deformed tests ofA. parkinsoniana occur in all cores (10–20% ofAmmonia), suggesting unprecedented stressful benthic conditions. These cores indicate that prior to the late 17th century, there was limited oxygen depletion. During the past 200 years, decadal scale variability in oxygen depletion has occurred, as dysoxic (DO=0.1–1.0 ml l−1), perhaps short-term anoxic (DO<0.1 ml l−1) conditions developed. The most extensive (spatially and temporally) anoxic conditions were reached during the 1970s. Over decadal timescales, DO variability seems to be linked closely to climatological factors influencing river discharge; the unprecedented anoxia since the early 1970s is attributed mainly to high freshwater flow and to an increase in nutrient concentrations from the watershed.

GIS in Human Health Studies

Databases used in the field of medical geology are generally comprised of geospatial and/or temporal elements. Although these are not requirements for all medical geology research projects, much of the discussion in this chapter will be focused on databases incorporated into geographic information systems (GIS). GIS are computer-based (or manual) methods that allow a user to input, store, retrieve, manipulate, analyze, and output spatial data (Aronoff 1989). There are four major systems of GIS: engineering mapping systems (computer-aided design/computer-assisted mapping; CAD/CAM), geographic base file systems, image processing systems, and generalized thematic mapping systems. Various software packages are available that perform one or more of these systems, and the relative ability to move data back and forth between them can be critical to the needs and success of a particular GIS. Relational databases are the most commonly used types of databases in GIS (Cromley and McLafferty 2002). Relational database management models are convenient for linking formerly disparate databases together in a GIS. The databases to be joined must share one common attribute, usually an identifier such as coded patient number, sample site, or latitude/longitude. Other database management structures, such as hierarchical and network systems, are not as well suited to health GIS applications, although they may be useful for extremely large databases.