Mind the Data Gap: Identifying and Assessing Drivers of Changing Eutrophication Condition

Abstract This study identified drivers of change in Barnegat Bay–Little Egg Harbor Estuary, NJ, USA over multiple long-term time periods by developing an assessment tool (an “Eutrophication Index”) capable of handling data gaps and identifying the condition of and relationships between ecosystem pressures, ecosystem state, and biotic responses. The Eutrophication Index integrates 15 indicators in 3 components: (1) water quality, (2) light availability, and (3) seagrass response. Annual quantitative assessments of condition and its consistency for three geographic segments range from 0 (highly degraded) to 100 (excellent condition). Eutrophication Index values significantly declined (p <0.05) by 34 and 36 % in central and south segments from 73 and 71 in the early 1990s to 48 and 45 in 2010, respectively. Ongoing declines despite periods of improvement (e.g., 1989–1992, 1996–2002, and 2006–2008) suggest these estuarine segments are currently undergoing eutrophication. The north segment had highest nutrient loading and lowest Eutrophication Index values (2010 Eutrophication Index value=37) but increased over time (from 14 in 1991 to 50 in 2009) in contrast to trends in central and south segments. Rapid initial declines of Eutrophication Index values with increasing loading highlight that the estuary is sensitive to loading. Ecosystem response to total nutrient loading, as described by the Index of Eutrophication, exhibited nonlinearity at loading rates of >1,200 and <5,000 kg TN km year and >100 and <250 kg TP km year, values similar to responses of seagrass to nutrient loading in many ecosystems. While nutrient loading is initially a critical driver of ecosystem change, other factors, e.g., light availability and drive ecosystem condition, yield nonlinearity. Empirical evidence for switches in the driving factors of ecosystem stress adds complexity to the conceptualization of ecosystem resiliency due to feedback from multiple dynamic, nonlinear stressors.