Uncertainty in model predictions of Vibrio vulnificus response to climate variability and change: a Chesapeake Bay case study

Abstract

The effect that climate change and variability will have on waterborne bacteria is a topic of increasing concern for coastal ecosystems, including the Chesapeake Bay. Surface water temperature trends in the Bay indicate a warming pattern of roughly 0.3-0.4°C per decade over the past 30 years. It is unclear what impact future warming will have on pathogens currently found in the Bay, including Vibrio spp. Using historical environmental data, combined with three different statistical models of Vibrio vulnificus probability, we explore the relationship between environmental change and predicted Vibrio vulnificus presence in the upper Chesapeake Bay. We find that the predicted response of V. vulnificus probability to high temperatures in the Bay differs systematically between models of differing structure. As existing publicly available datasets are inadequate to determine which model structure is most appropriate, the impact of climatic change on the probability of V. vulnificus presence in the Chesapeake Bay remains uncertain. This result points to the challenge of characterizing climate sensitivity of ecological systems in which data are sparse and only statistical models of ecological sensitivity exist.

Figure 1. Map of the study area, showing contours of average surface water salinity.

Dark markers represent in situ monitoring stations used for each of the subregions in this study: upper (star), mid (circle), and lower (square).

Figure 2. Contour plots of V. vulnificus probability with temperature and salinity for (a) NOAA GLM, (b) JHU GLM, and (c) JHU GAM.

Black dots represent monthly average (April-July) of in situ conditions; black lines represents in situ trend line, and dashed line represents shift in present day temperature and salinity, (d) Plot of temperature regressed against V.vulnificus probability at 11.5 salinity for each empirical method. Green circles represent the range of temperature observations during bacterium sampling.

Figure 3. Monthly climatology of temperature and V. vulnificus probability for each method in the upper (a), mid (b), and lower (c) regions of the Chesapeake Bay.

Peak temperature observations by year versus V. vulnificus probability for each method in the upper (d), mid (e), and lower (f) regions of the Chesapeake Bay. Trend lines are included for each method's observations.

Figure 4. Monthly climatology of Chlorophyll a and V. vulnificus probability for each method averaged over the entire upper Chesapeake Bay.

Figure 5. Upper Chesapeake Bay monthly V. vulnificus probability hind-casts for April through October 2012, for NOAA GLM, JHU GLM, and JHU GAM methods.