Inferring Controls on Dissolved Oxygen Criterion Attainment in the Chesapeake Bay

Environmental monitoring
programs generate multivariate time series
for the assessment of ecosystem health. Recent developments in causal
inference offer ways to translate these observational data into networks
able to explain gains and losses in the trajectories of indicator
variables. Here, we present a case study of this approach using surface
water dissolved oxygen (DO) criteria attainment across the Chesapeake
Bay. We sought to understand the long-term fluctuations of DO in response
to external watershed inputs (freshwater, nutrients, sediments) and
internal water properties (water temperature, chlorophyll-a, nutrient
concentrations). We found contrasting controls across different regions
of the Chesapeake Bay. Summer freshwater and sediment inputs reduced
surface water DO criteria attainment in landward regions but elevated
attainment in open, mainstem waters. Algal biomass was often positively
associated with AD in surface waters, in contrast to deep waters where
algae are well-understood to lower oxygen levels. Using estimates
of net effects, we also discovered that sediment flowing into many
of the mainstem segments during the winter-spring season has had a
net negative effect on oxygen levels. These segments have yet to deteriorate,
which has masked this risk. This work demonstrates the utility of
long-term monitoring programs to better understand and manage complex
ecosystems.