Using near-term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density.

Near-term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water quality. Importantly, ecological forecasts can identify where there is uncertainty in the forecasting system, which is necessary to improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance introduced by different sources, including specification of the model structure, errors in driver data, and estimation of current states (initial conditions). Uncertainty partitioning could be particularly useful in improving forecasts of highly variable cyanobacterial densities, which are difficult to predict and present a persistent challenge for lake managers. As cyanobacteria can produce toxic and unsightly surface scums, advance warning when cyanobacterial densities are increasing could help managers mitigate water quality issues. Here, we fit 13 Bayesian state-space models to evaluate different hypotheses about cyanobacterial densities in a low nutrient lake that experiences sporadic surface scums of the toxin-producing cyanobacterium, Gloeotrichia echinulata. We used data from several summers of weekly cyanobacteria samples to identify dominant sources of uncertainty for near-term (1- to 4-week) forecasts of G. echinulata densities. Water temperature was an important predictor of cyanobacterial densities during model fitting and at the 4-week forecast horizon. However, no physical covariates improved model performance over a simple model including the previous week's densities in 1-week-ahead forecasts. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and did not capture rare peak occurrences, indicating that significant explanatory variables when fitting models to historical data are not always effective for forecasting. Uncertainty partitioning revealed that model process specification and initial conditions dominated forecast uncertainty. These findings indicate that long-term studies of different cyanobacterial life stages and movement in the water column as well as measurements of drivers relevant to different life stages could improve model process representation of cyanobacteria abundance. In addition, improved observation protocols could better define initial conditions and reduce spatial misalignment of environmental data and cyanobacteria observations. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems.

Factors affecting MeHg bioaccumulation in stream biota: the role of dissolved organic carbon and diet.

The bioaccumulation of the neurotoxin methylmercury (MeHg) in freshwater ecosystems is thought to be mediated by both water chemistry (e.g., dissolved organic carbon [DOC] and dissolved mercury [Hg]) and diet (e.g., trophic position and diet composition). Hg in small streams is of particular interest given their role as a link between terrestrial and aquatic processes. Terrestrial processes determine the quantity and quality of streamwater DOC, which in turn influence the quantity and bioavailability of dissolved MeHg. To better understand the effects of water chemistry and diet on Hg bioaccumulation in stream biota, we measured DOC and dissolved Hg in stream water and mercury concentration in three benthic invertebrate taxa and three fish species across up to 12 tributary streams in a forested watershed in New Hampshire, USA. As expected, dissolved total mercury (THg) and MeHg concentrations increased linearly with DOC. However, mercury concentrations in fish and invertebrates varied non-linearly, with maximum bioaccumulation at intermediate DOC concentrations, which suggests that MeHg bioavailability may be reduced at high levels of DOC. Further, MeHg and THg concentrations in invertebrates and fish, respectively, increased with δ15N (suggesting trophic position) but were not associated with δ13C. These results show that even though MeHg in water is strongly determined by DOC concentrations, mercury bioaccumulation in stream food webs is the result of both MeHg availability in stream water and trophic position.

Dissolved organic carbon modulates mercury concentrations in insect subsidies from streams to terrestrial consumers.

Mercury (Hg) concentrations in aquatic environments have increased globally, exposing consumers of aquatic organisms to high Hg levels. For both aquatic and terrestrial consumers, exposure to Hg depends on their food sources as well as environmental factors influencing Hg bioavailability. The majority of the research on the transfer of methylmercury (MeHg), a toxic and bioaccumulating form of Hg, between aquatic and terrestrial food webs has focused on terrestrial piscivores. However, a gap exists in our understanding of the factors regulating MeHg bioaccumulation by non-piscivorous terrestrial predators, specifically consumers of adult aquatic insects. Because dissolved organic carbon (DOC) binds tightly to MeHg, affecting its transport and availability in aquatic food webs, we hypothesized that DOC affects MeHg transfer from stream food webs to terrestrial predators feeding on emerging adult insects. We tested this hypothesis by collecting data over 2 years from 10 low-order streams spanning a broad DOC gradient in the Lake Sunapee watershed in New Hampshire, USA. We found that streamwater MeHg concentration increased linearly with DOC concentration. However, streams with the highest DOC concentrations had emerging stream prey and spiders with lower MeHg concentrations than streams with intermediate DOC concentrations; a pattern that is similar to fish and larval aquatic insects. Furthermore, high MeHg concentrations found in spiders show that MeHg transfer in adult aquatic insects is an overlooked but potentially significant pathway of MeHg bioaccumulation in terrestrial food webs. Our results suggest that although MeHg in water increases with DOC, MeHg concentrations in stream and terrestrial consumers did not consistently increase with increases in streamwater MeHg concentrations. In fact, there was a change from a positive to a negative relationship between aqueous exposure and bioaccumulation at streamwater MeHg concentrations associated with DOC above ~5 mg/L. Thus, our study highlights the importance of stream DOC for MeHg dynamics beyond stream boundaries, and shows that factors modulating MeHg bioavailability in aquatic systems can affect the transfer of MeHg to terrestrial predators via aquatic subsidies.

Ecosystem effects of a tropical cyclone on a network of lakes in northeastern North America.

Here we document the regional effects of Tropical Cyclone Irene on thermal structure and ecosystem metabolism in nine lakes and reservoirs in northeastern North America using a network of high-frequency, in situ, automated sensors. Thermal stability declined within hours in all systems following passage of Irene, and the magnitude of change was related to the volume of water falling on the lake and catchment relative to lake volume. Across systems, temperature change predicted the change in primary production, but changes in mixed-layer thickness did not affect metabolism. Instead, respiration became a driver of ecosystem metabolism that was decoupled from in-lake primary production, likely due to addition of terrestrially derived carbon. Regionally, energetic disturbance of thermal structure was shorter-lived than disturbance from inflows of terrestrial materials. Given predicted regional increases in intense rain events with climate change, the magnitude and longevity of ecological impacts of these storms will be greater in systems with large catchments relative to lake volume, particularly when significant material is available for transport from the catchment. This case illustrates the power of automated sensor networks and associated human networks in assessing both system response and the characteristics that mediate physical and ecological responses to extreme events.