Floating solar panels on reservoirs impact phytoplankton populations:A modelling experiment

Floating solar photovoltaic (FPV) deployments are increasing globally as the switch to renewable energy intensifies, representing a considerable water surface transformation. FPV installations can potentially impact aquatic ecosystem function, either positively or negatively. However, these impacts are poorly resolved given the challenges of collecting empirical data for field or modelling experiments. In particular, there is limited evidence on the response of phytoplankton to changes in water body thermal dynamics and light climate with FPV. Given the importance of understanding phytoplankton biomass and species composition for managing ecosystem services, we use an uncertainty estimation approach to simulate the effect of FPV coverage and array siting location on a UK reservoir. FPV coverage was modified in 10 % increments from a baseline with 0 % coverage to 100 % coverage for three different FPV array siting locations based on reservoir circulation patterns. Results showed that FPV coverage significantly impacted thermal properties, resulting in highly variable impacts on phytoplankton biomass and species composition. The impacts on phytoplankton were often dependent on array siting location as well as surface coverage. Changes to phytoplankton species composition were offset by the decrease in phytoplankton biomass associated with increasing FPV coverage. We identified that similar phytoplankton biomass reductions could be achieved with less FPV coverage by deploying the FPV array on the water body's faster-flowing area than the central or slower flowing areas. The difference in response dependent on siting location could be used to tailor phytoplankton management in water bodies. Simulation of water body-FPV interactions efficiently using an uncertainty approach is an essential tool to rapidly develop understanding and ultimately inform FPV developers and water body managers looking to minimise negative impacts and maximise co-benefits

Floating solar panels on reservoirs impact phytoplankton populations: a modelling experiment

Floating solar photovoltaic (FPV) deployments are increasing globally as the switch to renewable energy intensifies, representing a considerable water surface transformation. FPV installations can potentially impact aquatic ecosystem function, either positively or negatively. However, these impacts are poorly resolved given the challenges of collecting empirical data for field or modelling experiments. In particular, there is limited evidence on the response of phytoplankton to changes in water body thermal dynamics and light climate with FPV. Given the importance of understanding phytoplankton biomass and species composition for managing ecosystem services, we use an uncertainty estimation approach to simulate the effect of FPV coverage and array siting location on a UK reservoir. FPV coverage was modified in 10% increments from a baseline with 0% coverage to 100% coverage for three different FPV array siting locations based on reservoir circulation patterns. Results showed that FPV coverage significantly impacted thermal properties, resulting in highly variable impacts on phytoplankton biomass and species composition. The impacts on phytoplankton were often dependent on array siting location as well as surface coverage. Changes to phytoplankton species composition were offset by the decrease in phytoplankton biomass associated with increasing FPV coverage. We identified that similar phytoplankton biomass reductions could be achieved with less FPV coverage by deploying the FPV array on the water body's faster-flowing area than the central or slower flowing areas. The difference in response dependent on siting location could be used to tailor phytoplankton management in water bodies. Simulation of water body-FPV interactions efficiently using an uncertainty approach is an essential tool to rapidly develop understanding and ultimately inform FPV developers and water body managers looking to minimise negative impacts and maximise co-benefits

Unexpectedly high degree of anammox and DNRA in seagrass sediments: description and application of a revised isotope pairing technique

Understanding the magnitude of nitrogen (N) loss and recycling pathways is crucial for coastal N management efforts. However, quantification of denitrification and anammox by a widely-used method, the isotope pairing technique, is challenged when dissimilatory NO3−reduction to NH4+ (DNRA) occurs. In this study, we describe a revised isotope pairing technique that accounts for the influence of DNRA on NO3− reduction (R-IPT-DNRA). The new calculation procedure improves on previous techniques by (1) accounting for N2O production, (2) distinguishing canonical anammox from coupled DNRA-anammox, and (3) including the production of 30N2 by anammox in the quantification of DNRA. This approach avoids the potential for substantial underestimates of anammox rates and overestimates of denitrification rates in systems where DNRA is a significant NO3− reduction pathway. We apply this technique to simultaneously quantify rates of anammox, denitrification, and DNRA in intact sediments adjacent to a seagrass bed in subtropical Australia. The effect of organic carbon lability on NO3− reduction was also addressed by adding detrital sources with differing C:N (phytoplankton- or seagrass-derived). DNRA was the predominant pathway, contributing 49–74% of total NO3− reduction (mean 0.42 µmol N m−2 h−1). In this high C:N system, DNRA outcompetes denitrification for NO3−, functioning to recycle rather than remove N. Anammox exceeded denitrification (mean 0.18 and 0.04 µmol N m−2 h−1, respectively) and accounted for 64–86% of N loss, a rare high percentage in shallow coastal environments. Owing to low denitrification activity, N2O production was ∼100-fold lower than in other coastal sediments (mean 7.7 nmol N m−2 h−1). All NO3− reduction pathways were stimulated by seagrass detritus but not by phytoplankton detritus, suggesting this microbial community is adapted to process organic matter that is typically encountered. The R-IPT-DNRA is widely applicable in other environments where the characterization of co-existing NO3− reduction pathways is desirable