Phytoplankton biomass in northern lakes reveals a complex response to global change.

Global change may introduce fundamental alterations in phytoplankton biomass and community structure that can alter the productivity of northern lakes. In this study, we utilized Swedish and Finnish monitoring data from lakes that are spatially (135 lakes) and temporally (1995-2019, 110 lakes) extensive to assess how phytoplankton biomass (PB) of dominant phytoplankton groups related to changes in water temperature, pH and key nutrients [total phosphorus (TP), total nitrogen (TN), total organic carbon (TOC), iron (Fe)] along spatial (Fennoscandia) and temporal (25 years) gradients. Using a machine learning approach, we found that TP was the most important determinant of total PB and biomass of a specific species of Raphidophyceae - Gonyostomum semen - and Cyanobacteria (both typically with adverse impacts on food-webs and water quality) in spatial analyses, while Fe and pH were second in importance for G. semen and TN and pH were second and third in importance for Cyanobacteria. However, in temporal analyses, decreasing Fe and increasing pH and TOC were associated with a decrease in G. semen and an increase in Cyanobacteria. In addition, in many lakes increasing TOC seemed to have generated browning to an extent that significantly reduced PB. The identified discrepancy between the spatial and temporal results suggests that substitutions of data for space-for-time may not be adequate to characterize long-term effects of global change on phytoplankton. Further, we found that total PB exhibited contrasting temporal trends (increasing in northern- and decreasing in southern Fennoscandia), with the decline in total PB being more pronounced than the increase. Among phytoplankton, G. semen biomass showed the strongest decline, while cyanobacterial biomass showed the strongest increase over 25 years. Our findings suggest that progressing browning and changes in Fe and pH promote significant temporal changes in PB and shifts in phytoplankton community structures in northern lakes.

Declining calcium concentration drives shifts toward smaller and less nutritious zooplankton in northern lakes.

Zooplankton community composition of northern lakes is changing due to the interactive effects of climate change and recovery from acidification, yet limited data are available to assess these changes combined. Here, we built a database using archives of temperature, water chemistry and zooplankton data from 60 Scandinavian lakes that represent broad spatial and temporal gradients in key parameters: temperature, calcium (Ca), total phosphorus (TP), total organic carbon (TOC), and pH. Using machine learning techniques, we found that Ca was the most important determinant of the relative abundance of all zooplankton groups studied, while pH was second, and TOC third in importance. Further, we found that Ca is declining in almost all lakes, and we detected a critical Ca threshold in lake water of 1.3 mg L-1 , below which the relative abundance of zooplankton shifts toward dominance of Holopedium gibberum and small cladocerans at the expense of Daphnia and copepods. Our findings suggest that low Ca concentrations may shape zooplankton communities, and that current trajectories of Ca decline could promote widespread changes in pelagic food webs as zooplankton are important trophic links from phytoplankton to fish and different zooplankton species play different roles in this context.

Multi-decadal changes in phytoplankton biomass in northern temperate lakes as seen through the prism of landscape properties.

Ecologists collectively predict that climate change will enhance phytoplankton biomass in northern lakes. Yet there are unique variations in the structures and regulating functions of lakes to make this prediction challengeable and, perhaps, inaccurate. We used archived Landsat TM/ETM+ satellite products to estimate epilimnetic chlorophyll-a (Chl-a) concentration as a proxy for phytoplankton biomass in 281 northern temperate lakes over 28 years. We explored the influence of climate (air temperature, precipitation) and landscape proxies for nutrient sources (proportion of wetlands in a contributing catchment, size of the littoral zone, potential for wind-driven sediment resuspension as estimated by the dynamic ratio) or nutrient sinks (lake volume) in a random forest model to explain heterogeneity in peak Chl-a. Lakes with higher Chl-a (median Chl-a = 2.4 µg L-1 , n = 40) had smaller volumes (<44 × 104  m3 ) and were more sensitive to increases in temperature. In contrast, lakes with lower Chl-a (median Chl-a = 0.6 µg L-1 , n = 241) had larger volumes (≥44 × 104  m3 ), contributing catchments with smaller proportions of wetlands (<4.5% of catchment area, n = 70), smaller littoral zones (<16.4 ha, n = 137), minimal wind-driven sediment resuspension (as defined by the dynamic ratio; <0.45, n = 232), and were more sensitive to increases in precipitation. Lakes with larger volumes were generally less responsive to climate factors; however, larger volume lakes with a significant proportion of wetlands and larger littoral zones behaved similarly to lakes with smaller volumes. Our finding that lakes with different landscape properties respond differently to climate factors may help predict the susceptibility of lakes to eutrophication under changing climatic conditions.