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.

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.

A random forest approach to improve estimates of tributary nutrient loading.

Estimating constituent loads from discrete water quality samples coupled with stream discharge measurements is critical for management of freshwater resources. Nutrient loads calculated based on discharge-concentration relationships form the basis of government nutrient load targets and scientific studies of the response of receiving waters to external loads. In this study, a new model is developed using random forests and applied to estimate concentrations and loads of total phosphorus, dissolved phosphorus, total nitrogen, and chloride, using data from 17 tributaries to Lake Champlain monitored from 1992 to 2021.

Disruption of ecological networks in lakes by climate change and nutrient fluctuations.

Climate change interacts with local processes to threaten biodiversity by disrupting the complex network of ecological interactions. While changes in network interactions drastically affect ecosystems, how ecological networks respond to climate change, in particular warming and nutrient supply fluctuations, is largely unknown. Here, using an equation-free modelling approach on monthly plankton community data in ten Swiss lakes, we show that the number and strength of plankton community interactions fluctuate and respond nonlinearly to water temperature and phosphorus.

Deep Learning Classification of Lake Zooplankton.

Plankton are effective indicators of environmental change and ecosystem health in freshwater habitats, but collection of plankton data using manual microscopic methods is extremely labor-intensive and expensive. Automated plankton imaging offers a promising way forward to monitor plankton communities with high frequency and accuracy in real-time. Yet, manual annotation of millions of images proposes a serious challenge to taxonomists.

Lowered nutritional quality of plankton caused by global environmental changes.

Global environmental changes are causing widespread nutrient depletion, declines in the ratio of dissolved inorganic nitrogen (N) to total phosphorus (DIN:TP), and increases in both water temperature and terrestrial colored dissolved organic carbon (DOC) concentration (browning) in high-latitude northern lakes. Declining lake DIN:TP, warming, and browning alter the nutrient limitation regime and biomass of phytoplankton, but how these stressors together affect the nutritional quality in terms of polyunsaturated fatty acid (PUFA) contents of the pelagic food web components remains unknown. We assessed the fatty acid compositions of seston and zooplankton in 33 lakes across south-to-north and boreal-to-subarctic gradients in Sweden.

Underwater dual-magnification imaging for automated lake plankton monitoring.

The Dual Scripps Plankton Camera (DSPC) is a new approach for automated in-situ monitoring of phyto- and zooplankton communities based on a dual magnification dark-field imaging microscope. Here, we present the DSPC and its associated image processing while evaluating its capabilities in i) detecting and characterizing plankton species of different size and taxonomic categories and ii) measuring their abundance in both laboratory and field applications. In the laboratory, body size and abundance estimates by the DSPC significantly and robustly scaled with measurements derived by microscopy.

Earlier winter/spring runoff and snowmelt during warmer winters lead to lower summer chlorophyll-a in north temperate lakes.

Winter conditions, such as ice cover and snow accumulation, are changing rapidly at northern latitudes and can have important implications for lake processes. For example, snowmelt in the watershed-a defining feature of lake hydrology because it delivers a large portion of annual nutrient inputs-is becoming earlier. Consequently, earlier and a shorter duration of snowmelt are expected to affect annual phytoplankton biomass.

The misuse of ratios in ecological stoichiometry.

Ecological stoichiometry is concerned with the ratios of different elements, particularly carbon, nitrogen, and phosphorus. Ratios by their nature do not respond symmetrically to changes in the numerator and denominator and do not follow normal distributions; however, researchers frequently fail to consider these properties in their analyses, which has biased reported results. Calculating means, variance, or linear slopes based on untransformed ratios results in biased results.

Dynamic Coupling of Iron, Manganese, and Phosphorus Behavior in Water and Sediment of Shallow Ice-Covered Eutrophic Lakes.

Decreasing duration and occurrence of northern hemisphere ice cover due to recent climate warming is well-documented; however, biogeochemical dynamics underneath the ice are poorly understood. We couple time-series analyses of water column and sediment water interface (SWI) geochemistry with hydrodynamic data to develop a holistic model of iron (Fe), manganese (Mn), and phosphorus (P) behavior underneath the ice of a shallow eutrophic freshwater bay. During periods of persistent subfreezing temperatures, a highly reactive pool of dissolved and colloidal Fe, Mn, and P develops over time in surface sediments and bottom waters due to reductive dissolution of Fe/Mn(oxy)hydroxides below the SWI.

Characterization of Organic Phosphorus Form and Bioavailability in Lake Sediments using P Nuclear Magnetic Resonance and Enzymatic Hydrolysis.

Lake sediments are known to be a significant source of phosphorus (P) to plankton populations under certain biogeochemical conditions; however, the contribution of sediment organic P (P) to internal P loads remains poorly understood. We investigated P speciation and bioavailability in sediments collected over multiple months from a shallow, eutrophic bay in Lake Champlain (Missisquoi Bay, VT) using solution P nuclear magnetic resonance (NMR) spectroscopy and enzymatic hydrolysis (EH) analysis of sediments collected during years with (2008) and without (2007) algal blooms. Sediments collected during bloom onset (July) and peak bloom (August) months contained the largest proportion of enzyme-labile P, whereas pre- and postbloom sediments were primarily composed of nonlabile P.