Quantifying pelagic phosphorus regeneration using three methods in lakes of varying productivity

Phosphorus (P) is often a limiting nutrient in freshwater ecosystems, and understanding P dynamics in lakes is critical for eutrophication management. Pelagic P regeneration can support a large fraction of primary production in stratified freshwaters. Various techniques have been used to quantify pelagic P regeneration including (1) P mass balance supply–demand, (2) regression using total P as a predictor, and, more recently, (3) whole-lake metabolism calculated from high-frequency dissolved oxygen (DO) data. To our knowledge no study comparing these methods in multiple lakes has been performed. To compare these 3 approaches, we investigated 3 Global Lake Ecological Observatory Network (GLEON) lakes that differ in productivity: Acton, a Midwestern USA hypereutrophic reservoir; and 2 Northeastern USA glacial lakes, oligotrophic Giles and mesotrophic/dystrophic Lacawac. In Acton, we used all 3 methods, but for Giles and Lacawac we used only the total P regression and metabolism techniques. Our results show the best agreement among methods in the mesotrophic lake, whereas the metabolism approach underestimated regeneration in the oligotrophic lake and overestimated regeneration in the hypereutrophic reservoir compared with other methods. P regeneration rates for the hypereutrophic reservoir were the most sensitive to the metabolism-based input parameters. Our study illustrates a novel use of high-frequency DO data, which are commonly collected on many GLEON buoys, to understand lake nutrient dynamics

Training macrosystems scientists requires both interpersonal and technical skills

Macrosystems science strives to integrate patterns and processes that span regional to continental scales. The scope of such research often necessitates the involvement of large interdisciplinary and/or multi-institutional teams composed of scientists across a range of career stages, a diversity that requires researchers to hone both technical and interpersonal skills. We surveyed participants in macrosystems projects funded by the US National Science Foundation to assess the perceived importance of different skills needed in their research, as well as the types of training they received. Survey results revealed a mismatch between the skills participants perceive as important and the training they received, particularly for interpersonal and management skills. We highlight lessons learned from macrosystems training case studies, explore avenues for further improvement of undergraduate and graduate education, and discuss other training opportunities for macrosystems scientists. Given the trend toward interdisciplinary research beyond the macrosystems community, these insights are broadly applicable for scientists involved in diverse, collaborative projects.https://esajournals.onlinelibrary.wiley.com/doi/full/10.1002/fee.228

Using near-term forecasts and uncertainty partitioning to improve predictions of low-frequency cyanobacterial events

Near-term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water and air quality. Importantly, ecological forecasts can identify where uncertainty enters the forecasting system, which is necessary to refine and improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance (uncertainty) introduced by different sources, including specification of the model structure, errors in driver data, and estimation of initial state conditions. Uncertainty partitioning could be particularly useful in improving forecasts of high-density cyanobacterial events, which are difficult to predict and present a persistent challenge for lake managers. Cyanobacteria can produce toxic or unsightly surface scums and advance warning of these events could help managers mitigate water quality issues. Here, we calibrate fourteen Bayesian state-space models to evaluate different hypotheses about cyanobacterial growth using data from eight summers of weekly cyanobacteria density samples in an oligotrophic (low nutrient) lake that experiences sporadic surface scums of the toxin-producing cyanobacterium, Gloeotrichia echinulata. We identify dominant sources of uncertainty for near-term (one-week to four-week) forecasts of G. echinulata densities over two years. Water temperature was an important predictor in calibration and at the four-week forecast horizon. However, no environmental covariates improved over a simple autoregressive (AR) model at the one-week horizon. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and often did not capture rare peak density occurrences, indicating that significant explanatory variables in calibration are not always effective for near-term forecasting of low-frequency events. Uncertainty partitioning revealed that model process specification and initial conditions uncertainty dominated forecasts at both time horizons. These findings suggest that observed densities result from both growth and movement of G. echinulata, and that imperfect observations as well as spatial misalignment of environmental data and cyanobacteria observations affect forecast skill. Future research efforts should prioritize long-term studies to refine process understanding and increased sampling frequency and replication to better define initial conditions. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems.Accepted manuscrip

Lake salinization drives consistent losses of zooplankton abundance and diversity across coordinated mesocosm experiments

Human-induced salinization increasingly threatens inland waters; yet we know little about the multifaceted response of lake communities to salt contamination. By conducting a coordinated mesocosm experiment of lake salinization across 16 sites in North America and Europe, we quantified the response of zooplankton abundance and (taxonomic and functional) community structure to a broad gradient of environmentally relevant chloride concentrations, ranging from 4 to ca. 1400 mg Cl- L-1. We found that crustaceans were distinctly more sensitive to elevated chloride than rotifers; yet, rotifers did not show compensatory abundance increases in response to crustacean declines. For crustaceans, our among-site comparisons indicate: (1) highly consistent decreases in abundance and taxon richness with salinity; (2) widespread chloride sensitivity across major taxonomic groups (Cladocera, Cyclopoida, and Calanoida); and (3) weaker loss of functional than taxonomic diversity. Overall, our study demonstrates that aggregate properties of zooplankton communities can be adversely affected at chloride concentrations relevant to anthropogenic salinization in lakes.Peer reviewe

Current water quality guidelines across North America and Europe do not protect lakes from salinization

Human-induced salinization caused by the use of road deicing salts, agricultural practices, mining operations, and climate change is a major threat to the biodiversity and functioning of freshwater ecosystems. Yet, it is unclear if freshwater ecosystems are protected from salinization by current water quality guidelines. Leveraging an experimental network of land-based and in-lake mesocosms across North America and Europe, we tested how salinization-indicated as elevated chloride (C-) concentration-will affect lake food webs and if two of the lowest Cl- thresholds found globally are sufficient to protect these food webs. Our results indicated that salinization will cause substantial zooplankton mortality at the lowest Cl- thresholds established in Canada (120 mg Cl-/L) and the United States (230 mg Cl-/L) and throughout Europe where Cl- thresholds are generally higher. For instance, at 73% of our study sites, Cl- concentrations that caused a >= 50% reduction in cladoceran abundance were at or below Cl thresholds in Canada, in the United States, and throughout Europe. Similar trends occurred for copepod and rotifer zooplankton. The loss of zooplankton triggered a cascading effect causing an increase in phytoplankton biomass at 47% of study sites. Such changes in lake food webs could alter nutrient cycling and water clarity and trigger declines in fish production. Current Cl- thresholds across North America and Europe clearly do not adequately protect lake food webs. Water quality guidelines should be developed where they do not exist, and there is an urgent need to reassess existing guidelines to protect lake ecosystems from human-induced salinization.Peer reviewe

Widespread variation in salt tolerance within freshwater zooplankton species reduces the predictability of community-level salt tolerance

The salinization of freshwaters is a global threat to aquatic biodiversity. We quantified variation in chloride (Cl-) tolerance of 19 freshwater zooplankton species in four countries to answer three questions: (1) How much variation in Cl- tolerance is present among populations? (2) What factors predict intraspecific variation in Cl- tolerance? (3) Must we account for intraspecific variation to accurately predict community Cl- tolerance? We conducted field mesocosm experiments at 16 sites and compiled acute LC(50)s from published laboratory studies. We found high variation in LC(50)s for Cl- tolerance in multiple species, which, in the experiment, was only explained by zooplankton community composition. Variation in species-LC50 was high enough that at 45% of lakes, community response was not predictable based on species tolerances measured at other sites. This suggests that water quality guidelines should be based on multiple populations and communities to account for large intraspecific variation in Cl- tolerance.Peer reviewe

The potential of high-frequency profiling to assess vertical and seasonal patterns of phytoplankton dynamics in lakes: An extension of the Plankton Ecology Group (PEG) model

The use of high-frequency sensors on profiling buoys to investigate physical, chemical, and biological processes in lakes is increasing rapidly. Profiling buoys with automated winches and sensors that collect high-frequency chlorophyll fluorescence (ChlF) profiles in 11 lakes in the Global Lake Ecological Observatory Network (GLEON) allowed the study of the vertical and temporal distribution of ChlF, including the formation of subsurface chlorophyll maxima (SSCM). The effectiveness of 3 methods for sampling phytoplankton distributions in lakes, including (1) manual profiles, (2) single-depth buoys, and (3) profiling buoys were assessed. High-frequency ChlF surface data and profiles were compared to predictions from the Plankton Ecology Group (PEG) model. The depth-integrated ChlF dynamics measured by the profiling buoy data revealed a greater complexity that neither conventional sampling nor the generalized PEG model captured. Conventional sampling techniques would have missed SSCM in 7 of 11 study lakes. Although surface-only ChlF data underestimated average water column ChlF, at times by nearly 2-fold in 4 of the lakes, overall there was a remarkable similarity between surface and mean water column data. Contrary to the PEG model’s proposed negligible role for physical control of phytoplankton during the growing season, thermal structure and light availability were closely associated with ChlF seasonal depth distribution. Thus, an extension of the PEG model is proposed, with a new conceptual framework that explicitly includes physical metrics to better predict SSCM formation in lakes and highlight when profiling buoys are especially informative

Turning up the heat: Long‐term water quality responses to wildfires and climate change in a hypereutrophic lake

Abstract Clear Lake (Lake County, CA, USA) is hypereutrophic and used for drinking water, tribal use, and supports a significant fishing economy. The Mendocino Complex (2018), one of the largest wildfires in California's post‐settlement history, burned 40% of the Clear Lake watershed, providing a timely opportunity to study the impacts of historical and current wildfires on this valuable aquatic resource. Using long‐term monthly monitoring data from 1968 to 2019, paired with historical watershed fire data, we found that for the three largest fire years in the watershed's history, 3‐year postfire median July–October epilimnetic total phosphorus (TP) concentrations were below or equal to 3‐year prefire TP concentrations. However, both median TP epilimnetic concentrations and deepwater temperature across the lake have increased since the late 1960s. Long‐term TP increases were more strongly correlated with monthly maximum air temperatures than precipitation, suggesting a potential role of warming‐induced water column stratification, dissolved oxygen (DO) depletion, and high potential for internal phosphorus loading. Hypoxic occurrences were correlated with higher hypolimnetic soluble reactive phosphorus and TP concentrations, but additional high‐frequency monitoring of DO will help determine the duration of anoxia and its contribution to internal phosphorus loading. These long‐term data suggest that for this large, hypereutrophic lake, wildfires did not significantly alter in‐lake TP concentrations based on long‐term, monthly monitoring and that other internal or external sources of TP may mask any wildfire effects. Nonetheless, our study underscores the value of synthesizing decades of water quality, watershed wildfire, and climate data to build a more comprehensive, nuanced picture of multiple long‐term threats to aquatic ecosystems under global change. Moreover, monitoring and studying fire effects across a wide range of lake types beyond this study will help promote more effective lake management during changing climates and increasingly frequent large wildfires