Jennifer A. Brentrup

Ecological consequences of long-term browning in lakes.

Increases in terrestrially-derived dissolved organic matter (DOM) have led to the browning of inland waters across regions of northeastern North America and Europe. Short-term experimental and comparative studies highlight the important ecological consequences of browning. These range from transparency-induced increases in thermal stratification and oxygen (O2) depletion to changes in pelagic food web structure and alteration of the important role of inland waters in the global carbon cycle. However, multi-decadal studies that document the net ecological consequences of long-term browning are lacking. Here we show that browning over a 27 year period in two lakes of differing transparency resulted in fundamental changes in vertical habitat gradients and food web structure, and that these responses were stronger in the more transparent lake. Surface water temperatures increased by 2–3 °C in both lakes in the absence of any changes in air temperature. Water transparency to ultraviolet (UV) radiation showed a fivefold decrease in the more transparent lake. The primary zooplankton grazers decreased, and in the more transparent lake were largely replaced by a two trophic level zooplankton community. These findings provide new insights into the net effects of the complex and contrasting mechanisms that underlie the ecosystem consequences of browning.

The importance of lake-specific characteristics for water quality across the continental United States.

Lake water quality is affected by local and regional drivers, including lake physical characteristics, hydrology, landscape position, land cover, land use, geology, and climate. Here, we demonstrate the utility of hypothesis testing within the landscape limnology framework using a random forest algorithm on a national-scale, spatially explicit data set, the United States Environmental Protection Agencys 2007 National Lakes Assessment. For 1026 lakes, we tested the relative importance of water quality drivers across spatial scales, the importance of hydrologic connectivity in mediating water quality drivers, and how the importance of both spatial scale and connectivity differ across response variables for five important in-lake water quality metrics (total phosphorus, total nitrogen, dissolved organic carbon, turbidity, and conductivity). By modeling the effect of water quality predictors at different spatial scales, we found that lake-specific characteristics (e.g., depth, sediment area-to-volume ratio) were important for explaining water quality (54-60% variance explained), and that regionalization schemes were much less effective than lake specific metrics (28-39% variance explained). Basin-scale land use and land cover explained between 45-62% of variance, and forest cover and agricultural land uses were among the most important basin-scale predictors. Water quality drivers did not operate independently; in some cases, hydrologic connectivity (the presence of upstream surface water features) mediated the effect of regional-scale drivers. For example, for water quality in lakes with upstream lakes, regional classification schemes were much less effective predictors than lake-specific variables, in contrast to lakes with no upstream lakes or with no surface inflows. At the scale of the continental United States, conductivity was explained by drivers operating at larger spatial scales than for other water quality responses. The current regulatory practice of using regionalization schemes to guide water quality criteria could be improved by consideration of lake-specific characteristics, which were the most important predictors of water quality at the scale of the continental United States. The spatial extent and high quality of contextual data available for this analysis makes this work an unprecedented application of landscape limnology theory to water quality data. Further, the demonstrated importance of lake morphology over other controls on water quality is relevant to both aquatic scientists and managers.

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

Abstract 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 the 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 models 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.

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.

Browning-related oxygen depletion in an oligotrophic lake

ABSTRACT In recent decades, terrestrial dissolved organic matter (DOM) has increased in many northeastern North American and European lakes and is contributing to long-term browning. We used a long-term dataset (1988–2014) to study the consequences of browning-related decreased water transparency on dissolved oxygen dynamics in 2 small temperate lakes in Pennsylvania, USA, that differ in their dissolved organic carbon concentrations. The oligotrophic (“clearer”) lake has low productivity and historically oxygenated deep waters. The mesotrophic–slightly dystrophic (“browner”) lake also has relatively low productivity but historically anoxic deep waters. We examined whether browning coincided with changes in summer dissolved oxygen dynamics, with a focus on deep-water oxygen depletion. In the clearer lake, we found that minimum oxygen concentrations decreased by ∼4.4 mg L−1 over the 27-year period, and these changes were strongly associated with both decreased water transparency and increased water column stability. We also found a shallowing of the maximum dissolved oxygen depth by ∼4.5  m and anoxic conditions established in more recent years. In the browner lake, the metrics we used did not detect any significant changes in dissolved oxygen, supporting the prediction that vertical temperature and oxygen patterns in clearer lakes may be more sensitive to increasing DOM than darker lakes. Anoxia is traditionally considered to be a consequence of anthropogenic nutrient loading and, more recently, a warming climate. We show that browning is another type of environmental change that may similarly result in anoxia in oligotrophic lakes.