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China has made a concerted effort to successfully improve water quality of rivers, but lake water quality has not improved. Lakes require controls on both catchment external nutrient loads and in-lake internal loads, where nature-based solutions are coupled with engineered systems to achieve the United Nations Sustainable Development Goals (SDGs).

 

Abstract. The General Lake Model (GLM) is a one-dimensional open-source code designed to simulate the hydrodynamics of lakes, reservoirs, and wetlands. GLM was developed to support the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of researchers using sensors to understand lake functioning and address questions about how lakes around the world respond to climate and land use change. The scale and diversity of lake types, locations, and sizes, and the expanding observational datasets created the need for a robust community model of lake dynamics with sufficient flexibility to accommodate a range of scientific and management questions relevant to the GLEON community. This paper summarizes the scientific basis and numerical implementation of the model algorithms, including details of sub-models that simulate surface heat exchange and ice cover dynamics, vertical mixing, and inflow–outflow dynamics. We demonstrate the suitability of the model for different lake types that vary substantially in their morphology, hydrology, and climatic conditions. GLM supports a dynamic coupling with biogeochemical and ecological modelling libraries for integrated simulations of water quality and ecosystem health, and options for integration with other environmental models are outlined. Finally, we discuss utilities for the analysis of model outputs and uncertainty assessments, model operation within a distributed cloud-computing environment, and as a tool to support the learning of network participants.

 

Abstract Climate change and other anthropogenic stressors have led to long-term changes in the thermal structure, including surface temperatures, deepwater temperatures, and vertical thermal gradients, in many lakes around the world. Though many studies highlight warming of surface water temperatures in lakes worldwide, less is known about long-term trends in full vertical thermal structure and deepwater temperatures, which have been changing less consistently in both direction and magnitude. Here, we present a globally-expansive data set of summertime in-situ vertical temperature profiles from 153 lakes, with one time series beginning as early as 1894. We also compiled lake geographic, morphometric, and water quality variables that can influence vertical thermal structure through a variety of potential mechanisms in these lakes. These long-term time series of vertical temperature profiles and corresponding lake characteristics serve as valuable data to help understand changes and drivers of lake thermal structure in a time of rapid global and ecological change. 

Abstract Globally, lake surface water temperatures have warmed rapidly relative to air temperatures, but changes in deepwater temperatures and vertical thermal structure are still largely unknown. We have compiled the most comprehensive data set to date of long-term (1970–2009) summertime vertical temperature profiles in lakes across the world to examine trends and drivers of whole-lake vertical thermal structure. We found significant increases in surface water temperatures across lakes at an average rate of + 0.37 °C decade −1 , comparable to changes reported previously for other lakes, and similarly consistent trends of increasing water column stability (+ 0.08 kg m −3 decade −1 ). In contrast, however, deepwater temperature trends showed little change on average (+ 0.06 °C decade −1 ), but had high variability across lakes, with trends in individual lakes ranging from − 0.68 °C decade −1 to + 0.65 °C decade −1 . The variability in deepwater temperature trends was not explained by trends in either surface water temperatures or thermal stability within lakes, and only 8.4% was explained by lake thermal region or local lake characteristics in a random forest analysis. These findings suggest that external drivers beyond our tested lake characteristics are important in explaining long-term trends in thermal structure, such as local to regional climate patterns or additional external anthropogenic influences. 

Global warming and eutrophication contribute to the worldwide increase in cyanobacterial blooms, and the level of cyanobacterial biomass is strongly associated with rises in methane emissions from surface lake waters. Hence, methane‐metabolizing microorganisms may be important for modulating carbon flow in cyanobacterial blooms. Here, we surveyed methanogenic and methanotrophic communities associated with floatingMicrocystisaggregates in 10 lakes spanning four continents, through sequencing of 16S rRNA and functional marker genes. Methanogenic archaea (mainlyMethanoregulaandMethanosaeta) were detectable in 5 of the 10 lakes and constituted the majority (~50%–90%) of the archaeal community in these lakes. Three of the 10 lakes contained relatively more abundant methanotrophs than the other seven lakes, with the methanotrophic generaMethyloparacoccus,Crenothrix, and an uncultured species related toMethylobacterdominating and nearly exclusively found in each of those three lakes. These three are among the five lakes in which methanogens were observed. Operational taxonomic unit (OTU) richness and abundance of methanotrophs were strongly positively correlated with those of methanogens, suggesting that their activities may be coupled. TheseMicrocystis‐aggregate‐associated methanotrophs may be responsible for a hitherto overlooked sink for methane in surface freshwaters, and their co‐occurrence with methanogens sheds light on the methane cycle in cyanobacterial aggregates.

 

Bacteria play key roles in the function and diversity of aquatic systems, but aside from study of specific bloom systems, little is known about the diversity or biogeography of bacteria associated with harmful cyanobacterial blooms (cyanoHABs). CyanoHAB species are known to shape bacterial community composition and to rely on functions provided by the associated bacteria, leading to the hypothesized cyanoHAB interactome, a coevolved community of synergistic and interacting bacteria species, each necessary for the success of the others. Here, we surveyed the microbiome associated withMicrocystis aeruginosaduring blooms in 12 lakes spanning four continents as an initial test of the hypothesizedMicrocystisinteractome. We predicted that microbiome composition and functional potential would be similar across blooms globally. Our results, as revealed by 16S rRNA sequence similarity, indicate thatM. aeruginosais cosmopolitan in lakes across a 280° longitudinal and 90° latitudinal gradient. The microbiome communities were represented by a wide range of operational taxonomic units and relative abundances. Highly abundant taxa were more related and shared across most sites and did not vary with geographic distance, thus, likeMicrocystis, revealing no evidence for dispersal limitation. High phylogenetic relatedness, both within and across lakes, indicates that microbiome bacteria with similar functional potential were associated with all blooms. WhileMicrocystisand the microbiome bacteria shared many genes, whole‐community metagenomic analysis revealed a suite of biochemical pathways that could be considered complementary. Our results demonstrate a high degree of similarity across globalMicrocystisblooms, thereby providing initial support for the hypothesizedMicrocystisinteractome.