Kevin C. Rose

Diel surface temperature range scales with lake size

Ecological and biogeochemical processes in lakes are strongly dependent upon water temperature. Long-term surface warming of many lakes is unequivocal, but little is known about the comparative magnitude of temperature variation at diel timescales, due to a lack of appropriately resolved data. Here we quantify the pattern and magnitude of diel temperature variability of surface waters using high-frequency data from 100 lakes. We show that the near-surface diel temperature range can be substantial in summer relative to long-term change and, for lakes smaller than 3 km2, increases sharply and predictably with decreasing lake area. Most small lakes included in this study experience average summer diel ranges in their near-surface temperatures of between 4 and 7°C. Large diel temperature fluctuations in the majority of lakes undoubtedly influence their structure, function and role in biogeochemical cycles, but the full implications remain largely unexplored.

Long‐term trends and synchrony in dissolved organic matter characteristics in Wisconsin, USA, lakes: Quality, not quantity, is highly sensitive to climate

Dissolved organic matter (DOM) is a fundamental driver of many lake processes. In the past several decades, many lakes have exhibited a substantial increase in DOM quantity, measured as dissolved organic carbon (DOC) concentration. While increasing DOC is now widely recognized, fewer studies have sought to understand how characteristics of DOM (DOM quality) change over time. Quality can be measured in several ways, including the optical characteristics spectral slope (S275–295), spectral ratio (SR), absorbance at 254u2009nm (A254), and DOC-specific absorbance (SUVA; A254:DOC). However, long-term measurements of quality are not nearly as common as long-term measurements of DOC concentration. We used 24u2009years of DOC and absorbance data for seven lakes in the North Temperate Lakes Long-Term Ecological Research site in northern Wisconsin, USA, to examine temporal trends and synchrony in both DOC concentration and quality. We predicted lower SR and S275–295 and higher A254 and SUVA trends, consistent with increasing DOC and greater allochthony. DOC concentration exhibited both significant positive and negative trends among lakes. In contrast, DOC quality exhibited trends suggesting reduced allochthony or increased degradation, with significant long-term increases in SR in three lakes. Patterns and synchrony of DOM quality parameters suggest that they are more responsive to climatic variations than DOC concentration. SUVA was particularly responsive to the degree of soil moisture. These results demonstrate that DOC quantity and quality can exhibit different complex long-term trends and responses to climatic drivers, with implications for carbon cycling and microbial communities in aquatic ecosystems.

Historical foundations and future directions in macrosystems ecology

Macrosystems ecology is an effort to understand ecological processes and interactions at the broadest spatial scales and has potential to help solve globally important social and ecological challenges. It is important to understand the intellectual legacies underpinning macrosystems ecology: How the subdiscipline fits within, builds upon, differs from and extends previous theories. We trace the rise of macrosystems ecology with respect to preceding theories and present a new hypothesis that integrates the multiple components of macrosystems theory. The spatio-temporal anthropogenic rescaling (STAR) hypothesis suggests that human activities are altering the scales of ecological processes, resulting in interactions at novel space-time scale combinations that are diverse and predictable. We articulate four predictions about how human actions are expanding, shrinking, speeding up and slowing down ecological processes and interactions, and thereby generating new scaling relationships for ecological patterns and processes. We provide examples of these rescaling processes and describe ecological consequences across terrestrial, freshwater and marine ecosystems. Rescaling depends in part on characteristics including connectivity, stability and heterogeneity. Our STAR hypothesis challenges traditional assumptions about how the spatial and temporal scales of processes and interactions operate in different types of ecosystems and provides a lens through which to understand macrosystem-scale environmental change.

Climate change-induced increases in precipitation are reducing the potential for solar ultraviolet radiation to inactivate pathogens in surface waters

Climate change is accelerating the release of dissolved organic matter (DOM) to inland and coastal waters through increases in precipitation, thawing of permafrost, and changes in vegetation. Our modeling approach suggests that the selective absorption of ultraviolet radiation (UV) by DOM decreases the valuable ecosystem service wherein sunlight inactivates waterborne pathogens. Here we highlight the sensitivity of waterborne pathogens of humans and wildlife to solar UV, and use the DNA action spectrum to model how differences in water transparency and incident sunlight alter the ability of UV to inactivate waterborne pathogens. A case study demonstrates how heavy precipitation events can reduce the solar inactivation potential in Lake Michigan, which provides drinking water to over 10 million people. These data suggest that widespread increases in DOM and consequent browning of surface waters reduce the potential for solar UV inactivation of pathogens, and increase exposure to infectious diseases in humans and wildlife.

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.

Insights from the Global Lake Ecological Observatory Network (GLEON)

The Global Lake Ecological Observatory Network (GLEON) is a grass-roots network of people, data, and observatories. The network represents a unique effort to bring together a diverse community of scientists, engineers, information technology experts, and engaged stakeholders to understand, conserve, and predict the state of lakes and reservoirs globally. Individuals and teams in GLEON have generated a range of scientific, educational, and outreach products, from software tools to scientific publications to education modules and programs. This special issue of Inland Waters brings together a series of papers generated from the network. Here, we discuss the foundations of GLEON that have facilitated these publications and others like them in terms of network structure, research areas, and the threads that tie the network together. GLEON is underpinned by sophisticated analytical tools and a network of high-frequency in situ observatories that exploit advanced sensors and associated technologies. This approach expands the space and time domains available to inquiry and analysis of lake processes. Using team science, the network has also established a culture of collaboration, sharing, and trust. This flexible framework allows GLEON members to advance research on a range of topics and has led to an increasing number of collaborative cross-site products. Future success will depend on the network’s ability to continue to facilitate the successes of its members while also being responsive to evolving member needs, technologies, and societal priorities.

Watershed-Induced Limnological and Microbial Status in Two Oligotrophic Andean Lakes Exposed to the Same Climatic Scenario

Laguna Negra and Lo Encañado are two oligotrophic Andean lakes forming part of the system fed by meltwater from distinct glacial tongues of the Echaurren glacier in central Chile, which is in a recession period. The recent increase in temperature and decline in precipitation have led to an increase of glacial meltwater and sediments entering these lakes. Although the lacustrine systems are also hydrogeologically connected, the limnology of the lakes is strongly controlled by the surface processes related to the respective sub-watersheds and hydrology. Watershed characteristics (area and length, slope, lithology, resistance to erosion, among others) affect the chemical and physical characteristics of both lakes (e.g., nutrient concentration and turbidity). We studied physical and chemical variables and performed 16S rRNA amplicon sequencing to determine the specific microbial signature of the lakes. The transparency, temperature, turbidity and concentrations of chlorophyll-a, dissolved organic matter, nutrients and the total number of cells, revealed the different status of both lakes at the time of sampling. The predominant bacterial groups in both lakes were Proteobacteria, Verrucomicrobia, and Bacteroidetes. Interestingly, the contribution of phototrophs was significantly higher in LN compared to LE (13 and 4% respectively) and the major fraction corresponded to Anoxygenic Phototrophs (AP) represented by Chloroflexi, Alpha, and Betaproteobacteria. Multivariate analyses showed that the nutrient levels and the light availability of both lakes, which finally depend on the hydrological characteristics of the respective watersheds, explain the differential community composition/function. The abundance of a diverse photoheterotrophic bacterioplankton community suggests that the ability to utilize solar energy along with organic and inorganic substrates is a key function in these oligotrophic mountain lakes.

Characterizing hydrologic networks: Developing a tool to enable research of macroscale aquatic networks

Abstract Addressing continental scale challenges affecting inland aquatic systems requires data at comparable scales. Critically, local in-situ observations for both lotic and lentic ecosystems are frequently fragmented across federal, state and local agencies, and nonprofit or academic organizations and must be linked to other geospatial data to be useful. To advance macro-scale aquatic ecosystem science, better tools are needed to facilitate dataset integration. Key to integration of aquatic data is the linking of spatial data to the hydrologic network. This integration step is challenging as hydrologic network data are large and cumbersome to manage. Here we develop a new R package, hydrolinks, to ease linking aquatic data to the hydrologic network. We use hydrolinks to evaluate the spatial data quality for all lake and stream sites available through the U.S. Water Quality Portal. We find that 76.5% of lake sites and 13.9% of stream sites do not correspond with mapped waterbodies.