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Dive into the research topics where Jordan S. Read is active.

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Featured researches published by Jordan S. Read.


Geophysical Research Letters | 2015

Rapid and highly variable warming of lake surface waters around the globe

Catherine M. O'Reilly; Sapna Sharma; Derek K. Gray; Stephanie E. Hampton; Jordan S. Read; Rex J. Rowley; Philipp Schneider; John D. Lenters; Peter B. McIntyre; Benjamin M. Kraemer; Gesa A. Weyhenmeyer; Dietmar Straile; Bo Dong; Rita Adrian; Mathew G. Allan; Orlane Anneville; Lauri Arvola; Jay A. Austin; John L. Bailey; Jill S. Baron; Justin D. Brookes; Elvira de Eyto; Martin T. Dokulil; David P. Hamilton; Karl E. Havens; Amy L. Hetherington; Scott N. Higgins; Simon J. Hook; Lyubov R. Izmest'eva; Klaus D. Joehnk

In this first worldwide synthesis of in situ and satellite-derived lake data, we find that lake summer surface water temperatures rose rapidly (global mean = 0.34°C decade−1) between 1985 and 2009. Our analyses show that surface water warming rates are dependent on combinations of climate and local characteristics, rather than just lake location, leading to the counterintuitive result that regional consistency in lake warming is the exception, rather than the rule. The most rapidly warming lakes are widely geographically distributed, and their warming is associated with interactions among different climatic factors—from seasonally ice-covered lakes in areas where temperature and solar radiation are increasing while cloud cover is diminishing (0.72°C decade−1) to ice-free lakes experiencing increases in air temperature and solar radiation (0.53°C decade−1). The pervasive and rapid warming observed here signals the urgent need to incorporate climate impacts into vulnerability assessments and adaptation efforts for lakes.


Ecosystems | 2015

Ecosystem Consequences of Changing Inputs of Terrestrial Dissolved Organic Matter to Lakes: Current Knowledge and Future Challenges

Christopher T. Solomon; Stuart E. Jones; Brian C. Weidel; Ishi Buffam; Megan L. Fork; Jan Karlsson; Søren Larsen; Jay T. Lennon; Jordan S. Read; Jasmine E. Saros

Lake ecosystems and the services that they provide to people are profoundly influenced by dissolved organic matter derived from terrestrial plant tissues. These terrestrial dissolved organic matter (tDOM) inputs to lakes have changed substantially in recent decades, and will likely continue to change. In this paper, we first briefly review the substantial literature describing tDOM effects on lakes and ongoing changes in tDOM inputs. We then identify and provide examples of four major challenges which limit predictions about the implications of tDOM change for lakes, as follows: First, it is currently difficult to forecast future tDOM inputs for particular lakes or lake regions. Second, tDOM influences ecosystems via complex, interacting, physical-chemical-biological effects and our holistic understanding of those effects is still rudimentary. Third, non-linearities and thresholds in relationships between tDOM inputs and ecosystem processes have not been well described. Fourth, much understanding of tDOM effects is built on comparative studies across space that may not capture likely responses through time. We conclude by identifying research approaches that may be important for overcoming those challenges in order to provide policy- and management-relevant predictions about the implications of changing tDOM inputs for lakes.


The ISME Journal | 2012

Lake microbial communities are resilient after a whole-ecosystem disturbance

Ashley Shade; Jordan S. Read; Nicholas D. Youngblut; Noah Fierer; Rob Knight; Timothy K. Kratz; Noah R. Lottig; Eric E. Roden; Emily H. Stanley; Jesse Stombaugh; Rachel J. Whitaker; Chin H. Wu; Katherine D. McMahon

Disturbances act as powerful structuring forces on ecosystems. To ask whether environmental microbial communities have capacity to recover after a large disturbance event, we conducted a whole-ecosystem manipulation, during which we imposed an intense disturbance on freshwater microbial communities by artificially mixing a temperate lake during peak summer thermal stratification. We employed environmental sensors and water chemistry analyses to evaluate the physical and chemical responses of the lake, and bar-coded 16S ribosomal RNA gene pyrosequencing and automated ribosomal intergenic spacer analysis (ARISA) to assess the bacterial community responses. The artificial mixing increased mean lake temperature from 14 to 20 °C for seven weeks after mixing ended, and exposed the microorganisms to very different environmental conditions, including increased hypolimnion oxygen and increased epilimnion carbon dioxide concentrations. Though overall ecosystem conditions remained altered (with hypolimnion temperatures elevated from 6 to 20 °C), bacterial communities returned to their pre-manipulation state as some environmental conditions, such as oxygen concentration, recovered. Recovery to pre-disturbance community composition and diversity was observed within 7 (epilimnion) and 11 (hypolimnion) days after mixing. Our results suggest that some microbial communities have capacity to recover after a major disturbance.


Environmental Microbiology | 2011

Resistance, resilience and recovery: aquatic bacterial dynamics after water column disturbance

Ashley Shade; Jordan S. Read; David G. Welkie; Timothy K. Kratz; Chin H. Wu; Katherine D. McMahon

For lake microbes, water column mixing acts as a disturbance because it homogenizes thermal and chemical gradients known to define the distributions of microbial taxa. Our first objective was to isolate hypothesized drivers of lake bacterial response to water column mixing. To accomplish this, we designed an enclosure experiment with three treatments to independently test key biogeochemical changes induced by mixing: oxygen addition to the hypolimnion, nutrient addition to the epilimnion, and full water column mixing. We used molecular fingerprinting to observe bacterial community dynamics in the treatment and control enclosures, and in ambient lake water. We found that oxygen and nutrient amendments simulated the physical-chemical water column environment following mixing and resulted in similar bacterial communities to the mixing treatment, affirming that these were important drivers of community change. These results demonstrate that specific environmental changes can replicate broad disturbance effects on microbial communities. Our second objective was to characterize bacterial community stability by quantifying community resistance, recovery and resilience to an episodic disturbance. The communities in the nutrient and oxygen amendments changed quickly (had low resistance), but generally matched the control composition by the 10th day after treatment, exhibiting resilience. These results imply that aquatic bacterial assemblages are generally stable in the face of disturbance.


Scientific Data | 2015

A global database of lake surface temperatures collected by in situ and satellite methods from 1985–2009

Sapna Sharma; Derek K. Gray; Jordan S. Read; Catherine M. O’Reilly; Philipp Schneider; Anam Qudrat; Corinna Gries; Samantha Stefanoff; Stephanie E. Hampton; Simon J. Hook; John D. Lenters; David M. Livingstone; Peter B. McIntyre; Rita Adrian; Mathew G. Allan; Orlane Anneville; Lauri Arvola; Jay A. Austin; John L. Bailey; Jill S. Baron; Justin D. Brookes; Yuwei Chen; Robert Daly; Martin T. Dokulil; Bo Dong; Kye Ewing; Elvira de Eyto; David P. Hamilton; Karl E. Havens; Shane Haydon

Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global data set of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985–2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues.


Geophysical Research Letters | 2015

Small lakes show muted climate change signal in deepwater temperatures

Luke A. Winslow; Jordan S. Read; Gretchen J. A. Hansen; Paul C. Hanson

Water temperature observations were collected from 142 lakes across Wisconsin, USA, to examine variation in temperature of lakes exposed to similar regional climate. Whole lake water temperatures increased across the state from 1990 to 2012, with an average trend of 0.042°C yr−1 ± 0.01°C yr−1. In large (>0.5 km2) lakes, the positive temperature trend was similar across all depths. In small lakes ( 0.5 times the maximum lake depth. The differing response of small versus large lakes is potentially a result of wind-sheltering reducing turbulent mixing magnitude in small lakes. These results demonstrate that small lakes respond differently to climate change than large lakes, suggesting that current predictions of impacts to lakes from climate change may require modification.


Water Resources Research | 2015

Predicting the resilience and recovery of aquatic systems: A framework for model evolution within environmental observatories

Matthew R. Hipsey; David P. Hamilton; Paul C. Hanson; Cayelan C. Carey; Janaine Z. Coletti; Jordan S. Read; Bastiaan Willem Ibelings; F.J. Valesini; Justin D. Brookes

Maintaining the health of aquatic systems is an essential component of sustainable catchment management, however, degradation of water quality and aquatic habitat continues to challenge scientists and policy-makers. To support management and restoration efforts aquatic system models are required that are able to capture the often complex trajectories that these systems display in response to multiple stressors. This paper explores the abilities and limitations of current model approaches in meeting this challenge, and outlines a strategy based on integration of flexible model libraries and data from observation networks, within a learning framework, as a means to improve the accuracy and scope of model predictions. The framework is comprised of a data assimilation component that utilizes diverse data streams from sensor networks, and a second component whereby model structural evolution can occur once the model is assessed against theoretically relevant metrics of system function. Given the scale and transdisciplinary nature of the prediction challenge, network science initiatives are identified as a means to develop and integrate diverse model libraries and workflows, and to obtain consensus on diagnostic approaches to model assessment that can guide model adaptation. We outline how such a framework can help us explore the theory of how aquatic systems respond to change by bridging bottom-up and top-down lines of enquiry, and, in doing so, also advance the role of prediction in aquatic ecosystem management.


Inland Waters | 2015

A Global Lake Ecological Observatory Network (GLEON) for synthesising high–frequency sensor data for validation of deterministic ecological models

David P. Hamilton; Cayelan C. Carey; Lauri Arvola; Peter W. Arzberger; Carol A. Brewer; Jon J. Cole; Evelyn E. Gaiser; Paul C. Hanson; B.W. Ibelings; Eleanor Jennings; Timothy K. Kratz; Fang-Pang Lin; Chris G. McBride; David de Motta Marques; Kohji Muraoka; Ami Nishri; Boqiang Qin; Jordan S. Read; Kevin C. Rose; Elizabeth Ryder; Kathleen C. Weathers; Guangwei Zhu; Dennis Trolle; Justin D. Brookes

Abstract A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate process-based ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest.


Environmental Modelling and Software | 2015

Automated calculation of surface energy fluxes with high-frequency lake buoy data

R. Iestyn Woolway; Ian D. Jones; David P. Hamilton; Stephen C. Maberly; Kohji Muraoka; Jordan S. Read; Robyn L. Smyth; Luke A. Winslow

Lake Heat Flux Analyzer is a program used for calculating the surface energy fluxes in lakes according to established literature methodologies. The program was developed in MATLAB for the rapid analysis of high-frequency data from instrumented lake buoys in support of the emerging field of aquatic sensor network science. To calculate the surface energy fluxes, the program requires a number of input variables, such as air and water temperature, relative humidity, wind speed, and short-wave radiation. Available outputs for Lake Heat Flux Analyzer include the surface fluxes of momentum, sensible heat and latent heat and their corresponding transfer coefficients, incoming and outgoing long-wave radiation. Lake Heat Flux Analyzer is open source and can be used to process data from multiple lakes rapidly. It provides a means of calculating the surface fluxes using a consistent method, thereby facilitating global comparisons of high-frequency data from lake buoys.


Geophysical Research Letters | 2014

Decadal oscillation of lakes and aquifers in the upper Great Lakes region of North America: Hydroclimatic implications

Carl J. Watras; Jordan S. Read; K. D. Holman; Zhengyu Liu; Yu Song; A. J. Watras; S. Morgan; Emily H. Stanley

We report a unique hydrologic time series which indicates that water levels in lakes and aquifers across the upper Great Lakes region of North America have been dominated by a climatically driven, near-decadal oscillation for at least 70 years. The historical oscillation (~13 years) is remarkably consistent among small seepage lakes, groundwater tables, and the two largest Laurentian Great Lakes despite substantial differences in hydrology. Hydrologic analyses indicate that the oscillation has been governed primarily by changes in the net atmospheric flux of water (P − E) and stage-dependent outflow. The oscillation is hypothetically connected to large-scale atmospheric circulation patterns originating in the midlatitude North Pacific that support the flux of moisture into the region from the Gulf of Mexico. Recent data indicate an apparent change in the historical oscillation characterized by an ~12 years downward trend beginning in 1998. Record low water levels region wide may mark the onset of a new hydroclimatic regime.

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Luke A. Winslow

United States Geological Survey

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Paul C. Hanson

University of Wisconsin-Madison

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Kevin C. Rose

University of Wisconsin-Madison

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Emily K. Read

United States Geological Survey

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Chin H. Wu

University of Wisconsin-Madison

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Gretchen J. A. Hansen

University of Wisconsin-Madison

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Hilary A. Dugan

University of Wisconsin-Madison

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Katherine D. McMahon

University of Wisconsin-Madison

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