Catherine M. O'Reilly

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

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.

Effects of land-use change on aquatic biodiversity: A view from the paleorecord at Lake Tanganyika, East Africa

Population growth and watershed deforestation in northwestern Tanzania threaten the biodiversity of Lake Tanganyika through erosion and habitat degradation. We used cores collected offshore from Gombe Stream National Park and a deforested watershed to reconstruct how land-use changes in the Gombe Stream area since A.D. 1750 have affected lake biodiversity. Paleoenvironmental and paleoecological data reveal substantial changes in mass accumulation rates for sediment and organic matter, nitrogen stable isotope values, and benthic species composition offshore from the deforested watershed since 1880. Comparable changes were not observed offshore from the park.

Extensive and drastically different alpine lake changes on Asia's high plateaus during the past four decades

Asias high plateaus are sensitive to climate change and have been experiencing rapid warming over the past few decades. We found 99 new lakes and extensive lake expansion on the Tibetan Plateau during the last four decades, 1970-2013, due to increased precipitation and cryospheric contributions to its water balance. This contrasts with disappearing lakes and drastic shrinkage of lake areas on the adjacent Mongolian Plateau: 208 lakes disappeared, and 75% of the remaining lakes have shrunk. We detected a statistically significant coincidental timing of lake area changes in both plateaus, associated with the climate regime shift that occurred during 1997/1998. This distinct change in 1997/1998 is thought to be driven by large-scale atmospheric circulation changes in response to climate warming. Our findings reveal that these two adjacent plateaus have been changing in opposite directions in response to climate change. These findings shed light on the complex role of the regional climate and water cycles and provide useful information for ecological and water resource planning in these fragile landscapes.

Nutrient uptake dynamics across a gradient of nutrient concentrations and ratios at the landscape scale

Understanding interactions between nutrient cycles is essential for recognizing and remediating human impacts on water quality, yet multielemental approaches to studying nutrient cycling in streams are currently rare. Here we utilized a relatively new approach (tracer additions for spiraling curve characterization) to examine uptake dynamics for three essential nutrients across a landscape that varied in absolute and relative nutrient availability. We measured nutrient uptake for soluble reactive phosphorous, ammonium-nitrogen, and nitrate-nitrogen in 16 headwater streams in the Catskill Mountains, New York. Across the landscape, ammonium-nitrogen and soluble reactive phosphorus had shorter uptake lengths and higher uptake velocities than nitrate-nitrogen. Ammonium-nitrogen and soluble reactive phosphorus uptake velocities were tightly correlated, and the slope of the relationship did not differ from one, suggesting strong demand for both nutrients despite the high ambient water column dissolved inorganic nitrogen: soluble reactive phosphorus ratios. Ammonium-nitrogen appeared to be the preferred form of nitrogen despite much higher nitrate-nitrogen concentrations. The uptake rate of nitrate-nitrogen was positively correlated with ambient soluble reactive phosphorus concentration and soluble reactive phosphorus areal uptake rate, suggesting that higher soluble reactive phosphorus concentrations alleviate phosphorus limitation and facilitate nitrate-nitrogen uptake. In addition, these streams retained a large proportion of soluble reactive phosphorus, ammonium-nitrogen, and nitrate-nitrogen supplied by the watershed, demonstrating that these streams are important landscape filters for nutrients. Together, these results (1) indicated phosphorus limitation across the landscape but similarly high demand for ammonium-nitrogen and (2) suggested that nitrate-nitrogen uptake was influenced by variability in soluble reactive phosphorus availability and preference for ammonium-nitrogen.

Organic matter stoichiometry influences nitrogen and phosphorus uptake in a headwater stream

Abstract.  The concept of nutrient spiraling combines the geological, hydrological, and biological processes that influence nutrient cycling in streams. Spiraling studies have demonstrated connections between metabolic and nutrient cycles, organic matter (OM) dynamics, and hydrologic controls. Most spiraling studies have addressed the dynamics of a single element. However, nutrients do not move through ecosystems in isolation. Recent models have used ecological stoichiometric theory to couple N and P cycles, but empirical data to support these conceptual frameworks are generally lacking. We investigated the relationship between N and P uptake and the extent to which OM stoichiometry was related to the relative uptake of N and P in a headwater stream across 2 seasons. In addition, we explored whether our results were consistent with theoretical predictions derived from ecological stoichiometry and consumer–resource imbalances. We found that higher respiration led to higher NH4+ and P uptake rates. NH4+ and P uptake were strongly correlated, but the nature of this relationship shifted with a seasonal change in the dominant OM to fresh leaf litter in autumn. OM stoichiometry was a strong predictor of relative nutrient uptake (NH4∶SRP uptake ratios). Seasonal input of low N∶P leaf litter led to relatively higher NH4+ uptake from the water column, which caused a shift in relative nutrient uptake but did not alter the strength of the coupling. Our results indicate that stoichiometric imbalances between nutrient consumers and resources have a strong influence on nutrient uptake in streams. Moreover, stoichiometric models of consumer–resource imbalances between microbes and dominant OM substrates accurately captured N and P uptake dynamics in our study system. Integrating stoichiometry with metabolic controls provides insights into nutrient dynamics and acts as a framework to link N and P cycles.

Didymo Control: Increasing the Effectiveness of Decontamination Strategies and Reducing Spread

ABSTRACT Nuisance algal blooms formed by the benthic diatom Didymosphenia geminata (didymo) have been spreading rapidly, with negative ecological and economic effects. This microscopic alga is transported on fishing equipment, and controlling the spread of didymo involves proper cleaning of gear. Our study experimentally tested several common decontamination treatments and determined the response of state agencies and fishermen to decontamination procedures. In testing decontamination products, we found that dish liquid detergent was the most effective, followed by bleach, Virkon, and salt. Decontaminants were more effective on cells that were not still attached to their stalks. From the fishermens perspective, didymo was the aquatic invasive species of highest concern, but there was a wide range of approaches to didymo control. Our final recommendations concentrate on the importance of comprehensive information sources and standards for didymo decontamination and education, specifically, and for invasiv...

Variations in otolith elemental compositions of two clupeid species, Stolothrissa tanganicae and Limnothrissa miodon in Lake Tanganyika

Lake Tanganyika in East Africa has two primary basins (Northern and Southern) and borders four sovereign countries. Effective management of the fisheries of this lake requires sound biological understanding of the various fish stocks. The feasibility of fish stock identification within different basins and sub-basins of this lake was attempted through otolith elemental composition analysis. Element ratio signatures of whole sagittal otoliths (Mg/Ca, Sr/Ca and Ba/Ca) of two commercially important clupeid species (Stolothrissa tanganicae, n=18; Limnothrissa miodon, n=32) were used to classify individual fish to their resident basins. No element ratios in L. miodon otoliths were significantly different between Southern sub-basins, yet Ba/Ca and Sr/Ca ratios were significantly different for individuals from the Northern and Southern basins. Sr/Ca and Ba/Ca ratios were also significantly different between otoliths of sympatric L. miodon and S. tanganicae in the Northern Bujumbura Sub-basin. Species differences may be due to ontogenetic and environmental variables. Sr/Ca and Ba/Ca element concentration ratios contributed greatly to basin classification of individual fish. Canonical discriminant analysis correctly classified 91% of L. miodon and 83.3% of S. tanganicae to the Bujumbura sub-basin, compared to 59.9% of L. miodon collected from the Southern Basin that were correctly classified to this basin. These classification rates are similar to those found for estuarine species. Our results of a limited study suggest that otolith element compositions can be used as a natural tag to identify fish stocks in Lake Tanganyika and assist in the implementation of a multi-national fisheries best management plan.

Generating community-built tools for data sharing and analysis in environmental networks

Rapid data growth in many environmental sectors has necessitated tools to manage and analyze these data. The development of tools often lags behind the proliferation of data, however, which may slow exploratory opportunities and scientific progress. The Global Lake Ecological Observatory Network (GLEON) collaborative model supports an efficient and comprehensive data–analysis–insight life cycle, including implementations of data quality control checks, statistical calculations/derivations, models, and data visualizations. These tools are community-built and openly shared. We discuss the network structure that enables tool development and a culture of sharing, leading to optimized output from limited resources. Specifically, data sharing and a flat collaborative structure encourage the development of tools that enable scientific insights from these data. Here we provide a cross-section of scientific advances derived from global-scale analyses in GLEON. We document enhancements to science capabilities made possible by the development of analytical tools and highlight opportunities to expand this framework to benefit other environmental networks.

Using Large Data Sets for Open-Ended Inquiry in Undergraduate Science Classrooms

National Science Foundations Transforming Undergraduate Education in Science, Technology, Engineering, and Mathematics (TUES) [1245707]; National Association of Geoscience Teachers (NAGT)

EDDIE modules are effective learning tools for developing quantitative literacy and seismological understanding

ABSTRACT Environmental Data-Driven Inquiry and Exploration (EDDIE) modules engage students in analysis of data collected by networks of environmental sensors, which are used to study various natural phenomena, such as nutrient loading, climate change, and stream discharge. We compared two approaches to EDDIE module implementation in an undergraduate time-series analysis course. Course goals were to use high-frequency and long-term environmental datasets to improve quantitative literacy, develop data manipulation and analysis skills, construct scientific knowledge about natural phenomena, highlight the inherent variability in real data, and develop informed views about the nature of science (NOS). In both instructional treatments, students explored data and developed skills through a scaffolded in-class analysis and then solved more complex problems in homework assignments. In Treatment 1, engage and explore lesson phases involved discussion of instructor-prepared plots using the think–pair–share method. Conversely, in Treatment 2s engage and explore lesson phases, students prepared graphs and completed activities in a computer lab, which required more guidance in data manipulation and thus contained less structured discussion of data analysis and interpretation. We administered a pre/postquestionnaire to compare learning gains between the two treatments in quantitative literacy, statistical reasoning, nature-of-science (NOS) understanding, and understanding of seismological concepts. Results indicate that EDDIE modules are sufficiently flexible to be effective in both learning environments. Our results indicate that students reacted similarly to both instructional treatments, suggesting that EDDIE modules are flexible enough platforms to achieve measurable learning gains in a variety of pedagogical environments.