
NSF Org: |
EF Emerging Frontiers |
Recipient: |
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Initial Amendment Date: | June 10, 2011 |
Latest Amendment Date: | June 10, 2011 |
Award Number: | 1065649 |
Award Instrument: | Standard Grant |
Program Manager: |
Elizabeth Blood
EF Emerging Frontiers BIO Directorate for Biological Sciences |
Start Date: | June 15, 2011 |
End Date: | May 31, 2017 (Estimated) |
Total Intended Award Amount: | $235,385.00 |
Total Awarded Amount to Date: | $235,385.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
1350 BEARDSHEAR HALL AMES IA US 50011-2103 (515)294-5225 |
Sponsor Congressional District: |
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Primary Place of Performance: |
1350 BEARDSHEAR HALL AMES IA US 50011-2103 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | MacroSysBIO & NEON-Enabled Sci |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.074 |
ABSTRACT
Because climate and land use strongly affect ecosystems and the services that they provide to society, understanding of both individual factors and their interactions is integral for developing effective environmental management and policy. Cross-scale interactions, wherein a factor at one scale interacts with a factor at another scale, are of particular interest, given their complexity and lack of study. The main goal of this research is to develop tools to measure and understand how climate and land use, by themselves and as interacting factors, affect lake ecosystems across scales of time and space, even as these factors are themselves, changing. Lakes are unique study systems to address questions of cross-scale interactions; for example, agricultural land use in a surrounding lake watershed can interact with the climate of the region in which the lake is located, leading to situations where lakes in different climatic zones may respond differently to similar surrounding environmental inputs, such as nutrient inputs from agricultural land use in their watersheds. This project will identify and measure the most important cross-scale interactions that control lake nutrients and water quality and will be guided by a landscape limnology conceptual framework. A collaborative team from three universities will collect a large dataset on lakes, nutrients, and watersheds, including over 5,000 lake ecosystems in 11 U.S. states spanning up to 30 years. Several new and innovative statistical modeling approaches will be used to detect and model cross-scale interactions, including Bayesian hierarchical modeling (a statistical method for learning and modeling complex relationships in data).
Identifying the conditions or the environments prone to cross-scale interactions is needed to forecast, manage, and restore ecosystems, such as lakes, responding to change operating at local to regional scales. The research framework, design, and analysis of this work provide an innovative approach that has the potential change the conduct of research on large-scale, living systems, beyond the lakes under study. Additionally, because commonly-measured lake water quality variables used in water resource policy will be used in this analysis, results from this project will directly inform state and federal agencies responsible for lake and water management. Finally, several undergraduate, graduate, and post-doctoral researchers will be trained as a result, helping to foster a new generation of biologists with skills in tackling broad-scaled research and policy problems.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
As part of a larger collaborative research effort, our proposal aimed to improve knowledge of cross-scale interactions, which occur when processes operating at different spatial and temporal scales interact to produce potentially novel environmental responses, and how they influence water quality at sub-continental spatial scales. Cross-scale interactions are one of the major knowledge gaps in macrosystems ecology (study of ecological phenomena at regional to continental scales and their interactions with phenomena at other scales), and in this case, limit our understanding of how lake water quality will respond to interacting pressures of human activities, land use, weather patterns, and geology.
To address our research questions, we created the LAGOS-NE database of 50,000 lakes across 17 states in the Northeastern and Midwestern United States, which also contained water quality data on 10,000 of these lakes. This database is one of the largest harmonized datasets on water quality within the United States, thereby allowing water quality predictive models to be developed as functions of various environmental drivers across diverse landscapes at large spatial extents. The database is available through an online data repository, so it is freely-accessible by other researchers, natural resources agencies, policy-makers, and the public, and will help improve understanding of lake water quality responses beyond the life of this project.
In addition to other research efforts conducted by the larger collaboration, researchers here focused largely on how algae respond to nutrients (nitrogen and phosphorus) across large spatial extents, how differences in regional landscape characteristics can alter these water quality relationships that are commonly used to manage lakes, and how temporal trends in water clarity have differed across regions. A brief summary of major findings resulting from this research follows.
- Counter to current evidence, high concentrations of nitrogen, in particular nitrate, can produce lakes that have surprisingly low amounts of algae (measured as chlorophyll) and are relatively clearer than would be expected based on nutrient concentrations. High nitrate concentrations may lead to the accumulation of reactive oxygen species that burst algae cells in the water column, thereby increasing water clarity.
- This threshold relationship between chlorophyll and nitrogen was not widespread in agricultural regions of the Midwestern United States, but was limited to two of the most intense agricultural regions studied that had some of the highest nitrogen levels. Although nitrogen stress effects on phytoplankton were rare, interactions among land use, weather patterns, and hydrogeology will likely make these relationships more common in the future.
- Across diverse regions, algae abundance (measured as chlorophyll) increased nonlinearly as a function of increasing limiting nutrients (phosphorus) rather than increasing at a constant rate as previously described. Additionally, the form of these relationships varied for different regions, with pasturelands and wetlands influencing the shape of the response curve.
- Across large geographic areas using citizen science data, lakes showed differing temporal trends (increase, decrease, no trend) in water clarity, which is often used as a measure of lake water quality. Although most lakes across eight states did not show changes through time, lakes further south tended to show more negative long-term trends and greater variability within years than northern lakes, and the ability to detect long-term trends was influenced by the duration of monitoring data.
- Environmental factors regulating whether or not lakes were sources or sinks of carbon dioxide to the atmosphere varied by region, with precipitation amount, elevation, and wetland cover having the largest influences. Carbon dioxide levels in lakes were largely influenced by alkalinity and algae where precipitation was low and agriculture was high, whereas they were largely influenced by algae and water color where precipitation and wetlands were high.
Overall, this collaborative research project trained numerous graduate students and post-docs who will serve as the next generation of macrosystems ecologists. Under this contract, one post-doc, who is now in an academic research post, was trained in macrosystems ecology, advanced statistical analyses, and database management, and gained experience leading large interdisciplinary, collaborative research teams. Although no graduate students were formally trained under this contract, project personnel informally trained and frequently worked with graduate students housed at other academic institutions within the larger collaboration. Because our findings can be applied to lake management, we frequently discussed this project with natural resources agencies and lake associations, presented findings at lake management society conferences (such as North American Lake Management Society), and presented research at National Science Foundation Principal Investigator Meetings.
In addition to the LAGOS-NE water quality database, this research generated several supporting research products that are freely-accessible to the ecological research community and the public: 1) computer code (script) to create customizable and reproducible ecological regions from terrestrial, climatic, and freshwater geospatial data to answer macroscale ecology research questions, and 2) dataset of observed and predicted lake depths for 17 states in the Northeastern and Midwestern United States.
Last Modified: 11/08/2017
Modified by: John A Downing
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