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Landscape Approaches for Understanding and Managing Lakes

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Landscape Approaches for Understanding and Managing Lakes Landscape approaches for understanding and managing lakes Dr. Kendra Spence Cheruvelil Scottish Freshwater Group 24 October 2013 Making inferences from well‐studied ecosystems Variable Time Lake (data) Making inferences from well‐studied ecosystems Option 1 Lake (data) Making inferences from well‐studied ecosystems Option 1Option 2 Data Making inferences from well‐studied ecosystems Within‐region variability Levy et al. under review Frontiers in Ecology & the Environment Making inferences from well‐studied ecosystems Option 1Option 2 Data Making inferences from well‐studied ecosystems Option 1OptionOption 2 3 Data Data Data Data Data What do we need to make better inferences? • Conceptual models of relationships across scales • Large datasets ‐ Multi‐scaled, multi‐themed • Robust modeling approaches for multi‐scaled data Conceptual Underpinning: Landscape limnology The spatially explicit study of lakes, streams, and wetlands as they interact with freshwater, terrestrial, and human landscapes to determine the effects of pattern on ecosystem processes across temporal and spatial scales www.fw.msu.edu/~LLRG From left to right: Patricia Soranno, Kendra Spence Cheruvelil, Katherine Webster, Mary Tate Bremigan Soranno et al. 2010 BioScience Conceptual Underpinning: Landscape limnology HydrologyPrecipitation Geomorph.Glacial history HumanPrecipitation Climate-Atm Freshwater state or response across space and time (ecosystem variation) Conceptual Underpinning: Landscape limnology Hydrology Geomorph. Human Climate-Atm Precipitation Glacial history Precipitation Runoff Geology Runoff Catchment Groundwater morph. Groundwater Drainage Soils Drainage network network Ecosystem Riparian Ecosystem morph. char. morph. Scale and hierarchy Scale and Freshwater state or response across space and time (ecosystem variation) Conceptual Underpinning: Landscape limnology Hydrology Geomorph. Human Climate-Atm Precipitation Glacial history Precipitation Runoff Geology Runoff Catchment Groundwater morph. Groundwater Drainage Soils Drainage network network Ecosystem Riparian Ecosystem morph. char. morph. Scale and hierarchy Scale and Freshwater state or response across space and time (ecosystem variation) Conceptual Underpinning: Landscape limnology Patch connectivity Patch context Hydrology Geomorph. Human Climate-Atm Precipitation Glacial history Precipitation Runoff Geology Runoff Catchment Groundwater morph. Groundwater Drainage Soils Drainage network network Ecosystem Riparian Ecosystem morph. char. morph. Scale and hierarchy Scale and Freshwater state or response across space and time (ecosystem variation) Conceptual model Regional‐scale Driver Driver drivers: Local‐scale Driver Driver Driver drivers: Lake state or response Soranno et al. In press. Frontiers in Ecology & the Environment Conceptual model Regional‐scale Driver Driver drivers: Local‐scale Driver Driver Driver drivers: Lake state or response CSI = Process occurring at one scale interacting with process at another scale (Peters et al. 2007 Ecosystems) Soranno et al. In press. Frontiers in Ecology & the Environment Conceptual model Cross‐scale interactions (CSIs) What do we need to make better inferences? • Conceptual models of relationships across scales • Large datasets ‐ Multi‐scaled, multi‐themed • Robust modeling approaches for multi‐scaled data Case Study: BIG data across scales Local: Lake watershed Watershed Lake Soranno et al. In press. Frontiers in Ecology & the Environment Case Study: BIG data across scales Regional: Ecological Drainage Units Cheruvelil et al. 2013 Ecological Applications; Soranno et al. In press. FEE Case study: Testing for CSIs Q: Does regional agriculture affect local wetland relationships with lake phosphorus? http://michpics.wordpress.com/2009/12/19/michigan‐farming‐and‐other‐success‐stories/ http://www.visitusa.com/maine Mid‐west US region Northeast US region Case study: Conceptual model % Lake Drain. % % Local: wetlands GW depth ratio Agric Urban Lake phosphorus (~2,000 lakes) Case study: Conceptual model Cross‐scale interaction between regional agriculture and local wetlands % Regional: Agric % Lake Drain. % % Local: wetlands GW depth ratio Agric Urban Lake phosphorus (~2,000 lakes) Case study: Study lakes & data n = 1,790 lakes N = 23 regions * * Ecological Drainage Units Case study: Multilevel mixed effect models Fixed‐Effect Random‐ Random‐ Intercept Intercept & Slope Grand mean P slope P P Lake Lake Lake Wetland % Wetland % Wetland % Emi Fergus Case study: Multilevel mixed effect models Random‐Intercept & Slope P on P the effect of Lake Slopes wetland Wetland % Regional agriculture (%) Case study: Results CSI: Regional agriculture modifies the relationship between local wetlands and lake P 0.9 LOW regional agric.: P Wetlands have POS effect slope on 0.4 TP ‐ 0 the effect ‐0.1 of wetland differences ‐0.6 HIGH regional agric.: Wetlands have NEG effect Slopes wetland 2 Regional r = 0.62 ‐1.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 RegionalRegional Agriculture Agriculture (proportion) Case study: Results Wetland and lake P relationships are affected by regional context Low regional agriculture High regional agriculture Making inferences from well‐studied ecosystems What about time? NSF‐MSB Project: The effects of cross‐scale interactions on freshwater ecosystem state www.CSI‐limnology.org C. Filstrup, K. Webster, K. Spence Cheruvelil, E. Norton Henry, N. Lottig, E. Stanley, J. Downing, C.E. Fergus, P‐N. Tan, P. Soranno, C. Stow, E. Bissell, T. Kratz, S. Oliver, S. Yuan, L. Winslow, E. Erdman. (missing, M. Tate Bremigan, T. Wagner, P. Hanson) not in order of appearance! Lagos A geospatial database of all lakes >4 ha ~60,000 total lakes ~ 15,000 lakes with nutrient data Lagos ‐ Lake datasets with >20 yrs of data Summary: Landscape approaches for understanding and managing lakes • Develop conceptual models – Landscape limnology • Compile multi‐scaled, multi‐themed databases ‐ Lagos • Test for CSIs – Hierarchical models (Bayesian) Soranno et al. In Press. Frontiers in Ecology and the Environment Summary: Landscape approaches “across the pond” • Understanding variation in biota among lakes at different scales (Scotland, UK, EU) • Making better inferences GLOBO Lakes, UK Lake Hydromorphology Typology (Rowan 2010) • Building capacity and training high‐ performance research teams Creating and maintaining high‐performing collaborative research teams: the importance of diversity and interpersonal skills Lead PA Soranno KC Weathers PC Hanson KS Cheruvelil SJ Goring CT Filstrup EK Read Cheruvelil et al. In press. Frontiers in Ecology and the Environment How can you make great research teams? Diversity Interpersonal skills Team Team functioning communication Research outcomes • Generation/publication of transformative knowledge • Creation of new high‐performing teams • Translation to sound management, conservation and policy • Innovative training and education • Effective public engagement Cheruvelil et al. In press. Frontiers in Ecology and the Environment Acknowledgements Award# EF‐1065786 STRIVE AWARD: EPA‐2011‐W‐FS‐7 More Qs? Email me! Kendra Spence Cheruvelil [email protected].
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