Landscape approaches for understanding and managing lakes. Dr. Kendra Spence Cheruvelil Scottish Freshwater Group 24 October 2013

Transcription

1 Landscape approaches for understanding and managing lakes Dr. Kendra Spence Cheruvelil Scottish Freshwater Group 24 October 2013

2 Making inferences from well studied ecosystems Variable Time Lake (data)

3 Making inferences from well studied ecosystems Option 1 Lake (data)

4 Making inferences from well studied ecosystems Option 1 Option 2 Data

5 Making inferences from well studied ecosystems Within region variability Levy et al. under review Frontiers in Ecology & the Environment

6 Making inferences from well studied ecosystems Option 1 Option 2 Data

7 Making inferences from well studied ecosystems Option 1 Option 2 Option 3 Data Data Data Data Data

8 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

9 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 From left to right: Patricia Soranno, Kendra Spence Cheruvelil, Katherine Webster, Mary Tate Bremigan Soranno et al BioScience

10 Conceptual Underpinning: Landscape limnology Hydrology Precipitation Geomorph. Glacial history Human Precipitation Climate-Atm Freshwater state or response across space and time (ecosystem variation)

11 Conceptual Underpinning: Landscape limnology Scale and hierarchy Hydrology Precipitation Runoff Groundwater Drainage network Ecosystem morph. Geomorph. Glacial history Geology Catchment morph. Soils Riparian char. Human Precipitation Runoff Groundwater Drainage network Ecosystem morph. Climate-Atm Freshwater state or response across space and time (ecosystem variation)

12 Conceptual Underpinning: Landscape limnology Scale and hierarchy Hydrology Precipitation Runoff Groundwater Drainage network Ecosystem morph. Geomorph. Glacial history Geology Catchment morph. Soils Riparian char. Human Precipitation Runoff Groundwater Drainage network Ecosystem morph. Climate-Atm Freshwater state or response across space and time (ecosystem variation)

13 Conceptual Underpinning: Landscape limnology Patch connectivity Patch context Scale and hierarchy Hydrology Precipitation Runoff Groundwater Drainage network Ecosystem morph. Geomorph. Glacial history Geology Catchment morph. Soils Riparian char. Human Precipitation Runoff Groundwater Drainage network Ecosystem morph. Climate-Atm Freshwater state or response across space and time (ecosystem variation)

14 Conceptual model Regional scale drivers: Driver Driver Local scale drivers: Driver Driver Driver Lake state or response Soranno et al. In press. Frontiers in Ecology & the Environment

15 Conceptual model Regional scale drivers: Driver Driver Local scale drivers: Driver Driver Driver Lake state or response CSI = Process occurring at one scale interacting with process at another scale (Peters et al Ecosystems) Soranno et al. In press. Frontiers in Ecology & the Environment

16 Conceptual model Cross scale interactions (CSIs)

17 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

18 Case Study: BIG data across scales Local: Lake watershed Watershed Lake Soranno et al. In press. Frontiers in Ecology & the Environment

19 Case Study: BIG data across scales Regional: Ecological Drainage Units Cheruvelil et al Ecological Applications; Soranno et al. In press. FEE

20 Case study: Testing for CSIs Q: Does regional agriculture affect local wetland relationships with lake phosphorus? farming and other success stories/ Mid west US region Northeast US region

21 Case study: Conceptual model Local: % wetlands GW Lake depth Drain. ratio % Agric % Urban Lake phosphorus (~2,000 lakes)

22 Case study: Conceptual model Cross scale interaction between regional agriculture and local wetlands Regional: % Agric Local: % wetlands GW Lake depth Drain. ratio % Agric % Urban Lake phosphorus (~2,000 lakes)

23 Case study: Study lakes & data n = 1,790 lakes N = 23 regions * * Ecological Drainage Units

24 Case study: Multilevel mixed effect models Fixed Effect Random Intercept Random Intercept & Slope Lake P Grand mean slope Lake P Lake P Wetland % Wetland % Wetland % Emi Fergus

25 Case study: Multilevel mixed effect models Lake P Random Intercept & Slope Slopes of the wetland effect on P Wetland % Regional agriculture (%)

26 Case study: Results CSI: Regional agriculture modifies the relationship between local wetlands and lake P Regional wetland TP slope differences Slopes of the wetland effect on P r 2 = Regional Agriculture Regional Agriculture (proportion) LOW regional agric.: Wetlands have POS effect HIGH regional agric.: Wetlands have NEG effect

27 Case study: Results Wetland and lake P relationships are affected by regional context Low regional agriculture High regional agriculture

28 Making inferences from well studied ecosystems What about time?

29 NSF MSB Project: The effects of cross scale interactions on freshwater ecosystem state 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!

30 Lagos A geospatial database of all lakes >4 ha ~60,000 total lakes ~ 15,000 lakes with nutrient data

31 Lagos Lake datasets with >20 yrs of data

32 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

33 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 highperformance research teams

34 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

35 How can you make great research teams? Diversity Interpersonal skills Team functioning Team 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

36 Acknowledgements Award# EF STRIVE AWARD: EPA 2011 W FS 7 More Qs? me! Kendra Spence Cheruvelil ksc@msu.edu