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Understanding the Central Great Plains as a Coupled Climatic-Hydrological-Human System: Lessons Learned in Operationalizing Interdisciplinary Collaboration

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Collaboration Across Boundaries for Social-Ecological Systems Science

Abstract

This chapter discusses an interdisciplinary and transdisciplinary project to understand the interactions of agriculture, climate, and water resources in the Central Great Plains as a coupled natural-human system. We focus on the Smoky Hills Watershed in Kansas, where we gathered socioeconomic, hydrological, and climatic data, along with ecological data on fish species. The project involved substantial stakeholder engagement, which was complicated by post-truth attitudes about climate science and environmental regulation by some groups. We discuss the challenges of team management, stakeholder engagement, and data integration for modeling, notably the incorporation of stakeholder support for environmental policy in the context of extreme climatic events. We conclude by offering a framework for good collaborative practice to manage the complications of crossing boundaries in transdisciplinary research and outreach.

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References

  • Albright, E. A. (2011). Policy Change and Learning in Response to Extreme Flood Events in Hungary: An Advocacy Coalition Approach. Policy Studies Journal, 39(3), 485–511. https://doi.org/10.1111/j.1541-0072.2011.00418.x.

    Article  Google Scholar 

  • Arnold, J. G., Srinivasan, R., Muttiah, R. S., & Williams, J. R. (1998). Large Area Hydrologic Modeling and Assessment Part I: Model Development. Journal of the American Water Resource Association, 34, 73–89. https://doi.org/10.1111/j.1752-1688.1998.tb05961.x.

    Article  Google Scholar 

  • Arnold, J. G., Youssef, M. A., Yen, H., et al. (2015). Hydrological Processes and Model Representation: Impact of Soft Data on Calibration. Transactions of the ASABE, 58, 1637–1660. https://doi.org/10.13031/trans.58.10726.

    Article  Google Scholar 

  • Baron, J. S., Poff, N. L., Angermeier, P. L., Dahm, C. N., Gleick, P. H., Hairston, N. G., Jr., et al. (2002). Meeting Ecological and Societal Needs for Freshwater. Ecological Applications, 12, 1247–1260.

    Article  Google Scholar 

  • Caldas, M. M., Sanderson, M. R., Mather, M., Daniels, M. D., Bergtold, J. S., Aistrup, J. A., et al. (2015). Opinion: Endogenizing Culture in Sustainability Science Research and Policy. Proceedings of the National Academy of Science, 112(27), 8157–8159.

    Article  Google Scholar 

  • Campbell, S. W., Szuwalski, S., Tabor, V. M., & deNoyelles, F. (2016). Challenges to Reintroduction of a Captive Population of Topeka Shiner (Notropis topeka) into Former Habitats in Kansas. Transactions of the Kansas Academy of Science, 119(1), 83–92.

    Article  Google Scholar 

  • Cardinale, B. J. (2011). Biodiversity Improves Water Quality Through Niche Partitioning. Nature, 472, 86–89.

    Article  Google Scholar 

  • Chatterjee, S., Daniels, M., Sheshukov, A., & Gao, J. (2018). Projected Climate Change Impacts on Hydrologic Flow Regimes in the Great Plains of Kansas. River Research Applications, 34, 195–206.

    Article  Google Scholar 

  • Chave, J. (2013). The Problem of Pattern and Scale in Ecology: What Have We Learned in 20 Years? Ecology Letters, 16, 4–16.

    Google Scholar 

  • Dawson, T. P., Jackson, S. T., House, J. I., Prentice, I. C., & Mace, G. M. (2011). Beyond Predictions: Biodiversity Conservation in a Changing Climate. Science, 332, 53–58.

    Article  Google Scholar 

  • Feld, C. K., Sousa, J. P., Martins da Silva, P., & Dawson, T. P. (2010). Indicators for Biodiversity and Ecosystem Services: Towards an Improved Framework for Ecosystems Assessment. Biodiversity and Conservation, 19, 2895–2919.

    Article  Google Scholar 

  • Fleishman, E., Noss, R., & Noon, B. (2006). Utility and Limitations of Species Richness Metrics for Conservation Planning. Ecological Indicators, 6, 543–553.

    Article  Google Scholar 

  • Frank, H. J., Mather, M. E., Muth, R. M., Pautzke, S. M., Smith, J. M., & Finn, J. T. (2009). The Adopt-a-Herring Program as a Fisheries Conservation Tool. Fisheries, 34, 496–507.

    Article  Google Scholar 

  • Gao, J., Sheshukov, A. Y., Yen, H., & White, M. (2017a). Impacts of Alternative Climate Information on Hydrologic Processes with SWAT: A Comparison of NCDC, PRISM and NEXRAD Datasets. CATENA, 156, 353–364. https://doi.org/10.1016/j.catena.2017.04.010.

    Article  Google Scholar 

  • Gao, J., Sheshukov, A., Yen, H., Kastens, J., & Peterson, D. (2017b). Impacts of Incorporating Dominant Crop Rotation Patterns as Primary Land Use Change on Hydrologic Model Performance. Agriculture, Ecosystems & Environment, 247, 33–42.

    Article  Google Scholar 

  • Gleick, P. H. (1996). Water Resources. In S. H. Schneider (Ed.), Encyclopedia of Climate and Weather (Vol. 2, pp. 817–823) New York: Oxford University Press.

    Google Scholar 

  • Gleick, P. H. (1998). Water in Crisis: Paths to Sustainable Water Use. Ecological Applications, 8, 571–579.

    Article  Google Scholar 

  • Goodin, G., Mitchell, J., Knapp, M., & Bivens, R. E. (1995). Climate and Weather Atlas of Kansas. Lawrence, USA: Kansas Geological Survey.

    Google Scholar 

  • Hooper, D. U., Chapin I, F. S., Ewel, J. J., Hector, A., Inchausti, P., Lavorel, S., et al. (2005). Effects of Biodiversity on Ecosystem Functioning: A Consensus of Current Knowledge. Ecological Monographs, 75, 3–35.

    Google Scholar 

  • Laurila-Pant, M., Lehikoinen, A., Uusitalo, L., & Venesjärvi, R. (2015). How to Value Biodiversity in Environmental Management? Ecological Indicators, 55, 1–11.

    Article  Google Scholar 

  • Levin, S. A. (1992). The Problem of Pattern and Scale in Ecology. Ecology, 73(6), 1943–1967.

    Google Scholar 

  • Loreau, M., Naeem, S., Inchausti, P., Bengtsson, J., Grime, J. P., Hector, A., et al. (2001). Biodiversity and Ecosystem Functioning: Current Knowledge and Future Challenges. Science, 294, 804–808.

    Article  Google Scholar 

  • Malmqvist, B., & Rundle, S. (2002). Threats to the Running Water Ecosystems of the World. Environmental Conservation, 29, 134–153.

    Article  Google Scholar 

  • Mankin, K. R., Barnes, P. L., Harner, J. P., Kalita, P. K., & Boyer, J. E. (2006). Field Evaluation of Vegetative Filter Effectiveness and Runoff Quality from Unstocked Feedlots. Journal of Soil and Water Conservation, 61(4), 209–217.

    Google Scholar 

  • Nohrstedt, D., & Nyberg, L. (2015). Do Floods Drive Hazard Mitigation Policy? Evidence from Swedish Municipalities. Geografiska Annaler: Series A, Physical Geography, 97(1), 109–122. https://doi.org/10.1111/geoa.12081.

    Article  Google Scholar 

  • Peck, J. C. (1986). Groundwater Management Institutions in Kansas. Journal of Irrigation and Drainage Engineering, 112(3). https://ascelibrary.org/doi/10.1061/%28ASCE%290733-9437%281986%29112%3A3%28203%29.

  • Pinto, R., de Jonge, V. N., & Marques, J. C. (2014). Linking Biodiversity Indicators, Ecosystem Functioning, Provision of Services and Human Well-Being in Estuarine Systems: Application of a Conceptual Framework. Ecological Indicators, 36, 644–655.

    Article  Google Scholar 

  • Postel, L. (2000). Entering an Era of Water Scarcity: The Challenges Ahead. Ecological Applications, 10, 941–948.

    Article  Google Scholar 

  • Prato, T. (1999). Multiple Attribute Decision Analysis for Ecosystem Management. Ecological Economics, 30(2), 207–222.

    Article  Google Scholar 

  • Sanderson, M. R., Bergtold, J. S., Stamm, J. L. H., Caldas, M. M., & Ramsey, S. M. (2017). Bringing the ‘Social’ into Sociohydrology: Conservation Policy Support in the Central Great Plains of Kansas, USA. Water Resources Research, 53(8), 6725–6743.

    Google Scholar 

  • Smith, J. M., & Mather, M. E. (2012). Using Assemblage Data in Ecological Indicators: A Comparison and Evaluation of Commonly Available Statistical Tools. Ecological Indicators, 13, 253–262.

    Article  Google Scholar 

  • Stern, P. C. (2000). Toward a Coherent Theory of Environmentally Significant Behavior. Journal of Social Issues, 56(3), 407–424.

    Article  Google Scholar 

  • Stern, P. C., Dietz, T., & Guagnano, G. A. (1995). The New Ecological Paradigm Is Social-Psychological Context. Environmental Behavior, 27(6), 723–743.

    Article  Google Scholar 

  • Summerfelt, R. C. (1967). Fishes of the Smoky Hill River, Kansas. Transactions of the Kansas Academy of Science, 70(1), 102–139.

    Article  Google Scholar 

  • Tilman, D., Wedin, D., & Knops, J. (1996). Productivity and Sustainability Influenced by Biodiversity in Grassland Ecosystems. Nature, 379, 718–720.

    Article  Google Scholar 

  • Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R., & Polasky, S. (2002). Agricultural Sustainability and Intensive Production Practices. Nature, 418, 671–677.

    Article  Google Scholar 

  • Tuppad, P., Douglas-Mankin, K. R., & McVay, K. A. (2010). Strategic Targeting of Cropland Management Using Watershed Modeling. Agricultural Engineering International: A CIGR Journal, 12(3), 12–24.

    Google Scholar 

  • U.S. Department of the Interior, U.S. Fish and Wildlife Service, and U.S. Department of Commerce, U.S. Census Bureau. (2016). National Survey of Fishing, Hunting, and Wildlife-Associated Recreation.

    Google Scholar 

  • Vörösmarty, C. J., Green, P., Salisbury, J., & Lammers, R. B. (2000). Global Water Resources: Vulnerability from Climate Change Acid Population Growth. Science, 289, 284–288.

    Article  Google Scholar 

Download references

Acknowledgements

This research was funded by the National Science Foundation (NSF #1313815 Dynamics of Coupled Natural and Human Systems). Errors of interpretation and otherwise are the responsibility of the authors. The Kansas Cooperative Fish and Wildlife Research Unit is a joint effort among Kansas State University, the U.S. Geological Survey, U.S. Fish and Wildlife Service, the Kansas Department of Wildlife, Parks, and Tourism (KDWPT), and the Wildlife Management Institute.

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Authors and Affiliations

  1. Department of Geography, Kansas State University, Manhattan, KS, USA

    Marcellus Caldas

  2. Division of Biology, Kansas State University, U.S. Geological Survey, Kansas Cooperative Fish and Wildlife Research Unit, Manhattan, KS, USA

    Martha Mather & David Haukos

  3. Department of Agricultural Economics, Kansas State University, Manhattan, KS, USA

    Jason Bergtold

  4. Stroud Water Center, Avondale, PA, USA

    Melinda Daniels

  5. Department of Geography and Anthropology, California State Polytechnic University, Pomona, CA, USA

    Gabriel Granco

  6. College of Liberal Arts, Auburn University, Auburn, AL, USA

    Joseph A. Aistrup

  7. Department of Biological and Agricultural Engineering, Kansas State University, Manhattan, KS, USA

    Aleksey Y. Sheshukov

  8. Department of Sociology, Anthropology, and Social Work, Kansas State University, Manhattan, KS, USA

    Matthew R. Sanderson

  9. Department of Industrial and Manufacturing Systems Engineering, Kansas State University, Manhattan, KS, USA

    Jessica L. Heier Stamm

Authors
  1. Marcellus Caldas
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  2. Martha Mather
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  3. Jason Bergtold
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  4. Melinda Daniels
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  5. Gabriel Granco
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  6. Joseph A. Aistrup
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  7. David Haukos
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  8. Aleksey Y. Sheshukov
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  9. Matthew R. Sanderson
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  10. Jessica L. Heier Stamm
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Corresponding author

Correspondence to Marcellus Caldas .

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Editors and Affiliations

  1. Department of Sociology and Criminology and Law, University of Florida, Gainesville, FL, USA

    Stephen G. Perz

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Caldas, M. et al. (2019). Understanding the Central Great Plains as a Coupled Climatic-Hydrological-Human System: Lessons Learned in Operationalizing Interdisciplinary Collaboration. In: Perz, S. (eds) Collaboration Across Boundaries for Social-Ecological Systems Science. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-13827-1_8

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  • DOI: https://doi.org/10.1007/978-3-030-13827-1_8

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  • Publisher Name: Palgrave Macmillan, Cham

  • Print ISBN: 978-3-030-13826-4

  • Online ISBN: 978-3-030-13827-1

  • eBook Packages: Social SciencesSocial Sciences (R0)

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