Land use, land cover changes, and ecosystem-specific management practices are increasingly recognized for their roles in mediating the climatic effects on ecosystem structure and function. As demonstrated by some scholars, human activities can influence C fluxes and storage far more than climatic changes (IPCC 2014).
Our understanding and forecasting of ecosystem C fluxes cannot rely solely on conventional biophysical regulations at any scale, from the local ecosystem to the globe. We must quantify the magnitude of the C fluxes from managed ecosystems and landscapes over the lifetime of the C cycle and deduct the various energy inputs during management from the amount of C sequestered by an ecosystem (West & Marland 2003). For example, conventional crop management often includes tillage, fertilization, irrigation, applications of pesticides and herbicides, harvesting, transportation to the market, land conversion, etc. All of these activities require a CO2-equivalent (CO2eq) amount of energy (“social C flux”) to offset the actual amount of C sequestered by the ecosystems and landscapes. A complete life cycle assessment (LCA) is needed to account for the actual sequestration strength at different spatial and temporal scales.
Our overall objective is to quantify the landscape-scale C fluxes at annual scale of both managed agricultural-forest landscapes and people, using the Kalamazoo watershed in southwestern Michigan as our testbed.
Questions to be answered
- (1) What are the quantitative contributions of land cover change, specific management practices, and climate changes (means and extremes) to the social and physical C fluxes of managed ecosystems and landscapes?
- (2) What are the spatial and temporal changes of their contributions in managed agricultural-forest landscapes?
- (3) How will future land use changes (including alternative management practices) impact C sequestration in an upper, mid-latitude managed ecosystem?
- March 20, 2017: Annual Legislative Breakfast hosted by the Kalamazoo Environmental Council.
- May-July 2017: Five flux towers can be found across the Kalamazoo Watershed representing urban, marsh, forest, and agricultural land.
- July 10, 2017:
Changes in land cover type across the Kalamazoo Watershed (Landsat 30m resolution data) demonstrate the increasing rates of urbanization and from 1996 to 2011. Credit: Rong Zhang
Our overarching hypothesis is that social C flux is more responsible than physical C flux for the dynamics, and especially the uncertainty, of the cumulative CO2eq production of these intensively-managed landscapes. However, their proportions vary significantly among the landscapes and over history because of the great variations in land conversions, land use practices, climatic changes and extremes in the watershed.
Figure 1. (above) Proposed research components and their linkages for process-based predictions of the spatiotemporal changes in CO2eq production that will be quantified by estimating “social C flux”, and “physical C flux” at contrasting landscapes (i.e., different land cover compositions) within the Kalamazoo Watershed as well as the entire watershed (Fig. 2, below).
Life cycle assessment (LCA) will be employed for major patch types to quantify the C production at different temporal scales. The statistical downscaling modeling will be used to predict future local climate from Representative Concentration Pathways scenarios. Bayesian structural equation models (SEM) will be constructed to explore the contributions of climate change and human activities.
Figure 2. (above) Current land cover of the Kalamazoo Watershed (NLCD), which includes 127 sub-watersheds (USGS). The entire watershed will be examined for the changes of CO2eq during a 40-year period (1978–2018) using Landsat/Sentinel with the climate and human activities following our working framework (Fig. 1), while four contrasting landscapes will be quantified with high-resolution RS data and historical records and survey statistics over an 80-year period (1938–2018).
Task 1: Dynamics of Physical C Fluxes
Quantify the changes of the physical C flux on an annual scale, which will be converted to CO2eq, by integrating: (1) remotely-sensed land cover type and other surface properties; (2) geospatial records of climate, vegetation, soil, and management practices for model parameterization; (3) direct measurements of net ecosystem exchange of CO2 using EC flux towers for model validation; and (4) a customized ecosystem model (i.e. CLM).
Task 2: Dynamics of Social C Fluxes
Estimate the social C fluxes of major management practices for different land cover types by classifying historical land cover, identifying land ownership, and by surveying historical management practices of individual land-owners (parcel scale). Back-of-the-envelope calculations will be applied to scale up the CO2eq fluxes to the landscapes and the watershed.
Task 3: The dynamics and the regulations of CO2eq in time and space
Diagnose the mechanistic/empirical causal relationships based on biophysical models and SEM, and to quantify the ecosystem, landscape, and watershed C fluxes at multiple temporal scales and under alternative management/climate scenarios.
In alliance with NASA, our researchers openly share their data with the broader community. The latest information and resources from our project can be found here for exploration and education.
Data use policy
Use of this data is for non-profit, personal, or educational use only. To publish this data or apply it in other for-profit endeavours, please contact Dr. Jiquan Chen for information. For help interpreting the data, contact the author listed. Information provided here does not conflict with our committment to confidentiality or expose personal information from survey participants.
- Eddy-Covariance Flux Data
- Geospatial and Remote Sensing Data
- Socio-Economic Carbon Data
- Community Land Model Data
- Background Information Database
- Lei, C., M. Abraha, Y.J. Su, and J. Chen. Variability of root production in bioenergy systems using ingrowth cores and eddy covariance. Journal of Plant Ecology (Submitted August 2018)
- Reed, D. Multiple Resource Use Efficiency (mRUE) In Agriculture Systems. Conference on Agricultural and Forest Meteorology, May 2018, Boise, ID, USA.
- Shirkey, G., P. Sciusco, R. John, D. Reed, K. O'Brien, L. Cooper, J. Chen, K. Dahlin. Integrating historical land cover and land management in Michigan’s Kalamazoo Watershed: a story of carbon flux impact.Great Lakes Bioenergy Research Center Annual Science Meeting Poster Session, May 2018, Lake Geneva, WI, USA.
- Shirkey, G. Implementing an agricultural Life Cycle Assessment (LCA) at the regional scale in southwest Michigan. Global Change and Agroecosystems: Challenges and Opportunities Poster Session, January 2018, East Lansing, MI, USA.
- Chen, J., K. Dahlin, R. John, G. Shirkey, S. R. Wu, P. Robertson, S. Hamilton, L. Cooper, D. Lusch, and A. Karnieli, R. Lafortezza, and G. S. Labini. Socioecological Carbon Production in Managed Agricultural-Forest Landscapes. 2017 Joint NACP & AmeriFlux PI Meeting, March 27-30, 2017, North Bethesda, MD, USA.
- Chen, J., K. Dahlin, R. John, G. Shirkey, S. R. Wu, P. Robertson, S. Hamilton, L. Cooper, D. Lusch, and A. Karnieli, R. Lafortezza, and G. S. Labini. Socioecological Carbon Production in Managed Agricultural-Forest Landscapes. Worldcover 2017 Conference, 14–16 March 2017, Rome, Italy.
- Dahlin, K. Resolution and the Carbon Cycle: Spatial, temporal, and spectral variation in ecosystems. Invited seminar for the Wayne State University Department of Biological Sciences. Nov. 13, 2017.
- Chen, J. Institution in Ecosystem Analysis: A Forgotten Driver. Distinguished Ecologist Lecture Series (DELS), School of Forest Resources and Environmental Science, Michigan Tech University, Oct. 26, 2017.
Download graduate position details Two PhD opportunities are available. Those interested in applying should contact Dr. Jiquan Chen with your CV, GRE scores, TOEFL (if applicable), and experience for more information.
|Dr. Jiquan Chen||Professor, PI
Michigan State University
|Dr. Kyla Dahlin||Assistant Professor, Co-PI
Michigan State University
|Dr. Ranjeet John||Research Associate, Co-PI
Michigan State University
|Dr. Phil Robertson||Collaborator
Kellogg Biological Station (GLBRC)
|Dr. Steve Hamilton||Collaborator
Kellogg Biological Station (LTER)
|Dr. David Lusch||Collaborator, RS/GIS
Michigan State University
|Lauren Cooper||Collaborator, Forest Climate Program Michigan State Universityfirstname.lastname@example.org|
|Dr. Arnon Karnieli||CollaboratorBen Gurion University, Israelemail@example.com|
|Giovanni Sylos Labini||Collaborator Planetek, Italy||website|
|Rong Zhang||Collaborator Michigan State University||zhangr38msu.edu|
|Dr. David Reed||Postdoctoral Research Associate Michigan State Universityfirstname.lastname@example.org|
|Gabriela Shirkey||MS Student Michigan State Universityemail@example.com|
|Ryan Nagelkirk||PhD Student Michigan State Universityfirstname.lastname@example.org|
|Kaitlyn O'Brien||Undergraduate Student Michigan State Universityemail@example.com|
|Tina Guo||Undergraduate Student Michigan State Universityfirstname.lastname@example.org|
|Connor Crank||Research Technologist Michigan State Universityemail@example.com|
|Cheyenne Lei||PhD Student Michigan State Universityfirstname.lastname@example.org|
|Zutao Ouyang||Postdoctoral Research Associate Michigan State University|