Assessing Resilience of Intensively Managed Landscapes through Feedbacks
Abstract
Intensively managed landscapes such as those of the United States agricultural Midwest are hypothesized to be on a different trajectory than natural landscapes in terms of ecosystem processes and landscape evolution. Process networks provide a method to analyze system states as patterns of couplings and feedbacks. It has been shown using FLUXNET data that variables such as precipitation, soil temperature, soil moisture, latent heat flux, and net ecosystem exchange may exhibit synchronized relationships, time-lagged forcing behavior, or feedbacks. The strength of these couplings weakens or breaks down with environmental extremes such as drought. This study compares couplings in measured fluxes observed using a process network approach with couplings of modeled ecohydrological variables. MLCan is a multi-layer canopy-air exchange model that uses FLUXNET tower climate and flux data as input to simulate leaf uptake, stomatal conductance, photosynthesis, soil hydrology, and other descriptors of ecosystem state. This model has been used to assess vegetation acclimation to climate change, altered hydrology due to biofuel crops, and root hydraulic redistribution in different ecosystems. For this study, MLCan is used to simulate conditions for the 2005 growing season at the location of the Bondville, IL flux tower. A process network is defined with nodes representing key measured and simulated variables including streamflow at a nearby gage, precipitation, radiation, soil moisture, leaf uptake, and nutrient fluxes. Couplings are identified using mutual information and transfer entropy statistics. This study effectively validates whether simulated ecosystem state variables demonstrate information flow to the same extent as measured data. The inclusion of streamflow introduces a spatial element to the process network approach that begins to link processes with topography and land use in the watershed. Analysis of coupling types and strengths can be applied to assess resilience characteristics of intensively managed versus natural landscapes.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2013
- Bibcode:
- 2013AGUFM.H21K..03G
- Keywords:
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- 0402 BIOGEOSCIENCES Agricultural systems;
- 1843 HYDROLOGY Land/atmosphere interactions;
- 1813 HYDROLOGY Eco-hydrology;
- 1872 HYDROLOGY Time series analysis