Multiscale Interactions betweenWater and Carbon Fluxes and Environmental Variables in A Central U.S. Grassland

Abstract

Abstract:The temporal interactions between water and carbon cycling and the controlling environmental variables are investigated using wavelets and information theory. We used 3.5 years of eddy covariance station observations from an abandoned agricultural field in the central U.S. Time-series of the entropy of water and carbon fluxes exhibit pronounced annual cycles, primarily explained by the modulation of the diurnal flux amplitude by other variables, such as the net radiation. Entropies of soil moisture and precipitation show almost no annual cycle, but the data were collected during above average precipitation years, which limits the role of moisture stress on the resultant fluxes. We also investigated the information contribution to resultant fluxes from selected environmental variables as a function of time-scale using relative entropy. The relative entropy of latent heat flux and ecosystem respiration show that the radiation terms contribute the most information to these fluxes at scales up to the diurnal scale. Vapor pressure deficit and air temperature contribute to the most information for the gross primary productivity and net ecosystem exchange at the daily time-scale. The relative entropy between the fluxes and soil moisture illustrates that soil moisture contributes information at approximately weekly time-scales, while the relative entropy with precipitation contributes information predominantly at the monthly time-scale. The use of information theory metrics is a relatively new technique for assessing biosphere-atmosphere interactions, and this study illustrates the utility of the approach for assessing the dominant time-scales of these interactions.

On the ecohydrology of the Yucatan Peninsula: Evapotranspiration and carbon intake dynamics across an eco‐climatic gradient

“…ET and carbon intakes are two highly coupled fluxes that provide information about productivity and ecosystem dynamics. However, in this study, and similar to other works, these fluxes respond differently among ecosystems and are tightly controlled by vegetation phenology and environmental and climatic factors (Brunsell & Wilson, ; Newman et al, ). Commonly, the rates of these fluxes are estimated at small scales and the spatial variation of vegetation productivity and ET in precipitation‐controlled ecosystem is rarely estimated.…”

“…It is well known that evapotranspiration (ET) and the assimilation of atmospheric CO 2 by vegetation (gross primary productivity [GPP]) are two tightly coupled processes that together regulate the productivity of ecosystems through photosynthesis and their exchanges of water and energy fluxes with the atmosphere (Brunsell & Wilson, 2013;Ferguson & Veizer, 2007;Law et al, 2002;Wang & Dickinson, 2012). In the YP, these two processes respond accordingly to ecosystem phenology that are mainly controlled by a clear climatic gradient going from a drier west-north-west to a wetter east-south-east (Gondwe, Lerer, et al, 2010).…”

Identifying scale‐emergent, nonlinear, asynchronous processes of wetland methane exchange

“…The robustness of information metrics to nonlinearity and asynchrony has already improved our understanding of the feedback network of processes influencing CO 2 and H 2 O exchange across ecosystems [ Ruddell and Kumar , , ] and the sensitivity and dynamics of biosphere‐atmosphere exchange to climate variability [ Kumar and Ruddell , ; Ruddell et al ., ]. Despite these benefits, combining wavelets and information theory to understand multiscale eco‐atmosphere interactions is rare, and thus far has only been applied to terrestrial upland sites [ Brunsell and Anderson , ; Brunsell and Wilson , ; Brunsell et al ., ]. To our knowledge, multiscale information theory analysis has not yet been leveraged to interpret measurements of whole‐ecosystem wetland methane exchange.…”

The sensitivity of carbon exchanges in Great Plains grasslands to precipitation variability

“…Arguably, the different scales over which climate and grassland processes interact and feed back on each other makes it difficult to attribute ongoing ecosystem processes to specific climate forcings [Laio et al, 2002;Austin et al, 2004;Teuling et al, 2006;Brunsell and Gillies, 2003;Brunsell and Wilson, 2013]. For example, total annual precipitation may correlate to grassland vegetation productivity over long time periods and across large spatial areas [Sala et al, 1988;Epstein et al, 1996;Tieszen et al, 1997], yet variability in precipitation forcings at shorter timescales and at local (<10 km 2 ) spatial scales has a large influence on grassland productivity as well [Harper et al, 2005;Vermeire et al, 2009;Brunsell and Wilson, 2013;Byrne et al, 2013]. In these grasslands, ecosystem C dynamics are a valuable way to investigate how climate forcings influence grassland processes because they approximate the combined magnitude of ecosystem processes as a single variable [Zhang et al, 2010[Zhang et al, , 2011.…”