Modeling in situ soil enzyme activity using continuous field soil moisture and temperature data

Moisture and temperature are key drivers of soil organic matter decomposition, but there is little consensus on how climate change will affect the degradation of specific soil compounds under field conditions. Soil enzyme activities are a useful metric of soil community microbial function because they are they are the direct agents of decomposition for specific substrates in soil. However, current standard enzyme assays are conducted under optimized conditions in the laboratory and do not accurately reflect in situ enzyme activity, where diffusion and substrate availability may limit reaction rates. The Arrhenius equation, k= A*e(-Ea/RT), can be used to predict enzyme activity (k), collision frequency (A) or activation energy (Ea), but is difficult to parameterize when activities are measured under artificial conditions without diffusion or substrate limitation. We developed a modifed equation to estimate collision frequency and activation energy based on soil moisture to model in-situ enzyme activites. Our model was parameterized using data we collected from the Boston Area Climate Experiment (BACE) in Massachusetts; a multi-factor climate change experiment that provides an opportunity to assess how changes in moisture availability and temperature may impact enzyme activity. Soils were collected from three precipitation treatments and four temperature treatments arranged in a full-factorial design at the BACE site in June 2008, August 2008, January 2009 and June 2009. Enzyme assays were performed at four temperatures (4, 15, 25 and 35°C) to calculate temperature sensitivity and activation energy over the different treatments and seasons. Enzymes activities were measured for six common enzymes involved in carbon (β-glucosidase, cellobiohydrolase, xylosidase), phosphorus (phosphatase) and nitrogen cycling (N-acetyl glucosaminidase, and leucine amino peptidase). Potential enzyme activity was not significantly affected by precipitation, warming or the interaction of the field treatments at any of the dates, however season explained the majority of the variance in enzyme activity for cellobiohydrolase, xylosidase, N-acetyl glucosaminidase and leucine amino peptidase (p<0.01). Changes in seasonal climate appear to have a large effect on enzyme potentials and are likely masking any treatment effects. To model in-situ enzyme activities over the course of a year, daily measurements collected on soil moisture and temperature were used to estimate the collision frequency and activation energy. Our results suggest that collision frequency is largely affected by soil moisture and activation energy affected by soil temperature. Thus, soil enzyme activities are controlled not only by the size of the enzyme pool, but are also strongly affected by temperature and by moisture. Currently, there are no suitable technologies to measure in-situ activities in real-time, but we can make progress in understanding the ecology of enzymes through the combination of lab assays, field sensors, and modeling.