Decomposition is a vital ecosystem process that results in the recycling of nutrients needed for plant growth. Most existing decomposition models predict rates indirectly form measures of regional climate and litter chemical composition. Mechanistic models of litter decay, based on the actual level of microbial activity, are still lacking. This reduces our ability to predict the effects of ecosystem disturbances such as those anticipated form global climate change. We will address this problem by evaluating a decomposition model based directly on microbial production of enzymes involved in litter breakdown. Our model is based o the testable hypothesis that microbial populations grow by optimizing the relative production of extracellular enzymes that obtain essential carbon (C) and nitrogen (N) from their environment. We propose that microbes will change the amount of (C-acquiring enzymes produced depending on the availability of N compounds in the environment. If inorganic N compounds are easily obtained, microbes should allocate more of their resources to producing C-acquiring enzymes. This should result in grater microbial growth and faster decomposition of litter. If inorganic N is in low supply, microbes should produce more organic N- acquiring enzymes and allocate less resources towards acquiring C compounds. This should result in both reduced microbial growth and decomposition rats for litter. To evaluate this model, we will place mesh bags containing three of types of leaf litter on forest soil plots. Some of these plots will receive N fertilizer at two levels of application. Others will not receive N fertilizer. This will provide a range of variation in inorganic N availability over which to test the model. During decomposition, litter samples will be collected and analyzed for microbial biomass and the activities of several enzymes involved obtaining C and N form organic compounds. These enzyme activities will serve as measures of microbial resource allocation to nutrient acquisition. The significance of our model is that it mechanistically links N availability to decomposition rates. If validated, it may facilitate assessments of nutrient limitation in field studies as well as contribute new information for nutrient cycle modeling. Such information should also improve our ability to predict forest ecosystem responses to inputs of atmospheric N pollution at levels now found in forests near agricultural and urban areas.
