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Modeling mechanisms of species effects on soil nitrogen cycling in a California coastal prairie grassland. Corbin, Jeffrey*,1, D'Antonio, Carla2, 1 University of California, Berkeley, CA, USA2 University of California, Santa Barbara, CA, USA ABSTRACT- Over the past two decades, the accelerated pace of species losses and additions to natural ecosystems has fostered interest in the effect of species composition on ecosystem functioning. For many woody species, species effects on soil nitrogen (N) mineralization are largely predictable based on leaf litter quality. Controls over species effects on N cycling for herbaceous species, however, have proven to be more complex. We have tested the effect of species composition on rates of net N mineralization and net nitrification in California coastal prairie grasslands by establishing experimental field plots dominated by three groups of species: native perennial bunchgrasses, exotic annual grasses, and exotic perennial grasses. We hypothesized that, because of differences in litter decomposition and phenology between exotic annual grasses and either group of perennial grasses, plots associated with exotic annual grasses would have significantly faster rates of N cycling. Instead, annual net N cycling rates were actually lower in exotic annual-dominated plots as compared to either native or exotic perennial-dominated plots. We propose that differences in litter quantity play a larger role in the development of species effects than litter quality in these ecosystems, as both native and exotic perennial-dominated plots had greater annual productivity than exotic annual plots. We have parameterized DAYCENT for each species group to test whether N cycling rates change as species traits - particularly productivity and tissue chemistry - change. The application of quantitative ecosystem models to invasion ecology offer the opportunity to investigate when species effects might develop, particularly in the cases of the interactions between species traits and environmental conditions such as soil texture, climatic conditions, or disturbance history that are very difficult to manipulate experimentally. Key words: invasive species, daycent model, ecosystem modeling, grassland |
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