Evaluation of a Resource Allocation Model for Regulation of Litter Decomposition

分解是一个重要的生态系统过程，导致植物生长所需的营养物质的再循环。大多数现有的分解模型通过测量区域气候和凋落物化学成分来间接预测速率。基于微生物活动实际水平的凋落物腐烂机制模型仍然缺乏。这降低了我们预测生态系统扰动影响的能力，比如全球气候变化。我们将通过评估直接基于微生物产生的参与凋落物分解的酶的分解模型来解决这个问题。我们的模型基于一个可测试的假设，即微生物种群的增长是通过优化细胞外酶的相对产量来实现的，这些酶可以从环境中获得必需的碳(C)和氮(N)。我们提出微生物将根据环境中N化合物的可用性改变产生的(c)获取酶的数量。如果无机N化合物很容易获得，微生物应该分配更多的资源来生产c获取酶。这将导致更大的微生物生长和更快的分解凋落物。如果无机氮供应不足，微生物应该产生更多的有机N获取酶，并分配更少的资源用于获取C化合物。这应该会导致微生物生长减少和垃圾分解。为了评估这一模型，我们将在森林土壤地块上放置装有三种凋落叶的网袋。其中一些地块将分两级施用氮肥。其他的将不会得到氮肥。这将为测试模型提供无机氮可用性的变化范围。在分解过程中，将收集凋落物样品并分析微生物生物量和几种酶的活性，这些酶涉及以有机化合物的形式获得C和N。这些酶的活性将作为微生物资源分配到养分获取的措施。我们的模型的意义在于，它在机制上将氮的可利用性与分解速率联系起来。如果得到验证，它可以促进实地研究中营养限制的评估，并为营养循环建模提供新的信息。这些信息还应提高我们预测森林生态系统对目前在农业和城市地区附近森林中发现的大气氮污染输入的反应的能力。

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.