Hill Brian H, Elonen Colleen M, Herlihy Alan T, Jicha Terri M, Serenbetz Gregg
Office of Research and Development, National Health and Environmental Effects Research Laboratory, Mid-Continent Ecology Division, US Environmental Protection Agency, 6201 Congdon Blvd., Duluth, MN 55804, USA.
Department of Fisheries and Wildlife, Oregon State University, Corvallis, OR 97331, USA.
Wetl Ecol Manag. 2018;26(3):425-439. doi: 10.1007/s11273-017-9584-5.
Microbial respiration (R) and ecoenzyme activities (EEA) related to microbial carbon, nitrogen, and phosphorus acquisition were measured in 792 freshwater and estuarine wetlands (representing a cumulative area of 217,480 km) across the continental United States as part of the US EPA's 2011 National Wetland Condition Assessment. EEA stoichiometry was used to construct models for and assess nutrient limitation, carbon use efficiency (CUE), and organic matter decomposition (- ). The wetlands were classified into ten groups based on aggregated ecoregion and wetland type. The wetlands were also assigned to least, intermediate, and most disturbed classes, based on the extent of human influences. Ecoenzyme activity related to C, N and P acquisition, R, CUE, and (- differed among ecoregion-wetland types and, with the exception of C acquisition and (- , among disturbance classes. R and EEA were positively correlated with soil C, N and P content (r = 0.15-0.64) and stoichiometry (r = 0.15-0.48), and negatively correlated with an index of carbon quality (r = - 0.22 to - 0.39). EEA stoichiometry revealed that wetlands were more often P- than N-limited, and that P-limitation increases with increasing disturbance. Our enzyme-based approach for modeling C, N, and P acquisition, and organic matter decomposition, all rooted in stoichiometric theory, provides a mechanism for modeling resource limitations of microbial metabolism and biogeochemical cycling in wetlands. Given the ease of collecting and analyzing soil EEA and their response to wetland disturbance gradients, enzyme stoichiometry models are a cost-effective tool for monitoring ecosystem responses to resource availability and the environmental drivers of microbial metabolism, including those related to global climate changes.
作为美国环境保护局2011年全国湿地状况评估的一部分,在美国大陆的792个淡水和河口湿地(总面积达217,480平方千米)中测量了与微生物碳、氮和磷获取相关的微生物呼吸作用(R)和生态酶活性(EEA)。利用EEA化学计量学构建模型并评估养分限制、碳利用效率(CUE)和有机质分解(-)。这些湿地根据综合生态区域和湿地类型分为十组。根据人类影响程度,湿地还被划分为受干扰最少、中等和最严重的类别。与碳、氮和磷获取、R、CUE以及(-)相关的生态酶活性在生态区域 - 湿地类型之间存在差异,除了碳获取和(-)之外,在干扰类别之间也存在差异。R和EEA与土壤碳、氮和磷含量(r = 0.15 - 0.64)以及化学计量学(r = 0.15 - 0.48)呈正相关,与碳质量指数呈负相关(r = -0.22至 -0.39)。EEA化学计量学表明,湿地中磷限制比氮限制更常见,并且磷限制随着干扰增加而增加。我们基于酶的用于模拟碳、氮和磷获取以及有机质分解的方法,均基于化学计量学理论,为模拟湿地中微生物代谢和生物地球化学循环的资源限制提供了一种机制。鉴于收集和分析土壤EEA的简便性及其对湿地干扰梯度的响应,酶化学计量学模型是监测生态系统对资源可用性响应以及微生物代谢环境驱动因素(包括与全球气候变化相关的因素)的经济有效工具。