Impact of ecosystem management on microbial community level physiological profiles of postmining forest rehabilitation
Impact of ecosystem management on microbial community level physiological profiles of postmining forest rehabilitation
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DOI：
10.1007/s00248-007-9278-2
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发表时间：
2008-02-01
影响因子：
3.6
通讯作者：
Murphy, D. V.
中科院分区：
文献类型：
--
作者：
Cookson, W. R.;O'Donnell, A. J.;Murphy, D. V.
我们调查了森林间伐，规定的火，和轮廓采伐群落水平的生理剖面（CLPP）的土壤微生物种群在采矿后森林恢复的影响。我们假设，这些管理措施会影响CLPP通过对土壤有机质的质量和数量的影响。研究地点是Jarrah（Eucalyptus marginata Donn ex Sm.）恢复12年前开采铝土矿的森林。在2003年4月（秋季）未处理的森林和从3，000 - 8，000茎/公顷（-1）间伐到600 - 800茎/公顷（-1）的森林中建立三个重复样地（20 × 20 m），随后在2003年9月（春季）进行规定的火灾或保持未燃烧。2004年8月，从两个土壤深度（0 - 5厘米和5 - 10厘米）以及采矿后等高松土造成的土丘和犁沟内采集了土壤样本。火烧迹地土壤pH值、有机碳、全碳和全氮含量均高于未火烧迹地，粗、细凋落物质量低于未火烧迹地，但火烧迹地对CLPP的影响不明显。然而，CLPP的影响，森林间伐，细枯落物质量，土壤C/N比，土壤pH值，这都是在变薄比非变薄的地块。垄沟土壤粗、细枯落物质量、无机磷（P）、有机磷（P）、有机碳（C）、全碳（C）、全氮（N）、铵态氮（NH4+）、微生物生物量碳（C）含量均高于丘耕地，但土壤pH值和土壤C/N比低于丘耕地。土壤pH值、无机磷、有机磷、有机碳、全碳、全氮、铵态氮和微生物生物量碳含量随深度的增加而降低，而土壤C/N比随深度的增加而增加。CLPP的差异在很大程度上（94%）与葡萄糖酸、苹果酸（未间伐土壤比间伐土壤和土堆比犁沟土壤更大）、L-酒石酸、琥珀酸和尿酸（间伐土壤比未间伐土壤、土堆比犁沟土壤和5 - 10 cm土壤比0 - 5 cm土壤更大）的相对利用有关。氨基酸的相对利用率随土壤全碳和有机碳含量的增加而增加，随硝酸盐含量的增加而降低，而羧酸的相对利用率则相反。只有45%的变异CLPP解释使用多元多元回归模型，但土壤C和N库和凋落物质量显着预测CLPP。处理之间的土壤质地成分的差异也与CLPP，这些差异的可能原因进行了讨论。我们的研究结果表明，1年后的治疗，CLPP从这个矿山森林生态系统是弹性的春天规定的火灾，但不是森林间伐。我们的结论是，CLPP的差异很可能是由于复杂的相互作用，介导基质的可用性，微生物营养需求，和微生物群落组成的土壤特性。
We investigated the impacts of forest thinning, prescribed fire, and contour ripping on community level physiological profiles (CLPP) of the soil microbial population in postmining forest rehabilitation. We hypothesized that these management practices would affect CLPP via an influence on the quality and quantity of soil organic matter. The study site was an area of Jarrah (Eucalyptus marginata Donn ex Sm.) forest rehabilitation that had been mined for bauxite 12 years previously. Three replicate plots (20x20 m) were established in nontreated forest and in forest thinned from 3,000-8,000 stems ha(-1) to 600-800 stems ha(-1) in April (autumn) of 2003, followed either by a prescribed fire in September (spring) of 2003 or left nonburned. Soil samples were collected in August 2004 from two soil depths (0-5 cm and 5-10 cm) and from within mounds and furrows caused by postmining contour ripping. CLPP were not affected by prescribed fire, although the soil pH and organic carbon (C), total C and total nitrogen (N) contents were greater in burned compared with nonburned plots, and the coarse and fine litter mass lower. However, CLPP were affected by forest thinning, as were fine litter mass, soil C/N ratio, and soil pH, which were all higher in thinned than nonthinned plots. Furrow soil had greater coarse and fine litter mass, and inorganic phosphorous (P), organic P, organic C, total C, total N, ammonium, microbial biomass C contents, but lower soil pH and soil C/N ratio than mound soil. Soil pH, inorganic P, organic P, organic C, total C and N, ammonium, and microbial biomass C contents also decreased with depth, whereas soil C/N ratio increased. Differences in CLPP were largely (94%) associated with the relative utilization of gluconic, malic (greater in nonthinned than thinned soil and mound than furrow soil), L-tartaric, succinic, and uric acids (greater in thinned than nonthinned, mound than furrow, and 5-10 cm than 0-5 cm soil). The relative utilization of amino acids also tended to increase with increasing soil total C and organic C contents but decreased with increasing nitrate content, whereas the opposite was true for carboxylic acids. Only 45% of the variance in CLPP was explained using a multivariate multiple regression model, but soil C and N pools and litter mass were significant predictors of CLPP. Differences in soil textural components between treatments were also correlated with CLPP; likely causes of these differences are discussed. Our results suggest that 1 year after treatment, CLPP from this mined forest ecosystem are resilient to a spring prescribed fire but not forest thinning. We conclude that differences in CLPP are likely to result from complex interactions among soil properties that mediate substrate availability, microbial nutrient demand, and microbial community composition.