- 1.
北京林业大学林学院,北京 100083
- 2.
山西省太原国有林场,山西 太原 030003
- 3.
河北省塞罕坝机械林场,河 围场 068466
基金项目:“十三五”国家重点研发计划(2016YFD0600205(/div>
详细信息
常旭。主要研究方向:森林资源监测与评价。Email9a href="//www.inggristalk.com/j/article/doi/10.12171/mailto:837378159@qq.com">837378159@qq.com 地址?00083 北京市海淀区清华东?5号北京林业大学林学院
彭道黎,教授。主要研究方向:森林资源监测与评价、林业遥感与信息技术、森林经营理论与技术。Email9a href="//www.inggristalk.com/j/article/doi/10.12171/mailto:dlpeng@bjfu.edu.cn">dlpeng@bjfu.edu.cn 地址:同三/span>
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出版历程
- 收稿日期:2021-05-17
- 修回日期:2021-06-21
- 网络出版日期:2021-07-22
- 刊出日期:2021-08-31
Soil fertility quality evaluation of pure and mixedLarix principis-rupprechtiiforests in Saihanba, Hebei Province of northern China
- 1.
School of Forestry, Beijing Forestry University, Beijing 100083, China
- 2.
Taiyuan State-Owned Forest Farm of Shanxi Province, Taiyuan 030003, Shanxi, China
- 3.
Saihanba Mechanized Forest Farm of Hebei Province, Weichang 068466, Hebei, China
摘要:
目的基于土壤质量指数(SQI),研究华北落叶松林不同混交方式对土壤肥力质量的影响,为其合理经营和地力恢复提供理论依据、/sec>
方法该研究以河北省塞罕坝林场华北落叶松纯林(落叶松纯林)、华北落叶松白桦混交林(落桦混交林)和华北落叶松樟子松混交林(落樟混交林)为研究对象,采集和分析0 ~ 20 cm土层的土壤进行土壤理化性质、生物性质的调查研究,利用SQI法进行土壤肥力质量评价。建立SQI包括3个步骤:采用主成分分析法筛选最小数据集(MDS),利用非线性得分函数计算MDS指标得分,利用加权求和模型计算SQI、/sec>
结果不同混交方式间土壤理化和生物性质存在不同程度的差异。与落叶松纯林相比,落桦混交林的土壤理化和生物性质有了明显改善;落樟混交林的土壤理化状况较差,土壤生物性质与落叶松纯林没有明显差异。在17个土壤肥力质量指标中,MDS由土壤微生物生物量氮、全磷、氨?个指标组成。不同混交方式间SQI差异显著,表现为落桦混交林(0.59 > 落叶松纯林(0.47 > 落樟混交林(0.39)、/sec>
结论土壤肥力质量在不同混交方式下差异显著,塞罕坝机械林场落叶松白桦混交林有利于改善土壤肥力。利用指数法建立SQI进行土壤肥力质量评价,可为其他树种或其他地区的森林土壤质量评价提供借鉴、/sec>
Abstract:
ObjectiveIn this study, soil quality index (SQI) was used to evaluate the effects of different mixed modes on soil fertility quality in
Larix principis-rupprechtiiforests, in order to provide theoretical basis for proper management and soil fertility recovery.
MethodThe pure
Larix principis-rupprechtiistands (LP), mixed
Larix principis-rupprechtiiand
Betula platyphyllastands (BL), and mixed
Larix principis-rupprechtiiand
Pinus sylvestrisvar.
mongolicastands (ML) were selected as the research objects in Saihanba Mechanical Forest Farm of Hebei Province, northern China. The soils of 0?0 cm soil depths were collected and analyzed to investigate the soil physicochemical and biological properties. SQI was used to evaluate soil fertility quality. SQI was determined in three steps by selecting a minimum data set (MDS) through principal component analysis, scoring the MDS indicators using non-linear scoring functions, and integrating the indicator scores into a SQI using the weighted additive equation.
ResultThere were different degrees of differences in soil physicochemical and biological properties among different mixed modes. Compared with LP, the soil physicochemical and biological properties of BL were significantly improved. The soil physicochemical conditions in ML were worse than those in LP. And there were no obvious differences in soil biological properties in ML and LP. The MDS consisted of soil microbial biomass nitrogen, total phosphorus, and ammonia nitrogen among 17 soil fertility quality indicators. There were significant differences in the SQI among three mixed modes, which were showed as: BL (0.59) > LP (0.47) > ML (0.39).
ConclusionThe soil fertility quality differed significantly among varied mixed modes. The mixed
Larix principis-rupprechtiiand
Betula platyphyllastands in Saihanba Mechanical Forest Farm can improve soil fertility. Soil fertility quality evaluation based on SQI by indexing approach can provide the basis for evaluating forest soil quality of other species and regions.
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