我们的网站为什么显示成这样?

可能因为您的浏览器不支持样式,您可以更新您的浏览器到最新版本,以获取对此功能的支持,访问下面的网站,获取关于浏览器的信息:

|Table of Contents|

基于森林资源清查数据的江西省主要森林类型净生产力研究(PDF)

《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

Issue:
2019年05期
Page:
193-198
Column:
研究简报
publishdate:
2019-09-20

Article Info:/Info

Title:
Study on NPP of main forest types based on national forest inventory data in Jiangxi Province,China
Article ID:
1000-2006(2019)05-0193-06
Author(s):
WU Wenyue YAO Shunbin XU Zhiyang
(East China Inventory and Planning Institute of National Forestry and Grassland Administration,Hangzhou 310019,China)
Keywords:
national forest inventory biomass net primary productivity(NPP) modelling method forest litters mortality Jiangxi Province
Classification number :
S757
DOI:
10.3969/j.issn.1000-2006.201903045
Document Code:
A
Abstract:
【Objective】 The stand net primary productivity(NPP)of the major forest types in Jiangxi Province was estimated based on the National Forest Inventory(NFI)data of 2011 and 2016 to provide a basis for the scientific management of forest resources. 【Method】 Based on the NFI data on Jiangxi Province in 2011 and 2016, at the sample tree level, individual tree biomass, and its growth and dry caustic consumption was calculated using a biomass regression individual tree model, then details were accumulated to the plot level and enlarged to the overall level of arbor layer. Then, the biomass at the shrub and herb layers were estimated based on the biomass at the arbor layer. Finally, the NPP of different forest types was calculated by combining the data estimated at the arbor, shrub and herb layers. 【Result】 Based on the model of individual tree-level biomass, with a comprehensive consideration of the effect of the arbor, shrub and herb layers, the NPP of the major forest types in Jiangxi Province was estimated from the NFI-repositioned sample tree level. The highest NPP was for mixed broad-leaved forest, followed by mixed coniferous and broad-leaved forest and then coniferous and single broad-leaved forest. The results showed that the average stand NPP in Jiangxi Province was 7.28 t/(hm2·a)during the interval, with mixed broad-leaved forest having the maximum NPP [11.26 t/(hm2·a)],mixed coniferous and broad-leaved forest having the second NPP[7.63 t/(hm2·a)],but coniferous and single broad-leaved forest lower than the average NPP. 【Conclusion】 This study explored a NPP estimation schema in the framework of national standards and provides a reference for more accurate and objective calculation of NPP based on major forest types in a large range of area by adopting unified standards nationwide.

References

[1] 戴尔阜, 李双元, 吴卓, 等.中国南方红壤丘陵区植被净初级生产力空间分布及其与气候因子的关系: 以江西省泰县为例[J]. 地理研究, 2015, 34(7): 1222-1234. DOI:10.11821/dlyj201507003. DAI E F, LI S Y, WU Z, et al. Spatial pattern of net primary productivity and its relationship with climatic factors in Hilly Red Soil Region of southern China: a case study in Taihe County, Jiangxi Province[J]. Geographical Research, 2015, 34(7): 1222-1234.
[2] HÄRKÖNEN S, PULKKINEN M, DUURSMA R, et al. Estimating annual GPP, NPP and stem growth in Finland using summary models[J]. Forest Ecology and Management, 2010, 259(3): 524-533. DOI:10.1016/j.foreco.2009.11.009.
[3] HÄRKÖNEN S, LEHTONEN A, EERIKÄINEN K, et al. Estimating forest carbon fluxes for large regions based on process-based modelling, NFI data and Landsat satellite images[J]. Forest Ecology and Management, 2011, 262(12): 2364-2377. DOI:10.1016/j.foreco.2011.08.035.
[4] LENIA N, DOMIN GOS L, REGO C, et al. Aboveground biomass and net primary production of pine, oak and mixed pine-oak forests on the Vila Real District, Portugal[J]. Forest Ecology and Management, 2013, 305: 38-47. DOI:10.1016/j.foreco.2013.05.034. [5] 李文华. 森林生物生产量的概念及其研究的基本途径[J]. 自然资源, 1978(1): 71-92.
[6] 方精云,刘国华,徐嵩龄. 我国森林植被的生物量和净生产量[J]. 生态学报, 1996, 16(5): 497-508. FANG J Y, LIU G H, XU S L. Biomass and net production of forest vegetation in China[J]. Acta Ecologica Sinica, 1996, 16(5): 497-508.
[7] 高艳平, 潘明亮, 丁访军, 等. 贵州西部光皮桦天然次生林生物量和净生产力的研究[J]. 中南林业科技大学学报, 2012, 32(4): 55-60. DOI:10.14067/j.cnki.1673-923x.2012.04.029. GAO Y P, PAN M L, DING F J, et al. Study on biomass and net productivity of natural secondary forests of Betula luminifera in west Guizhou[J]. Journal of Central South University of Forestry & Technology, 2012, 32(4): 55-60.
[8] 李海奎, 雷渊才. 中国森林植被生物量和碳储量评估[M]. 北京: 中国林业出版社, 2010.
[9] 李明泽, 王斌, 范文义, 等. 东北林区净初级生产力及大兴安岭地区林火干扰影响的模拟研究[J]. 植物生态学报, 2015, 39(4): 322-332. DOI:10.17521/cjpe.2015.0031. LI M Z, WANG B, FAN W Y, et al. Simulation of forest net primary production and the effects of fire disturbance in Northeast China[J]. Chinese Journal of Plant Ecology, 2015, 39(4): 322-332.
[10] 李登秋, 张春华, 居为民, 等. 江西省森林净初级生产力动态变化特征及其驱动因子分析[J]. 植物生态学报, 2016, 40(7): 643-657. DOI:10.17521/cjpe.2015.0348. LI D Q, ZHANG C H, JU W M, et al. Forest net primary productivity dynamics and driving forces in Jiangxi Province, China[J]. Chinese Journal of Plant Ecology, 2016, 40(7): 643-657.

[12] 曾伟生, 陈新云, 蒲莹, 等. 基于国家森林资源清查数据的不同生物量和碳储量估计方法的对比分析[J]. 林业科学研究, 2018, 31(1): 66-71. DOI:10.13275/j.cnki.lykxyj.2018.01.008. ZENG W S, CHEN X Y, PU Y, et al. Comparison of different methods for estimating forest biomass and carbon storage based on national forest inventory data[J]. Forest Research, 2018, 31(1): 66-71.
[12] HÄRKÖNEN S, NEUMANN M, MUES V, et al. A climate-sensitive forest model for assessing impacts of forest management in Europe[J]. Environmental Modelling & Software, 2019, 115: 128-143. DOI:10.1016/j.envsoft.2019.02.009.
[13] CRAMER W, KICKLIGHTER D W, BONDEAU A, et al. Comparing global models of terrestrial net primary productivity(NPP): overview and key results[J]. Global Change Biology, 1999, 5(S1): 1-15. DOI:10.1046/j.1365-2486.1999.00009.x.
[14] 朴世龙, 方精云, 郭庆华. 1982—1999年我国植被净第一性生产力及其时空变化[J]. 北京大学学报(自然科学版), 2001, 37(4): 563-569. DOI:10.13209/j.0479-8023.2001.102. PIAO S L, FANG J Y, GUO Q H. Terrestrial net primary production and its spatio-temporal patterns in China during 1982: 1999[J]. Acta Scicentiarum Naturalum Universitis Pekinesis, 2001, 37(4): 563-569.
[15] 国家林业局.立木生物量模型及碳计量参数——杉木:LY/T 2264—2014[S].北京:中国标准出版社,2015.
[16] 国家林业局.立木生物量模型及碳计量参数——马尾松:LY/T 2263—2014[S].北京:中国标准出版社,2015.
[17] 国家林业局.立木生物量模型及碳计量参数——湿地松:LY/T 2261—2014[S].北京:中国标准出版社,2015.
[18] 国家林业局.立木生物量模型及碳计量参数——栎树:LY/T 2658—2016[S].北京:中国标准出版社,2017.
[19] 国家林业局.立木生物量模型及碳计量参数——木荷:LY/T 2660—2016[S].北京:中国标准出版社,2017.
[20] 国家林业局.立木生物量模型及碳计量参数——枫香:LY/T 2661—2016[S].北京:中国标准出版社,2017.

[22] 国家林业局.国家林业局关于公布北京等6省(区、市)2016年森林资源清查主要结果的通知[EB/OL].(2017-01-15).www.forestry.gov.cn/main/72/content-936008.html.,2017.
[22] 李海奎,赵鹏祥,雷渊才,等.基于森林清查资料的乔木林生物量估算方法的比较[J].林业科学,2012,48(5):44-52.DOI:10.11707/j.1001-7488.20120507. LI H K,ZHAO P X,LEI Y C,et al.Comparison on estimation of wood biomass using forest inventory data[J].Scientia Silvae Sinicae,2012,48(5):44-52.
[23] 曾伟生.基于木材密度的34个树种组一元立木生物量模型建立[J].林业资源管理,2017(12):41-46.DOI:10.13466/j.cnki.lyzygl.2017.06.008. ZENG W S.Developing one-variable individual tree biomass models based on wood density for 34 tree species in China[J].Forest Resources Management,2017(12):41-46.
[24] 冯宗炜,王效科,吴刚.中国森林生态系统的生物量和生产力[M].北京:科学出版社,1999.
[25] 王斌,刘某承,张彪.基于森林资源清查资料的森林植被净生产量及其动态变化研究[J].林业资源管理,2009(1):35-43.DOI:10.13466/j.cnki.lyzygl.2009.01.008. WANG B,LIU M C,ZHANG B.Dynamics of net production of Chinese forest vegetation based on forest inventory data[J].Forest Resources Management,2009(1):35-43.
[26] 国家林业局.国家森林资源连续清查数据处理统计规范:LY/T 1957—2011[S].北京:中国标准出版社,2011.
[27] 罗天祥, 赵士洞. 中国杉木林生物生产力格局及其数学模型[J]. 植物生态学报, 1997, 21(5): 403-415. LUO T X,ZHAO S D.Patterns and mathematical models of Chinese-fir productivity in China[J]. Chin J Plan Ecolo, 1997, 21(5): 403-415.

Last Update: 2019-10-08