林业资源管理 ›› 2019›› Issue (5): 113-120.doi: 10.13466/j.cnki.lyzygl.2019.05.018
慕晓炜1(), 闫平1, 徐健楠1, 陈平2(
), 曹新光2
收稿日期:
2019-08-02
修回日期:
2019-10-21
出版日期:
2019-10-28
发布日期:
2020-09-18
通讯作者:
陈平
作者简介:
慕晓炜(1984-),男,吉林长春人,工程师,主要从事林业规划设计方面的工作。 Email: 基金资助:
MU Xiaowei1(), YAN Ping1, XU Jiannan1, CHEN Ping2(
), CAO Xinguang2
Received:
2019-08-02
Revised:
2019-10-21
Online:
2019-10-28
Published:
2020-09-18
Contact:
CHEN Ping
摘要:
蓝光强度是一种新的反映树轮密度的指标,自2002年提出以来,由于其操作简便且可能提供木质素密度的信息,在重建北半球高纬度、高海拔地区夏季气温变化方面展现出巨大潜力。对蓝光强度的原理和试验方法进行了概述,并对国外蓝光强度研究所取得的进展进行总结。通过对其存在的几个亟待解决的问题及现有的解决方案的论述,进一步明确蓝光强度的研究潜力,尤其是针对在国内开展蓝光强度研究的可能性进行了探讨。
中图分类号:
慕晓炜, 闫平, 徐健楠, 陈平, 曹新光. 树木年轮蓝光强度研究进展[J]. 林业资源管理, 2019,(5): 113-120.
MU Xiaowei, YAN Ping, XU Jiannan, CHEN Ping, CAO Xinguang. Research Progress on Blue Intensity of Tree Rings[J]. FOREST RESOURCES WANAGEMENT, 2019,(5): 113-120.
[1] | Sheppard P R. Overcoming extraneous wood color variation during low-magnification reflected-light image analysis of conifer tree rings[J]. Wood and fiber science:journal of the Society of Wood Science and Technology, 1999,31(2):106-115. |
[2] | Schweingruber F H, Fritts H C, Braker O U, et al. The X-ray technique as applied to dendrochronology[J]. Tree-ring Bulletin, 1978,38:61-91. |
[3] |
Mccarroll D, Pettigrew E, Luckman A. Blue Reflectance Provides a Surrogate for Latewood Density of High-latitude Pine Tree Rings[J]. Arctic Antarctic and Alpine Research, 2002,34(4):450-453.
doi: 10.1080/15230430.2002.12003516 |
[4] | Sheppard P R, Alex W. An advancement in removing extraneous color from wood for low-magnification reflected-light image analysis of conifer tree rings[J]. Wood & Fiberence, 2007,39(1):173-183. |
[5] |
Wilson R, Rohit R, Rydval M, et al. Blue Intensity for dendroclimatology:The BC blues:A case study from British Columbia,Canada[J]. The Holocene, 2014,8:1-11.
doi: 10.1191/095968398670905088 |
[6] |
Wilson R, Wilson D, Rydval M, et al. Facilitating tree-ring dating of historic conifer timbers using Blue Intensity[J]. Journal of Archaeological Science, 2016,78:99-111.
doi: 10.1016/j.jas.2016.11.011 |
[7] |
Rydval M, Larsson L, Laura M, et al. Blue intensity for dendroclimatolog:Should we have the blues?Experiments from Scotland[J]. Dendrochronologia, 2014,32(3):191-204.
doi: 10.1016/j.dendro.2014.04.003 |
[8] | Mauricio F, Björklund J, Seftigen K, et al. A comparison between Tree-Ring Width and Blue Intensity high and low frequency signals from Pinus sylvestris L.from the Central and Northern Scandinavian Mountains[J]. TRACE-Tree Rings in Archaeology,Climatology and Ecology, 2016,14:38-43. |
[9] |
Campbell R, McCarroll D, Neil J L, et al. Blue intensity in Pinus sylvestris tree-rings:developing a new palaeoclimate proxy[J]. The Holocene, 2007,17(6):821-828.
doi: 10.1177/0959683607080523 |
[10] | Babst F, Frank D, Büntgen U, et al. Effect of sample preparation and scanning resolution on the Blue Reflectance of Picea abies[J]. TRACE-Tree Rings in Archeology,Climatology and Ecology, 2009,7:189-195. |
[11] |
Björklund J A, Gunnarson B E, Seftigen K, et al. Blue intensity and density from northern Fennoscandian tree rings,exploring the potential to improve summer temperature reconstructions with earlywood information[J]. Climate of the Past, 2014,10(2):877-885.
doi: 10.5194/cp-10-877-2014 |
[12] |
Björklund J A, Gunnarson B E, Seftigen K, et al. Using adjusted Blue Intensity data to attain high-quality summer temperature information:A case study from Central Scandinavia[J]. The Holocene, 2015,25(3):547-556.
doi: 10.1177/0959683614562434 |
[13] |
Mccarroll D, Mervi T, Campbell R, et al. A critical evaluation of multi-proxy dendroclimatology in northern Finland[J]. Journal of Quaternary Science, 2011,26(1):7-14.
doi: 10.1002/jqs.1408 |
[14] | Österreicher A, Weber G, Leuenberger M, et al. Exploring blue intensity-comparison of blue intensity and MXD data from Alpine spruce trees[J]. TRACE-Tree Rings in Archaeology,Climatology and Ecology, 2015,13:56-61. |
[15] |
Rydval M, Gunnarson B E, Loader N J, et al. Spatial reconstruction of Scottish summer temperatures from tree rings[J]. International Journal of Climatology, 2016.
doi: 10.1002/joc.4326 pmid: 27478303 |
[16] |
Dolgova E. June-September temperature reconstruction in the Northern Caucasus based on blue intensity data[J]. Dendrochronologia, 2016,39:17-23.
doi: 10.1016/j.dendro.2016.03.002 |
[17] | Rydval M, Neil J L, Björn E G, et al. Reconstructing 800 years of summer temperatures in Scotland from tree rings[J]. Climate Dynamics, 2017,49(9):3478-3486. |
[18] | Fuentes M, Riikka S, Jesper B, et al. A 970-year-long summer temperature reconstruction from Rogen,west-central Sweden,based on blue intensity from tree rings[J]. The Holocene, 2017,28(2):1-13. |
[19] |
Wilson R, Rosanne D, Laia A, et al. Experiments based on blue intensity for reconstructing North Pacific temperatures along the Gulf of Alaska[J]. Climate of the Past, 2017,13(8):1007-1022.
doi: 10.5194/cp-13-1007-2017 |
[20] |
Babst F, Wright W E, Szejner P, et al. Blue intensity parameters derived from Ponderosa pine tree rings characterize intra-annual density fluctuations and reveal seasonally divergent water limitations[J]. Trees, 2016,30(4):1403-1415.
doi: 10.1007/s00468-016-1377-6 |
[21] |
Buckley B M, Kyle G H, Kevin L G, et al. Blue intensity from a tropical conifer’s annual rings for climate reconstruction:An ecophysiological perspective[J]. Dendrochronologia, 2018,50:10-22.
doi: 10.1016/j.dendro.2018.04.003 |
[22] |
Arbellay E, Ingrid J, Raphaёl D C, et al. Tree-ring proxies of larch bud moth defoliation:latewood width and blue intensity are more precise than tree-ring width[J]. Tree Physiology, 2018,38:1237-1245.
doi: 10.1093/treephys/tpy057 pmid: 29788327 |
[23] | 黎韦水, 符韵林. 木材心材形成原因和机理研究进展[J]. 陕西林业科技, 2017(6):78-83. |
[24] | 吴祥定. 树木年轮与气候变化[M]. 北京: 气象出版社, 1990. |
[25] |
Li Minxiong, Okada N, Fujiwara T, et al. The dendrochronological potential of ten species in the Three Gorges Reservoir region of China[J]. IAWA Journal, 2000,21(2):181-196.
doi: 10.1163/22941932-90000244 |
[26] | 梁先娥. 基于Resistograph数据树木年轮对环境变化的响应[D]. 南京:南京林业大学, 2017. |
[27] |
段建平. 树木年轮密度研究进展[J]. 第四纪研究, 2015,35(5):1271-1282.
doi: 10.11928/j.issn.1001-7410.2015.05.23 |
[1] | 李郊, 王冰, 王晨, 高鹤, 吴辉龙, 郑鑫, 彭华福. 2005—2020年江西省森林碳储量时空变化趋势及影响因素[J]. 林草资源研究, 2024, 0(1): 17-24. |
[2] | 李慧杰, 李婉婷, 王兵, 牛香, 梁咏亮, 李静尧. 宁夏贺兰山国家级自然保护区生态系统服务功能评估[J]. 林草资源研究, 2024, 0(1): 25-33. |
[3] | 郝君, 吕康婷, 胡天祺, 王云阁, 徐刚. 基于机器学习的红树林生物量遥感反演研究[J]. 林草资源研究, 2024, 0(1): 65-72. |
[4] | 丁琦珂, 豆浩, 张二山, 胡传伟, 何静. 郑州市园林绿化树种的含碳率分析[J]. 林草资源研究, 2024, 0(1): 95-101. |
[5] | 史哲瑜, 李自豪. 穿透雨减少对辽西北沙地樟子松树干液流的影响[J]. 林草资源研究, 2023, 0(6): 137-145. |
[6] | 曹聪, 郭泽鑫, 郭彦青, 莫燕卿, 刘萍. 基于地理加权回归模型的珠三角森林碳储量空间分布[J]. 林草资源研究, 2023, 0(6): 98-104. |
[7] | 刘艳, 牛香, 王兵. 罗霄山区近25年生境质量时空演变及预测[J]. 林草资源研究, 2023, 0(6): 39-51. |
[8] | 钱慧, 张超, 范金明, 邓再春, 朱夏力, 李成荣. 基于改进CASA模型的云南省植被NPP时空格局分析[J]. 林草资源研究, 2023, 0(6): 120-128. |
[9] | 朱子丞, 戚春林, 杨小波, 李东海, 苏凡. 鹦哥岭野茶群落物种组成与竞争关系研究[J]. 林草资源研究, 2023, 0(6): 129-136. |
[10] | 吴庭天, 陈毅青, 陈宗铸, 雷金睿, 陈小花, 李苑菱. 海南热带雨林代表性种群空间分布特征研究[J]. 林草资源研究, 2023, 0(5): 133-141. |
[11] | 连子文, 黄荣伟, 杜虎, 曾馥平, 彭晚霞, 尹力初. 广西不同林龄软阔林细根碳氮磷化学计量和储量特征[J]. 林草资源研究, 2023, 0(5): 72-79. |
[12] | 高珊珊, 谌玉洁, 海新权. 基于Meta分析的庆阳子午岭森林生态系统服务价值评估[J]. 林草资源研究, 2023, 0(5): 80-88. |
[13] | 刘鑫, 黄浪, 卿东升, 李建军. 基于Voronoi空间单元的林分空间结构智能优化研究[J]. 林业资源管理, 2023, 0(4): 27-35. |
[14] | 李仲牧, 聂恺宏, 田登娟, 刘胜红, 鲁赛, 李根前. 中国沙棘早衰人工林不同构件碳氮磷生态化学计量特征[J]. 林业资源管理, 2023, 0(4): 62-70. |
[15] | 李思颖, 郭昊天, 陈晓蔚, 周梦丽, 靳姗姗, 闫东锋. 栓皮栎人工林土壤有机碳空间分布特征及其影响因素[J]. 林业资源管理, 2023, 0(4): 80-89. |
阅读次数 | ||||||
全文 |
|
|||||
摘要 |
|
|||||