Skip navigation

DSpace

機構典藏 DSpace 系統致力於保存各式數位資料(如:文字、圖片、PDF)並使其易於取用。

點此認識 DSpace
DSpace logo
English
中文
  • 瀏覽論文
    • 校院系所
    • 出版年
    • 作者
    • 標題
    • 關鍵字
    • 指導教授
  • 搜尋 TDR
  • 授權 Q&A
    • 我的頁面
    • 接受 E-mail 通知
    • 編輯個人資料
  1. NTU Theses and Dissertations Repository
  2. 理學院
  3. 地理環境資源學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/59734
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor黃倬英(Cho-Ying Huang)
dc.contributor.authorKai-Ting Huen
dc.contributor.author胡愷庭zh_TW
dc.date.accessioned2021-06-16T09:35:22Z-
dc.date.available2022-02-17
dc.date.copyright2017-02-17
dc.date.issued2017
dc.date.submitted2017-02-13
dc.identifier.citationAllen, A., Gillooly, J., & Brown, J. (2005). Linking the global carbon cycle to individual metabolism. Functional Ecology, 19, 202-213
Anderson, J.E., Plourde, L.C., Martin, M.E., Braswell, B.H., Smith, M.-L., Dubayah, R.O., Hofton, M.A., & Blair, J.B. (2008). Integrating waveform lidar with hyperspectral imagery for inventory of a northern temperate forest. Remote Sensing of Environment, 112, 1856-1870
Aragão, L., Malhi, Y., Metcalfe, D., Silva-Espejo, J.E., Jiménez, E., Navarrete, D., Almeida, S., Costa, A., Salinas, N., & Phillips, O.L. (2009). Above-and below-ground net primary productivity across ten Amazonian forests on contrasting soils. Biogeosciences, 6, 2759-2778
Baccini, A., Laporte, N., Goetz, S., Sun, M., & Dong, H. (2008). A first map of tropical Africa’s above-ground biomass derived from satellite imagery. Environmental Research Letters, 3, 045011
Chambers, J.Q., Asner, G.P., Morton, D.C., Anderson, L.O., Saatchi, S.S., Espírito-Santo, F.D., Palace, M., & Souza, C. (2007). Regional ecosystem structure and function: ecological insights from remote sensing of tropical forests. Trends in Ecology & Evolution, 22, 414-423
Chang, S.-C., Tseng, K.-H., Hsia, Y.-J., Wang, C.-P., & Wu, J.-T. (2008). Soil respiration in a subtropical montane cloud forest in Taiwan. Agricultural and Forest Meteorology, 148, 788-798
Chang, S.-C., Yeh, C.-F., Wu, M.-J., Hsia, Y.-J., & Wu, J.-T. (2006). Quantifying fog water deposition by in situ exposure experiments in a mountainous coniferous forest in Taiwan. Forest Ecology and Management, 224, 11-18
Clark, D., Brown, S., Kicklighter, D., Chambers, J., Thomlinson, J., & Ni, J. (2001). MEASURING NET PRIMARY PRODUCTION IN FORESTS: CONCEPTS AND FIELD METHODS. Ecological applications, 11, 356-370
Clark, M.L., Roberts, D.A., Ewel, J.J., & Clark, D.B. (2011). Estimation of tropical rain forest aboveground biomass with small-footprint lidar and hyperspectral sensors. Remote Sensing of Environment, 115, 2931-2942
Coomes, D. A. and Allen, R. B. 2009. Testing the metabolic scaling theory of tree growth. Journal of Ecology, 97, 1369–1373
Coomes, D. A., Lines, E. R., Allen, R. B. (2011). Moving on from metabolic scaling theory: hierarchical models of tree growth and asymmetric competition for light. Journal of Ecology, 99, 748–756
Coomes, D., Duncan, R., Allen, R., & Truscott, J. (2003). Disturbances prevent stem size-density distributions in natural forests from following scaling relationships. Ecology letters, 6, 980-989
Dubayah, R.O., & Drake, J.B. (2000). Lidar remote sensing for forestry. Journal of Forestry, 98, 44-46
Ehleringer, J.R., & Christopher, B. (1993). Scaling physiological processesleaf to globe. In
Enquist, B., West, G., & Brown, J. (2009). Extensions and evaluations of a general quantitative theory of forest structure and dynamics. Proceedings of the National Academy of Sciences of the United States of America, 106, 7046-7051
Enquist, B.J., & Niklas, K.J. (2002). Global allocation rules for patterns of biomass partitioning in seed plants. Science, 295, 1517-1520
Enquist, B.J., Allen, A.P., Brown, J.H., Gillooly, J.F., Kerkhoff, A.J., Niklas, K.J., Price, C.A., & West, G.B. (2007a). Biological scaling: does the exception prove the rule? Nature, 445, E9-10; discussion E10-11
Enquist, B.J., Kerkhoff, A.J., Huxman, T.E., & Economo, E.P. (2007b). Adaptive differences in plant physiology and ecosystem paradoxes: insights from metabolic scaling theory. Global Change Biology, 13, 591-609
Enquist, B.J., Kerkhoff, A.J., Stark, S.C., Swenson, N.G., McCarthy, M.C., & Price, C.A. (2007c). A general integrative model for scaling plant growth, carbon flux, and functional trait spectra. Nature, 449, 218-222
Farquhar, G.v., von Caemmerer, S.v., & Berry, J. (1980). A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta, 149, 78-90
Gates, D.M. (1980). Biophysical ecology, 611 pp. In: Springer, New York
Helliker, B.R., & Richter, S.L. (2008). Subtropical to boreal convergence of tree-leaf temperatures. Nature, 454, 511-514
Hemmingsen, A.M. (1950). The relation of standard (basal) energy metabolism to total fresh weight of living organisms. Rep. Steno Mem. Hosp., 4, 7-58
Huang, C. -M., Duh C. -T., Chang, S. -C., Lin, K. -C. (2012) Estimation of tree biomass and growth of Hinoki stand in Chilanshan area of North-eastern Taiwan. Quarterly Journal of Chinese Forestry 45(2):137-150
Huang, T, -C., 1993-2000. Flora of Taiwan. Editorial Committee of the Flora of Taiwan, Department of Botany, National Taiwan University, Taipei, Taiwan.
Huxley, J.S. (1993). Problems of relative growth.
Johnson, E.A., & Martin, Y.E. (2016). A biogeoscience approach to ecosystems. Cambridge : Cambridge University Press
Kerkhoff, A., & Enquist, B. (2006). Ecosystem allometry: the scaling of nutrient stocks and primary productivity across plant communities. Ecology letters, 9, 419-427
Kerkhoff, A., & Enquist, B. (2007). The Implications of Scaling Approaches for Understanding Resilience and Reorganization in Ecosystems. BioScience, 57, 489
Kerkhoff, A.J., Enquist, B.J., Elser, J.J., & Fagan, W.F. (2005). Plant allometry, stoichiometry and the temperature‐dependence of primary productivity. Global Ecology and Biogeography, 14, 585-598
Kleiber, M. (1932). Body size and metabolism. ENE, 1, E9
Lai, J., Coomes, D.A., Du, X., Hsieh, C.-f., Sun, I.F., Chao, W.-C., Mi, X., Ren, H., Wang, X., Hao, Z., & Ma, K. (2013). A general combined model to describe tree-diameter distributions within subtropical and temperate forest communities. Oikos, 122, 1636-1642
Lefsky, M.A., Cohen, W.B., Harding, D.J., Parker, G.G., Acker, S.A., & Gower, S.T. (2002a). Lidar remote sensing of above-ground biomass in three biomes. Global Ecology and Biogeography, 11, 393-399
Lefsky, M.A., Cohen, W.B., Parker, G.G., & Harding, D.J. (2002b). Lidar Remote Sensing for Ecosystem Studies Lidar, an emerging remote sensing technology that directly measures the three-dimensional distribution of plant canopies, can accurately estimate vegetation structural attributes and should be of particular interest to forest, landscape, and global ecologists. BioScience, 52, 19-30
Levin, S.A. (1992). The problem of pattern and scale in ecology: the Robert H. MacArthur award lecture. Ecology, 73, 1943-1967
Lu, D. (2006). The potential and challenge of remote sensing‐based biomass estimation. International Journal of Remote Sensing, 27, 1297-1328
Luckman, A., Baker, J., Kuplich, T.M., Yanasse, C.d.C.F., & Frery, A.C. (1997). A study of the relationship between radar backscatter and regenerating tropical forest biomass for spaceborne SAR instruments. Remote Sensing of Environment, 60, 1-13
Marquet, P.A., Allen, A.P., Brown, J.H., Dunne, J.A., Enquist, B.J., Gillooly, J.F., Gowaty, P.A., Green, J.L., Harte, J., Hubbell, S.P., O'Dwyer, J., Okie, J.G., Ostling, A., Ritchie, M., Storch, D., & West, G.B. (2014). On Theory in Ecology. BioScience, 64, 701-710
Michaletz, S.T., Cheng, D., Kerkhoff, A.J., & Enquist, B.J. (2014). Convergence of terrestrial plant production across global climate gradients. Nature, 512, 39-43
Muller-Landau, H.C., Condit, R.S., Harms, K.E., Marks, C.O., Thomas, S.C., Bunyavejchewin, S., Chuyong, G., Co, L., Davies, S., Foster, R., Gunatilleke, S., Gunatilleke, N., Hart, T., Hubbell, S.P., Itoh, A., Kassim, A.R., Kenfack, D., LaFrankie, J.V., Lagunzad, D., Lee, H.S., Losos, E., Makana, J.-R., Ohkubo, T., Samper, C., Sukumar, R., Sun, I.F., Nur Supardi, M.N., Tan, S., Thomas, D., Thompson, J., Valencia, R., Vallejo, M.I., Muñoz, G.V., Yamakura, T., Zimmerman, J.K., Dattaraja, H.S., Esufali, S., Hall, P., He, F., Hernandez, C., Kiratiprayoon, S., Suresh, H.S., Wills, C., & Ashton, P. (2006). Comparing tropical forest tree size distributions with the predictions of metabolic ecology and equilibrium models. Ecology letters, 9, 589-602
Nelson, R., Ranson, K., Sun, G., Kimes, D., Kharuk, V., & Montesano, P. (2009). Estimating Siberian timber volume using MODIS and ICESat/GLAS. Remote Sensing of Environment, 113, 691-701
Ni-Meister, W., Lee, S., Strahler, A.H., Woodcock, C.E., Schaaf, C., Yao, T., Ranson, K.J., Sun, G., & Blair, J.B. (2010). Assessing general relationships between aboveground biomass and vegetation structure parameters for improved carbon estimate from lidar remote sensing. Journal of Geophysical Research: Biogeosciences, 115, n/a-n/a
Peters, R.H., & Wassenberg, K. (1983). The effect of body size on animal abundance. Oecologia, 60, 89-96
Price, C. A., Enquist, B. J., & Savage, V. M. (2007). A general model for allometric covariation in botanical form and function. Proceedings of the National Academy of Sciences, 104 (32), 13204-13209
Price, C.A., Gilooly, J.F., Allen, A.P., Weitz, J.S., & Niklas, K.J. (2010). The metabolic theory of ecology: prospects and challenges for plant biology. New Phytologist, 188, 696-710
Rosette, J., Cook, B., Suárez, J., North, P., Nelson, R., & Los, S. (2012). Lidar remote sensing for biomass assessment. INTECH Open Access Publisher
Russo, S. E., Wiser, S. K., & Coomes, D. A. (2007). Growth-size scaling relationships of woody plant species differ from predictions of the metabolic ecology model. Ecology Letters, 10, 889–901
Russo, S. E., Wiser, S. K., Coomes, D. A. (2008). A re-analysis of growth-size scaling relationships of woody plant species. Ecology Letters, 11, 311–312
Savage, V.M. (2004). Improved approximations to scaling relationships for species, populations, and ecosystems across latitudinal and elevational gradients. Journal of Theoretical Biology, 227, 525-534
Schutz, B., Zwally, H., Shuman, C., Hancock, D., & DiMarzio, J. (2005). Overview of the ICESat mission. Geophysical Research Letters, 32
Stark, S. C., Bentley, L. P., Enquist, B. J. (2011). Response to Coomes and Allen (2009) 'Testing the metabolic scaling theory of tree growth’. Journal of Ecology, 99, 741–747
Stegen, J., Swenson, N., Enquist, B., White, E., Phillips, O., J?rgensen, P., Weiser, M., Monteagudo Mendoza, A., & Núñez Vargas, P. (2011). Variation in above-ground forest biomass across broad climatic gradients. Global Ecology and Biogeography, 20, 744-754
Steininger, M. (2000). Satellite estimation of tropical secondary forest above-ground biomass: data from Brazil and Bolivia. International Journal of Remote Sensing, 21, 1139-1157
Stephenson, N.L., Das, A.J., Condit, R., Russo, S.E., Baker, P.J., Beckman, N.G., Coomes, D.A., Lines, E.R., Morris, W.K., Ruger, N., Alvarez, E., Blundo, C., Bunyavejchewin, S., Chuyong, G., Davies, S.J., Duque, A., Ewango, C.N., Flores, O., Franklin, J.F., Grau, H.R., Hao, Z., Harmon, M.E., Hubbell, S.P., Kenfack, D., Lin, Y., Makana, J.R., Malizia, A., Malizia, L.R., Pabst, R.J., Pongpattananurak, N., Su, S.H., Sun, I.F., Tan, S., Thomas, D., van Mantgem, P.J., Wang, X., Wiser, S.K., & Zavala, M.A. (2014). Rate of tree carbon accumulation increases continuously with tree size. Nature, 507, 90-93
Su, Y., Guo, Q., Xue, B., Hu, T., Alvarez, O., Tao, S., & Fang, J. (2016). Spatial distribution of forest aboveground biomass in China: Estimation through combination of spaceborne lidar, optical imagery, and forest inventory data. Remote Sensing of Environment, 173, 187-199
Swatantran, A., Dubayah, R., Roberts, D., Hofton, M., & Blair, J.B. (2011). Mapping biomass and stress in the Sierra Nevada using lidar and hyperspectral data fusion. Remote Sensing of Environment, 115, 2917-2930
Tobin, B., Black, K., Osborne, B., Reidy, B., Bolger, T., & Nieuwenhuis, M. (2006). Assessment of allometric algorithms for estimating leaf biomass, leaf area index and litter fall in different-aged Sitka spruce forests. Forestry, 79, 453-465
West, G., Enquist, B., & Brown, J. (2009). A general quantitative theory of forest structure and dynamics. Proceedings of the National Academy of Sciences of the United States of America, 106, 7040-7045
West, G.B., Brown, J.H., & Enquist, B.J. (1997). A general model for the origin of allometric scaling laws in biology. Science, 276, 122-126
West, G.B., Brown, J.H., & Enquist, B.J. (1999a). The Fourth Dimension of Life: Fractal Geometry and Allometric Scaling of Organisms. Science, 284, 1677
West, G.B., Brown, J.H., & Enquist, B.J. (1999b). A general model for the structure and allometry of plant vascular systems. Nature, 400, 664-667
White, E.P., Enquist, B.J., & Green, J.L. (2008). On estimating the exponent of power-law frequency distributions. Ecology, 89, 905-912
Yang, Y.-S., Chen, G.-S., Guo, J.-F., Xie, J.-S., & Wang, X.-G. (2007). Soil respiration and carbon balance in a subtropical native forest and two managed plantations. Plant Ecology, 193, 71-84
Yen, T. M., Lee, J. S., Hunag, K. L. (2008) Growth and yield models for thinning demonstration zones of Taiwan red cypress (Chamaecyparis formosensis Matsum.) and Japancese cedar (Cryptomeria japonica D. Don) plantations in Central Taiwan. Quarterly Journal of Chinese Forestry 30 (3):31-40
Yoda, K., T. Kira, H. Ogawa, Hozumi K. (1963). Self-thinning in overcrowded pure stands under cultivated and natural conditions. Journal of Biology, 14, 107-129
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/59734-
dc.description.abstract枯落物在森林生態系中是重要的代謝產物,因此了解由冠層進入森林地表之枯落產量,將有助於掌握森林中的養分及碳循環動態。然而,單以現地收集枯落物的方式需要耗費大量人力及時間,且目前本來就為數不多的枯落物模型所需的冠層參數 (例如:冠層厚度、冠層直徑及冠層高),也常不利大面積、頻繁規律地收集。在生態代謝理論中,代謝速率與體型大小比例 (scaling) 關係使我們得以由總體生物量的大小與淨生產量之間的關係推估枯落物產量。相對於直接地測量或間接的模型估算枯落物產量,遙測技術的進步在估森林總體生物量上有較高的效率及準確度,因此以遙測方法所得之森林總生物量後,再推估枯落物產量,更可能全面的了解大範圍森林覆蓋之區域。而透過遙測技術進行的生態系監測通常皆須品質良好準確的地面資料進行經驗模型建立,因此本研究選擇有悠久林業歷史及台灣長期生態樣區之一,且是目前台灣現存最大之檜木林之棲蘭山地區作為研究區,並以已有現成生物量推估公式 (allometric equation) 之檜木 (Chamaecyparis obtusa var. formosana and Chamaecyparis formosensis) 做為目標物種,使用不易於高生物量地區受到飽和作用影響之遙測感測器──光達 (lidar),將其取得之三維樹高模型進行進一步的生物量推估。我們架設了15個樣區共60個0.5 m^2的枯落物網,並測量樣區中共1128顆檜木的胸高斷徑 (diameter at breast height, DBH),依據現地生物量與枯落物的關係為基準,使用生物量進行兩期:非干擾季與颱風干擾季之枯落物推估。兩季之枯落物與樣區內生物量皆有顯著相關 (R2 = 0.75, p < 0.05),且發現隨著樣區內生物量增加,枯落物產量在樣區生物量約大於200 Mg ha-1後反而隨生物量增加而下降。最後我們使用3組現地收集之枯落物資料驗證此枯落物產量地圖並有相當高的相關性 (R2 = 0.98, p < 0.05, RMSE = 23.12 Mg ha^-1 month^-1)。本研究除了可使未來對於枯落物動態不再受限於單點式的推估,能更有效率的了解生態系中物質、養分循環之動態,也提供實證資料討論生態代謝理論中縮放關係 (scaling relationship) 於生態系面臨干擾下之適用性。zh_TW
dc.description.abstractLitterfall plays a crucial role in the carbon and nutrient cycles of forest ecosystems. The amount of litterfall governs the amount of carbon and nutrient to be returned in a forest ecosystem. However, when it comes to quantifying forest litterfall, collection of canopy characteristic parameters for existing litterfall models is usually time-consuming and labor-intensive. Recent studies indicated that, in metabolic scaling theory, there is a common relationship between terrestrial plant production and biomass; a major part of the production is contributed by litterfall. Therefore, there could be a relationship between litterfall and biomass, which could facilitate large spatial scale estimation of litterfall since biomass may be assessed using remote sensing. To investigate this relationship, we acquired monthly litterfall of a hinoki (Chamaecyparis spp.) dominant montane forest in the northeastern Taiwan (23.98 N, 120.97 E) across the elevation range of 1267–2080 m a.s.l. Monthly litterfall data were recorded from fifteen 0.09 ha plots and each plot consisted from four randomly arranged 0.5 m2 litterfall traps. In addition, diameter at breast height of each live hinoki tree (n = 1,128) within all plots was measured and total biomass was derived using an in-situ species-specific allometry. Species-specific hinoki litterfall regression models were developed for two seasons (growing season: March–June, typhoon season: July–October) across a wide range of biomass density. We found that the relationship between biomass and litterfall might depend on the amount of total biomass. In both seasons, increase of litter production with increase of biomass density could be found when biomass is less than about 200 Mg ha-1, after that, inverse relationship appears. With the aid of high spatial resolution airborne light detection and ranging (lidar) data, we may be able to provide a spatial layer of hinoki biomass and map monthly litterfall over a vast region based on this biomass-litterfall relationship. At the end, the litterfall map were verified by three ground truth litterfall measurements with satisfactory results (R2 = 0.98, p < 0.05, RMSE = 23.12 Mg ha^-1 month^-1). Furthermore, the study could facilitate our understanding of the mechanism governing the litter production and improve future prediction of metabolic scaling theory on ecosystem function.en
dc.description.provenanceMade available in DSpace on 2021-06-16T09:35:22Z (GMT). No. of bitstreams: 1
ntu-106-R03228005-1.pdf: 3607474 bytes, checksum: 746a9d74ab16cc5c5130adcd4b1f4b7f (MD5)
Previous issue date: 2017
en
dc.description.tableofcontentsTable of Contents
摘要 i
Abstract ii
Table of Contents iii
List of Figures iv
List of Table vii
1. Introduction 1
2. Literature review 4
2.1 Topic Species 4
2.1.1 Botanical Description 4
2.1.2 Forestry history in Chilan Mountain 5
2.2 Theoretical foundations on MST 6
2.3 Scaling from plant individual traits to ecosystem function 9
2.4 Lidar-based biomass estimation 11
3. Material and Methods 13
3.1 Study Areas 13
3.2 Data Preprocess and Preparation 15
3.2.1 Field Data Acquisition 16
3.2.2 Lidar-derived Canopy Height Model 18
3.3 Hinoki Biomass Mapping 20
3.4 Statistical Analysis 21
3.4.1 Seasonality of Chilan Mountain 21
3.4.2 Regression models 24
4. Results 25
4.1 Litterfall collection 25
4.2 Biomass measurements 28
4.3 Classification of forest cover in Chilan 33
4.4 Biomass map 35
4.5 Relationship between biomass and litter production 40
5. Discussion 46
5.1 Linkage between individual trait and ecosystem flux 46
5.2 “Bent down” curve of the litterfall-biomass relationship 50
5.3 Potential limitation 52
6. Conclusions 53
Reference 55
dc.language.isoen
dc.subject扁柏zh_TW
dc.subject淨初級生產量zh_TW
dc.subject紅檜zh_TW
dc.subject光達zh_TW
dc.subject干擾zh_TW
dc.subject遙測zh_TW
dc.subject碳循環zh_TW
dc.subject淨初級生產量zh_TW
dc.subject扁柏zh_TW
dc.subject紅檜zh_TW
dc.subject光達zh_TW
dc.subject干擾zh_TW
dc.subject遙測zh_TW
dc.subject碳循環zh_TW
dc.subjectChamaecyparis formosensisen
dc.subjectChamaecyparis obtusa var. formosanaen
dc.subjecthinokien
dc.subjectlidaren
dc.subjecthinokien
dc.subjectChamaecyparis formosensisen
dc.subjectdisturbanceen
dc.subjectChamaecyparis obtusa var. formosanaen
dc.subjectlidaren
dc.subjectdisturbanceen
dc.title由生態代謝理論之觀點推估近熱帶山地森林枯落物產量zh_TW
dc.titleA metabolic scaling theory driven approach to estimate litter production in near tropical montane forestsen
dc.typeThesis
dc.date.schoolyear105-1
dc.description.degree碩士
dc.contributor.oralexamcommittee黃誌川(Jr-Chuan Huang),林登秋(Teng-Chiu Lin)
dc.subject.keyword淨初級生產量,扁柏,紅檜,光達,干擾,遙測,碳循環,zh_TW
dc.subject.keywordChamaecyparis obtusa var. formosana,Chamaecyparis formosensis,hinoki,lidar,disturbance,en
dc.relation.page60
dc.identifier.doi10.6342/NTU201700528
dc.rights.note有償授權
dc.date.accepted2017-02-13
dc.contributor.author-college理學院zh_TW
dc.contributor.author-dept地理環境資源學研究所zh_TW
顯示於系所單位:地理環境資源學系

文件中的檔案:
檔案 大小格式 
ntu-106-1.pdf
  未授權公開取用
3.52 MBAdobe PDF
顯示文件簡單紀錄


系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。

社群連結
聯絡資訊
10617臺北市大安區羅斯福路四段1號
No.1 Sec.4, Roosevelt Rd., Taipei, Taiwan, R.O.C. 106
Tel: (02)33662353
Email: ntuetds@ntu.edu.tw
意見箱
相關連結
館藏目錄
國內圖書館整合查詢 MetaCat
臺大學術典藏 NTU Scholars
臺大圖書館數位典藏館
本站聲明
© NTU Library All Rights Reserved