تحلیل پویایی روشنه های تاجی با استفاده از تصاویر هوایی رقومی التراکم و پهپاد در توده های سوزنی برگ دست کاشت عرب داغ استان گلستان

نوع مقاله : مقاله کامل علمی پژوهشی

نویسندگان

1 دانشجوی دکتری ، گروه جنگلداری، دانشکده منابع طبیعی، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری، ایران.

2 استاد، گروه جنگلداری، دانشکده منابع طبیعی، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری، ایران

3 استاد ، گروه جنگلداری، دانشکده علوم جنگل، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران

چکیده

مقدمه و هدف: تحلیل پویایی روشنه‌ها باعث ایجاد درک صحیحی از روند پویایی توده جنگلی می‌شود که نقش مهمی در آینده مدیریتی بوم‌سازگان جنگل دارد. در مطالعه حاضر به بررسی پویایی روشنه‌ها در جنگلکاری‌های‌عرب داغ استان گلستان با استفاده از داده‌های سنجش ‌از دور هوایی در یک دوره زمانی 9 ساله می‌پردازد.
مواد و روش‌ها: شناسایی و تهیه نقشه روشنه‌ها با روش طبقه‌بندی شی‌‌ء پایه انجام شد. طبقه‌بندی شی‌‌ء پایه در سه مرحله کلی قابل انجام است که شامل قطعه‌بندی، طبقه‌بندی و ارزیابی صحت طبقه‌بندی می‌باشد. در مرحله بعد، 1345 روشنه در سال 1390 و 1058 روشنه در سال 1399، از بهترین نقشه روشنه استخراج گردید. خصوصیات روشنه‌ها در هر مقطع زمانی به دست آمد. همچنین با تلاقی این دو نقشه، پویایی روشنه‌ها از طریق محاسبه مشخصه‌های نرخ شکل‌گیری روشنه، نرخ بسته‌شدن روشنه‌، نرخ گسترش روشنه، نرخ کاهش روشنه و نرخ افزایش لگاریتمی تعداد روشنه تحلیل گردید.
یافته‌ها: نتایج در بازه زمانی 9 ساله نشان داد که تعداد و تراکم روشنه‌ها کاهش یافت؛ اما میانگین مساحت روشنه‌ها و سهم مساحت روشنه‌ها از مساحت کل افزایش یافت. در هر دو مقطع زمانی 65 درصد روشنه‌ها مساحت کمتر از 150 مترمربع دارند و روشنه‌های بزرگ (بزرگ‌تر از 300 مترمربع) کمترین فراوانی و سهم از مساحت کل روشنه‌ها را پوشش دادند بیشترین نرخ تغییرات روشنه‌ها مربوط به نرخ گسترش روشنه‌های اولیه بوده است (09/1 درصد در سال). نرخ بسته شدن با نرخ کاهش روشنه‌های اولیه تقریبا برابر است. کمترین نرخ تغییرات روشنه‌ها را نرخ شکل‌گیری روشنه (77/0 درصد در سال) تشکیل داده است. نرخ افزایش لگاریتمی تعداد روشنه‌ها منفی بوده است (6/2-) و نشان می‌دهد در منطقه موردمطالعه، تعداد روشنه‌های بسته‌شده در سال بیشتر از تعداد روشنه‌های جدیدی است که تشکیل می‌شود
نتیجه‌گیری: با گذشت 9 سال تراکم روشنه‌ها و تعداد روشنه‌ها کاهش یافته و سطح کل روشنه‌ها افزایش یافته است. این افزایش سطح کل روشنه را می‌توان به افزایش گسترش روشنه‌های اولیه در طول دوره نسبت داد؛ زیرا نرخ گسترش روشنه‌های اولیه بیشتر از نرخ تشکیل روشنه، نرخ بسته شدن و کاهش روشنه‌های اولیه است. در هر دو مقطع زمانی فراوان‌ترین اندازه مربوط به روشنه‌های کوچک بوده است. که نشان‌دهنده غلبه روشنه‌های کوچک در منطقه موردمطالعه می‌باشد. روشنه‌های کوچک بیشتر پویایی روشنه‌ها را تشکیل می‌دهند و سریع‌تر از روشنه‌های بزرگ بسته می‌شوند.
نتیجه‌گیری: با گذشت 9 سال تراکم روشنه‌ها و تعداد روشنه‌ها کاهش یافته و سطح کل روشنه‌ها افزایش یافته است. این افزایش سطح کل روشنه را می‌توان به افزایش گسترش روشنه‌های اولیه در طول دوره نسبت داد؛ زیرا نرخ گسترش روشنه‌های اولیه بیشتر از نرخ تشکیل روشنه، نرخ بسته شدن و کاهش روشنه‌های اولیه است. در هر دو مقطع زمانی فراوان‌ترین اندازه مربوط به روشنه‌های کوچک بوده است. که نشان‌دهنده غلبه روشنه‌های کوچک در منطقه موردمطالعه می‌باشد. روشنه‌های کوچک بیشتر پویایی روشنه‌ها را تشکیل می‌دهند و سریع‌تر از روشنه‌های بزرگ بسته می‌شوند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Analysis of dynamics of canopy gap in the coniferous forest stands using UltraCam-D digital aerial camera and Unmanned Aerial vehicles data(Case Study: Arab Dagh Region in Golestan Province)

نویسندگان [English]

  • zeynab khalili 1
  • Asghar Fallah 2
  • Shaban Shataee 3
1 PhD student of Department of Forestry, Faculty of Natural Resources, Sari University of Agricultural Sciences and Natural Resources, Sari, Iran.
2 Professor of Forestry Department, Faculty of Natural Resources, Sari University of Agricultural Sciences and Natural Resources, Sari, Iran
3 Professor of Forestry Department, Faculty of Forest Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
چکیده [English]

Introduction and Objective: Natural disturbances caused by the canopy gap an important role in forest dynamics. Analyzing the dynamics of the canopy gap provides an accurate understanding of the process of forest stands dynamics as well as natural disturbances that play an important role in the future management of the forest ecosystem. The present study examines the dynamics of the canopy gap in the Arab Dagh forestry in Golestan province.
Material and Methods: The identification and preparation of the gaps map was done by the basic object classification method. The classification of the basic object can be done in three general stages, which include segmentation, classification and evaluation of classification accuracy.In the next step, the 1345 canopy gap in 2011 and the 1058 canopy gap in 2019 were extracted from the method that had the best performance compared to other methods of preparing gap maps. The characteristics of the gaps were obtained at each time period. Also, with the intersection of these two maps, the dynamics of the gaps was analyzed by calculating the characteristics Gap formation rate, Gap closure rate, Gap expansion rate, Gap reduction rate, and Gap number increase rate.
Results: The results of the canopy gap dynamics during the 9 years showed that the number and density of the canopy gap decreased. But the average area canopy gap and the share of the area of the canopy gap in the total area increased.In both periods, 65% of the canopy gap have an area of less than 150 m2, and a large canopy gap (larger than 300 m2) covered the lowest frequency and share of the total area of the canopy gap. The highest rate of changes in the canopy gap source was related to the Gap expansion rate (1.09% per year). The Gap closure rate is almost equal to the Gap reduction rate. The lowest rate of changes in the light is the Gap formation rate (0.77% per year). The logarithmic Gap number increase rate (GNIR) was negative (-2.6) that in all canopy gap classes, the number of closed canopy gaps per year is more than It is the number of new canopy gap that is created.
Conclusion: With the passage of 9 years, the density of gaps and the number of gaps have decreased and the total surface of gaps has increased. This increase in the total level of gap can be attributed to the increase in the Gap expansion during the period. Because the Gap expansion rate is higher than the Gap formation rate, the Gap closure rate and Gap reduction rate.In both periods of time, the most abundant size was related to small holes. which indicates the predominance of small lights in the studied area. which shows the predominance of small gaps in the studied area, small gaps make up most of the dynamics of gaps and close faster than big gaps.
Keywords: Gap, UAV, dynamic indicators, coniferous forestry, remote sensing
ps.

کلیدواژه‌ها [English]

  • Gap Size
  • Long-Term Study
  • Object-based classification
  • coniferous forestry
  • remote sensing

مراجع

1.Amiri, M., Rahmani, R., & Sagheb-Talebi, Kh. (2015). Canopy gaps characteristics and structural dynamics in a natural unmanaged oriental beech (Fagus orientalis Lipsky) stand in the north of Iran. Caspian J. of Environmental Sciences. 13(3), 259-264. [In Persian]
2.Khodaverdi, S., Amiri, M., Kartoolinejad, D., & Mohammadi, J. (2018). Characteristics of canopy gap in a broad-leaved mixed forest (Case study: District No. 2, Shast-Kalateh Forest, Golestan province). Iranian J. of Forest and Poplar Research. 26(1), 24-35. [In Persian]
3.Orman, O., Dobrowolska, D., & Szwagrzykc, J. (2018). Gap regeneration patterns in Carpathian old-growth mixed beech forests – Interactive effects of the spruce bark beetle canopy disturbance and deer herbivory. Forest Ecology and Management. 430, 451-459.
4.Sefidi, K., & Marvi-Mohajer, M.R. (2010). Characteristics of coarse woody debris in successional stages of natural beech (Fagus orientalis Lipsky) forests of Northern Iran. J. of Forest Science. 56(1), 7-17. [In Persian]
5.Muscolo, A., Bagnato, S., Sidari, M., & Mercurio, R. (2014). A review of the roles of forest canopy gaps. J. of Forestry Research. 25, 725-736. https://doi.org/ 10.1007/ s11676-014-0521-7.
6.Goodbody, T. R. H. H., Tompalski, P., Coops, N. C., White, J. C., Wulder, M. A., & Sanelli, M. (2020). Uncovering spatial and ecological variability in gap size frequency distributions in the Canadian boreal forest. Scientific Reports. 10(1), 1-12. https://doi.org/10.1038/ s41598-020-62878-z.
7.Yao, A. W., Chiang, J. M., Mcewan, R., & Lin, T. C. (2015). The effect of typhoon-related defoliation on the ecology of gap dynamics in a subtropical rain forest of Taiwan. J. of Vegetation Science, 26(1), 145-154. https://doi.org/ 10.1111/jvs.12217.
8.Petritan, A. M., Nuske, R. S., Petritan, I. C., & Tudose, N. C. (2013). Gap disturbance patterns in an old-growth sessile oak (Quercus petraea L.) European beech (Fagus sylvatica L.) forest remnant in the Carpathian Mountains, Romania. Forest Ecology and Management. 308, 67-75.
9.Abdollahnejad, A., Panagiotidis, D., & Surový, P. (2017). Forest canopy density assessment using different approaches - Review. J. of Forest Science. 63(3), 107-116. https://doi.org/10.17221/110/2016-JFS.
10.Nuske, R. S. (2019). Acquisition and Characterization of Canopy Gap Patterns of Beech Forests. (Doctoral dissertation, Georg-August-Universität Göttingen).
11.Hopkinson, C., Chasmer, L., Barr, A. G., Kljun, N., Black, T. A., & McCaughey, J. H. M. (2016). Monitoring boreal forest biomass and carbon storage change by integrating airborne laser scanning. biometry and eddy covariance data. Remote Sensing of Environment, 181, 82-95. https://doi.org/10.1016/ j.rse.2016.04.010.
12.Valbuena, R., Maltamo, M., Mehtätalo, L., & Packalen, P. (2017). Key structural features of boreal forests may be detected directly using L‐moments from airborne lidar data. Remote Sensing of Environment, 194, 437-446. https:// doi.org/10.1016/j.rse.2016.10.024.
13.Perroy, L. Y., Sullivan, T., & Stephenson, N. (2017). Assessing the impact of canopy openness and flight parameters on detecting a sub-canopy tropical invasive plant using a small unmanned aerial system. ISPRS J. of Photogrammetry and Remote Sensing. 125, 174-183.
14.Tang, L., & Shao, G. (2015). Drone remote sensing for forestry research and practices. J. of Forestry Research, 26, 791-797.
15.Zhang, Ch., & Kovacs, J. M. (2012). The application of small unmanned aerial systems for precision agriculture: a review. Precision Agriculture. 13, 693-712. DOI: 10.1007/s11119-012-9274-5.
16.Torresan, C., Berton, A., Carotenuto, F., Di Gennaro, S. F., Gioli, B., Matese, A., Miglietta, F., Vagnoli, C., Zaldei, A. & Wallace, L. (2017). Forestry applications of UAVs in Europe: a review. International J. of Remote Sensing. 38(8-10), 2427-2447.
17.Mlambo, R., Woodhouse, H. I., Gerard, F., & Anderson, K. (2017). Structure from Motion (SFM) photogrammetry with drone data: A low-cost method for monitoring greenhouse gas emissions from forests in developing countries. Forests. 8(68), 1-20.
18.Hunt, E. R., Hively, W. D., Daughtry, C. S., McCarty, G. W., Fujikawa, S. J., Ng, T. L., Tranchitella, M., Linden, D. S., & Yoel, D. W. (2008). Remote sensing of crop leaf area index using unmanned airborne vehicles. In Proceedings of the Pecora. 17, (18-20).
19.Amini, Sh., Shataee Jouibary, Sh., Moayeri, M. H., & Rahmani, R. (2021). Canopy gap delineation using UAV data in a Hyrcanian forest (Case study: Shastklateh Forest). Iranian J. of Forest. 14(2), 135-154. [In Persian]
20.Tanaka, H., & Nakashizuka, T. (1997). Fifteen years of canopy gap dynamics analyzed by aerial photographs in a temperate deciduous forest, Japan. Ecology. 78(2), 612-620.
21.Henbo, Y., Itaya, A., Nishimura, N., & Yamamoto, S. I. (2006). Long-term canopy dynamics analyzed by aerial photographs and digital elevation data in a subalpine old-growth coniferous forest. Ecoscience, 13(4), 451-458.
22.Kenderes, K., Mihok, B., & Standovar, T. 2008. Thirty years of gap dynamics in a central European beech forest reserve. Forestry. 81(1), 111-123. https://doi.org/ 10.1093/forestry/cpn001.
23.Kathke, S., & Bruelheide, H. (2010). Gap dynamics in a near-natural spruce forest at Mt. Brocken, Germany. Forest Ecology and Management. 259(3), 624-632. https://doi.org/ 10.1016/S0378-1127(00)00284-X
24.Sefidi, K., Mohadjer, M. R., & Mosandl, R. (2011). Canopy gaps and regeneration in old-growth oriental beech (Fagus orientalis, Lipsky) stands, northern Iran. Forest Ecology and Management, 262(6), 1094-1099, https://doi.org/10.1016/j.foreco.2011.06.008.
25.Feldmann, E., Drößler, L., Hauck, M., Kucbel, S., Pichler, V., & Leuschner, C. (2018). Canopy gap dynamics and tree understory release in a virgin beech forest, Slovakian Carpathians. Forest Ecology and Management. 415, 38-46.
26.Khodaverdi, S., Amiri, M., Kartoolinejad, D., & Mohammadi, J. (2019). Canopy gaps characteristics of pure and mixed stands in the Hyrcanian forests of northern Iran. Annals of Silvicultural Research. 43(2), 62-70. https://doi.org/10.12899/asr-1882.
27.Akbari Mazdi, R., Mataji, A., & Fallah, A. (2021). Canopy gap dynamics, disturbances, and natural regeneration patterns in a Beech-dominated Hyrcanian old-growth forest. Baltic Forestry. 27(1), 535. https://doi.org/ 10.46490/bf535.
28.Vepakomma, U., Kneeshaw, D., & Fortin, M. J. (2012). Spatial contiguity and continuity of canopy gaps in mixed wood boreal forests: persistence, expansion, shrinkage, and displacement. Journal of Ecology. 100(5), 1257-1268. https://doi.org/10.2307/23257547.
29.Littell, J. S., Peterson, D. L., & Tjoelker, M. (2008). Douglas-fir growth in mountain ecosystems: water limits
tree growth from stand to region. Ecological Monographs. 78(3), 349-368. https://doi.org/10.1890/07-0712.1.
30.Gray, A. N., Spies, T. A., & Pabst, R. J. (2012). Canopy gaps affect long-term patterns of tree growth and mortality in mature and old-growth forests in the Pacific Northwest. Forest Ecology and Management. 281, 111-120. https://doi.org/10.1016/j.foreco.2012.06.035.
31.Diaci, J., Adamic, T., & Rozman, A. (2012). Gap recruitment and partitioning in an old-growth beech forest of the Dinaric Mountains: influences of the light regime, herb competition, and browsing. Forest Ecology and Management. 285, 20-28. https://doi.org/ 10.1016/j.foreco.2012.08.010.
32.Zhu, C., Zhu, J., Zheng, X., Lu, D., & Li, X. (2017). Comparison of gap formation and distribution pattern induced by wind/snowstorm and flood in a temperate secondary forest ecosystem, Northeast China. Silva Fennica. 51(5). https://doi.org/10.14214/sf.7693.
33.Henbo, Y., Itaya, A., & Nishimura, N. (2004). Long-term canopy dynamics in a large area of temperate old-growth beech (Fagus crenata) forest: analysis by aerial photographs and digital elevation models. Journal of Ecology. 92(6), 945-953. https://doi.org/10. 1111/j.1365-2745.2004.00932.x.
34.Kenderes, K., Král, K., Vrška, T., & Standovár, T. (2009). Natural gap dynamics in a Central European mixed beech-spruce-fir old-growth forest. Ecoscience. 16 (1), 39-47.
35.Blackburn, G. A. (2014). Forest disturbance and regeneration: a mosaic of discrete gap dynamics and open matrix regimes? Journal of Vegetation Science. 25(6), 1341-1354. https:// doi.org/10.1111/jvs. 12201.
36.Zhu, C., Zhu, J.,Wang, G., Zheng, X., Lu, D., & Gao, T. (2019). Dynamics of gaps and large openings in a secondary forest of Northeast China over 50 years. Annals of Forest Science. 76(72), https://doi.org/10.1007/s13595-019-0844-9.
37.Bartemucci, P., Coates, K. D., Harper, K. A., & Wright, E. F. (2002). Gap disturbances in northern old-growth forests of British Columbia, Canada. J. of Vegetation Science. 13(5),685-696. https://doi.org/ 10.1111/j.1654-1103. 2002.tb02096.
38.Rugani, T., Diaci, J., & Hladnik, D. (2013). Gap dynamics and structure of two old-growth beech forest remnants in Slovenia. PLoS ONE. 8(1), e52641. https://doi.org/10.1371/journal.pone.0052641.
39.Sadeghzadeh, H., & Rostaghi., A. (2011). A Study of Vegetative Yield of Borussia Pine (Case Study: Arab-Dagh Forestry Project). Iranian J. of Forest. 3, 201-212. [In Persian]
40.Baatz, M., & Schape, A. (1999). Object-oriented and multi-scale image analysis in the semantic network. in Proc. of
2nd Int. symposium on operalization of remote sensing. Enschede, ITC. 148-157.
41.Naseri, M. H., Shataee Jouibary, Sh., & Habashi, H. (2023). Analysis of forest tree dieback using UltraCam and UAV imagery. Scandinavian J. of Forest Research.
42.Naseri, M. H., Shataee Jouibary, Sh., & Habashi, H. (2023). Zoning of tree crown leaf burn using UAV and Sentinel 2 images in Deland Forest Park, Golestan province. J. of Wood and Forest Science and Technology. 29 (4), 75-92.
43.Runkle, J. R. (1981). Patterns of disturbance in some old-growth mesic forests of Eastern North America. Ecology. 63(5), 1533-1546.
44.Brokaw, N. V., & Scheiner, S. M. (1982). Species composition in gaps and structure of a tropical forest. Ecology, 538-541.
45.Bonnet, S., Gaulton, R., Lehaire, F., & Lejeune, P. (2015). Canopy gap mapping from airborne laser scanning: An assessment of the positional and geometrical accuracy. Remote Sensing. 7(9), 11267-11294. https://doi.org/ 10. 3390/rs70911267.
46.Koukoulas, S., & Blackburn, G.A. (2004). Quantifying the spatial properties of forest canopy gaps using LiDAR imagery and GIS. International J. Remote Sensing. 25(15), 3049-3072. https://doi.org/10.1080/014311603100016.
47.Gaulton, R., & Malthus, T.J. (2010). LiDAR mapping of canopy gaps in continuous cover forests: A comparison of canopy height model and point cloud-based techniques. International J of Remote Sensing. 31(5), 1193-1211. https://doi.org/10.1080/01431160903380565.
48.Kucbel, S., Jaloviar, P., Saniga, M., Vencurik, J., & Klimaš, V. (2010). Canopy gaps in an old-growth fir-beech forest remnant of Western Carpathians. European J. of Forest Research. 129(3), 249–259. https://doi.org/ 10. 1007/s10342-009-0322-2.
49.White, J. C., Tompalski, P., Coops, N. C., & Wulder, M. A. (2018). Comparison of airborne laser scanning and digital stereo imagery for characterizing forest canopy gaps in coastal temperate rainforests. Remote Sensing of Environment. 208, 1-14.
50.Vaughn, N. R., Asner, G. P., & Giardina, C. P. (2015). Long‐term fragmentation effects on the distribution and dynamics of canopy gaps in a tropical montane forest. Ecosphere. 6(12), 1-15.
51.Senécal, J. F., Doyon, F., & Messier, C. (2018). Tree death not resulting in gap creation: an investigation of canopy dynamics of northern temperate deciduous forests. Remote Sensing. 10(1), 121.
52.Xuegang, M., Liang, Z., & Fan. W. (2020). Object-oriented automatic identification of forest gaps using digital orthophoto maps and LiDAR data. Canadian J. of Remote Sensing, 46(2), 177-192. https://doi.org/ 10. 1080/07038992.2020.1768515.
53.Schliemann, S. A., & Bockheim, J. G. (2011). Methods of studying treefall gaps: a review. Forest Ecology and Management. 261(7), 1143-1151.
54.Manabe, T., Shimatani, K., Kawarasaki, S., Aikawa, S. I., & Yamamoto, S. I. (2009). The patch mosaic of an old-growth warm-temperate forest: patch level descriptions of 40-year gap-forming processes and community structures. Ecological research. 24(3), 575-586. https://doi.org/ 10. 1007/s11284-008-0528-7.
55.Stiers, M., Willim, K., Seidel, D., Ammer, C., Kabal, M., Stillhard, J., & Annighöfer, P. (2019). Analyzing spatial distribution patterns of European beech (Fagus sylvatica L.) regeneration in dependence of canopy openings. Forests. 10(8). https://doi.org/ 10.3390/ f10080637.
56.Liu, QH., & Hytteborn, H. (1991). Gap structure, disturbance, and regeneration in a primeval Picea-abies forest. J. of Vegetation Science. 2(3), 391-402. https://doi.org/10.2307/3235932.
57.Caron, M. N., Kneeshaw, D. D., De Grandpré, L., Kauhanen, H., & Kuuluvainen, T. (2009). Canopy gap characteristics and disturbance dynamics in old-growth Picea abies stands in northern Fennoscandia: Is the forest in quasi-equilibrium? In Annales Botanici Fennici. 46(4), 251-262.
58.Kian, S., Kouchaksaraei, M. T., Esmailzadeh, O., & Alavi, S. J. (2017). Gap characteristics and disturbance regime in an intact Hyrcanian oriental beech forest, Iran. Austrian Journal of Forest Science. 2017(4), 323-345.
59.Bi, S., Tan, Y., Wang, Y., Liu, M., & Mao, X. (2020). Quantification of spatial structure characteristics of typical natural secondary forest gaps in Northeastern China. Research Square. https://doi.org/10.21203/rs.3.rs-38728/ v1.
60.Dobrowolska, D., Piasecka, Z., Kuberski, L., & Stere´nczak, K. (2022). Canopy gap characteristics and regeneration patterns in the Białowie˙za forest based on remote sensing data and field measurements. Forest Ecology and Management. 511, 120123.
61.Vepakomma, U., St‐Onge, B., & Kneeshaw, D. (2011). Response of a boreal forest to canopy opening: assessing vertical and lateral tree growth with multi‐temporal lidar data. Ecological Applications. 21(1), 99-121.
62.Torimaru, T., Itaya, A., & Yamamoto, S. I. (2012). Quantification of repeated gap formation events and their spatial patterns in three types of old-growth forests: Analysis of long-term canopy dynamics using aerial photographs and digital surface models. Forest Ecology and Management. 284, 1-11. https:// doi.org/10.1016/j.foreco.2012.07.044.
63.Fujita, T., Itaya, A., Miura, M., Manabe, T., & Yamamoto, S.I. (2003). Long-term canopy dynamics analyzed by aerial photographs in a temperate old-growth evergreen broad-leaved forest. J. of Ecology. 91(4), 686-693. https:// doi.org/10. 1046/ j.1365-2745.2003.00796.x.
64.Vaughn, N. R., Asner, G. P., & Giardina, C. P. (2015). Long-term fragmentation effects on the distribution and dynamics of canopy gaps in a tropical montane forest. Ecosphere. 6(12), 1-15. https://doi.org/10.1890/ ES15-00235.1.
پژوهش‌های علوم و فناوری چوب و جنگل
دوره 30، شماره 3
مهر 1402
صفحه 1-26

فایل ها

هم رسانی

ارجاع به این مقاله

آمار