The influence of topographic variation on forest structure in two woody plant communities: A remote sensing approach
Abstract
Aim of study: The study aimed to characterise variation in structural attributes of vegetation in relation to variations in topographic position using LIDAR data over landscapes.
Area of study: The study was conducted in open canopy eucalypt-dominated forest (Richmond Range National Park-RRNP) and closed canopy subtropical rainforest (Border Ranges National Park-BRNP) in north-eastern New South Wales, Australia.
Material and Methods: one metre resolution digital canopy height model (CHM) was extracted from the LIDAR data and used to estimate maximum overstorey height and crown area. LIDAR fractional cover representing the photosynthetic and non-photosynthetic component of canopy was calculated using LIDAR points aggregated into 50 m spatial bins. Potential solar insolation, Topographic Wetness Index (TWI), slope and the elevation were processed using LIDAR derived digital elevation models.
Main results: No relationship was found between maximum overstorey height and insolation gradient in the BRNP. Maximum overstorey height decreased with increasing insolation in the RRNP (R2 0.45). Maximum overstorey height increased with increasing TWI in the RRNP. Average crown area decreased with increasing insolation in both study areas. LIDAR fractional cover decreased with increasing insolation (R2 0.54), and increased with increasing TWI (R2 0.57) in the RRNP.
Research highlights: The characterization of structural parameters of vegetation in relation to the variation of the topography was possible in eucalyptus dominated open canopy forest. No reportable difference in variation of structural elements of vegetation was detected with topographic variation of subtropical rainforest.
Downloads
References
References
Ackerly DD, Knight CA, Weiss SB, Barton K, Starmer KP, 2002. Leaf size, specific leaf area and microhabitat distribution of chaparral woody plants: contrasting patterns in species level and community level analyses. Oecologia 130: 449-457. http://dx.doi.org/10.1007/s004420100805
Aiba S, Kitayama K, 1999. Structure, composition and species diversity in an altitude-substrate matrix of rain forest tree communities on Mount Kinabalu, Borneo. Plant Ecol 140: 139-157. http://dx.doi.org/10.1023/A:1009710618040
Armston JD, Denham RJ, Danaher TJ, Scarth PF, Moffiet TN, 2009. Prediction and validation of foliage projective cover from Landsat-5 TM and Landsat-7 ETM+ imagery. J Appl Remote Sens 3: 1-28. http://dx.doi.org/10.1117/1.3216031
Ashton PMS 1992. Some measurements of the microclimate within a Sri Lankan tropical rainforest. Agr Forest Meteorol 59: 217-235. http://dx.doi.org/10.1016/0168-1923(92)90094-K
Ashton PS, Hall P, 1992. Comparisons of Structure Among Mixed Dipterocarp Forests of North-Western Borneo. J Ecol 80: 459-481. http://dx.doi.org/10.2307/2260691
Bale CL, Charley JL, 1994. The impact of aspect on forest floor characteristics in some Eastern Australian sites. Forest Ecol Manag 67: 305-317. http://dx.doi.org/10.1016/0378-1127(94)90025-6
Bale CL, Williams JB, Charley JL, 1998. The impact of aspect on forest structure and floristics in some Eastern Australian sites. Forest Ecol Manag 110: 363-377. http://dx.doi.org/10.1016/S0378-1127(98)00300-4
Bellingham PJ, Tanner EVJ, 2000. The Influence of Topography on Tree Growth, Mortality, and Recruitment in a Tropical Montane Forest1. Biotropica, 32:378-384. http://dx.doi.org/10.1111/j.1744-7429.2000.tb00484.x
Beven KJ, Kirkby MJ, 1979. A physical based variable contributing area model of basin hydrology. Hydrol Sci Bull 24: 43-69. http://dx.doi.org/10.1080/02626667909491834
Bruijnzeel LA,Veneklaas EJ, 1998. Climatic conditions and tropical montane forest productivity: the fog has not lifted yet. Ecology 79: 3-9. http://dx.doi.org/10.1890/0012-9658(1998)079[0003:CCATMF]2.0.CO;2
Bureau of Meteorology. 2010. Bureau of Meteorology. [Accessed 05/July 2010 2010].
Chen Q, Baldocchi D, Gong P, Kelly M, 2006. Isolating Individual Trees in a Savanna Woodland Using Small Footprint LiDAR Data. Photogramm Eng Rem S 72: 923-932. http://dx.doi.org/10.14358/PERS.72.8.923
Chen ZS, Hsieh CF, Jiang FY, Hsieh TH, Sun IF, 1997. Relations of soil properties to topography and vegetation in a subtropical rain forest in southern Taiwan. Plant Ecol 132: 229-241. http://dx.doi.org/10.1023/A:1009762704553
Ediriweera S, 2013. Refinement of predictions of forest structure and biomass using Remote Sensing techniques in a topographically complex landscape. Doctaral Thesis. Southern Cross University, Australia.
Ediriweera S, Pathirana S, Danaher T, Nichols D, 2014. LiDAR remote sensing of structural properties of subtropical rainforest and eucalypt forest in complex terrain in North-eastern Australia. J Trop For Sci 26: 397–408
Ediriweera S, Singhakumara BMP, Ashton MS, 2008. Variation in canopy structure, light and soil nutrition across elevation of a Sri Lankan tropical rain forest. Forest Ecol Manag 256: 1339-1349. http://dx.doi.org/10.1016/j.foreco.2008.06.035
Fu S, Bell FW, Chen HYH, 2007. Long-term effects of intensive silvicultural practices on productivity, composition, and structure of northern temperate and boreal plantations in Ontario, Canada. Forest Ecol Manag 241: 115-126. http://dx.doi.org/10.1016/j.foreco.2007.01.032
Galicia L, Lopez-Blanco J, Zarco-Arista AE, Filips V, Garcia-Oliva F, 1999. The relationship between solar radiation interception and soil water content in a tropical deciduous forest in Mexico. Catena 36: 153-164. http://dx.doi.org/10.1016/S0341-8162(98)00121-0
Gatziolis D, Fried, JS, Monleon, VS, 2010. Challenges to Estimating Tree Height via LiDAR in Closed-Canopy Forests: A Parable from Western Oregon. Forest Sci 56: 139-155
Hancock GR, 2005. The use of digital elevation models in the identification and characterization of catchments over different grid scales. Hydrol Process 19: 1727-1749. http://dx.doi.org/10.1002/hyp.5632
Holmgren J, Nilsson M, Olsson H, 2003. Estimation of tree height and stem volume on plots-using airborne laser scanning. Forest Sci 49: 419-428.
Isbell RF, 1998. The Australian Soil Classification. CSIRO Publishing, Collingwood, Victoria, Australia.132 pp.
Kerr J T, Ostrovsky M, 2003. From space to species: ecological applications for remote sensing. Trends Ecol Evol 18: 299-305. http://dx.doi.org/10.1016/S0169-5347(03)00071-5
Kitayama K, Aiba S, 2002. Ecosystem structure and productivity of tropical rain forests along altitudinal gradients with contrasting soil phosphorus pools on Mount Kinabalu, Borneo. J Ecol 90: 37-51. http://dx.doi.org/10.1046/j.0022-0477.2001.00634.x
Kopecky M, Cizkova S, 2010. Using topographic wetness index in vegetation ecology: does the algorithm matter. Appl Veg Sci 13: 450-459. http://dx.doi.org/10.1111/j.1654-109X.2010.01083.x
Lovell JL, Jupp DLB, Culvenor DS, Coops NC, 2003. Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests. Can J Remote Sens 29: 607-622. http://dx.doi.org/10.5589/m03-026
Magnussen S, Boudewyn P, 1998. Derivation of stand heights from airborne laser scanner data with canopy based quantile estimates. Can J Forest Res 28: 1016-1031. http://dx.doi.org/10.1139/x98-078
Nilsson M, 1996. Estimation of tree heights and stand volume using an airborne lidar system. Remote Sens Env 56: 1-7. http://dx.doi.org/10.1016/0034-4257(95)00224-3
Olivero AM, Hix DM, 1998. Influence of aspect and stand age on ground flora of southeastern Ohio forest ecosystems. Plant Ecol 139: 177-187. http://dx.doi.org/10.1023/A:1009758501201
Popescu SC, 2007. Estimating biomass of individual pine trees using airborne LiDAR. Biomass Bioenerg 31: 646-655. http://dx.doi.org/10.1016/j.biombioe.2007.06.022
Popescu SC, Wynne RH, Nelson RF, 2002. Estimating plot-level tree heights with lidar: local filtering with a canopy-height based variable window size. Computers and Electronics in Agric 37: 71-95. http://dx.doi.org/10.1016/S0168-1699(02)00121-7
Popescu SC, Wynne RH, Nelson RF, 2003. Measuring individual tree crown diameter with LiDAR and assessing its influence on estimating forest volume and biomass. Can J Remote Sens 29: 564-577. http://dx.doi.org/10.5589/m03-027
Quinn P, Beven KJ, Chevallier P, Planchon O, 1991. The prediction of hillslope flow paths for distributed hydrological modeling using digital terrain models. Hydrol Process 5: 59-80. http://dx.doi.org/10.1002/hyp.3360050106
Singh SP, Adhikari BS, Zobel DB, 1994. Biomass, Productivity, Leaf Longevity, and Forest Structure in the Central Himalaya. Ecol Monogr 64: 401-421. http://dx.doi.org/10.2307/2937143
Smith RGB, Nichols JD, Vanclay JK, 2005. Dynamics of tree diversity in undisturbed and logged subtropcal rainforest in Australia. Biodivers Conserv 14: 2447-2463. http://dx.doi.org/10.1007/s10531-004-0215-0
Sørensen R, Seibert J, 2007. Effects of DEM resolution on the calculation of topographical indices: TWI and its components. J Hydrol 347: 79-89. http://dx.doi.org/10.1016/j.jhydrol.2007.09.001
Specht RL, 1988. Mediterranean-type Ecosystem: A data source book. Kluwer Academic Publisher, Dordrecht, Netherlands.140 pp. http://dx.doi.org/10.1007/978-94-009-3099-5
Specht RL, Specht A, 1999. Australian plant communities: dynamics of structure, growth and biodiversity, Oxford University Press.256 pp.
Stevens NC, 1977. The Border Ranges. A Land Use Conflict in Regional Perspective. In: Monreo R, Stevens NC (eds.) Geology and Landforms. Brisbane, Royal Society of Queensland.
Takyu M, Aiba S, Kitayama K, 2002. Effects of topography on tropical lower montane forests under different geological conditions on Mount Kinabalu, Borneo. Plant Ecol 159: 35-49. http://dx.doi.org/10.1023/A:1015512400074
Tanner EVJ, 1980a. Litterfall in Montane Rain Forests of Jamaica and its Relation to Climate. J Ecol 68: 833-848. http://dx.doi.org/10.2307/2259459
Tanner, EVJ, 1980b. Studies on the Biomass and Productivity in a Series of Montane Rain Forests in Jamaica. J Ecol 68: 573-588. http://dx.doi.org/10.2307/2259423
Tokuchi N, Takeda H, Yoshida K, Iwatsubo G, 1999. Topographical variations in a plant-soil system along a slope on Mt Ryuoh, Japan. Ecol Res 14: 361-369. http://dx.doi.org/10.1046/j.1440-1703.1999.00309.x
Weaver PL, Murphy PG, 1990. Forest Structure and Productivity in Puerto Rico's Luquillo Mountains. Biotropica 22: 69-82. http://dx.doi.org/10.2307/2388721
Webb LJ, Tracey JG,Williams WT, 1972. Regeneration and pattern in the subtropical rainforest. J Ecol, 60: 675-695. http://dx.doi.org/10.2307/2258559
Weller D, Denham R, Witte C, Mackie C, Smith D, 2003. Assessment and monitoring of foliage projected cover and canopy height across native vegetation in Queensland, Australia, using laser profiler data. Can J Remote Sens 29: 578-591. http://dx.doi.org/10.5589/m03-028
Wu Y, Strahler AH, 1994. Remote Estimation of Crown Size, Stand Density, and Biomass on the Oregon Transect. Ecol Appl 4: 299-312. http://dx.doi.org/10.2307/1941935
Wulder MA, White JC, Nelson RF, Næsset E, Ørka HO, Coops NC, Hilker T, Bater CW, Gobakken T, 2012. Lidar sampling for large-area forest characterization: A review. Remote Sens Env 121: 196-209. http://dx.doi.org/10.1016/j.rse.2012.02.001
Zhang W, Montgomery DR, 1994. Digital elevation model grid size, landscape representation. Water Resour Res 30: 1019–1028. http://dx.doi.org/10.1029/93WR03553
© CSIC. Manuscripts published in both the printed and online versions of this Journal are the property of Consejo Superior de Investigaciones Científicas, and quoting this source is a requirement for any partial or full reproduction.
All contents of this electronic edition, except where otherwise noted, are distributed under a “Creative Commons Attribution 4.0 International” (CC BY 4.0) License. You may read here the basic information and the legal text of the license. The indication of the CC BY 4.0 License must be expressly stated in this way when necessary.
Self-archiving in repositories, personal webpages or similar, of any version other than the published by the Editor, is not allowed.
