[en] Permanent forest dynamics plots have provided valuable insights into many aspects of forest ecology. The evaluation of their representativeness within the landscape is necessary to understanding the limitations of findings from permanent plots at larger spatial scales. Studies on the representativeness of forest plots with respect to landscape heterogeneity and disturbance effect have already been carried out, but knowledge of how multiple disturbances affect plot representativeness is lacking-particularly in sites where several disturbances can occur between forest plot censuses. This study explores the effects of five typhoon disturbances on the Fushan Forest Dynamics Plot (FFDP) and its surrounding landscape, the Fushan Experimental Forest (FEF), in Taiwan where typhoons occur annually. The representativeness of the FFDP for the FEF was studied using four topographical variables derived from a digital elevation model and two vegetation indices (VIs), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Infrared Index (NDII), calculated from Landsat-5 TM, Landsat-7 ETM+, and Landsat-8 OLI data. Representativeness of four alternative plot designs were tested by dividing the FFDP into subplots over wider elevational ranges. Results showed that the FFDP neither represents landscape elevational range (<10%) nor vegetation cover (<7% of the interquartile range, IQR). Although disturbance effects (i.e., DVIs) were also different between the FFDP and the FEF, comparisons showed no under-or over-exposure to typhoon damage frequency or intensity within the FFDP. In addition, the DVIs were of the same magnitudes in the plots and the reserve, and the plot covered 30% to 75.9% of IQRs of the reserve DVIs. Unexpectedly, the alternative plot designs did not lead to increased representation of damage for 3 out of the 4 tested typhoons and they did not suggest higher representativeness of rectangular vs. square plots. Based on the comparison of mean Euclidian distances, two rectangular plots had smaller distances than four square or four rectangular plots of the same area. Therefore, this study suggests that the current FFDP provides a better representation of its landscape disturbances than alternatives, which contained wider topographical variation and would be more dicult to conduct ground surveys. However, upscaling needs to be done with caution as, in the case of the FEF, plot representativeness varied among typhoons.
Disciplines :
Environmental sciences & ecology
Author, co-author :
Peereman, Jonathan ; Université de Liège - ULiège > Sphères ; Biodiversity Program, Taiwan International Graduate Program, Biodiversity Research Center, Academia Sinica and National Taiwan Normal University, Nankang District, Taipei, Taiwan ; Department of Life Science, National Taiwan Normal University, Wenshan District, Taipei, Taiwan
Hogan, James Aaron ; Department of Biological Sciences, Florida International University, Miami, United States
Lin, Teng-Chiu; Department of Life Science, National Taiwan Normal University, Wenshan District, Taipei, Taiwan
Language :
English
Title :
Landscape representation by a permanent forest plot and alternative plot designs in a Typhoon Hotspot, Fushan, Taiwan
Condit, R. Research in large, long-term tropical forest plots. Trends Ecol. Evol. 1995, 10, 18-22. [CrossRef]
Anderson-Teixeira, K.J.; Davies, S.J.; Bennett, A.C.; Gonzalez-Akre, E.B.; Muller-Landau, H.C.; Wright, S.J.; Abu Salim, K.; Almeyda Zambrano, A.M.; Alonso, A.; Baltzer, J.L.; et al. CTFS-ForestGEO: A worldwide network monitoring forests in an era of global change. Glob. Chang. Biol. 2015, 21, 528-549. [CrossRef] [PubMed]
Malhi, Y.; Phillips, O.L.; Lloyd, J.; Baker, T.; Wright, J.; Almeida, S.; Arroyo, L.; Frederiksen, T.; Grace, J.; Higuchi, N.; et al. An international network to monitor the structure, composition and dynamics of Amazonian forests (RAINFOR). J. Veg. Sci. 2002, 13, 439-450. [CrossRef]
Lewis, S.L.; Phillips, O.L.; Baker, T.R.; Lloyd, J.; Malhi, Y.; Almeida, S.; Higuchi, N.; Laurance, W.F.; Neill, D.A.; Silva, J.N.; et al. Concerted changes in tropical forest structure and dynamics: Evidence from 50 South American long-term plots. Philos. Trans. R. Soc. B 2004, 359, 421-436. [CrossRef] [PubMed]
John, R.; Dalling, J.W.; Harms, K.E.; Yavitt, J.B.; Stallard, R.F.; Mirabello, M.; Hubbell, S.P.; Valencia, R.; Navarrete, H.; Vallejo, M.; et al. Soil nutrients influence spatial distributions of tropical tree species. Proc. Natl. Acad. Sci. USA 2007, 104, 864-869. [CrossRef]
Laurance, S.G.W.; Laurance, W.F.; Nascimento, H.E.M.; Andrade, A.; Fearnside, P.M.; Rebello, E.R.G.; Condit, R. Long-term variation in Amazon forest dynamics. J. Veg. Sci. 2009, 20, 323-333. [CrossRef]
Cleveland, C.C.; Townsend, A.R.; Taylor, P.; Alvarez-Clare, S.; Bustamante, M.M.C.; Chuyong, G.; Dobrowski, S.Z.; Grierson, P.; Harms, K.E.; Houlton, B.Z.; et al. Relationships among net primary productivity, nutrients and climate in tropical rain forest: A pan-tropical analysis. Ecol. Lett. 2011, 14, 939-947. [CrossRef]
Wright, S.J.; Yavitt, J.B.; Wurzburger, N.; Turner, B.L.; Tanner, E.V.J.; Sayer, E.J.; Santiago, L.S.; Kaspari, M.; Hedin, L.O.; Harms, K.E.; et al. Potassium, phosphorus, or nitrogen limit root allocation, tree growth, or litter production in a lowland tropical forest. Ecology 2011, 92, 1616-1625. [CrossRef]
Chisholm, R.A.; Condit, R.; Rahman, K.A.; Baker, P.J.; Bunyavejchewin, S.; Chen, Y.Y.; Chuyong, G.; Dattaraja, H.S.; Davies, S.; Ewango, C.E.N.; et al. Temporal variability of forest communities: Empirical estimates of population change in 4000 tree species. Ecol. Lett. 2014, 17, 855-865. [CrossRef]
Yu, K.; Smith, W.K.; Trugman, A.T.; Condit, R.; Hubbell, S.P.; Sardans, J.; Peng, C.; Zhu, K.; Peñuelas, J.; Cailleret, M.; et al. Pervasive decreases in living vegetation carbon turnover time across forest climate zones. Proc. Natl. Acad. Sci. USA 2019, 116, 24662-24667. [CrossRef]
Neyland, M.G.; Brown, M.J.; Su, W. Assessing the representativeness of long-term ecological research sites: A case study at Warra in Tasmania. Aust. For. 2000, 63, 194-198. [CrossRef]
Rodríguez-González, P.M.; Albuquerque, A.; Martínez-Almarza, M.; Díaz-Delgado, R. Long-term monitoring for conservation management: Lessons from a case study integrating remote sensing and field approaches in floodplain forests. J. Environ. Manag. 2017, 202, 392-402. [CrossRef] [PubMed]
Marvin, D.C.; Asner, G.P.; Knapp, D.E.; Anderson, C.B.; Martin, R.E.; Sinca, F.; Tupayachi, R. Amazonian landscapes and the bias in field studies of forest structure and biomass. Proc. Natl. Acad. Sci. USA 2014, 111, E5224-E5232. [CrossRef] [PubMed]
Vitousek, P.; Asner, G.P.; Chadwick, O.A.; Hotchkiss, S. Landscape-level variation in forest structure and biogeochemistry across a substrate age gradient in Hawaii. Ecology 2009, 90, 3074-3086. [CrossRef] [PubMed]
Fisher, J.I.; Hurtt, G.C.; Thomas, R.Q.; Chambers, J.Q. Clustered disturbances lead to bias in large-scale estimates based on forest sample plots. Ecol. Lett. 2008, 11, 554-563. [CrossRef] [PubMed]
Lloyd, J.; Gloor, E.U.; Lewis, S.L. Are the dynamics of tropical forests dominated by large and rare disturbance events? Ecol. Lett. 2009, 12, E19-E21. [CrossRef] [PubMed]
Muller-Landau, H.C.; Detto, M.; Chisholm, R.A.; Hubbell, S.P.; Condit, R. Detecting and projecting changes in forest biomass from plot data. In Forests and Global Change; Coomes, D.A., Burslem, D.F.R.P., Simonson, W.D., Eds.; Cambridge University Press: Cambridge, UK, 2014; pp. 381-415.
Di Vittorio, A.V.; Negrón-Juárez, R.I.; Higuchi, N.; Chambers, J.Q. Tropical forest carbon balance: Effects of field-and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass. Environ. Res. Lett. 2014, 9, 034010. [CrossRef]
Hopkins, M.S.; Graham, A.W. Gregarious flowering in a lowland tropical rainforest: A possible response to disturance by Cyclone Winifred. Aust. J. Ecol. 1987, 12, 25-29. [CrossRef]
Bellingham, P.J. Landforms influence patterns of hurricane damage: Evidence from Jamaican montane forests. Biotropica 1991, 23, 427-433. [CrossRef]
Walker, L.R.; Voltzow, J.; Ackerman, J.D.; Fernández, D.S.; Fetcher, N. Immediate impact of Hurricane Hugo on a Puerto Rican rain forest. Ecology 1992, 73, 691-694. [CrossRef]
Turton, S.M. Landscape-scale impacts of Cyclone Larry on the forests of northeast Australia, including comparisons with previous cyclones impacting the region between 1858 and 2006. Austral Ecol. 2008, 33, 409-416. [CrossRef]
McEwan, R.W.; Lin, Y.-C.; Sun, I.F.; Hsieh, C.-F.; Su, S.-H.; Chang, L.-W.; Song, G.-Z.M.; Wang, H.-H.; Hwong, J.-L.; Lin, K.-C.; et al. Topographic and biotic regulation of aboveground carbon storage in subtropical broad-leaved forests of Taiwan. For. Ecol. Manag. 2011, 262, 1817-1825. [CrossRef]
Chi, C.-H.; McEwan, R.W.; Chang, C.-T.; Zheng, C.; Yang, Z.; Chiang, J.-M.; Lin, T.-C. Typhoon disturbance mediates elevational patterns of forest structure, but not species diversity, in humid monsoon Asia. Ecosystems 2015, 18, 1410-1423. [CrossRef]
Inagaki, Y.; Kuramoto, S.; Torii, A.; Shinomiya, Y.; Fukata, H. Effects of thinning on leaf-fall and leaf-litter nitrogen concentration in hinoki cypress (Chamaecyparis obtusa Endlicher) plantation stands in Japan. For. Ecol. Manag. 2008, 255, 1859-1867. [CrossRef]
Boose, E.R.; Foster, D.R.; Fluet, M. Hurricane impacts to tropical and temperate forest landscapes. Ecol. Monogr. 1994, 64, 369-400. [CrossRef]
Yap, S.L.; Davies, S.J.; Condit, R. Dynamic response of a Philippine dipterocarp forest to typhoon disturbance. J. Veg. Sci. 2016, 27, 133-143. [CrossRef]
Noguchi, Y. Vegetation asymmetry in Hawaii under the trade wind regime. J. Veg. Sci. 1992, 3, 223-230. [CrossRef]
Ostertag, R.; Silver, W.L.; Lugo, A.E. Factors affecting mortality and resistance to damage following hurricanes in a rehabilitated subtropical moist forest. Biotropica 2005, 37, 16-24. [CrossRef]
Tanner, E.V.J.; Rodriguez-Sanchez, F.; Healey, J.R.; Holdaway, R.J.; Bellingham, P.J. Long-term hurricane damage effects on tropical forest tree growth and mortality. Ecology 2014, 95, 2974-2983. [CrossRef]
Webb, E.L.; Van de Bult, M.; Fa'aumu, S.; Webb, R.C.; Tualaulelei, A.; Carrasco, L.R. Factors affecting tropical tree damage and survival after catastrophic wind disturbance. Biotropica 2014, 46, 32-41. [CrossRef]
Hogan, J.A.; Zimmerman, J.K.; Thompson, J.; Uriarte, M.; Swenson, N.G.; Condit, R.; Hubbell, S.; Johnson, D.J.; Sun, I.F.; Chang-Yang, C.-H.; et al. The frequency of cyclonic wind storms shapes tropical forest dynamism and functional trait dispersion. Forests 2018, 9, 404. [CrossRef]
Lin, S.-Y.; Shaner, P.-J.L.; Lin, T.-C. Characteristics of old-growth and secondary forests in relation to age and typhoon disturbance. Ecosystems 2018, 21, 1521-1532. [CrossRef]
Su, S.-H.; Chang-Yang, C.H.; Lu, C.-L.; Tsui, C.-C.; Lin, T.-T.; Lin, C.-L.; Chiou, W.-L.; Kuan, L.-H.; Chen, Z.-S.; Hsieh, C.-F. Fushan Subtropical Forest Dynamics Plot: Tree Species Characteristics and Distribution Patterns; Taiwan Forestry Research Institute: Taipei, Taiwan, 2007.
Hu, T.; Smith, R.B. The impact of Hurricane Maria on the vegetation of Dominica and Puerto Rico using multispectral remote sensing. Remote Sens. 2018, 10, 827. [CrossRef]
Simpson, R.H.; Riehl, H. The Hurricane and Its Impact; Louisiana State University Press: Baton Rouge, LA, USA, 1981; p. 398.
Knapp, K.R.; Kruk, M.C.; Levinson, D.H.; Diamond, H.J.; Neumann, C.J. The International Best Track Archive for Climate Stewardship (IBTrACS): Unifying tropical cyclone best track data. Bull. Am. Meteorol. Soc. 2010, 91, 363-376. [CrossRef]
Knapp, K.R.; Diamond, H.J.; Kossin, J.P.; Kruk, M.C.; Schreck, C.J. International Best Track Archive for Climate Stewardship (IBTrACS) Project, Version 4; [IBTrACS. EP. list. v04r00]; NOAA National Centers for Environmental Information: Asheville, North Carolina, 2018. [CrossRef]
USGS. Earthexplorer. Available online: https://earthexplorer.usgs.gov/ (accessed on 4 July 2019).
Foga, S.; Scaramuzza, P.L.; Guo, S.; Zhu, Z.; Dilley, R.D., Jr.; Beckmann, T.; Schmidt, G.L.; Dwyer, J.L.; Joseph Hughes, M.; Laue, B. Cloud detection algorithm comparison and validation for operational Landsat data products. Remote Sens. Environ. 2017, 194, 379-390. [CrossRef]
She, X.; Zhang, L.; Cen, Y.; Wu, T.; Huang, C.; Baig, M.H.A. Comparison of the continuity of vegetation indices derived from Landsat 8 OLI and Landsat 7 ETM+ data among different vegetation types. Remote Sens. 2015, 7, 13485-13506. [CrossRef]
Vogelmann, J.E.; Gallant, A.L.; Shi, H.; Zhu, Z. Perspectives on monitoring gradual change across the continuity of Landsat sensors using time-series data. Remote Sens. Environ. 2016, 185, 258-270. [CrossRef]
JAXA. ALOS Global Digital Surface Model "ALOS World 3D-30m (AW3D30)". Available online: https: //www.eorc.jaxa.jp/ALOS/en/aw3d30/index.htm (accessed on 5 July 2019).
Hansen, M.C.; Potapov, P.V.; Moore, R.; Hancher, M.; Turubanova, S.A.; Tyukavina, A.; Thau, D.; Stehman, S.V.; Goetz, S.J.; Loveland, T.R.; et al. High-Resolution global maps of 21st-century forest cover change. Science 2013, 342, 850-853. [CrossRef] [PubMed]
Leutner, B.; Horning, N.; Schwalb-Willmann, J. RStoolbox: Tools for Remote Sensing Data Analysis. 2019. Available online: https://cran.r-project.org/web/packages/RStoolbox/index.html (accessed on 17 February 2020).
Achard, F.; Beuchle, R.; Mayaux, P.; Stibig, H.J.; Bodart, C.; Brink, A.; Carboni, S.; Desclée, B.; Donnay, F.; Eva, H.D.; et al. Determination of tropical deforestation rates and related carbon losses from 1990 to 2010. Glob. Chang. Biol. 2014, 20, 2540-2554. [CrossRef] [PubMed]
Vieilledent, G.; Grinand, C.; Rakotomalala, F.A.; Ranaivosoa, R.; Rakotoarijaona, J.-R.; Allnutt, T.F.; Achard, F. Combining global tree cover loss data with historical national forest cover maps to look at six decades of deforestation and forest fragmentation in Madagascar. Biol. Conserv. 2018, 222, 189-197. [CrossRef]
Rouse, J.W.; Haas, R.H.; Schell, J.A.; Deering, D.W.; Harlan, J.C. Monitoring the Vernal Advancement of Rétrogradation (Green Wave Effect) of Natural Vegetation; Type III Final Rep; NASA/GSFC: Greenbelt, MD, USA, 1974; p. 371.
Hardisky, M.A.; Klemas, V.; Smart, R.M. The influences of soil salinity, growth form, and leaf moisture on the spectral reflectance of Spartina alterniflora canopies. Photogramm. Eng. Remote Sens. 1983, 49, 77-83.
Kerr, J.T.; Ostrovsky, M. From space to species: Ecological applications for remote sensing. Trends Ecol. Evol. 2003, 18, 299-305. [CrossRef]
Pettorelli, N.; Vik, J.O.; Mysterud, A.; Gaillard, J.-M.; Tucker, C.J.; Stenseth, N.C. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends Ecol. Evol. 2005, 20, 503-510. [CrossRef]
Carlson, T.N.; Ripley, D.A. On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sens. Environ. 1997, 62, 241-252. [CrossRef]
Clark, D.B.; Olivas, P.C.; Oberbauer, S.F.; Clark, D.A.; Ryan, M.G. First direct landscape-scale measurement of tropical rain forest Leaf Area Index, a key driver of global primary productivity. Ecol. Lett. 2008, 11, 163-172. [CrossRef]
Townsend, P.A.; Singh, A.; Foster, J.R.; Rehberg, N.J.; Kingdon, C.C.; Eshleman, K.N.; Seagle, S.W. A general Landsat model to predict canopy defoliation in broadleaf deciduous forests. Remote Sens. Environ. 2012, 119, 255-265. [CrossRef]
Hijmans, R.J. Raster: Geographic Data Analysis and Modeling. 2019. Available online: https://cran.r-project. org/web/packages/raster/index.html (accessed on 17 February 2020).
Weiss, A. Topographic position and landform analysis. In Proceedings of the ESRI User Conference: Poster Presentation, San Diego, CA, USA, 9-13 July 2001.
Jin, S.; Yang, L.; Danielson, P.; Homer, C.; Fry, J.; Xian, G. A comprehensive change detection method for updating the National Land Cover Database to circa 2011. Remote Sens. Environ. 2013, 132, 159-175. [CrossRef]
Hargrove, W.W.; Hoffman, F.M.; Law, B.E. New analysis reveals representativeness of the AmeriFlux network. Eos Trans. AGU 2003, 84. [CrossRef]
He, H.; Zhang, L.; Gao, Y.; Ren, X.; Zhang, L.; Yu, G.; Wang, S. Regional representativeness assessment and improvement of eddy flux observations in China. Sci. Total Environ. 2015, 502, 688-698. [CrossRef]
Hoffman, F.M.; Kumar, J.; Mills, R.T.; Hargrove, W.W. Representativeness-based sampling network design for the State of Alaska. Landsc. Ecol. 2013, 28, 1567-1586. [CrossRef]
Langford, Z.; Kumar, J.; Hoffman, F.M.; Norby, R.J.; Wullschleger, S.D.; Sloan, V.L.; Iversen, C.M. Mapping Arctic plant functional type distributions in the Barrow Environmental Observatory using WorldView-2 and LiDAR datasets. Remote Sens. 2016, 8, 733. [CrossRef]
Chang, C.-T.; Wang, L.-J.; Huang, J.-C.; Liu, C.-P.; Wang, C.-P.; Lin, N.-H.; Wang, L.; Lin, T.-C. Precipitation controls on nutrient budgets in subtropical and tropical forests and the implications under changing climate. Adv. Water Resour. 2017, 103, 44-50. [CrossRef]
Lieberman, D.; Lieberman, M.; Peralta, R.; Hartshorn, G.S. Tropical forest structure and composition on a large-scale altitudinal gradient in Costa Rica. J. Ecol. 1996, 84, 137-152. [CrossRef]
Vázquez, J.A.; Givnish, T.J. Altitudinal gradients in tropical forest composition, structure, and diversity in the Sierra de Manantlán. J. Ecol. 1998, 86, 999-1020. [CrossRef]
Hsieh, C.-F.; Chen, Z.-S.; Hsu, Y.-M.; Yang, K.-C.; Hsieh, T.-H. Altitudinal zonation of evergreen broad-leaved forest on Mount Lopei, Taiwan. J. Veg. Sci. 1998, 9, 201-212. [CrossRef]
Rocchini, D.; Hernández-Stefanoni, J.L.; He, K.S. Advancing species diversity estimate by remotely sensed proxies: A conceptual review. Ecol. Inform. 2015, 25, 22-28. [CrossRef]
White, J.D.; Running, S.W.; Nemani, R.; Keane, R.E.; Ryan, K.C. Measurement and remote sensing of LAI in Rocky Mountain montane ecosystems. Can. J. For. Res. 1997, 27, 1714-1727. [CrossRef]
Cheng, Y.-B.; Zarco-Tejada, P.J.; Riaño, D.; Rueda, C.A.; Ustin, S.L. Estimating vegetation water content with hyperspectral data for different canopy scenarios: Relationships between AVIRIS and MODIS indexes. Remote Sens. Environ. 2006, 105, 354-366. [CrossRef]
Marra, D.M.; Chambers, J.Q.; Higuchi, N.; Trumbore, S.E.; Ribeiro, G.H.; Dos Santos, J.; Negrón-Juárez, R.I.; Reu, B.; Wirth, C. Large-scale wind disturbances promote tree diversity in a Central Amazon forest. PLoS ONE 2014, 9, e103711. [CrossRef]
Abbas, S.; Nichol, J.E.; Fischer, G.A.; Wong, M.S.; Irteza, S.M. Impact assessment of a super-typhoon on Hong Kong's secondary vegetation and recommendations for restoration of resilience in the forest succession. Agric. For. Meteorol. 2020, 280. [CrossRef]
Salk, C.F.; Chazdon, R.L.; Andersson, K.P. Detecting landscape-level changes in tree biomass and biodiversity: Methodological constraints and challenges of plot-based approaches. Can. J. For. Res. 2013, 43, 799-808. [CrossRef]
Reese, G.C.; Wilson, K.R.; Hoeting, J.A.; Flather, C.H. Factors affecting species distribution predictions: A simulation modeling experiment. Ecol. Appl. 2005, 15, 554-564. [CrossRef]
Chambers, J.Q.; Negron-Juarez, R.I.; Marra, D.M.; Di Vittorio, A.; Tews, J.; Roberts, D.; Ribeiro, G.H.P.M.; Trumbore, S.E.; Higuchi, N. The steady-state mosaic of disturbance and succession across an old-growth Central Amazon forest landscape. Proc. Nαtl. Acαd. Sci. USA 2013, 110, 3949-3954. [CrossRef]
Chang, C.-P.; Yang, Y.-T.; Kuo, H.-C. Large increasing trend of tropical cyclone rainfall in Taiwan and the roles of terrain. J. Clim. 2013, 26, 4138-4147. [CrossRef]
Kossin, J.P.; Emanuel, K.A.; Vecchi, G.A. The poleward migration of the location of tropical cyclone maximum intensity. Nature 2014, 509, 349-352. [CrossRef] [PubMed]
Altman, J.; Ukhvatkina, O.N.; Omelko, A.M.; Macek, M.; Plener, T.; Pejcha, V.; Cerny, T.; Petrik, P.; Srutek, M.; Song, J.S.; et al. Poleward migration of the destructive effects of tropical cyclones during the 20th century. Proc. Natl. Acad. Sci. USA 2018, 115, 11543-11548. [CrossRef] [PubMed]