Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-26T22:40:34.838Z Has data issue: false hasContentIssue false
  • English
  • Français

Using photography to estimate above-ground biomass of small trees

Published online by Cambridge University Press:  23 September 2020

Brandon R. Hays ,
Corinna Riginos ,
Todd M. Palmer ,
Benard C. Gituku  and
Jacob R. Goheen
Brandon R. Hays*
Affiliation:
Department of Zoology and Physiology, University of Wyoming,Laramie, WY82071, USA
Corinna Riginos
Affiliation:
The Nature Conservancy, 258 Main Street, Lander, WY82520, USA
Todd M. Palmer
Affiliation:
Department of Biology, University of Florida,Gainesville, 32611Florida, USA
Benard C. Gituku
Affiliation:
Department of Land Resource Management & Agricultural Technology, University of Nairobi, P.O. Box 30197, Nairobi, Kenya Ol Pejeta Conservancy, 10400Nanyuki, Kenya
Jacob R. Goheen
Affiliation:
Department of Zoology and Physiology, University of Wyoming,Laramie, WY82071, USA
*
Author for correspondence: *Brandon R. Hays, Email: bhays3@uwyo.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Quantifying tree biomass is an important research and management goal across many disciplines. For species that exhibit predictable relationships between structural metrics (e.g. diameter, height, crown breadth) and total weight, allometric calculations produce accurate estimates of above-ground biomass. However, such methods may be insufficient where inter-individual variation is large relative to individual biomass and is itself of interest (for example, variation due to herbivory). In an East African savanna bushland, we analysed photographs of small (<5 m) trees from perpendicular angles and fixed distances to estimate above-ground biomass. Pixel area of trees in photos and diameter were more strongly related to measured, above-ground biomass of destructively sampled trees than biomass estimated using a published allometric relation based on diameter alone (R2 = 0.86 versus R2 = 0.68). When tested on trees in herbivore-exclusion plots versus unfenced (open) plots, our predictive equation based on photos confirmed higher above-ground biomass in the exclusion plots than in unfenced (open) plots (P < 0.001), in contrast to no significant difference based on the allometric equation (P = 0.43). As such, our new technique based on photographs offers an accurate and cost-effective complement to existing methods for tree biomass estimation at small scales with potential application across a wide variety of settings.

Keywords

Acaciaherbivoryphotographic analysisremote sensingsavanna
Type
Research Article
Information
Journal of Tropical Ecology , Volume 36 , Issue 5 , September 2020 , pp. 213 - 219
Check for updates
Copyright
© The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Antonio, N, Tomé, M, Tomé, J, Soares, P and Fontes, L (2007) Effect of tree, stand, and site variables on the allometry of Eucalyptus globulus tree biomass. Canadian Journal of Forest Research 37, 895–906.CrossRefGoogle Scholar
Archer, S (1996) Assessing and interpreting grass–woody plant dynamics. In Hodgson, J and Illius, A (eds), The Ecology and Management of Grazing Systems. Wallingford: CAB International, pp. 101–134.Google Scholar
Barbour, MA, Rodriguez-Cabal, MA, Wu, ET, Julkunen-Tiitto, R, Ritland, CE, Miscampbell, AE, Jules, ES and Crutsinger, GM (2015) Multiple plant traits shape the genetic basis of herbivore community assembly. Functional Ecology 29, 995–1006.CrossRefGoogle Scholar
Birkett, A (2002) The impact of giraffe, rhino and elephant on the habitat of a black rhino sanctuary in Kenya. African Journal of Ecology 40, 276–282.CrossRefGoogle Scholar
Chave, J, Andalo, C, Brown, S, Cairns, MA, Chambers, JQ, Eamus, D, Fölster, H, Fromard, F, Higuchi, N, Kira, T and Lescure, JP (2005) Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145, 87–99.CrossRefGoogle ScholarPubMed
Cho, MA, Mathieu, R, Asner, GP, Naidoo, L, van Aardt, J and Ramoelo, A (2012) Mapping tree species composition in South African savannas using an integrated airborne spectral and LiDAR system. Remote Sensing of Environment 125, 214–226.CrossRefGoogle Scholar
Copenhaver, PE and Tinker, DB (2014) Stand density and age affect tree-level structural and functional characteristics of young, postfire lodgepole pine in Yellowstone National Park. Forest Ecology and Management 320, 138–148.CrossRefGoogle Scholar
Dutcă, I, Mather, R and Ioraş, F (2017) Tree biomass allometry during the early growth of Norway spruce (Picea abies) varies between pure stands and mixtures with European beech (Fagus sylvatica). Canadian Journal of Forest Research 48, 77–84.CrossRefGoogle Scholar
Fox-Dobbs, K, Doak, DF, Brody, AK and Palmer, TM (2010) Termites create spatial structure and govern ecosystem function by affecting N2 fixation in an East African savanna. Ecology 91, 1296–1307.CrossRefGoogle Scholar
Goheen, JR and Palmer, TM (2010) Defensive plant-ants stabilize megaherbivore-driven landscape change in an African savanna. Current Biology 20, 1768–1772.CrossRefGoogle Scholar
Gonzalez de Tanago, J, Lau, A, Bartholomeus, H, Herold, M, Avitabile, V, Raumonen, P, Martius, C, Goodman, RC, Disney, M, Manuri, S, Burt, A and Calders, K (2018) Estimation of above-ground biomass of large tropical trees with terrestrial LiDAR. Methods in Ecology and Evolution 9, 223–234.CrossRefGoogle Scholar
Grömping, U (2006) Relative importance for linear regression in R: the package relaimpo. Journal of Statistical Software 17, 1–27.CrossRefGoogle Scholar
Henry, M, Picard, N, Trotta, C, Manlay, R, Valentini, R, Bernoux, M and Saint André, L (2011) Estimating tree biomass of sub-Saharan African forests: a review of available allometric equations. Silva Fennica 245, 477–569.Google Scholar
Holdo, RM, Holt, RD and Fryxell, JM (2009) Grazers, browsers, and fire influence the extent and spatial pattern of tree cover in the Serengeti. Ecological Applications 19, 95–109.CrossRefGoogle ScholarPubMed
House, JI, Archer, S, Breshears, DD and Scholes, RJ (2003) Conundrums in mixed woody–herbaceous plant systems. Journal of Biogeography 30, 1763–1777.CrossRefGoogle Scholar
Hubau, W, De Mil, T, Van den Bulcke, J, Phillips, OL, Ilondea, BA, Van Acker, J, Sullivan, MJ, Nsenga, L, Toirambe, B, Couralet, C and Banin, LF (2019) The persistence of carbon in the African forest understory. Nature Plants 5, 133–140.CrossRefGoogle ScholarPubMed
Kartzinel, TR, Chen, PA, Coverdale, TC, Erickson, DL, Kress, WJ, Kuzmina, ML, Rubenstein, DI, Wang, W and Pringle, RM (2015) DNA metabarcoding illuminates dietary niche partitioning by African large herbivores. Proceedings of the National Academy of Sciences USA 112, 8019–8024.CrossRefGoogle ScholarPubMed
Kuhn, M. Contributions from Wing, J, Weston, S, Williams, A, Keefer, C, Engelhardt, A, Cooper, T, Mayer, Z, Kenkel, B, the R Core Team, Benesty, M, Lescarbeau, R, Ziem, A, Scrucca, L, Tang, Y, Candan, C and Hunt, T (2019) Classification and Regression Training. R package version 6.0-82. https://CRAN.R-project.org/package=caret.Google Scholar
Louhaichi, M, Johnson, MD, Woerz, AL, Jasra, AW and Johnson, DE (2010) Digital charting technique for monitoring rangeland vegetation cover at local scale. International Journal of Agriculture and Biology 12, 406–410.Google Scholar
Louhaichi, M, Hassan, S, Clifton, K and Johnson, DE (2017) A reliable and non-destructive method for estimating forage shrub cover and biomass in arid environments using digital vegetation charting technique. Agroforestry Systems 92, 1341–1352.CrossRefGoogle Scholar
Munyati, C, Shaker, P and Phasha, MG (2011) Using remotely sensed imagery to monitor savanna rangeland deterioration through woody plant proliferation: a case study from communal and biodiversity conservation rangeland sites in Mokopane, South Africa. Environmental Monitoring and Assessment 176, 293–311.CrossRefGoogle ScholarPubMed
Muriithi, FK (2016) Land use and land cover (LULC) changes in semi-arid sub-watersheds of Laikipia and Athi River basins, Kenya, as influenced by expanding intensive commercial horticulture. Remote Sensing Applications: Society and Environment 3, 73–88.CrossRefGoogle Scholar
Okello, BD, O’Connor, TG and Young, TP (2001) Growth, biomass estimates, and charcoal production of Acacia drepanolobium in Laikipia, Kenya. Forest Ecology and Management 142, 143–153.CrossRefGoogle Scholar
Palmer, TM, Stanton, ML, Young, TP, Goheen, JR, Pringle, RM and Karban, R (2008) Breakdown of an ant–plant mutualism follows the loss of large herbivores from an African savanna. Science 319, 192–195.CrossRefGoogle ScholarPubMed
Palmer, TM, Doak, DF, Stanton, ML, Bronstein, JL, Kiers, ET, Young, TP, Goheen, JR and Pringle, RM (2010) Synergy of multiple partners, including freeloaders, increases host fitness in a multispecies mutualism. Proceedings of the National Academy of Sciences USA 107, 17234–17239.CrossRefGoogle Scholar
Pastor, J, Aber, JD and Melillo, JM (1984) Biomass prediction using generalized allometric regressions for some northeast tree species. Forest Ecology and Management 7, 265–274.CrossRefGoogle Scholar
Poorter, H, Niklas, KJ, Reich, PB, Oleksyn, J, Poot, P and Mommer, L (2012) Biomass allocation to leaves, stems and roots: meta-analyses of interspecific variation and environmental control. New Phytologist 193, 30–50.CrossRefGoogle ScholarPubMed
Popescu, SC (2007) Estimating biomass of individual pine trees using airborne lidar. Biomass and Bioenergy 31, 646–655.CrossRefGoogle Scholar
Pringle, RM, Prior, KM, Palmer, TM, Young, TP and Goheen, JR (2016) Large herbivores promote habitat specialization and beta diversity of African savanna trees. Ecology 97, 2640–2657.CrossRefGoogle ScholarPubMed
Raumonen, P, Åkerblom, M, Kaasalainen, M, Casella, E, Calders, K and Murphy, S (2015) Massive-scale tree modelling from TLS data. ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences 2, 189–196.CrossRefGoogle Scholar
R Core Team (2018) R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. https://www.R-project.org/.Google Scholar
Riginos, C, Karande, MA, Rubenstein, DI and Palmer, TM (2015) Disruption of a protective ant–plant mutualism by an invasive ant increases elephant damage to savanna trees. Ecology 96, 654–661.CrossRefGoogle ScholarPubMed
Schepaschenko, D, Chave, J, Phillips, OL, Lewis, SL, Davies, SJ, Réjou-Méchain, M, Sist, P, Scipal, K, Perger, C, Hérault, B and Labrière, N (2019) The Forest Observation System, building a global reference dataset for remote sensing of forest biomass. Scientific Data 6, 1–11.CrossRefGoogle ScholarPubMed
Stanton, ML, Palmer, TM, Young, TP, Evans, A and Turner, ML (1999) Sterilization and canopy modification of a swollen thorn acacia tree by a plant-ant. Nature 401, 578–581.CrossRefGoogle Scholar
Ter-Mikaelian, MT and Parker, WC (2000) Estimating biomass of white spruce seedlings with vertical photo imagery. New Forests 20, 145–162.CrossRefGoogle Scholar
Venables, WN and Ripley, BD (2002) Modern Applied Statistics with S. Fourth Edition. New York, NY: Springer.CrossRefGoogle Scholar
Whitham, TG and Mopper, S (1985) Chronic herbivory: impacts on architecture and sex expression of pinyon pine. Science 228, 1089–1091.CrossRefGoogle ScholarPubMed
Yao, W, Krzystek, P and Heurich, M (2012) Tree species classification and estimation of stem volume and DBH based on single tree extraction by exploiting airborne full-waveform LiDAR data. Remote Sensing of Environment 123, 368–380.CrossRefGoogle Scholar
Young, HE, Strand, L and Altenberger, R (1964) TB12: preliminary fresh and dry weight tables for seven tree species in Maine. Maine Agricultural Experimental Station Technical Bulletin 12, 1–83.Google Scholar
Young, TP, Okello, BD, Kinyua, D and Palmer, TM (1997 a) KLEE: A long-term multi-species herbivore exclusion experiment in Laikipia, Kenya. African Journal of Range & Forage Science 14, 94–102.CrossRefGoogle Scholar
Young, TP, Stubblefield, CH and Isbell, LA (1997 b) Ants on swollen-thorn acacias: species coexistence in a simple system. Oecologia 109, 98–107.CrossRefGoogle Scholar