Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-24T16:14:27.545Z Has data issue: false hasContentIssue false
  • English
  • Français

Pyrus calleryana allometric equations and stand structure in southwestern Ohio and northern Kentucky

Published online by Cambridge University Press:  04 November 2020

Richard L. Boyce Open the ORCID record for Richard L. Boyce [Opens in a new window]  and
Miciah Ocasio
Richard L. Boyce*
Affiliation:
Professor, Department of Biological Sciences, Northern Kentucky University, Highland Heights, KY, USA
Miciah Ocasio
Affiliation:
Undergraduate Student, Department of Biological Sciences, Northern Kentucky University, Highland Heights, KY, USA
*
Author for correspondence: Richard L. Boyce, Department of Biological Sciences, Northern Kentucky University, 1 Nunn Drive, Highland Heights, KY41099. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Callery pear (Pyrus calleryana Decne.), a native of eastern Asia, has recently emerged as an important woody invader in much of the eastern United States. Little is known about its ecology in its new range. Its shade tolerance may be an important indicator of areas it is likely to invade. In this study, allometric equations were first developed to predict aboveground biomass components, including wood, branches, bark, leaves, and fruit, from diameter at stump height (dsh; 25 cm), by destructively harvesting 13 trees, ranging from 0.1 to 19.3 cm dsh. Then, a total of 23 wild-grown stands in the northern Kentucky/southwestern Ohio region were surveyed, with diameters of all woody stems sampled. Pyrus calleryana density, basal area, aboveground biomass, stand density index, size distribution inequality, and importance value were calculated for each site. Two-factor Weibull distributions were fit to diameter distributions. Allometric equations provided good fits for total aboveground biomass as well as individual components. Aboveground biomass levels fell below mean levels of native forest stands found in the United States. Stand density indices yielded values typical of shade-intolerant or midtolerant species. Stands with smaller trees generally had steeply declining monotonic diameter distributions, while stands with larger trees trended toward positively skewed monotonic distributions. These findings are consistent with a species that is either shade-intolerant or midtolerant. Thus, while this species is expected to invade open or disturbed areas, it is not expected to be an important invader under forest canopies. However, its extended deciduous habit is one shared by other understory woody invaders, and so this may allow it to survive under forest canopies.

Keywords

Aboveground biomassdiameter structureinvasive plantssize structurestand development
Type
Research Article
Information
Invasive Plant Science and Management , Volume 13 , Issue 4 , December 2020 , pp. 239 - 246
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of the Weed Science Society of America

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.)

Footnotes

Associate Editor: Songlin Fei, Purdue University

References

Baskerville, GL (1972) Use of logarithmic regression in the estimation of plant biomass. Can J For 2:49–53 Google Scholar
Birdsey, RA (1992) Carbon Storage and Accumulation in United States Forest Ecosystems. General Technical Report WO-59. Radnor, PA: USDA Forest Service. 51 pCrossRefGoogle Scholar
Boyce, RL (2018) High mortality seen in open-grown, but not forest-understory, Amur honeysuckle (Lonicera maackii, Caprifoliaceae) stands in northern Kentucky. J Torrey Bot Soc 145:21–29 CrossRefGoogle Scholar
Brower, JE, Zar, JH, Von Ende, CN (1997) Field and Laboratory Methods of General Ecology. 4th ed. New York: McGraw-Hill Education. 288 p Google Scholar
Burkhardt, HE, Avery, TE, Bullock, BP (2018) Forest Measurements. 6th ed. Long Grove, IL: Waveland Press. 434 p Google Scholar
Clifford, D, Cressie, N, England, JR, Roxburgh, SH, Paul, KI (2013) Correction factors for unbiased, efficient estimation and prediction of biomass from log–log allometric models. For Ecol Manag 310:375–381 CrossRefGoogle Scholar
Cochran, PH, Geist, JM, Clemens, DL, Clausnitzer, RR, Powell, DC (1994) Suggested stocking levels for forest stands in northeastern Oregon and southeastern Washington. Research Note PNW-RN-513. Bend, OR: USDA Forest Service, Pacific Northwest Research Station. 21 pCrossRefGoogle Scholar
Coomes, DA, Allen, RB (2007) Mortality and tree-size distributions in natural mixed-age forests. J Ecol 95:27–40 CrossRefGoogle Scholar
Culley, TM (2017) The rise and fall of the ornamental Callery pear tree. Arnoldia 74(3):2–11 Google Scholar
Culley, TM, Hardiman, NA (2009) The role of intraspecific hybridization in the evolution of invasiveness: a case study of the ornamental pear tree Pyrus calleryana . Biol Invasions 11:1107–1119 CrossRefGoogle Scholar
Culley, TM, Hardiman, NA, Hawks, J (2011) The role of horticulture in plant invasions: how grafting in cultivars of Callery pear (Pyrus calleryana) can facilitate spread into natural areas. Biol Invasions 13:739–746 CrossRefGoogle Scholar
Duan, N (1983) Smearing estimate: a nonparametric retransformation method. J Am Stat Assoc 78:605–610 CrossRefGoogle Scholar
[EDDMapS] Early Detection and Distribution Mapping System (2020) EDDMapS. University of Georgia–Center for Invasive Species and Ecosystem Health. http://www.eddmaps.org. Accessed: June 1, 2020Google Scholar
Gilman, EF, Watson, DG (1994) Pyrus calleryana ‘Bradford’: ‘Bradford’ Callery Pear. Fact Sheet ST-537. Gainesville, FL: Gainesville: Environmental Horticulture Department, Florida Cooperative Extensive Service, Institute of Food and Agricultural Sciences, University of Florida. 4 pGoogle Scholar
Hardiman, NA, Culley, TM (2010) Reproductive success of cultivated Pyrus calleryana (Rosaceae) and establishment ability of invasive, hybrid progeny. Am J Bot 97:1698–1706 CrossRefGoogle ScholarPubMed
Jenkins, JC, Chojnacky, DC, Heath, LS, Birdsey, RA (2004) Comprehensive database of diameter-based biomass regressions for North American tree species. General Technical Report NE-319. Newtown Square, PA: USDA Forest Service. 45 pCrossRefGoogle Scholar
Kahle, D, Wickham, H (2013) ggmap: Spatial visualization with ggplot2. R Journal 5:144–161. http://journal.r-project.org/archive/2013-1/kahle-wickham.pdf. Accessed: June 1, 2020CrossRefGoogle Scholar
Larcher, W (2003) Physiological Plant Ecology. 4th ed. Berlin: Springer. 513 p CrossRefGoogle Scholar
Leak, WB (2002) Origin of Sigmoid Diameter Distributions. Research Paper NE-718. Newtown Square, PA: USDA Forest Service. 10 pCrossRefGoogle Scholar
Lorimer, CG, Krug, AG (1983) Diameter distributions in even-aged stands of shade-tolerant and midtolerant tree species. Am Midl Nat 109:331–345 CrossRefGoogle Scholar
Lorimer, CG, Dahir, SE, Nordheim, EV (2001) Tree mortality rates and longevity in mature and old-growth hemlock-hardwood forests. J Ecol 89:960–971 CrossRefGoogle Scholar
Merritt, BJ, Jones, JB, Hardiman, NA, Culley, TM (2013) Comparison of photosynthetic characteristics in cultivated and wild offspring of the invasive Callery pear (Pyrus calleryana Decne.). Biol Invasions 16:393–400 CrossRefGoogle Scholar
Missouri Department of Conservation (2018) Callery Pear—Invasive Species. https://mdc.mo.gov/sites/default/files/downloads/callerypearinvasive.pdf. Accessed: June 1, 2020.Google Scholar
Mohler, CL, Marks, PL, Sprugel, DG (1978) Stand structure and allometry of trees during self-thinning of pure stands. J Ecol 66:599–614 CrossRefGoogle Scholar
Oliver, CD, Larson, BC (1996) Forest Stand Dynamics. Update ed. New York: Wiley. 520 p Google Scholar
R Core Team (2020) R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org. Accessed: March 5, 2020Google Scholar
Rouvinen, S, Kuuluvainen, T (2005) Tree diameter distributions in natural and managed old Pinus sylvestris-dominated forests. For Ecol Manag 208:45–61 CrossRefGoogle Scholar
Rubin, BD, Manion, PD, Faber-Langendoen, D (2006) Diameter distributions and structural sustainability in forests. For Ecol Manag 222:427–438 CrossRefGoogle Scholar
Shimano, K (2000) A power function for forest structure and regeneration pattern of pioneer and climax species in patch mosaic forests. Plant Ecol 146:207–220 CrossRefGoogle Scholar
Smith, DM, Larson, BC, Kelty, MJ, Ashton, MS (1997) The Practice of Silviculture: Applied Forest Ecology. 9th ed. New York: Wiley. 570 p Google Scholar
Smith, JE, Domke, GM, Nichols, MC, Walters, BF (2019) Carbon stocks and stock change on federal forest lands of the United States. Ecosphere 10:e02637 CrossRefGoogle Scholar
Snowdon, P (1991) A ratio estimator for bias correction in logarithmic regressions. Can J For Res 21:720–724 CrossRefGoogle Scholar
[USDA-NRCS] U.S. Department of Agriculture–Natural Resources Conservation Service (2020) Welcome to the PLANTS Database. USDA PLANTS. https://plants.sc.egov.usda.gov/java. Accessed: June 1, 2020Google Scholar
Vincent, MA (2005) On the spread and current distribution of Pyrus calleryana in the United States. Castanea 70:20–31 CrossRefGoogle Scholar
Whittaker, RH, Woodwell, GM (1968) Dimension and production relations of trees and shrubs in the Brookhaven Forest, New York. J Ecol 56:1–25 CrossRefGoogle Scholar
Woodall, CW, Miles, PD, Vissage, JS (2005). Determining maximum stand density index in mixed species stands for strategic-scale stocking assessments. For Ecol Manage 216:367–37CrossRefGoogle Scholar
Zeide, B (2004) How to measure stand density. Trees 19:1–14 CrossRefGoogle Scholar
Supplementary material: File

Boyce and Ocasio supplementary material

Boyce and Ocasio supplementary material

Download Boyce and Ocasio supplementary material(File)
File 24.4 KB