Implications of incorrectly determining site index on stand-level management activities and financial returns in older generation loblolly pine plantations

Authors

  • Curtis VanderSchaaf Mississippi State University

DOI:

https://doi.org/10.21750/REFOR.16.01.106

Keywords:

Pinus taeda, Land expectation value, Economics, Growth and yield

Abstract

Predicting future yields normally requires an estimate of site quality.  A commonly used measure is site index (SI). SI is often incorrectly quantified operationally due to the ambiguity associated with selecting “site” trees.  Plus, error in the measurement of height itself occurs.  This study quantifies the impacts on the number and timing of thinnings, and the final harvest ages, as well as financial returns when incorrectly determining SI.  Three values of SI (base age 25 years) were examined using two older generation loblolly pine plantation growth and yield simulation models from the Western Gulf, USA; 16.76 m, 21.34 m, and 25.91 m.  Firstly, a particular SI was assumed to be the “true” value, growth and yield estimates were obtained, and financial assessments were conducted.  The same process was then conducted again, but assuming that the SI was incorrectly determined by varying positively and negatively the SI by up to 1.22 m from the assumed “true” value.

For these older generation plantations, incorrectly determining SI did impact the age of the first thinning by as much as 5 years.  In some cases, errors of +/- 1.22 m in SI estimation had little impact on the estimated timing of the first thinning.  Errors in SI of up to +/- 1.22 m had little impact on the number of thinnings across economic rotation ages. For both unthinned and twice-thinned stands, final harvest (clearcut) ages differed by as much as 4 years for SI errors up to +/- 1.22 m.  These errors led to differences in Land Expectation Value (LEV) up to $406.50 ha-1.  Across the three SI (16.76, 21.34, and 25.91 m), differences in LEV ranged from $237.49 to $406.50 ha-1.  These differences in LEV could be enough to incorrectly not conduct, or incorrectly conduct, a silvicultural operation such as an herbicide treatment or a fertilization treatment across a rotation, among other treatments.

Downloads

Download data is not yet available.

References

Akers MK, Kane M, Zhao D, Teskey RO, Daniels RF (2013) Effects of planting density and cultural intensity on stand and crown attributes of mid-rotation loblolly pine plantations. Forest Ecol Manag 310: 468-475. https://doi.org/10.1016/j.foreco.2013.07.062 DOI: https://doi.org/10.1016/j.foreco.2013.07.062

Amateis RL, Burkhart HE (1985) Site index curves for loblolly pine plantations on cutover site-prepared lands. South J Appl For 9: 166-169. https://doi.org/10.1093/sjaf/9.3.166 DOI: https://doi.org/10.1093/sjaf/9.3.166

Antoń-Fernańdez C, Burkhart HE, Strub M, Amateis RL (2011) Effects of initial spacing on height development of loblolly pine. Forest Sci 57: 201-211.

Borders B, Harrison WM, Clutter ML, Shiver BD, Souter RA (2008) The value of timber inventory information for management planning. Can J Forest Res 38: 2287-2294. https://doi.org/10.1139/X08-075 DOI: https://doi.org/10.1139/X08-075

Boyer WD (1983) Variations in height-over-age curves for young longleaf pine plantations. Forest Sci 29: 15-27.

Burkhart HE, Tennent RB (1977) Site index equations for radiata pine in New Zealand. NZ J Forestry Sci 7: 408-416.

Burkhart HE, Yang S (2022) A retrospective comparison of carrying capacity of two generations of loblolly pine plantations. Forest Ecol Manag 504: 8 p. https://doi.org/10.1016/j.foreco.2021.119834 DOI: https://doi.org/10.1016/j.foreco.2021.119834

Burkhart HE, Avery TE, Bullock BP (2019) Forest Measurements. Waveland Press, Inc. Long Grove, IL: 6th ed, 434 p.

Cao QV, Baldwin Jr VC, Lohrey RE (1997) Site index curves for direct-seeded loblolly and longleaf pines in Louisiana. South J Appl For 21: 134-138. https://doi.org/10.1093/sjaf/21.3.134 DOI: https://doi.org/10.1093/sjaf/21.3.134

Chhetri SG, Pelkki M (2022) Current forest management intensity and cost associated with major forestry practices in Arkansas, USA. J For Busi Res 1(1): 51-74.

Coble, DW (2009) A new whole-stand model for unmanaged loblolly and slash pine plantations in East Texas. South J Appl For 33: 69-76. https://doi.org/10.1093/sjaf/33.2.69 DOI: https://doi.org/10.1093/sjaf/33.2.69

Dean TJ, Baldwin Jr VC (1993) Using a stand density-management diagram to develop thinning schedules for loblolly pine plantations. Res. Pap. SO-275. New Orleans, LA: USDA Forest Service, Southern Forest Experiment Station. 7 p. https://doi.org/10.2737/SO-RP-275 DOI: https://doi.org/10.2737/SO-RP-275

Dixon GE comp. (2002) Essential FVS: A user's guide to the Forest Vegetation Simulator. Internal Rep. Fort Collins, CO: USDA Forest Service, Forest Management Service Center. 239 p.

Eid T (2000) Use of uncertain inventory data in forestry scenario models and consequential incorrect harvest decisions. Silva Fenn 34: 89-100. https://doi.org/10.14214/sf.633 DOI: https://doi.org/10.14214/sf.633

Fox TR, Jokela EJ, Allen HL (2007) The development of pine plantation silviculture in the southern United States. J Forest 105: 337-347.

Gertner GZ, Dzialowy PJ (1984) Effects of measurement errors on an individual tree-based growth projection system. Can J Forest Res 14: 311-316. https://doi.org/10.1139/x84-057 DOI: https://doi.org/10.1139/x84-057

Golden MS, Meldahl R, Knowe SA, Boyer WD (1981) Predicting site index for old-field loblolly pine plantations. South J Appl For 5: 109-114. https://doi.org/10.1093/sjaf/5.3.109 DOI: https://doi.org/10.1093/sjaf/5.3.109

Gregory GR (1987) Resource Economics for Foresters. John Wiley & Sons, Inc. New York: 477 p.

Guo J (2022) Louisiana Stumpage Report - Fourth Quarter 2021. LSU AgCenter Research & Extension, Staff Report #2022-11. Baton, Rouge, LA.

Haywood JD, Tiarks AE (2002) Response of Second-Rotation Southern Pines to Fertilizer and Planting on Old Beds--Fifteenth-Year Results. Gen. Tech. Rep. SRS 48. Asheville, NC: USDA Forest Service, Southern Research Station. p 497-502.

Jokela EJ, Martin TA, Vogel JG (2010) Twenty-five years of intensive forest management with southern pines: important lessons learned. J Forest 108: 338-347.

Kangas A, Mehtätalo L, Mäkinen A, Vanhatalo K (2011) Sensitivity of harvest decisions to errors in stand characteristics. Silva Fenn 45: 693-709. https ://doi.org/10.14214 /sf.100. https://doi.org/10.14214/sf.100 DOI: https://doi.org/10.14214/sf.100

Keyser CE; comp. (2008) (revised September 2018) Southern (SN) Variant Overview - Forest Vegetation Simulator. Internal Rep. Fort Collins, CO: USDA Forest Service, Forest Management Service Center. 80 p.

Lee YJ, Coble DW (2006) A new diameter distribution model for unmanaged loblolly pine plantations in East Texas. South J Appl For 30: 13-20. https://doi.org/10.1093/sjaf/30.1.13 DOI: https://doi.org/10.1093/sjaf/30.1.13

Lenhart JD, Hunt EV, Blackard JA (1986) Site index equations for loblolly and slash pine plantations on non-old-fields in East Texas. South J Appl For 10: 109-112. https://doi.org/10.1093/sjaf/10.2.109 DOI: https://doi.org/10.1093/sjaf/10.2.109

McKeand SE, Jokela EJ, Huber DA, Byram TD, Allen HL, Li B, Mullin TJ (2006) Performance of improved genotypes of loblolly pine across different soils, climates, and silvicultural inputs. Forest Ecol Manag 227: 178-184. https://doi.org/10.1016/j.foreco.2006.02.016 DOI: https://doi.org/10.1016/j.foreco.2006.02.016

McKeand SE, Payn KG, Heine AJ, Abt RC (2021) Economic significance of continued improvement of loblolly pine genetics and its efficient deployment to landowners in the southern United States. J Forest 119: 45-55. https://doi.org/10.1093/jofore/fvaa044 DOI: https://doi.org/10.1093/jofore/fvaa044

McRoberts RE, Hahn JT, Hefty GJ, Van Cleve Jr (1994) Variation in forest inventory field measurements. Can J Forest Res 24: 1766-1770. https://doi.org/10.1139/x94-228 DOI: https://doi.org/10.1139/x94-228

MacFarlane DW, Green EJ, Burkhart HE (2000) Population density influences assessment and application of site index. Can J Forest Res 30: 1472-1475. https://doi.org/10.1139/x00-079 DOI: https://doi.org/10.1139/x00-079

Maggard A (2021) Costs & Trends of Southern Forestry Practices 2020. Alabama Cooperative Extension System, Alabama A&M and Auburn Universities, Auburn, AL, FOR 2115. 6 p.

Mason GN, Lorio PL, Belanger RP, Nettleton WA (1985) Rating the susceptibility of stands to southern pine beetle attack. USDA Forest Service Agriculture Handbook No. 637, Cooperative State Research Service, Washington, DC. 31 p.

Reineke LH (1933) Perfecting a stand-density index for even-aged forests. Journal of Agricultural Research 46: 627- 638.

Ritchie M, Zhang J, Hamilton T (2012) Effects of stand density on top height estimation for ponderosa pine. West J Appl For 27: 18-24. https://doi.org/10.1093/wjaf/27.1.18 DOI: https://doi.org/10.1093/wjaf/27.1.18

Ruotsalainen R, Pukkala T, Kangas A, Packalen P (2021) Effects of errors in basal area and mean diameter on the optimality of forest management prescriptions. Ann Forest Sci 78: 18. https://doi.org/10.1007/s13595-021-01037-4 DOI: https://doi.org/10.1007/s13595-021-01037-4

Sharma M, Amateis RL, Burkhart HE (2002) Top height definition and its effects on site index determination in thinned and unthinned loblolly pine plantations. Forest Ecol Manag 168: 163-175. https://doi.org/10.1016/S0378-1127(01)00737-X DOI: https://doi.org/10.1016/S0378-1127(01)00737-X

Subedi P, Jokela EJ, Vogel JG, Martin TA (2014) Inter-rotational effects of fertilization and weed control on juvenile loblolly pine productivity and nutrient dynamics. Soil Sci Soc Am J 78(S1): S152-S167. https://doi.org/10.2136/sssaj2013.08.0345nafsc DOI: https://doi.org/10.2136/sssaj2013.08.0345nafsc

Tiarks AE, Haywood JD (1996) Site preparation and fertilization effects on growth of slash pine for two rotations. Soil Sci Soc Am J 60: 1654-1663. https://doi.org/10.2136/sssaj1996.03615995006000060008x DOI: https://doi.org/10.2136/sssaj1996.03615995006000060008x

USDA Forest Service (2022) Forest Inventory and Analysis National Core Field Guide: Volume I: Field Data Collection Procedures for Phase 2 Plots; Version 9.2. 529 p. https://www.fia.fs.usda.gov/library/field-guides-methods-proc/docs/2022/core_ver9-2_9_2022_SW_HW%20table_rev_12_13_2022.pdf

VanderSchaaf CL, Burkhart HE (2012) Development of planting density-specific density management diagrams for loblolly pine. South J Appl For 36: 126-129. https://doi.org/10.5849/sjaf.10-043 DOI: https://doi.org/10.5849/sjaf.10-043

Yáñez MA, Fox TR, Seiler JR (2017) Silvicultural intensity and site effects on stand uniformity of loblolly pine varieties and families. Forest Sci 63(6): 606-613. https://doi.org/10.5849/FS-2016-036R2 DOI: https://doi.org/10.5849/FS-2016-036R2

Zarnoch SJ, Feduccia DP (1984) Slash pine plantation site index curves for the West Gulf. South J Appl For 8: 223-225. https://doi.org/10.1093/sjaf/8.4.223 DOI: https://doi.org/10.1093/sjaf/8.4.223

Zhai L, Jokela, EJ, Gezan, SA, Vogel, JG (2015) Family, environment and silviculture effects in pure-and mixed-family stands of loblolly (Pinus taeda L.) and slash (P. elliottii Engelm. var. elliotttii) pine. Forest Ecol Manag 337: 28-40. https://doi.org/10.1016/j.foreco.2014.10.030 DOI: https://doi.org/10.1016/j.foreco.2014.10.030

Zhang D, Pearse PH (2012) Forest Economics. UBC Press, Vancouver, BC: 1st ed, 390 p. https://doi.org/10.59962/9780774821544 DOI: https://doi.org/10.59962/9780774821544

Downloads

Published

2023-12-29

Issue

Section

Articles

How to Cite

“Implications of Incorrectly Determining Site Index on Stand-Level Management Activities and Financial Returns in Older Generation Loblolly Pine Plantations”. REFORESTA, no. 16 (December 29, 2023): 1–15. Accessed May 20, 2024. https://journal.reforestationchallenges.org/index.php/REFOR/article/view/179.