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Parameter testing and application of the 3PG model for Eucalyptus grandis x urophylla on the Zululand coastal plain, South Africa

Thesis (MSc) -- Stellenbosch University, 2021.

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Main Author: Gakenou, Oluwaseun
Other Authors: Drew, David M.
Format: Thesis
Language:en_ZA
Published: Stellenbosch : Stellenbosch University 2021
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access_status_str Open Access
author Gakenou, Oluwaseun
author2 Drew, David M.
author_browse Drew, David M.
Gakenou, Oluwaseun
author_facet Drew, David M.
Gakenou, Oluwaseun
author_sort Gakenou, Oluwaseun
collection Thesis
dc_rights_str_mv Stellenbosch University
description Thesis (MSc) -- Stellenbosch University, 2021.
format Thesis
id oai:scholar.sun.ac.za:10019.1/124237
institution Stellenbosch University (South Africa)
language en_ZA
last_indexed 2026-06-10T12:47:09.638Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2021
publishDateRange 2021
publishDateSort 2021
publisher Stellenbosch : Stellenbosch University
publisherStr Stellenbosch : Stellenbosch University
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source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/124237 Parameter testing and application of the 3PG model for Eucalyptus grandis x urophylla on the Zululand coastal plain, South Africa Gakenou, Oluwaseun Drew, David M. Germishuizen, Ilaria Stellenbosch University. Faculty of AgriSciences. Dept. of Forest and Wood Science. Eucalyptus grandis -- South Africa -- Zululand Calibration Spatial interpolation Interpolation Commercial forests Thesis (MSc) -- Stellenbosch University, 2021. ENGLISH ABSTRACT: This study aims to calibrate the 3PG (Physiological Processes Predicting Growth) model for Eucalyptus grandis x urophylla growing in the coastal Zululand region, South Africa. Parameter values developed for this hybrid across regions in Brazil were used as baseline parameters. To generate a set of reliable point estimates of weather data for growth modelling, we evaluated the performance of two spatial interpolation techniques (Random Forest and the R package “Meteoland”) using Mean Absolute Error, Root Mean Square Error, Coefficient of Determination, Index of Agreement and Nash Sutcliffe Model Efficiency Index. We collected observed long term weather data from the South African Weather Services (SAWS) and the South African Sugarcane Research Institute (SASRI). Weather stations spread across the KwaZulu-Natal region were used for the performance analysis. Both models showed great potential. However, the Random Forest model was the best performing model used to generate weather data in this study for growth modelling. Parameter estimation of the model was based on 17 permanent sample plots (PSPs) managed by two forestry companies, Mondi Ltd and Sappi Ltd. Allometric parameters for stem mass as a function of stem diameter at breast height were calibrated using biomass harvest data from sampling undertaken in 2018. Eleven parameters were selected from the list of base parameters to be adjusted using a parsimonious optimization approach. A novel method for ranking the parameter set combinations, called extended Root Mean Square Error (eRMSE), was created and used to select the optimal parameter set. Using the new parameter set resulted in good predictions of three key output variables (Mean stand height (H, m), stand basal area (BA, m2 /ha), and mean stem diameter at breast height (DBH, cm)) which were then used to calculate stand volume (V, m3 /ha). Model performance at 15 independent validation sites allowed the comparison with three other Brazilian parameter sets. Overall, the 3PG model gave a good but slightly overestimated stand volume prediction at the validation sites. We compared the 3PG model with three simpler models. The forest companies’ statistical growth and yield models outperformed all other models in terms of all metrics used, followed by a very simple model using the cumulative rainfall model. Although the 3PG gave similar growth predictions, it demonstrates its usefulness in simulating growth patterns in response to environmental changes. AFRIKAANS OPSOMMING: "Geen opsomming biskikbaar" Masters 2021-12-06T10:01:21Z 2022-02-22T10:19:23Z 2021-12-06T10:01:21Z 2021-12 Thesis http://hdl.handle.net/10019.1/124237 en_ZA Stellenbosch University v, 95 pages application/pdf Stellenbosch : Stellenbosch University
spellingShingle Eucalyptus grandis -- South Africa -- Zululand
Calibration
Spatial interpolation
Interpolation
Commercial forests
Gakenou, Oluwaseun
Parameter testing and application of the 3PG model for Eucalyptus grandis x urophylla on the Zululand coastal plain, South Africa
title Parameter testing and application of the 3PG model for Eucalyptus grandis x urophylla on the Zululand coastal plain, South Africa
title_full Parameter testing and application of the 3PG model for Eucalyptus grandis x urophylla on the Zululand coastal plain, South Africa
title_fullStr Parameter testing and application of the 3PG model for Eucalyptus grandis x urophylla on the Zululand coastal plain, South Africa
title_full_unstemmed Parameter testing and application of the 3PG model for Eucalyptus grandis x urophylla on the Zululand coastal plain, South Africa
title_short Parameter testing and application of the 3PG model for Eucalyptus grandis x urophylla on the Zululand coastal plain, South Africa
title_sort parameter testing and application of the 3pg model for eucalyptus grandis x urophylla on the zululand coastal plain south africa
topic Eucalyptus grandis -- South Africa -- Zululand
Calibration
Spatial interpolation
Interpolation
Commercial forests
url http://hdl.handle.net/10019.1/124237
work_keys_str_mv AT gakenouoluwaseun parametertestingandapplicationofthe3pgmodelforeucalyptusgrandisxurophyllaonthezululandcoastalplainsouthafrica