On the development and application of indirect site indexes based on edaphoclimatic variables for commercial forestry in South Africa
Masters Degrees (Forest and Wood Science)
Esler, William Kevin
Stellenbosch University. Faculty of AgriSciences. Dept. of Forest and Wood Science.
Thesis (MScFor)--Stellenbosch University, 2012.
ENGLISH ABSTRACT: Site Index is used extensively in modern commercial forestry both as an indicator of current and future site potential, but also as a means of site comparison. The concept is deeply embedded into current forest planning processes, and without it empirical growth and yield modelling would not function in its present form. Most commercial forestry companies in South Africa currently spend hundreds of thousands of Rand annually collecting growth stock data via inventory, but spend little or no money on the default compartment data (specifically Site Index) which is used to estimate over 90% of the product volumes in their long term plans. A need exists to construct reliable methods to determine Site Index for sites which have not been physically measured (the socalled "default", or indirect Site Index). Most previous attempts to model Site Index have used multiple linear regression as the model, alternative methods have been explored in this thesis: Regression tree analysis, random forest analysis, hybrid or model trees, multiple linear regression, and multiple linear regression using regression trees to identify the variables. Regression tree analysis proves to be ideally suited to this type of data, and a generic model with only three site variables was able to capture 49.44 % of the variation in Site Index. Further localisation of the model could prove to be commercially useful.
One of the key assumptions associated with Site Index, that it is unaffected by initial planting density, was tested using linear mixed effects modelling. The results show that there may well be role played by initial stocking in some species (notably E. dunnii and E. nitens), and that further work may be warranted. It was also shown that early measurement of dominant height results in poor estimates of Site Index, which will have a direct impact on inventory policies and on data to be included in Site Index modelling studies.
This thesis is divided into six chapters: Chapter 1 contains a description of the concept of Site Index and it's origins, as well as, how the concept is used within the current forest planning processes. Chapter 2 contains an analysis on the influence of initial planted density on the estimate of Site Index. Chapter 3 explores the question of whether the age at which dominant height is measured has any effect on the quality of Site Index estimates. Chapter 4 looks at various modelling methodologies and compares the resultant models. Chapter 5 contains conclusions and recommendations for further study, and finally Chapter 6 discusses how any new Site Index model will effect the current planning protocol.
AFRIKAANSE OPSOMMING: Hedendaagse kommersiële bosbou gebruik groeiplek indeks (Site Index) as 'n aanduiding van huidige en toekomstige groeiplek moontlikhede, asook 'n metode om groeiplekke te vergelyk. Hierdie beginsel is diep gewortel in bestaande beplanningsprosesse en daarsonder kan empiriese groeien opbrengsmodelle nie in hul huidige vorm funksioneer nie. SuidAfrikaanse bosboumaatskappye bestee jaarliks groot bedrae geld aan die versameling van groeivoorraad data deur middel van opnames, maar weinig of geen geld word aangewend vir die insameling van ongemete vak data (veral groeiplek indeks) nie. Ongemete vak data word gebuik om meer as 90% van die produksie volume te beraam in langtermyn beplaning. 'n Behoefte bestaan om betroubare metodes te ontwikkel om groeiplek indeks te bereken vir groeiplekke wat nog nie opgemeet is nie. Die meeste vorige pogings om groeiplek indeks te beraam het meervoudige linêre regressie as model gebruik. Alternatiewe metodes is ondersoek; naamlik regressieboom analise, ewekansige woud analise, hibriedeof modelbome, meervoudige linêre regressie en meervoudige linêre regressie waarin die veranderlike faktore bepaal is deur regressiebome. Regressieboom analise blyk geskik te wees vir hierdie tipe data en 'n veralgemeende model met slegs drie groeiplek veranderlikes dek 49.44 % van die variasie in groeiplek indeks. Verdere lokalisering van die model kan dus van kommersiële waarde wees.
'n Sleutel aanname is gemaak dat aanvanklike plantdigtheid nie 'n invloed op groeiplek indeks het nie. Hierdie aanname is getoets deur linêre gemengde uitwerkings modelle. Die toetsuitslag dui op 'n moontlikheid dat plantdigtheid wel 'n invloed het op sommige spesies (vernaamlik E. dunnii en E. nitens) en verdere navorsing kan daarom geregverdig word. Dit is ook bewys dat metings van jonger bome vir dominante hoogtes gee aanleiding tot swak beramings van groeiplek indekse. Gevolglik sal hierdie toestsuitslag groeivoorraad opname beleid, asook die data wat vir groeiplek indeks modellering gebruik word, beïnvloed.
Hierdie tesis word in ses hoofstukke onderverdeel. Hoofstuk een bevat 'n beskrywing van die beginsel van groeiplek indeks, die oorsprong daarvan, asook hoe die beginsel tans in huidige bosbou beplannings prosesse toegepas word. Hoofstuk twee bestaan uit ń ontleding van die invloed van aanvanklike plantdigtheid op die beraming van groeplek indeks. In hoofstuk drie word ondersoek wat die moontlike invloed is van die ouderdom waarop metings vir dominante hoogte geneem word, op die kwaliteit van groeplek indeks beramings het. Hoofstuk vier verken verskeie modelle metodologieë en vergelyk die uitslaggewende modelle. Hoofstuk vyf bevat gevolgtrekkings en voorstelle vir verdere studies. Afsluitend, is hoofstuk ses ń bespreking van hoe enige nuwe groeiplek indeks modelle die huidige beplannings protokol kan beïnvloed.
148 p. ; ill.
Stellenbosch : Stellenbosch University
Indirect site index
Initial planting density -- South Africa
Random forests -- South Africa
Hybrid model trees -- South africa
Dissertations -- Forest and wood science
Theses -- Forest and wood science
Forest and Wood Science
Masters Degrees (Forest and Wood Science)