Changes in Environmental Variables on Site Index of Teak (Tectona grandis) in West Africa Stephen Adu-Bredu CSIR-FORESTRY RESEARCH INSTITUTE OF GHANA

Introduction Teak (Tectona grandis) is native to South Asia. Introduced into West Africa in the early 1900s. First Teak plantation in Ghana in 1905 Teak has gained a world wide reputation on account of attractiveness and wood durability. Teak does well in all the ecological zones in Ghana. Moist/Wet Evergreen, Moist Semi-deciduous, Dry Semi-deciduous Forests and Savannah.

Export of Teak Products (m 3 ) 2006 (4 th )2007 (1 st ) Lumber (KD) Lumber (AD)46, , Lumber (Overland)5.663 Sliced Veneer Poles15, , Pegs23.88 Billet7, , Boules (AD) Furniture Parts Flooring Broomstick Total69, ,

Introduction: Cont. There is the need to; Analyse the effects of site and silvicultural regimes on growth, stem form and wood quality Provide growth, stem form and wood quality prediction models Determine ecoclimatic suitable zones for economically and ecologically suitable teak plantations

Introduction: Cont. Site Productive Capacity Total stand biomass produced by stand when all resource available for tree growth from a site have been fully utilised, up to any stage in development It indicates maximum amount of wood Stand dominant height reflects productive capacity Dominant height is not affected by stocking density Stand dominant height at a particular age is termed “Site Index”.

Objectives To develop height growth model for Teak To determine Site Index of Teak To predict Site Index from environmental variables Sampling: Requires Data from permanent sample plots Ring analysis was carried out to retrieve height growth

Two main definitions SI age_ref = Dominant height at a given reference age SI age-ref Age ref Dominant Height (m) Age SI age_infinity = Maximum Dominant height that can be reached SI age_infinity

At the same reference age, SI of stand 2 is higher than SI of stand 1. Stand 2 will provide a higher MAI than stand 1 if appropriate silviculture are applied SI stand1 Age ref Dominant Height (m) Age SI stand2 Two stands of different Site Productive Capacity (combination of climate and soil properties)

Candidate growth functions FunctionEquation Chapman-RichardHt = a(1 - exp (-bt) ) c GompertzHt = a(exp -b exp(-ct) ) LogisticHt = a/(1 + c exp –bt ) KorfHt = a(exp -bt-c ) HossfeldHt = t c (b + t c/a )

Distribution of the sampled trees (Ghana) Ecozone Age Class (Years) Total MEF MSDF DSDF Savannah Total

Distribution of sampled trees (Cote d’Ivoire) EcozoneAge Class (Years) Total MEF MSDF DSDF Savannah Total

Distribution of the sample plots in Ghana

Data collected from each TSP Geographical Position Elevation Slope Current stocking (Trees ha -1 ) Canopy Closure Individual Tree height Individual Stem diameter at breast height (1.3m) Crown base height Soil samples collected up to 20cm depth Rainfall Amount Rainy Days Maximum and Minimum Temperatures

Destructive sampling

H = HS1 + {(HS2 – HS1)/(Nb1 – Nb2 +1)}

Performance of the candidate functions with respect to SE and RMSE FunctionabcRMSE Chapman- Richard (0.5247) (0.0240) (0.1121) Gompertz12.72 (0.3335) (0.1026) (0.0223) Logistic12.33 (0.2852) (0.0308) (0.6439) Korf20.34 (2.7097) (0.1260) (0.0918) Hossfeld15.63 (1.0524) (0.0745) (0.1200)

Prediction of stand dominant height Ht1 = a(1 - exp (-bt1) ) c Ht2 = a(1 - exp (-bt2) ) c Ht2 = Ht1 {(1 - exp (-bt2) )/(1 - exp (-bt1) )} c Phytocentric Site Index N = (sampled area / 100) – 1 SI = H0 /(1 - exp (-bt) ) c

Relationship between SI and Stand age

Relationship between SI and Stand Density

Correlation of Site Index with climatic and soil variables Climatic variables Edaphic variables VariableRelationshipR2R2 VariableRelationshipR2R2 DSRFPower0.5070NitrogenPower LatitudePower0.4170Organic MatterPower Max TempExponential0.3684Organic CarbonPower RainfallLogarithmic0.3160ClayPower SlopePolynomial0.3054C-N RatioExponential CanopyPower0.2800CECPower WSRFPolynomial0.1960CaPower R. DaysPolynomial TEBPower0.2001

Geocentric Site Index: Principal Component Analysis

Stepwise Multiple Regression Models of Site Index on environmental variables VariablesModelMultiple Regression EquationR2R2 RMSE DSRF, MTEMPGLMSI = DSRF MTEMP NLIN SI = (7.69x10 -8 DSRF ) + (706.4exp ( MTEMP ) ) DSRF, MTEMP, CaGLM SI = DSRF MTEMP Ca NLIN SI = (4.795x10 -8 DSRF ) + (605.4exp ( MTEMP ) ) + (1.5121Ca ) DSRF, MTEMP, Ca, CNRatioGLM SI = DSRF MTEMP Ca CNRatio NLIN SI = (1.257x10 -6 DSRF ) + (2500exp ( MTEMP ) ) + (0.2001Ca ) + (53.36exp ( CNRatio ) )

Conclusions Height growth curve have been developed for teak in West Africa Height growth can thus be predicted for teak Phytocentric SI has been developed SI can be predicted from climatic and edaphic variables even if teak plantation has not be established at that site What needs to be done is to verify the height growth curve prediction from independent data set.