Forestry

Background and Purpose: Nigeria is greatly endowed with numerous tree species of which majority of them are native while few are exotic. Report shows that high percentage of man-made forests in the country is dominated with exotic species. This culminated from the assumption that exotic trees are fast growing. However, this study investigated the growth of indigenous trees in tandem with that of exotic species with a purpose to clarify the assumption about the growth and conservation of indigenous species in natural forests. Materials and Methods: The study was conducted at the nursery unit of the Department of Forest Resources Management, University of Ibadan, Nigeria. Five (5) different one year old tree species seedlings were used for the study. Two of the species (Tectona grandis and Gmelina arborea) are exotic while the other three species (Khaya senegalensis, Khaya grandifolia and Afzelia africana) are native to Nigeria. They were planted on the field in a completely random design and then replicated eight times. Data were collected every month on their height growth, collar diameter and leaf number. Data obtained were subsequently analyzed with ANOVA. Results and Conclusions: Results show that K. grandifolia (45.39 cm) grew significantly better (p<0.05) in height than G. arborea (38.11 cm) and T. grandis (22.36 cm), while A. africana (40.03 cm) closely followed K. grandifolia. Based on the results, the selected indigenous species displayed promising potentials for conservation purpose. Hence, further research in this aspect is encouraged to confirm the findings.

Background and Purpose: Efficient forest stand management requires reliable estimates of growing stock. The reliability of stem volume estimates depends on the range and extent of available sample data. The potentials of canopy layers stratification in pure plantations as a means of improving the accuracy of stem volume equations have not been fully explored. Linear Mixed Model (LMM) approach is a statistical technique capable of yielding a more efficient prediction under clustered data structure. This study investigates the existence and potentials of canopy stratifications for improving the reliability of stem volume prediction equations under pure plantations using linear mixed model approach. Materials and Methods: Pinus caribaea Morelet plantations in Oluwa Forest Reserve, Ondo State, Nigeria were investigated. Individual tree growth variables, including diameters, heights and crown measurements were obtained in 2010 on twenty-five 0.04 ha plots representing five different stands planted between 1979 and 1991. Visual assessment of the trees within each plot was also done to classify them into four canopy strata (i.e. dominant, co-dominant, intermediate and suppressed). Linear mixed model approach was used to analyze the tree growth data using SAS Proc Mixed. Two variants of volume equations; simple linear and exponential were investigated. Results: Results show that simple linear mixed model consistently give better fit criteria (e.g. AIC) of 135.8, 18.9,-214.7 and-174.6 under dominant, co-dominant, intermediate and suppressed canopy layers, respectively. The covariance parameter estimate for dominant canopy (0.2219) is about 370 as large as that of suppressed (0.0006). This implies that canopy layers not only influence stem volume prediction but also reduce within-stand variance as well. Conclusion: Simple linear mixed model produced better fitting criteria in terms of lower values of Akaike's and Bayesian Information Criteria. Canopy stratification in pure stands of Pinus caribaea showed great potentials in improving the predictive ability of volume equations.

Forest timber production potential of any site is oftentimes measured quantitatively by site index, which is defined as dominant height of a particular stand at a specified age. A site index was developed for estimating site quality of monoculture Pinus caribaea plantations in southwestern Nigeria using a base age of 25 years. Dominant height data were collected from 60 Temporary Sample Plots (TSPs) of 20x20 m in plantations of 15 to 37 years. Linear and non-linear models as been widely applied in quantitative forest measurements were fitted to dominant height-age data and the best site index equation is : SI=Exp (InHd-23.495 (A-0.04). The site index curves constructed for the three sites (Omo Forest Reserve-OFR (J4), Oluwa Forest Reserve-OLFR and Shasha Forest Reserve-SFR) across the southwestern Nigeria using the chosen equation revealed that a 15 year old Pinus caribaea in the study area attained average dominant heights of 25, 22 and 21 m in OFR (J4), OLFR and SFR respectively. The site index equation and curves proffer veritable insight into better silvicultural options and management practices for the future plantations suitable sites.

Stem diameter variability is an essential inventory result that provides useful information in forest management decisions. Little has been done to explore the modelling potentials of standard deviation (SDD) and coefficient of variation (CVD) of diameter at breast height (dbh). This study, therefore, was aimed at developing and testing models for predicting SDD and CVD in stands of Pinus caribaea Morelet (pine) in south west Nigeria. Sixty temporary sample plots of size 20 m×20 m, ranging between 15 and 37 years were sampled, covering the entire range of pine in south west Nigeria. The dbh (cm), total and merchantable heights (m), number of stems and age of trees were measured within each plot. Basal area (m 2), site index (m), relative spacing and percentile positions of dbh at 24 th , 63 rd , 76 th and 93 rd (i.e. P24, P63, P76 and P93) were computed from measured variables for each plot. Linear mixed model (LMM) was used to test the effects of locations (fixed) and plots (random). Six candidate models (3 for SDD and 3 for CVD), using three categories of explanatory variables (i.e. (i) only stand size measures, (ii) distribution measures, and (iii) combination of i and ii). The best model was chosen based on smaller relative standard error (RSE), prediction residual sum of squares (PRESS), corrected Akaike Information Criterion (AICc) and larger coefficient of determination (R 2). The results of the LMM indicated that location and plot effects were not significant. The CVD and SDD models having only measures of percentiles (i.e. P24 and P93) as predictors produced better predictions than others. However, CVD model produced the overall best predictions, because of the lower RSE and stability in measuring variability across different stand developments. The results demonstrate the potentials of CVD in modelling stem diameter variability in relationship with percentiles variables.

Oban Forest health was assessed using tree slenderness coefficient (SC) and percent canopy cover as indicators. Systematic sampling technique was adopted for plot locations in Aking , Ekang , Erokut and Ekuri sites within the forest. Four transects of 2 km-long situated 600 m apart were established in each site. Five 0.25ha-plot were then alternately laid along each transect at 400 m intervals. A total of 20 plots per site, and 80 plots in all were used. Tree heights, Dbh and crown diameter were measured on trees with Dbh≥10cm to compute SC and percent canopy cover (%CC). Trees were classified based on their SC as high (SC&gt;80), moderate (SC: 70-80 and low (SC&lt;70). Data were analyzed using descriptive statistics and correlation analysis. There were 36, 49 and 67 trees/ha with high, moderate and low SC, respectively for the pooled data with 56.5% CC. On site basis, Aking had 145 trees/ha, and of these, 44, 45 and 56 trees/ha had high, moderate and low SC, respectively. Ekang had...

Crown ratio is the ratio of live crown length to tree height. It is often used as an important predictor variable for tree growth equation. It indicates tree vigor and is a useful parameter in forest health assessment. The objective of the study was to develop crown ratio prediction models for Tectona grandis. Based on the data set from the temporary sample plots, several non linear equations including logistics, Chapman Richard and exponential functions were tested. These functions were evaluated in terms of coefficient of determination (R 2) and standard error of the estimate (SEE). The significance of the estimated parameters was also verified. Plot of residuals against estimated crown ratios were observed. Although the logistic model had the highest R 2 and the least SEE, Chapman-Richard and Exponential functions were observed to be more consistent in their predictive ability; and were therefore recommended for predicting crown ratio in the stand.

The use of synthetic molecules to achieve specific goals is steadily increasing in the environment, and these molecules adversely impact human health and ecosystem services. Considering the adverse effects, a better understanding of how these molecules behave in the environment and their associated risks is necessary to keep their use acceptably limited. To meet the demands of farmers and combat weed problems, woodlands and farmlands are sprayed with agrochemicals, primarily glyphosate-based herbicides. Farmers increasingly embrace these herbicides containing glyphosate. Glyphosate and aminomethylphosphonic acid (AMPA), a key metabolite of glyphosate, have been reported as toxicological concerns when they become more prevalent in the food chain. The chemical glyphosate has been linked to various health issues in humans and other living organisms, including endocrine disruption, reproductive issues, tumours, non-Hodgkin lymphomas, and liver, heart, and blood problems. Therefore, the ...

Stem diameter distribution information is useful in forest management planning. Weibull function is flexible, and has been used in characterising diameter distributions, especially in single-species planted stands, the world over. We evaluated some Weibull parameter estimation methods for stem diameter characterisation in (Oban) multi-species Forest in southern Nigeria. Four study sites (Aking, Ekang, Erokut and Ekuri) were selected. Four 2 km-long transects situated at 600 m apart were laid in each location. Five 50m × 50m plots were alternately laid along each transect at 400 m apart (20 plots/location) using systematic sampling technique. Tree growth variables: diameter at breast height (Dbh), diameters at the base, middle and merchantable limit, total height, merchantable height, stem straightness, crown length and crown diameter were measured on all trees ≥ 10 cm to compute model response variables such as mean diameters, basal area and stem volume. Weibull parameters estimation methods used were: moment-based, percentile-based, hybrid and maximum-likelihood (ML). Data were analysed using descriptive statistics, regression models and ANOVA at α 0.05. Percentile-based method was the best for Weibull [location (a), scale (b) and shape (c)] parameters estimations with mLogL = 116.66±21.89, while hybrid method was least-suitable (mLogL = 690.14±128.81) for Weibull parameters estimations. Quadratic mean diameter (D q) was the only suitable predictor of Weibull parameters in Oban Forest.