2019, VOLUME 6 ISSUE 3Pages: 376-392
Efficient protocol of complete inventory for tree regeneration and recruitment studies over one hectare in selected tropical natural forests, Kenya
Joseph Hitimana*, James Legilisho Ole Kiyiapi and Balozi Kirongo Bekuta
*University of Eldoret; P.O.Box. 1125 Eldoret 30100
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This study sought to establish an efficient inventory protocol to estimate regeneration stock and dynamics in natural forests. Field and computer outputs were integrated to develop complete inventory protocol for selected natural forest types in Kenya. Inventory cost and precision for four plot sizes (5 m × 5 m, 10 m × 5 m, 10 m × 10 m and 20 m × 20 m) were determined and compared. Specific objectives were to determine (i) precision levels of estimating tree seedling density using different plot sizes across forest types; and (ii) optimum plot size which minimise both sampling error and inventory effort for use in each forest type. Seedling counts and time taken per plot were recorded systematically over 400, 200, 100 and 25 plots ha-1 for the respective plot sizes. Larger plots and their data were created by merging smaller ones through programming with R Software. Smallest population mean-variance, was obtained using data from 5 m x 5 m plots. Both precision and inventory effort varied with plot size used, but in reverse directions. Seedlings population mean errors were 15.4% of the mean for rain forest, 14.7% for moist montane forest and 9.9 % for dry forest type. Inventory cost decreased with increasing data compilation unit size, e.g., 50.42 hrs ha-1 for 25 m2 unit to 3.21 hrs ha-1 for 400 m2 unit in rainforest. Similar trend was observed in other forest types. Recommended plot sizes for tree seedlings are 75 m2; 62.4 m2 and 88.4 m2 for Kakamega rain forest, Mt Elgon montane forest and Loruk dry woodland forest, respectively. These plot sizes gave acceptable uncertainty levels between ±11% and ±17% of mean estimate ha-1. Tree diameter distributions from 5 m x 5 m plots revealed that tree component recruitment was irregular over time across forest types.