Tree Species Richness, Basal Area and Volume along Different Land Use Gradient of Maasai Semi-arid of Longido District, Tanzania
DOI:
https://doi.org/10.63002/gres.404.1668Keywords:
basal area, land use gradient, richness, semi-arid, tree species, volumeAbstract
This study focused on tree species richness (S), basal area (g) and volume (G) along different land use gradient of Maasai semi-arid of Longido District. Nine (9) transects of 500 m were established at different land use strata ((i) abandoned boma (AB), (ii) active boma (ACB), and (iii) traditionally reserved land for pasture (TRLP) ), in which 54, 20 m x 20 m plots were set. Habitats were described. All trees with DBH (cm) at 1.3 m from ground, together with their heights were measured and recorded for their botanical and Maasai names. Richness was read from the overall recorded trees from sampled sites. Trees basal area and volume were calculated across land use strata. ANOVA was used to test if the means of the three land use data groups were significantly different. A total of 20 tree species were recorded, most of them being from TRLP, followed by AB, and ACT was the least. The largest g (15,019.85) and G (31.891) were recorded at AB, followed by TRLP (g = 12,486.89 and G = 27,909.5). However, the mean sum of g (MSg) was led by ACB (MSg = 121), followed by AB (MSg = 62), and TRLP was the least (MSg/Ha = 45), while the MSG was led by AB (MSG/Ha = 132.88), followed by ACB (MSG/Ha = 121), and TRLP (MSG/Ha = 100.76). ANOVA results (p-value = 0.0000008 with the F – value of 2.65972), led to rejection of null hypothesis, revealing significant differences in richness, SST, g, and G of trees within different land use gradient. Semi-arid areas of Longido district encompass woody resources that needs to be scientifically recognized. Further study is required to reveal all forms of plants, sustainable utilization of resources is encouraged, livestock fodder plants have to be evaluated, and woody resource management strategies are required.
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Copyright (c) 2026 Canisius John Kayombo, Mhoza M. Felix, Aitor Burguet-Coca, Isabel Exposito, Llorenç Picornell-Gelabert, Ethel Allué

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