Mapping and Assessment of Ethno-Medicinal Trees in Built Up Areas - University of Port Harcourt, Nigeria

• Main Authors: Olatunde Sunday Eludoyin, Adekunle Tajudeen Oladele, Oluwatosin Muhibudeen Iyanda
• Format: Article
• Language: English
• Published: Croatian Forest Research Institute 2015-06-01
• Series: South-East European Forestry
• Subjects: geographic information systems; nearest neighbour analysis; urban forestry; species diversity; species richness; species evenness
• Online Access: http://www.seefor.eu/vol-6-no-1-eludoyin-et-al-mapping-and-assessment.html

Background and Purpose: Several urban tree species are important in ethno-medicine, especially in the developing tropical regions. Their assessment in urban landscapes is becoming an important issue. The study assessed and mapped the ethno-medicinal trees in the built up area land use type of the University of Port Harcourt, Nigeria, with a view to examining their spatial variation in terms of composition and diversity between the residential and non-residential areas of the University Park. Materials and Methods: The study employed the use of geographic information system (ArcGIS 9.3) for the mapping. Built up area land use was subdivided into residential and non-residential where the ethno-medicinal trees were recorded, identified and enumerated. Global positioning system was used to determine the coordinates of each tree. The species composition and diversity were calculated and a comparison was made between the residential and non- residential land use types. The pattern of spread of the ethno-medicinal trees was determined by the nearest neighbour analysis. Results: A total of 37 ethno-medicinal trees species were found in the study area, while the species composition was 499 in the residential area and 438 in the non-residential area. Azadirachta indica was the highest (233) in composition. Ethno-medicinal tree species in the study area consist of 19 families of which Anacardiaceae, Rutaceae, Moraceae and Combretaceae were the highest. Species diversity was higher in the non-residential land use (2.698) than in the residential land use (2.222). Conclusion: The nearest neighbour analysis reveals that the z-score value was higher in the non-residential area (-23.06) than in the residential area (-0.30), but the pattern of distribution in both areas were clustered. The study recommended periodic monitoring and the assessment of ethno-medicinal trees in the study area for conservation purposes.