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Olanipon, D. G.

Publications and source records attributed to Olanipon, D. G..

2 recordsLinked to original sources

Arbuscular mycorrhizal fungal diversity and association networks in African tropical rainforest trees

Tropical rainforests represent one of the most diverse and productive ecosystems on Earth. High productivity is sustained by efficient and rapid cycling of nutrients through decomposing organic matter, which is for a large part made possible by symbiotic associations between plants and mycorrhizal fungi. In this association, an individual plant typically associates simultaneously with multiple fungi and the fungus associates with multiple plants, creating complex networks between fungi and plants. However, there are still very few studies that have investigated mycorrhizal fungal composition and diversity in tropical rainforest trees, particularly in Africa, and assessed the structure of the network of associations between fungi and rainforest trees. In this study, we collected root and rhizosphere soil samples from Ise Forest Reserve (Southwest Nigeria), and employed a metabarcoding approach to identify the dominant arbuscular mycorrhizal (AM) fungal taxa associating with ten co-occurring tree species and to assess variation in AM communities. Network analysis was used to elucidate the architecture of the network of associations between fungi and tree species. A total of 194 AM fungal Operational Taxonomic Units (OTUs) belonging to six families were identified, with 68% of all OTUs belonging to Glomeraceae. While AM fungal diversity did not differ between tree species, AM fungal community composition did. Network analyses showed that the network of associations was not significantly nested and showed a relatively low level of specialization (H2 = 0.43) and modularity (M = 0.44). We conclude that, although there were some differences in AM fungal community composition, the studied tree species associate with a large number of AM fungi. Similarly, most AM fungi had a large host breadth and connected most tree species to each other, thereby potentially working as interaction network hubs. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/578868v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@4573ecorg.highwire.dtl.DTLVardef@1bd9974org.highwire.dtl.DTLVardef@a598ccorg.highwire.dtl.DTLVardef@1d27b76_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

Tree Species as Biomonitors of Air Pollution around a Scrap Metal Recycling Factory in Southwest Nigeria: Implications for Greenbelt Development

Trees are biomonitors and sinks for air pollutants but better sinking ability comes from trees with high tolerance for air pollution. Consequently, this study investigated the Air Pollution Tolerance Index (APTI) and Anticipated Performance Index (API) of six dominant tree species around a scrap metal recycling factory in Ile-Ife, Southwest Nigeria. Biochemical and physiological parameters such as the relative water content, total chlorophyll, leaf extract pH and ascorbic acid content of the leaves of the selected tree species were determined and used to compute the APTI. The biological and socio-economic characters of each tree species were equally examined to determine the API. The APTI of the selected tree species during the dry season was in the N. laevis (11.8) > A. boonei (11.2) > S. siamea (11.0) > B. micrantha (10.8) > T. orientalis (10.6) > T. grandis (9.6). According to the API grading, N. laevis and A. boonei were classified as "good" (62.5% each) tree species for greenbelt development for both dry and wet seasons, while T. orientalis was also classified as a "good" (62.5% each) tree species for greenbelt development for the wet season only. Native tree species such as N. laevis, A. boonei and T. orientalis exhibited better tolerance to gaseous pollutants and are recommended for biomonitoring environmental health and greenbelt establishment.

plant biology↗