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1.
Ecol Evol ; 12(6): e8961, 2022 Jul.
Article in English | MEDLINE | ID: mdl-35784038

ABSTRACT

Research on fern ecology has gained attention in the last decade, yet there is a paucity of information on the comparison of ferns communities across continents. This study focused on comparing the ferns community assemblages in some tropical forests of Malaysia and Nigeria, thereby assessing the patterns of species richness (SR) and phylogenetic diversity (PD) in relation to the bioclimatic drivers across the continents. The diversity and taxonomic compositions of ferns were assessed using 180 plots of 10 m × 10 m in each country. The species richness and other diversity indices were determined using the combined forests data for each country and for the individual forests. Also, the phylogenetic diversity of the ferns was assessed using the genus-based molecular sequences downloaded from the GeneBank. The patterns of the ferns SR and PD in the two countries as driven by some bioclimatic factors were evaluated using the regression analysis. The observed and rarefied-extrapolated fern species richness is significantly higher in Malaysian forests than in Nigerian forests. Also, the other diversity indices are significantly higher in Malaysian forests except for the Shannon index which showed no significant difference between the two biogeographic regions. There is a very low similarity (7.41%) in the taxonomic composition of ferns between the two biogeographic areas, although the similarity in composition increased with increasing taxonomic levels (species: 7.41%, genus: 12.77%, family: 70.96%). Terrestrial and epiphytic ferns are more dominant than the other life forms in the two countries. The precipitation variables drive the phylogenetic structure of ferns in Nigeria, whereas both precipitation and temperature variables drive the phylogenetic structure of ferns in Malaysia. This indicates that ferns assemblages in Nigeria and Malaysia are driven by both climatic variables. Besides, we also hypothesize that these observed differences could be due to other historical and evolutionary processes.

2.
Environ Monit Assess ; 191(11): 691, 2019 Oct 30.
Article in English | MEDLINE | ID: mdl-31667628

ABSTRACT

This study identified specific emission sources of atmospheric pollution in the vicinity of two secondary iron and steel smelting factories in Osun state, southwestern Nigeria, using transplanted biomonitors. A total of 120 biomonitors consisting of lichen and moss were grown under a controlled environment and later transplanted to the surroundings of each factory for monitoring of air pollutants for 3 months in both wet and dry seasons. The elemental contents (K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Br, Rb and Sr) of the biomonitors were determined by X-ray florescence (XRF) spectroscopy. The source identification was performed by applying positive matrix factorization (PMF) receptor modelling approach using the elemental data set from the two smelters. Among the measured elements, Fe had the highest average concentration in the lichen and moss samples as well as in both seasons. The average concentrations of Co, Ni, Cu, Zn, As and Br were low. The varying average elemental concentrations of lichen and moss reflect the pattern of impact of smelting on atmospheric airborne pollution around the factories. The four factors resolved by PMF and their respective contributions were metal processing (39.0%), Fe source (28.0%), crustal/soil (22.0%) and road dust (11.0%) for moss and Fe source (34.0%), crustal/soil (26.0%), coal combustion (25.0%) and road dust (15.0%) for lichen. The study showcases lichen and moss as cheaper and yet efficient uninterrupted monitoring tools of air pollution sources associated with iron and steel smelting industrial activities.


Subject(s)
Air Pollutants/analysis , Environmental Monitoring/methods , Environmental Pollution/analysis , Metallurgy , Steel , Air Pollution/analysis , Biological Monitoring , Bryophyta/chemistry , Coal/analysis , Dust , Environmental Pollution/statistics & numerical data , Iron/analysis , Lichens/chemistry , Nigeria , Seasons , Soil/chemistry
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