This research was aimed at assessing plants diversity, under the influence of siltation and solid waste effluents along the River Benue bank, Shinko area in Yola North Local Government Area of Adamawa State, Nigeria. Three plots of 20 m × 20 m were randomly established at the solid waste, silt solid waste, silted and no-silt; no-waste areas. A quadrat of 1 m × 1 m was laid at random to determine the population of plant species in each plot. The results of the population of plant species in the various sites revealed that, 10 plant species occurred at the solid waste area (SWA), 7 species at silt waste area (SSW), 12 pl ant species at silted area (SA) and 31 plant species at no-silt; no-waste area (NSW). Shannon-Wiener’s diversity index was used to analyse species diversity in the various sampling locations. Shannon-Wiener’s diversity indexes in the various sites were approximately 1.985, 1.788, 2.140 and 3.125 at SWA, SSW, SA and NSW respectively. The result obtained indicates high uncertainties; as each species are relatively distributed within SWA, SSW, SA and NSW areas. The results indicated that there were significant differences at P ≥ 0.05 as (p-value = 0.183377) in plant species among the study sites. Axonopus compressus had the highest occurrence in 3 of the study areas, except for the silted area.
The set of species that can be present at a given site is limited by historical contingency. In order to show up, a species must either have evolved in an area or dispersed there (either naturally or through anthropogenic activities), and must not have gone locally extinct. The set of species present locally is further limited to those that possess the physiological adaptations to survive the environmental conditions that exist. This group is further shaped through interactions with other species [
Environmental conditions play a key role in defining the function and distribution of plants, in combination with other factors. Changes in long term environmental conditions that can be collectively coined climate change are known to have had enormous impacts on plant diversity patterns in the future and are seen as having significant current impacts. It is predicted that climate change will remain one of the major drivers of biodiversity patterns in the future [
The inadequate information about the present status of most habitats and species both in protected areas and the natural environment makes management difficult. It has long been feared that human activity is causing massive extinctions. Despite increased efforts at conservation, it has not been enough and biodiversity losses continue [
The Benue River is a river in Africa. It is the major tributary of the Niger River. The river is about 1400 km long. It starts in the Adamawa Plateau of northern Cameroon. In the catchment area there is a very high level of plant endemism. Plant endemism in the upper catchment of the Benue is very high, with trees such as Anogeissus leiocarpus, Kigelia aethiopica, Acacia seyal, Combretum and Terminalia species. Grass cover often features the Elephant Grass (Cenchrus purpureum). The lower basin of the Benue River can be construed as the region below the joining of the Gongola River at the town of Numan, northwest (downstream) of Yola (Jimeta). In the northern part of this area the terrestrial ecoregion is characterised chiefly by the sprawling floodplain of the West Sudanian savannah, while Guinean forest-savannah mosaic covers much southern part of the lower basin, [
The study was carried out along Doubeli bypass road, in Shinko Ward of Yola North Local Government Area, Adamawa State at the on-set of the dry season, between latitudes 9˚7'30'' and 10˚50''N, and longitude 11˚40'' and 13˚20''E (
Generally, mean annual rainfall is less than 1000 mm in the central and North western part of the state. Annual distribution of rainfall is said to be influenced by altitude of the stations which is reflected in the orientation of the isohyets which exhibit strong correlation with highland ranges. Rain usually starts from April in the south to and May in the North while cessation dates are from September in the North to and November in the extreme south. Mean length of rainy season ranges from 120 - 210 days in the state.
According to [
Three plots of 20 m × 20 m were randomly selected in each of the sites using [
areas namely, solid waste area, silt + solid waste area, silted area and no-silt; no-solid waste area (
A visual estimate was made of the cover of individual species in the sample plots by using percentage classes given in the Domin and Braun-Blanquet scales [
Relativedensity = numberofindividualofthespecies × 100 numberofindividualofallthespecies (1) [
The computation of species diversity per plot was carried out using the Shannon-Wiener diversity index ( H ′ ) [
Shannon - W i e n e r I n d e x = ( H ′ ) = − ∑ ( − P i I n P i ) (2)
where H ′ = Diversity Index;
Pi = Proportion of a species in the whole sample population;
In = Natural Logarithm of the species;
∑ = Summation.
Evennessindex ( E ) = H ′ / H ′ max (3)
where: H ′ max = InS (where S = total number of species).
One-way analysis of variance was done to compare the flora species found in the four plant communities.
The species richness of the vascular plants was calculated by using the method “Margalef’s index of richness” (Dmg) [
Dmg = ( S − 1 ) / I n N (4)
where,
S = Total number of species.
N = Total number of individuals.
Result of plants identified showed a total of 133 plants having 10, 9, 12 and 31 species at SWA, SSW, SA and NSW respectively. The total frequencies at each site were 18, 25, 31 and 59 at SWA, SSW, SA and NSW respectively. The result also shows that there were few individual plant species in the solid waste area. Axonopus compressus and Amarathus spinosus had the highest number 33.33% and 22.22% respectively. The population of other herbaceous plant species at the SWA was low having 5.5% frequency each.
The result of plant species identified at silt + solid waste area indicated that there were 7 species belonging to four families; (Amarathaceae, Commelinaceae, Poaceae and Leguminosae). Commelina benghalensis has the highest frequency (28%) followed by Axonopus compressus and Chrisopogon zizanioides with frequency of 20%. The plant species with the lowest frequency was Mimosa invisa (4%).
A total of 31 individual plants were identified in the silted area belonging to 12 species and 7 families (Poaceae, Cyperaceae, Euphorbiaceae, Cleomaceae, Leguminosae,Convolvulaceae and Asteraceae). Cynodon dactylon had 25.8% frequency followed by Axonopus compressus with 19.3% and Chrisopogon zizanioide with 16.1% frequency. Those with lowest frequency of 3.2% were Cyperus iria, Cleome viscosa, Portulaca oleracea, Caesalpinia spp., Mimosa inuisa, Ipomoea involucrate, and Aspilia bussei.
Plants identified at no-silt; no-solid waste area revealed 31 plant belonging to Portulacaceae, Convolvulaceae, Nyctaginaceae, Leguminosae, Rubiaceae, Commelinaceae, Arecaceae, Mimosaceae, Cyperaceae, Boraginaceae, Cucurbitaceae, Verbenaceae, Euphorbiaceae, Asteraceae, Lamiaceae, Poaceae and Malvaceae families. Corchorus tridens, Corchorus olitorius, Axonopus compressus, Euphorbia hirta, Commelina benghalensis Luffa cylindrical, Acacia albida Chloris pilosa, Synedrella nodiflora and Hyphaene thebaica were some of the listed species of plants on this site. The most abundant was Corchorus tridens (13.55%) followed by Corchorus olitorius (10.16%) while the least abundant plant species in the area had 1.69% frequency.
The result obtained showed an approximate Shannon-Wiener diversity index (H’) values of 1.985, 1.788, 2.140 and 3.125 indicating average uncertainties as the species were relatively distributed within the area at SWA, SSW, SA and NSW respectively (Tables 2-5). This signifies that an individual species picked at random might not be known being that, the plant species were fairly well represented in each of the study sites. In a species aggregation where each of the species is fairly well represented, it is difficult to predict the identity of a randomly sampled individual [
The relative densities of the identified plant species revealed that Corchorus olitorius had 0.14, at NSW area. Cynodon dactylon had (0.25) at SA, followed by Axonopus compressus (0.019) and Chrisopogon zizanioides (0.16). At SSW, the relative density was (0.28) (Commenlina benghalensis) followed by A. compressuswith (0.2), Chrisopogon zizanioides and Amaranthus spinosus both had (0.12). SWA had a relative density of 0.35 (A. compressus) followed by 0.18 (A. spinosus). Species evenness (S) was approximately 0.69, 0.56, 0.62 and 0.77 at SWA, SSW, SA and NSW respectively. This indicates that plant species are not evenly distributed within the studied area. Species richness shows 10 species at SWA, 7 at SSW, 12 at SA and 31 at NSW area. Also, from the one-way ANOVA result (p-value = 0.183377 (p < 0.05)), there is significant difference in plant species between the four studied sites (SWA, SSW, SA and NSW).
When considering total plant species richness, the results are in disagreement with the hypothesis that plant species occurrence along river Benue bank is not
Plant species | Silted area | Solid waste area | Silt + solid waste area | No silt; no solid waste area |
---|---|---|---|---|
Kyllinga erecta | 0 | 1 | 0 | 0 |
Aeschynomene indica | 0 | 1 | 0 | 0 |
Acalypha fimbriata | 0 | 1 | 0 | 1 |
Axonopus compressus | 6 | 6 | 5 | 1 |
Phyllanthus amarus | 0 | 0 | 0 | 1 |
Portulaca quadrifida | 0 | 0 | 0 | 1 |
Vernonia galamensis | 0 | 0 | 0 | 1 |
Hewitta sublobata | 0 | 0 | 0 | 1 |
Boerhavia diffusa | 0 | 0 | 0 | 2 |
Senna obtusifolia | 0 | 0 | 0 | 1 |
Mitracarpus villosus | 0 | 0 | 0 | 1 |
Commelina benghalensis | 0 | 0 | 7 | 1 |
Brachiaria deflexa | 0 | 0 | 0 | 2 |
Setaria barbata | 0 | 0 | 0 | 1 |
Mariscus longibracteatus | 0 | 0 | 0 | 1 |
Hyphaene thebaica | 0 | 0 | 0 | 4 |
Acacia albida | 0 | 0 | 0 | 2 |
Mariscus flabelliformis | 0 | 0 | 0 | 1 |
Heliotropium ovalifolium | 0 | 0 | 0 | 1 |
Platostoma africanum | 0 | 0 | 0 | 1 |
Luffa cylindrical | 0 | 0 | 0 | 1 |
Stachytarpheta cayennensis | 0 | 0 | 0 | 1 |
Euphorbia hirta | 0 | 0 | 0 | 5 |
Laggera aurita | 0 | 0 | 0 | 1 |
Leonotis nepetifolia | 0 | 0 | 0 | 1 |
Synedrella nodiflora | 0 | 0 | 0 | 1 |
Chloris pilosa | 0 | 0 | 0 | 1 |
Platostoma africanum | 0 | 0 | 0 | 1 |
Elytrophorus spicatus | 0 | 0 | 0 | 1 |
Calopogonium mucunoides | 0 | 0 | 0 | 2 |
Corchorus olitorius | 0 | 0 | 0 | 4 |
Corchorus tridens | 0 | 0 | 0 | 8 |
Paspalum vaginatum | 0 | 0 | 2 | 0 |
Ludiwigia hyssopifolia | 0 | 0 | 2 | 0 |
Mimosa invisa | 1 | 0 | 1 | 0 |
Cynodon dactylon | 8 | 1 | 0 | 0 |
Cyperus iria | 1 | 0 | 0 | 0 |
Portulaca oleracea | 1 | 1 | 0 | 0 |
Euphorbia heterophylla | 1 | 1 | 0 | 0 |
Cleome viscosa | 1 | 0 | 0 | 0 |
Caesalpinia spp | 1 | 0 | 0 | 0 |
Ipomoea involucrate | 1 | 1 | 0 | 0 |
Dactyloctenium aegyptium | 3 | 1 | 0 | 0 |
Aspilia bussei | 1 | 0 | 0 | 0 |
Chrysopogon zizanioides | 5 | 0 | 5 | 0 |
Amarathus spinosus | 0 | 4 | 3 | 4 |
Total | 31 | 18 | 25 | 59 |
Source: Field survey, (2015).
Plant species | Frequency | Pi | Inpi | pi(Inpi) | Evenness | Richness (S) | Density | Relative Density |
---|---|---|---|---|---|---|---|---|
Amarathus spinosus | 4 | 0.222222 | −1.50408 | 0.334239 | 0.686781 | 10 | 0.0075 | 0.176 |
Kyllinga erecta | 1 | 0.055556 | −2.89037 | 0.160576 | 0.0025 | 0.059 | ||
Aeschynomene indica | 1 | 0.055556 | −2.89037 | 0.160576 | 0.0025 | 0.059 | ||
Acalypha fimbriata | 1 | 0.055556 | −2.89037 | 0.160576 | 0.0025 | 0.059 | ||
Axonopus compressus | 6 | 0.333333 | −1.09861 | 0.366204 | 0.015 | 0.353 | ||
Cynodon dactylon | 1 | 0.055556 | −2.89037 | 0.160576 | 0.0025 | 0.059 | ||
Portulaca oleracea | 1 | 0.055556 | −2.89037 | 0.160576 | 0.0025 | 0.059 | ||
Euphorbia heterophylla | 1 | 0.055556 | −2.89037 | 0.160576 | 0.0025 | 0.059 | ||
Ipomoea involucrate | 1 | 0.055556 | −2.89037 | 0.160576 | 0.0025 | 0.059 | ||
Dactyloctenium aegyptium | 1 | 0.055556 | −2.89037 | 0.160576 | 0.0025 | 0.059 | ||
Total | 18 | 1.985053 | 0.0425 |
Plant species | Frequency | pi | Inpi | pi(Inpi) | Evenness | Richness(s) | Density | Relative Density |
---|---|---|---|---|---|---|---|---|
Amaranthus spinosus | 3 | 0.12 | −2.12026 | 0.254432 | 0.555321 | 7 | 0.0075 | 0.12 |
Commelina benghalensis | 7 | 0.28 | −1.27297 | 0.35643 | 0.0175 | 0.28 | ||
Paspalum vaginatum | 2 | 0.08 | −2.52573 | 0.202058 | 0.005 | 0.08 | ||
Ludiwigia hyssopifolia | 2 | 0.08 | −2.52573 | 0.202058 | 0.005 | 0.08 | ||
Mimosa invisa | 1 | 0.04 | −3.21888 | 0.128755 | 0.0025 | 0.04 | ||
Axonopus compressus | 5 | 0.2 | −1.60944 | 0.321888 | 0.0125 | 0.2 | ||
Chrisopogon zizanioides | 5 | 0.2 | −1.60944 | 0.321888 | 0.0125 | 0.2 | ||
Total | 25 | 1.787509 | 0.0625 |
Plant species | Frequency | pi | Inpi | pi(Inpi) | Evenness | Richness(s) | Density | Relative Density |
---|---|---|---|---|---|---|---|---|
Cynodon dactylon | 8 | 0.258065 | −1.35455 | 0.34956 | 0.623165 | 12 | 0.02 | 0.258064516 |
Cyperus iria | 1 | 0.032258 | −3.43399 | 0.110774 | 0.0025 | 0.032258065 | ||
Axonopus compressus | 6 | 0.193548 | −1.64223 | 0.317851 | 0.015 | 0.193548387 | ||
Portulaca oleracea | 1 | 0.032258 | −3.43399 | 0.110774 | 0.0025 | 0.032258065 | ||
Euphorbia heterophylla | 2 | 0.064516 | −2.74084 | 0.176828 | 0.005 | 0.064516129 | ||
Cleome viscosa | 1 | 0.032258 | −3.43399 | 0.110774 | 0.0025 | 0.032258065 | ||
Caesalpinia spp. | 1 | 0.032258 | −3.43399 | 0.110774 | 0.0025 | 0.032258065 | ||
Mimosa inuisa | 1 | 0.032258 | −3.43399 | 0.110774 | 0.0025 | 0.032258065 | ||
Ipomoea involucrate | 1 | 0.032258 | −3.43399 | 0.110774 | 0.0025 | 0.032258065 | ||
Dactyloctenium aegyptium | 3 | 0.096774 | −2.33537 | 0.226004 | 0.0075 | 0.096774194 | ||
Aspilia bussei | 1 | 0.032258 | −3.43399 | 0.110774 | 0.0025 | 0.032258065 | ||
Chrysopogon zizanioides | 5 | 0.16129 | −1.82455 | 0.294282 | 0.0125 | 0.161290323 | ||
Total | 31 | 2.139942 | 0.0775 |
Plant species | Frequency | pi | Inpi | pi(Inpi) | Evenness | Richness(s) | Density | Relative Density |
---|---|---|---|---|---|---|---|---|
Phyllanthus amarus | 1 | 0.016949 | −4.07754 | 0.069111 | 0.766278 | 31 | 0.0025 | 0.024390244 |
Portulaca quadrifida | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Vernonia galamensis | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Hewitta sublobata | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Boerhavia diffusa | 2 | 0.033898 | −3.38439 | 0.114725 | 0.005 | 0.048780488 | ||
Senna obtusifolia | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Mitracarpus villosus | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Commelina benghalensis | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Brachiaria deflexa | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Setaria barbata | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Mariscus longibracteatus | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Hyphaene thebaica | 4 | 0.067797 | −2.69124 | 0.182457 | 0.001 | 0.009756098 | ||
Acacia albida | 2 | 0.033898 | −3.38439 | 0.114725 | 0.005 | 0.048780488 | ||
Mariscus flabelliformis | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Heliotropium ovalifolium | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Platostoma africanum | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Luffa cylindrical | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Acalypha fimbriata | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Stachytarpheta cayennensis | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Euphorbia hirta | 5 | 0.084746 | −2.4681 | 0.209161 | 0.0125 | 0.12195122 | ||
Laggera aurita | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Leonotis nepetifolia | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Amarathus spinosus | 4 | 0.067797 | −2.69124 | 0.182457 | 0.001 | 0.009756098 | ||
Synedrella nodiflora | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Chloris pilosa | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Platostoma africanum | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Elytrophorus spicatus | 1 | 0.016949 | −4.07754 | 0.069111 | 0.0025 | 0.024390244 | ||
Calopogonium mucunoides | 2 | 0.033898 | −3.38439 | 0.114725 | 0.005 | 0.048780488 | ||
Axonopus compressus | 4 | 0.067797 | −2.69124 | 0.182457 | 0.001 | 0.009756098 | ||
Corchorus olitorius | 6 | 0.101695 | −2.28578 | 0.232452 | 0.015 | 0.146341463 | ||
Corchorus tridens | 8 | 0.135593 | −1.9981 | 0.270928 | 0.002 | 0.019512195 | ||
Total | 59 | 3.124526 | 0.1025 |
Source: Field survey, (2015).
influenced by siltation and solid waste effluents. However plant species were high at the NSW area which might be as a result of the higher species diversity which increased productivity. This concurs with the findings of [
The Shannon-Wiener diversity index revealed that there is significant difference in the four studied areas which is in disagreement with [
The
There are variations in the individual number of plant species in the study area and the distribution is not even in the studied sites. Effluents from the solid waste and the silt depth level in the area could be among the factors threatening and causing variations in plant species diversity in the area as seen in the report. The land use system (farming) which involved the use of some chemicals, in the study sites, could also be the reason for inadequate natural regeneration in the area as this chemical content may be harmful to some flora species.
If the current trend of deforestation at the expense of the natural environment continues, the effects would be greater than the intending benefits of the
product. However, various measures could be considered in an attempt to reduce the negative effects of anthropogenic activities on the environment and to prevent future impacts on the ecosystem. Artificial regeneration should be encouraged in areas with trait of flooding and tree planting should be considered as part of all developmental projects. Appropriate laws and legislations on tree harvesting, bush burning and animal grazing should be established. To control waste effluents we strongly recommend that government should support industrial recycling activities such as those for used batteries, used paint, used pesticides, used oil and electronic wastes such as used computers and cell phones. Environmentally friendly products should be purchased whenever possible.
Adaeze, J.E., Dishan, E.E. and Tella, I.O. (2017) Plants Species Diversity along River Benue Bank under the Influence of Siltation and Solid Waste Effluents, Adamawa State, Nigeria. Open Access Library Journal, 4: e4125. https://doi.org/10.4236/oalib.1104125