The influence of environmental parameters on the abundance, distribution and species composition of macro-invertebrates in Fletcher Reservoir, Zimbabwe

Mwabvu, Tarombera; Sasa, A.

doi:10.1111/j.1365-2028.2008.00991.x

Cited by 11 publications

(11 citation statements)

References 5 publications

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“…Macrophyte cover is of great importance as a refuge for macroinvertebrate taxa from predation, offer a substrate for living on and also for laying eggs in water medium (Amakye, 2001;Kratzer, 2002). However, our findings are similar to findings by Mwabvu and Sasa (2009) who observed the same situation in Fletcher Reservoir. Kovalenko et al (2010) showed that the abundance of certain macrophytes could explain a small proportion of variability in macroinvertebrate communities.…”

Section: Discussionsupporting

confidence: 88%

“…Diversity indices provide more information than simply the number of species present, that is, they account for some species being rare and others being common hence they serve as valuable tools that enable biologists and water managers to quantify diversity in a community and describe its numerical structure (Brown and Lomolino, 1998). Studies by Mwabvu and Sasa (2009) also showed a positive correlation between Physidae (Bulinus africanus) and conductivity (r = 0.56) while Efitre et al (2001) reported that the Uganda lakes with higher conductivity and pH showed greater taxon richness and abundance of Mollusca. Therefore, high conductivity levels could have had an effect on Mollusca diversity in the Malilangwe Reservoir as it has been shown to be great importance for Mollusca shells (Mwabvu and Sasa, 2009).…”

Section: Discussionmentioning

confidence: 95%

“…Studies by Mwabvu and Sasa (2009) also showed a positive correlation between Physidae (Bulinus africanus) and conductivity (r = 0.56) while Efitre et al (2001) reported that the Uganda lakes with higher conductivity and pH showed greater taxon richness and abundance of Mollusca. Therefore, high conductivity levels could have had an effect on Mollusca diversity in the Malilangwe Reservoir as it has been shown to be great importance for Mollusca shells (Mwabvu and Sasa, 2009). Macrophyte cover was also identified as an important habitat variable influencing macroinvertebrate community in Malilangwe Reservoir.…”

Section: Discussionmentioning

confidence: 95%

“…A total of 42 macroinvertebrate taxa were recorded demonstrating a relatively similar taxa richness when compared to other small Reservoir studies in other regions such as 43 families in Lake Taabo (Kouamé et al, 2011), and 40 families in two lakes of the Paraná River floodplain (de Neiff and Carignan, 1997). Fewer taxa have been recorded from some Reservoirs in Zimbabwe such as 15 taxa in Lake Chivero (Brendonck et al, 2003) and 11 taxa from Fletcher Reservoir (Mwabvu and Sasa, 2009). This could be attributed to the timing, location or many other sampling technique factors and anthropogenic impacts such as sewage discharge in Fletcher Reservoir and Lake Chivero.…”

Section: Discussionmentioning

confidence: 99%

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Macroinvertebrate communities associated with littoral zone habitats and the influence of environmental factors in Malilangwe Reservoir, Zimbabwe

Dalu

Clegg

Nhiwatiwa

2012

Knowl. Managt. Aquatic Ecosyst.

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Key-words:Macroinvertebrates, diversity, Malilangwe reservoir, macrophyte cover, conductivity, water levelThe aim of our study was to investigate macroinvertebrate communities so as to understand factors and processes structuring macroinvertebrate communities in a small reservoir, Malilangwe reservoir over seven months (April to October). Sampling was performed by active sweep netting and searching soil sediments. Water temperature, conductivity, dissolved oxygen, pH, ammonia, nitrogen, phosphorus, chemical oxygen demand and macrophyte cover were determined. In total, forty-two macroinvertebrate families belonging to 10 orders were identified amongst 13 macrophyte species and sediments. Thiaridae and Physidae (Mollusca) were the dominant and most abundant taxa (57.71%) and there were followed by the Hemiptera (27.31%). High indices for sites 1 to 3 for the Simpsons index, the Shannon-Weaver index and evenness were recorded, while low indices were observed for sites 4 to 5, with significant differences being observed among the study site using the Kruskal-Wallis ANOVA test (p < 0.05). Redundancy Analysis revealed that among environmental factors, hydrologically linked parameters such as conductivity, water level and macrophyte cover had the strongest influence on macroinvertebrate distribution.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionmentioning

confidence: 95%

Section: Discussionmentioning

confidence: 95%

Section: Discussionmentioning

confidence: 99%

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Macroinvertebrate communities associated with littoral zone habitats and the influence of environmental factors in Malilangwe Reservoir, Zimbabwe

Dalu

Clegg

Nhiwatiwa

2012

Knowl. Managt. Aquatic Ecosyst.

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“…Participants were divided into four categories for our study: non-obese, general obesity alone, central obesity alone, and compound obesity. BMI ≥ 28 kg/m 2 were defined as abnormal BMI and WC ≥ 80 cm for a female or WC ≥ 85 cm for a male were defined as abnormal WC based on the Guidelines for Prevention and Control of Overweight and Obesity in Chinese Adults (18,19). Participants with a normal WC but an abnormal BMI were defined as general obesity alone; participants with a normal BMI but an abnormal WC were defined as central obesity alone; participants with abnormal WC and BMI were defined as compound obesity; and participants with normal WC and BMI were defined as non-obese.…”

Section: Definitionsmentioning

confidence: 99%

Association Between Obesity Type and Common Vascular and Metabolic Diseases: A Cross-Sectional Study

et al. 2020

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Background: The association between different types of obesity and some chronic diseases in Dehui, Jilin province, China, is still unclear. The aim of our study was to clarify the association between different types of obesity and chronic diseases. Methods: Residents aged 40 years or older were randomly selected using a multistage stratified cluster sampling method. Data were collected by means of face-to-face interview, physical examination, and laboratory examination. Descriptive data analyses were performed, and multiple logistic regression analyses were used to explore the adjusted association between different types of obesity and common vascular and metabolic diseases. Results: The prevalence of general obesity alone, central obesity alone and compound obesity were 0.15, 54.29, and 14.36%, respectively. The prevalence of coronary heart disease, stroke, hypertension, dyslipidemia, and diabetes mellitus was highest in the compound obesity group, and lowest in the non-obesity group. Hypertension, dyslipidemia, and diabetes mellitus were associated with compound obesity and central obesity alone [compound obesity (OR = 4.703, 95% CI: 3.714-5.956 for hypertension; OR = 4.244, 95% CI: 3.357-5.365 for dyslipidemia; OR = 4.575, 95% CI: 3.194-6.552 for diabetes mellitus); central obesity alone (OR = 2.210, 95% CI: 1.901-2.570 for hypertension; OR = 2.598, 95% CI: 2.241-3.012 for dyslipidemia; OR = 2.519, 95% CI: 1.834-3.459 for diabetes mellitus)]. Coronary heart disease was associated with compound obesity (OR = 1.761, 95% CI: 1.141-2.719) but not central obesity alone (OR = 1.409, 95% CI: 0.986-2.013). Stroke was associated with neither compound obesity (OR = 1.222, 95% CI: 0.815-1.833) nor associated with central obesity alone (OR = 1.080, 95% CI: 0.786-1.485). Conclusions: Central obesity alone and compound obesity are associated with the risk of hypertension, hyperlipidemia, and diabetes mellitus. Compound obesity but not central obesity alone is associated with the risk of coronary heart disease, but further research is needed to confirm it. There are no significant relationship between stroke and central obesity alone or compound obesity.

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Bioelectrical impedance analysis versus quantitative computer tomography and anthropometry for the assessment of body composition parameters in China

Qin

Yang

Chen

et al. 2021

Sci Rep

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Obesity, especially abdominal obesity, is correlated to increased risk of cardiovascular morbidity and mortality. It is urgent to search a simply method to predict visceral fat area (VFA). Herein, we evaluated the correlation of waist circumference (WC) measured by anthropometry and bioelectrical impedance analysis (BIA), and VFA estimated by BIA or measured by quantitative computed tomography (QCT) in China. The mean body mass index (BMI) was 25.09 ± 3.31 kg/m2 and the mean age was 49.16 ± 9.19 years in 2754 subjects. VFA-BIA were significantly smaller than VFA-QCT in both BMI and age subgroups between male and female (p < 0.001). High correlation was observed for WC between BIA and manually (r = 0.874 for all, r = 0.865 for male and r = 0.806 for female) and for VFA between BIA and QCT (r = 0.512 for all). The intraclass correlation coefficient (ICC) showed the perfect agreement between BIA and manually to measure WC (ICC = 0.832 for all, 0.845 for male and 0.697 for female) and implied a good reliability for VFA between BIA and QCT with women among subgroups (ICC = 0.623 for all, ICC = 0.634 for age < 50 years and ICC = 0.432 for BMI > 24 kg/m2), whereas the good reliability was lost in men (ICC = 0.174). The kappa analysis showed a moderate consistency for VFA measured by BIA and QCT (Kappa = 0.522 with age < 50 years, 0.565 with age ≥ 50 years in male; Kappa = 0.472 with age < 50 years, 0.486 with age ≥ 50 years in female). In addition, BIA to estimate VFA (r = 0.758 in male, r = 0.727 in female, P < 0.001) has a stronger correlation with VFA measured by QCT than BMI and WC according to gender categories. Furthermore, ROC analysis showed the cut-off point of VFA measured by BIA for predicting visceral obesity was: 101.90 cm2, 119.96 cm2 and 118.83 cm2 and the Youden’s index was 0.577, 0.577 and 0.651, respectively and the Kappa value was 0.532, 0.536 and 0.611 in unadjusted model, model 1 and model 2. In conclusion, being non-invasive and free of radiation, BIA can be used as a safe and convenient tool to estimate VFA in female; especially for monitoring the VFA of the same person, the BIA has superiority to a certain extent. However, the consistency is not most ideal between BIA and QCT. When using BIA to assess whether a person is visceral obesity, we must take into consideration age, BMI and WC. Therefore, we established a regression formula to reflect VFA-QCT by VFA-BIA, age, BMI, and WC. In addition, a more accurate formula is needed to match the CT data in China.

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The influence of environmental parameters on the abundance, distribution and species composition of macro-invertebrates in Fletcher Reservoir, Zimbabwe

Cited by 11 publications

References 5 publications

Macroinvertebrate communities associated with littoral zone habitats and the influence of environmental factors in Malilangwe Reservoir, Zimbabwe

Macroinvertebrate communities associated with littoral zone habitats and the influence of environmental factors in Malilangwe Reservoir, Zimbabwe

Association Between Obesity Type and Common Vascular and Metabolic Diseases: A Cross-Sectional Study

Bioelectrical impedance analysis versus quantitative computer tomography and anthropometry for the assessment of body composition parameters in China

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