Determination of antimicrobial and heavy metal resistance profiles of some bacteria isolated from aquatic amphibian and reptile species

The aim of the present study was to determine the level of antibiotic resistance patterns and distribution of heavy metal resistance of bacterial isolates from aquatic animals (Lissotriton vulgaris, Pelophylax ridibundus, Emys orbicularis, Mauremys rivulata, and Natrix natrix) in Turkey (Kavak Delta). A total of 153 bacteria have been successfully isolated from cloaca and oral samples of the aquatic amphibians and reptilians which were found, namely, Aeromonas sp. (n?=?29), Plesiomonas sp. (n?=?7), Vibrio sp. (n?=?12), Citrobacter sp. (n?=?12), Enterobacter sp. (n?=?11), Escherichia sp. (n?=?22), Klebsiella sp. (n?=?22), Edwardsiella sp. (n?=?6), Hafnia sp. (n?=?1), Proteus sp. (n?=?19), Providencia sp. (n?=?8), and Pseudomonas sp. (n?=?4). In terms of antibiotic and heavy metal susceptibility testing, each isolate was tested against 12 antibiotics and 4 metals. There was a high incidence of resistance to cefoxitin (46.40 %), ampicillin (44.44 %), erythromycin (35.29 %), and a low incidence of resistance to gentamicin (6.53 %), kanamycin (8.49 %), chloramphenicol (9.15 %), and cefotaxime (10.45 %). The multiple antibiotic resistance index of each bacterial species indicated that bacteria from raised amphibians and reptiles have been exposed to tested antibiotics, with results ranging from 0 to 0.58. Most isolates showed tolerance to different concentrations of heavy metals, and minimal inhibition concentrations ranged from100 to >3,200 μg/mL. According to these results, a significant occurrence of bacteria in the internal organs of reptiles and amphibians, with a high incidence of resistance against antibiotics and heavy metals, may risk aquatic animals and the public health. These data appoint the importance of epidemiological surveillance and microbiological monitoring and reinforce the need to implement environment protection programs for amphibian and reptile species.     

Long-term monitoring of the impact of a capture-based bluefin tuna aquaculture on water column nutrient levels in the Eastern Aegean Sea, Turkey

Capture-based aquaculture of Atlantic bluefin tuna in the Mediterranean has been expanding rapidly but little is known about its environmental impact. In order to understand the consequences of this new sector, long-term monitoring is needed. For this purpose, we investigated the impact of a capture-based tuna farm located in the Gerence Bay (Aegean Sea) on the water column on a seasonal basis from 2005 to 2008, where in the water column, temperature, salinity, pH, dissolved oxygen, nutrients (nitrite, nitrate, ammonium, and phosphate), and chlorophyll a, in the sediment organic carbon variables were measured. Although highest nutrient concentrations were observed at the cage station as compared to the two controls in the production period, differences were not statistically significant between stations. Monitoring of physico-chemical parameters, nutrients, and chlorophyll a in water column together with organic carbon in sediment did not show detectable impact of fattening of Atlantic bluefin tuna. This was probably caused by strong currents present in the area, location of the cages away from the coast, hence high water depth, controlled feeding, and periodic presence of tuna farming activity in the study area.     

Dissipation pattern and risk quotients assessment of amisulbrom in Korean melon cultivated in plastic house conditions

Amisulbrom formulated as suspension concentrate was applied at the rate recommended for Korean melon to determine the dissipation pattern (at two different sites), the pre-harvest residue limit (PHRL), and risk assessments. Samples collected over 10 days were extracted using liquid-liquid extraction (LLE) and cleaned up with solid-phase extraction (SPE) Florisil cartridge. Residual concentrations were determined using liquid chromatography-ultraviolet detector (LC-UVD) and confirmed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The standard showed good instrument response linearity with a correlation coefficient (R ²) = 0.9999, and the recovery ranged from 87.5 to 93.7%. The dissipation half-life calculated from two different sites were found to be 7.0 and 8.8 days for sites 1 and 2, respectively. A PHRL graph constructed from the data indicated that if the residue levels were less than 0.55–0.59 mg/kg 3 days before harvest or less than 0.61–0.74 mg/kg 7 days before harvest, then they would be lower than the maximum residue limits (MRLs) at harvest. Risk assessments showed that the risk quotient (RQ) was 4.39–3.47% at 0 day, declined to 1.53–1.63% at 10 days. Therefore, the current data indicate that the amisulbrom can be applied safely to Korean melon; hence, it is unlikely to induce adverse health effects in consumers.     

Can tree species diversity be assessed with Landsat data in a temperate forest?

The diversity of forest trees as an indicator of ecosystem health can be assessed using the spectral characteristics of plant communities through remote sensing data. The objectives of this study were to investigate alpha and beta tree diversity using Landsat data for six dates in the Gönen dam watershed of Turkey. We used richness and the Shannon and Simpson diversity indices to calculate tree alpha diversity. We also represented the relationship between beta diversity and remotely sensed data using species composition similarity and spectral distance similarity of sampling plots via quantile regression. A total of 99 sampling units, each 20 m × 20 m, were selected using geographically stratified random sampling method. Within each plot, the tree species were identified, and all of the trees with a diameter at breast height (dbh) larger than 7 cm were measured. Presence/absence and abundance data (tree species number and tree species basal area) of tree species were used to determine the relationship between richness and the Shannon and Simpson diversity indices, which were computed with ground field data, and spectral variables derived (2 × 2 pixels and 3 × 3 pixels) from Landsat 8 OLI data. The Shannon-Weiner index had the highest correlation. For all six dates, NDVI (normalized difference vegetation index) was the spectral variable most strongly correlated with the Shannon index and the tree diversity variables. The Ratio of green to red (VI) was the spectral variable least correlated with the tree diversity variables and the Shannon basal area. In both beta diversity curves, the slope of the OLS regression was low, while in the upper quantile, it was approximately twice the lower quantiles. The Jaccard index is closed to one with little difference in both two beta diversity approaches. This result is due to increasing the similarity between the sampling plots when they are located close to each other. The intercept differences between two investigated beta diversity were strongly related to the development stage of a number of sampling plots in the tree species basal area method. To obtain beta diversity, the tree basal area method indicates better result than the tree species number method at representing similarity of regions which are located close together. In conclusion, NDVI is helpful for estimating the alpha diversity of trees over large areas when the vegetation is at the maximum growing season. Beta diversity could be obtained with the spectral heterogeneity of Landsat data. Future tree diversity studies using remote sensing data should select data sets when vegetation is at the maximum growing season. Also, forest tree diversity investigations can be identified by using higher-resolution remote sensing data such as ESA Sentinel 2 data which is freely available since June 2015.     

A puzzle over ecological footprint,energy consumption and economic growth: the case of Turkey

Environmental and Ecological Statistics - The paper investigates the non-linear causality from energy consumption and economic growth to ecological footprint for the case of Turkey by employing...     

Treatment of residual lubricating oil using rice husk-based material as ecological adsorbent

Journal of Material Cycles and Waste Management - One of the most significant environmental problems the world population faces is the inadequate disposal of petroleum derivatives. Lubricant oil is...     

Another outlook into energy-growth nexus in Mexico for sustainable development: Accounting for the combined impact of urbanization and trade openness

This study corroborates the importance of United Nations Sustainable Development Goal 7 (SDG-7), intended to ensure access to affordable, reliable, sustainable energy for all, and SDG-8, designed to promote decent work and sustainable economic growth. This article is motivated by the highlighted SDGs and empirically explores the long-run and causality relationship between energy consumption, urbanization, trade openness, and economic growth for annual frequency data from 1965 to 2021 for the case of Mexico. To this end, we leverage the use of fully modified ordinary least squares, dynamic ordinary least squares, and canonical regression estimation methods, while for the direction of causality, the gradual shift and wavelet coherence methods are used. According to the Autoregressive distributed lag (ARDL), the bounds test traces a long-run relationship between the outlined variables over the sampled period. Empirical evidence validates the energy-induced growth hypothesis. This result resonates with the causality analysis, where energy consumption drives economic growth one way in Mexico. This suggests that Mexico cannot embark on energy-conservative policies, as such actions will hurt economic progress. In addition, unidirectional causality is seen between urbanization, trade openness, and economic growth. These findings have far-reaching implications for economic growth and macroeconomic indicators in Mexico. More insights are highlighted in the concluding section.     

Using landsat data to determine land use/land cover changes in Samsun, Turkey

The rapid industrialization and urbanization of an area require quick preparation of actual land use/land cover (LU/LC) maps in order to detect and avoid overuse and damage of the landscape beyond sustainable development limits. Remote sensing technology fits well for long-term monitoring and assessment of such effects. The aim of this study was to analyze LU/LC changes between 1980 and 1999 in Samsun, Turkey, using satellite images. Three Landsat images from 1980, 1987 and 1999 were used to determine changes. A post classification technique was used based on a hybrid classification approach (unsupervised and supervised). Images were classified into six LU/LC types; urban, agriculture, dense forest, open forest-hazelnut, barren land and water area. It is found that significant changes in land cover occurred over the study period. The results showed an increase in urban, open forest/hazelnut, barren land and water area and a decrease in agriculture and dense forest in between 1980 and 1999. In this period, urban land increased from 0.77% to 2.47% of the total area, primarily due to conversions from agricultural land and forest to a lesser degree. While the area of dense forest decreased from 41.09% to 29.64% of the total area, the area of open forest and hazelnut increased from 6.73% to 11.88%.     

Determination of heavy metal pollution with environmental physicochemical parameters in waste water of Kocabas Stream (Biga, Canakkale, Turkey) by ICP-AES

Waste water pollution of industrial areas can answer for the serious consequences of one of the most important environmental threats to the future. In this study, inductively coupled plasma-atomic emission spectrometry method (ICP-AES) is proposed to determine heavy metals (Pb, Cu, Cd, Cr, Zn, Al, Fe, Ni, Co, Mn) and major elements (Ca, Mg) in waste water of Kocabas Stream. The concentration of metals in the waste water samples taken from 9 different stations (St.) in Biga-Kocabas Stream in November 2004 (autumn period) were determined after simple pretreatment of samples by the proposed ICP-AES method. An analysis of a given sample is completed in about 15 min for ICP-AES the method. The results of heavy metals concentrations in waste water were found between 0.00001–77.69610 mg l⁻¹ by the ICP-AES technique. The concentrations of Pb, Cd, Cu, Zn, Cr, Al, Fe, Mn, Ni, Co, Mg and Ca 0.00001 (St.3,6,7) – 0.0087 mg l⁻¹ (St.9), 0.00001 (St.4-7) – 0.0020 mg l⁻¹ (St.8), 0.00001 (St.1,3-7,9) – 0.0041 mg l⁻¹ (St.2), 0.0620 (St.2) – 0.2080 mg l⁻¹ (St.3), 0.0082 (St.6) – 0.2290 mg l⁻¹ (St.8), 0.3580 (St.2) – 1.7400 mg l⁻¹ (St.3), 0.2240 (St.1) – 0.6790 mg l⁻¹ (St.3), 0.0080 (St.1) – 1.5840 mg l⁻¹ (St.3), 0.0170 (St.3) – 0.0640 mg l⁻¹ (St.2), 0.0010 (St.1,4,5,8) – 0.0080 mg l⁻¹ (St.3), 5.0640 (St.9) – 5.2140 mg l⁻¹ (St.1) and 43.3600 (St.2) – 77.6961 mg l⁻¹ (St.9), respectively. Also we measured environmental physicochemical parameters such as temperature, salinity, specific conductivity, total dissolved solid (TDS), pH, oxidation and reduction potential (ORP), and dissolved oxygen (DO) in the waste water at sampling stations.