Quality matters: Response of bacteria and ciliates to different allochthonous dissolved organic matter sources as a pulsed disturbance in shallow lakes.

Shallow lake ecosystems are particularly prone to disturbances such as pulsed dissolved organic matter (allochthonous-DOM; hereafter allo-DOM) loadings from catchments. However, the effects of allo-DOM with contrasting quality (in addition to quantity) on the planktonic communities of microbial loop are poorly understood. To determine the impact of different qualities of pulsed allo-DOM disturbance on the coupling between bacteria and ciliates, we conducted a mesocosm experiment with two different allo-DOM sources added to mesocosms in a single-pulse disturbance event: Alder tree leaf extract, a more labile (L) source and HuminFeed® (HF), a more recalcitrant source. Allo-DOM sources were used as separate treatments and in combination (HFL) relative to the control without allo-DOM additions (C). Our results indicate that the quality of allo-DOM was a major regulator of planktonic microbial community biomass and/or composition through which both bottom-up and top-down forces were involved. Bacteria biomass showed significant nonlinear responses in L and HFL with initial increases followed by decreases to pre-pulse conditions. Ciliate biomass was significantly higher in L compared to all other treatments. In terms of composition, bacterivore ciliate abundance was significantly higher in both L and HFL treatments, mainly driven by the bacterial biomass increase in the same treatments. GAMM models showed negative interaction between metazoan zooplankton biomass and ciliates, but only in the L treatment, indicating top-down control on ciliates. Ecosystem stability analyses revealed overperformance, high resilience and full recovery of bacteria in the HFL and L treatments, while ciliates showed significant shift in compositional stability in HFL and L with incomplete taxonomic recovery. Our study highlights the importance of allo-DOM quality shaping the response within the microbial loop not only through triggering different scenarios in biomass, but also the community composition, stability, and species interactions (top-down and bottom-up) in bacteria and plankton.

Utility of a source-related matrix in basin management studies: a practice on a sub-Basin in Turkey.

According to the water framework directive (WFD), the chemical status should be determined for each water body in a basin through monitoring and evaluation studies, and the gap between the status of water bodies and good water status should be revealed in river basin management plans. In this context, the methodology starting with the evaluation of the monitoring results of the priority substances (PSs) until the end of determining the measures to achieve good condition in surface waters was given in this study. The key aim was to provide a useful methodology defined as a matrix for determining the sources of pollutants that caused this gap. This matrix was applied to the most polluted sub-basin of Küçük Menderes Basin located on the western part of the Turkey. Monitoring studies were carried out in 21 water bodies for a 1-year period for 45 PSs and monitoring results were compared with environmental quality standards (EQS). It was determined that 13 of 45 PSs in 15 water bodies exceeded the EQS. The common PSs in the basin were lead, nickel, fluoranthene, benzo(a)pyrene, C10-13 chloroalkanes, and 4-nonylphenols and average rates of exceeding the EQS were 58.3%, 36.4%, 91.5%, 99.9%, 74.8%, and 49.4%, respectively. The detailed emission inventory of each water body in the basin has been made. Potential sources of PSs were searched via the matrix formed and a total number of 420 basic and supplementary measures were proposed to improve the water quality of the sub-basin.

Interaction effects of the main drivers of global climate change on spatiotemporal dynamics of high altitude ecosystem behaviors: process-based modeling.

Soil organic carbon and nitrogen (SOC-N) dynamics are indicative of the human-induced disturbances of the terrestrial ecosystems the quantification of which provides insights into interactions among drivers, pressures, states, impacts, and responses in a changing environment. In this study, a process-based model was developed to simulate the eight monthly outputs of net primary productivity (NPP), SOC-N pools, soil C:N ratio, soil respiration, total N emission, and sediment C-N transport effluxes for cropland, grassland, and forest on a hectare basis. The interaction effect of the climate change drivers of aridity, CO2 fertilization, land-use and land-cover change, and best management practices was simulated on high altitude ecosystems from 2018 to 2070. The best management practices were developed into a spatiotemporally composite index based on SOC-N stock saturation, 4/1000 initiative, and RUCLE-C factor. Our model predictions differed from the remotely sensed data in the range of - 64% (underestimation) for the cropland NPP to 142% (overestimation) for the grassland SOC pool as well as from the global mean values in the range of - 97% for the sediment C and N effluxes to 60% for the total N emission from the grassland. The interaction exerted the greatest negative impact on the monthly sediment N efflux, total N emission, and soil respiration from forest by - 90.5, - 82.7, and - 80.3% and the greatest positive impact on the monthly sediment C effluxes from cropland, grassland, and forest by 139.3, 137.1, and 133.3%, respectively, relative to the currently prevailing conditions.

Temperature Effects Explain Continental Scale Distribution of Cyanobacterial Toxins.

Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.

Large interannual variability in net ecosystem carbon dioxide exchange of a disturbed temperate peatland.

Peatland ecosystems play an important role in the global carbon (C) cycle as significant C sinks. However, human-induced disturbances can turn these sinks into sources of atmospheric CO2. Long-term measurements are needed to understand seasonal and interannual variability of net ecosystem CO2 exchange (NEE) and effects of hydrological conditions and their disturbances on C fluxes. Continuous eddy-covariance measurements of NEE were conducted between August 2010 and April 2014 at Yenicaga temperate peatland (Turkey), which was drained for agricultural usage and for peat mining until 2009. Annual NEE during the three full years of measurement indicated that the peatland acted as a CO2 source with large interannual variability, at rates of 246, 244 and 663 g Cm(-2)yr(-1) for 2011, 2012, and 2013 respectively, except for June 2011, and May to July 2012. The emission strengths were comparable to those found for severely disturbed tropical peatlands. The peak CO2 emissions occurred in the dry summer of 2013 when water table level (WTL) was below a threshold value of -60 cm and soil water content (SCW) below a threshold value of 70% by volume. Water availability index was found to have a stronger explanatory power for variations in monthly ecosystem respiration (ER) than the traditional water status indicators (SCW and WTL). Air temperature, evapotranspiration and vapor pressure deficient were the most significant variables strongly correlated with NEE and its component fluxes of gross primary production and ER.

Evaluating the impact of climate change on groundwater resources in a small Mediterranean watershed.

Western Mediterranean Region of Turkey is subject to considerable impacts of climate change that may adversely affect the water resources. Decrease in annual precipitation and winter precipitation as well as increase in temperatures are observed since 1960s. In this study, the impact of climate change on groundwater resources in part of Köycegiz-Dalyan Watershed was evaluated. Evaluation was done by quantifying the impacts of climate change on the water budget components. Hydrological modeling was conducted with SWAT model which was calibrated and validated successfully. Climate change and land use scenarios were used to calculate the present and future climate change impacts on water budgets. According to the simulation results, almost all water budget components have decreased. SWAT was able to allocate less irrigation water because of the decrease of overall water due to the climate change. This resulted in an increase of water stressed days and temperature stressed days whereas crop yields have decreased according to the simulation results. The results indicated that lack of water is expected to be a problem in the future. In this manner, investigations on switching to more efficient irrigation methods and to crops with less water consumption are recommended as adaptation measures to climate change impacts.

Monitoring diel dissolved oxygen dynamics through integrating wavelet denoising and temporal neural networks.

Diel dissolved oxygen (DO) time series measured continuously using proximal sensors in situ for a temperate lake were denoised using discrete wavelet transform (DWT) with the orthogonal wavelet families of coiflet, daubechies, and symmlet with order of 10. Diel DO time series denoised were modeled using nine temporal artificial neural networks (ANNs) as a function of water level, water temperature, electrical conductivity, pH, day of year, and hour. Our results showed that time-lag recurrent network (TLRN) using denoised data emulated diel DO dynamics better than the best-performing TLRN using the original data, time-delay neural network (TDNN), and recurrent network (RNN). Daubechies basis dealt with diel DO data slightly better than the other bases given its coefficient of determination (r (2) = 87.1 %), while symmlet performed slightly better than the other bases in terms of root mean square error (RMSE = 1.2 ppm) and mean absolute error (MAE = 0.9 ppm).

Monitoring spatiotemporal variations of diel radon concentrations in peatland and forest ecosystems based on neural network and regression models.

Concentrations of outdoor radon-222 ((222)Rn) in temperate grazed peatland and deciduous forest in northwestern Turkey were measured, compared, and modeled using artificial neural networks (ANNs) and multiple nonlinear regression (MNLR) models. The best-performing multilayer perceptron model selected out of 28 ANNs considerably enhanced accuracy metrics in emulating (222)Rn concentrations relative to the MNLR model. The two ecosystems had similar diel patterns with the lowest (222)Rn concentrations in the afternoon and the highest ones near dawn. Mean level (5.1 + 2.5 Bq m(-3) h(-1)) of (222)Rn in the forest was three times smaller than that (15.8 + 9.7 Bq m(-3)) of (222)Rn in the peatland. Mean (222)Rn level had negative and positive relationships with air temperature and relative humidity, respectively.

Using eddy covariance sensors to quantify carbon metabolism of peatlands: a case study in Turkey.

Net ecosystem exchange (NEE) of carbon dioxide (CO(2)) was measured in a cool temperate peatland in northwestern Turkey on a continuous basis using eddy covariance (EC) sensors and multiple (non-)linear regression-M(N)LR-models. Our results showed that hourly NEE varied between -1.26 and 1.06 mg CO(2) m(-2) s(-1), with a mean value of 0.11 mg CO(2) m(-2) s(-1). Nighttime ecosystem respiration (R(E)) was on average measured as 0.23 ± 0.09 mg CO(2) m(-2) s(-1). Two best-fit M(N)LR models estimated daytime R(E) as 0.64 ± 0.31 and 0.24 ± 0.05 mg CO(2) m(-2) s(-1). Total R(E) as the sum of nighttime and daytime R(E) ranged from 0.47 to 0.87 mg CO(2) m(-2) s(-1), thus yielding estimates of gross primary productivity (GPP) at -0.35 ± 0.18 and -0.74 ± 0.43 mg CO(2) m(-2) s(-1). Use of EC sensors and M(N)LR models is one of the most direct ways to quantify turbulent CO(2) exchanges among the soil, vegetation and atmosphere within the atmospheric boundary layer, as well as source and sink behaviors of ecosystems.

Monitoring and validating spatio-temporal dynamics of biogeochemical properties in Mersin Bay (Turkey) using Landsat ETM+.

The objective of this study was to devise and validate simple models for estimating spatio-temporal dynamics of seven optically (in)active biogeochemical properties in Mersin Bay using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data and GIS. Spatio-temporal dynamics of Secchi depth (S (depth)), dissolved oxygen (DO), nitrite nitrogen (NO(2)-N), nitrate nitrogen (NO3-N), silicate (SiO4), 5-day biological oxygen demand (BOD5), and chlorophyll-a (Chl-a) were estimated using best-fit multiple linear regression (MLR) models as a function of Landsat 7 ETM+ and ground data in 2007 and 2008, latitude, longitude, and day of year. Validation of the MLR models against Landsat and ground data in 2005 led to r values ranging from 0.39 for NO2-N (P = 0.008) to 0.79 for S (depth) (P < 0.001). Parsimonious MLR models built in this study appear to be promising for monitoring and predicting spatio-temporal dynamics of optically (in)active water quality characteristics in Mersin Bay.

Comparison of activated carbon and bottom ash for removal of reactive dye from aqueous solution.

The adsorption of reactive dye from synthetic aqueous solution onto granular activated carbon (GAC) and coal-based bottom ash (CBBA) were studied under the same experimental conditions. As an alternative to GAC, CBBA was used as adsorbent for dye removal from aqueous solution. The amount of Vertigo Navy Marine (VNM) adsorbed onto CBBA was lower compared with GAC at equilibrium and dye adsorption capacity increased from 0.71 to 3.82 mg g(-1), and 0.73 to 6.35 mg g(-1) with the initial concentration of dye from 25 to 300 mg l(-1), respectively. The initial dye uptake of CBBA was not so rapid as in the case of GAC and the dye uptake was slow and gradually attained equilibrium.

Coal-based bottom ash (CBBA) waste material as adsorbent for removal of textile dyestuffs from aqueous solution.

A locally available CBBA waste material was used as adsorbent for removal of reactive dyes from synthetic textile wastewater. This study presents the results of our investigation on color removal from synthetic wastewater containing Vertigo Blue 49 (CI Blue 49) and Orange DNA13 (CI Orange 13) by adsorption onto CBBA waste material. The effectiveness of CBBA waste material in adsorbing reactive dyes from aqueous solutions was studied as a function of contact time, initial dye concentration and pH by batch experiments. Leachability of waste material was also evaluated using standard leaching test with deionized water (DIN38414-S4). pH 7 was more favorable for color removal from both Vertigo Blue 49 (CI Blue 49) and Orange DNA (CI Orange 13). Dyestuff adsorption capacities of CBBA for Vertigo Blue 49 and Orange DNA13 were 13.51 and 4.54mg dye/g adsorbent, respectively. The adsorption isotherms for the CBBA can be better described by the Freundlich isotherm. The results showed that the dyestuff uptake process for both dyes followed the second-order kinetics. The bottom ash used in this study is not classified as ecotoxic/hazardous material according to the French proposal for a criterion and evaluation methods of waste ecotoxicity (CEMWE) and the German regulation on Hazardous Waste Classification (HWC).