Contribution of microalgae to carbon sequestration in a natural karst wetland aquatic ecosystem: An in-situ mesocosm study

A novel hierarchical approach to insight to spectral characteristics in surface water of karst wetlands and estimate its non-optically active parameters using field hyperspectral data

Wetlands cover only around 6 % of the Earth's land surface, and are recognized as one of the three major ecosystems, alongside forests and oceans. The ecological structure and function of karst wetlands are unique due to the influence of geologic structure. At present, the unclear spectral morphology of surface water in karst wetlands poses a significant challenge in remote sensing estimation of non-optically active water quality parameters (NAWQPs). This study proposed a novel multi-scale spectral morphology feature extraction (MSFE) method to insight to spectral characteristics in surface water of karst wetlands, and further screen the sensitive features of NAWQPs. Then we constructed three remote sensing inversion strategies for NAWQPs (TN, TP, NH3_N, DO), including direct estimation, indirect estimation, and auxiliary estimation. Finally, we constructed a novel pH-based hierarchical analysis framework (pH_HA) to thoroughly explore the influence of alkalinity-biased characteristics of karst water on the spectral domain of NAWQPs and its estimation accuracy using in-situ hyperspectral data, respectively. We found that the spectral characteristics of karst waters at the first reflectance peak (580 nm) differed significantly from other water body types. The MSFE successfully captured the sensitive spectral domains for NAWQPs, and focused on between 500 and 600 nm and 900-960 nm. The sensitive features captured by MSFE improved estimation accuracy of NAWQPs (R2 >0.9). Direct estimation presented more stable performance compared to the auxiliary estimation (average RMSE of 0.366 mg/L), and the auxiliary estimation model further improved the retrieval accuracy of TN compared to direct estimation model (R2 increasing from 0.43 to 0.56). The novel hierarchical framework clearly revealed the notable changes in the sensitive spectral domains of NAWQPs under different pH values, and enabled more precise determination of spectral subdomains of NAWQPs, and identified the optimal spectral features. The pH_HA framework effectively improved the estimation accuracy of NAWQPs (R2 increased from 0.514 to over 0.9), and the estimation accuracies (R2) of four NAWQPs were all more than 0.9 when the pH value was over 8.5. Our works provide an effective approach for monitoring water quality in karst wetlands.

Multi-sensor and multi-platform retrieval of water chlorophyll a concentration in karst wetlands using transfer learning frameworks with ASD, UAV, and Planet CubeSate reflectance data

China has one of the widest distributions of carbonate rocks in the world. Karst wetland is a special and important ecosystem of carbonate rock regions. Chlorophyll-a (Chla) concentration is a key indicator of eutrophication, and could quantitatively evaluate water quality status of karst wetland. However, the spectral reflectance characteristics of the water bodies of karst wetland are not yet clear, resulting in remote sensing retrieval of Chla with great challenges. This study is a pioneer in utilizing field-based full-spectrum hyperspectral data to reveal the spectral response characteristics of karst wetland water body and determine the sensitive spectral bands of Chla. We further evaluated the Chla retrieval performance of multi-platform spectral data between Analytical Spectral Device (ASD), Unmanned aerial vehicle (UAV), and PlanetScope (Planet). We proposed two multi-sensor weighted integration strategies and two transfer learning frameworks for estimating water Chla from the largest karst wetland in China by combing a partial least square with adaptive ensemble algorithms. The results showed that: (1) In the range of 500-850 nm, the spectral reflectance of water bodies in the karst wetland was overall 0.001-0.105 higher than the inland water bodies, and the sensitive spectral ranges of water Chla focus on 603-778 nm; (2) UAV images outperformed ASD and Planet data, and produced the highest inversion accuracy (R2 = 0.670) for water Chla in karst wetland; (3) Multi-sensor weighted integration retrieval methods improved the Chla estimation accuracy (R2 = 0.716). Integration retrieval methods with the different weights produced the better Chla estimation accuracy than that of methods with the equal weights; (4) The transfer learning methods from ASD to UAV platform provided the better retrieval performance (the average R2 = 0.669) than that of methods from UAV to Planet platform. The transfer learning methods obtained the highest estimation accuracy of Chla (R2 = 0.814) when the ratio of the training and test data in the target domain was 7:3. The transfer learning methods produced the higher estimation accuracies with the distribution of the absolute residuals between predicted and measured values <20.957 mg/m3 compared to the multi-sensor weighted integration retrieval methods, which demonstrated that transfer learning is more suitable for estimating Chla in karst wetland water bodies using multi-platform and multi-sensor data. The results provide a scientific basis for the protection and sustainable development of karst wetlands.

Ameliorative effect of natural floating island as fish aggregating devices on heavy metals distribution in a freshwater wetland

Growing human population and climate change are leading reasons for water quality deterioration globally; and ecologically important waterbodies including freshwater wetlands are in a vulnerable state due to increasing concentrations of pollutants like heavy metals. Given the declining health of these valuable resources, the present study was conducted to evaluate the effect of natural floating island in the form of fish aggregating devices (FADs) made of native weed mass on the distribution of heavy metals in the abiotic and bio compartments of a freshwater wetland. Lower concentrations of surface water heavy metals were observed inside the FADs with a reduction of 73.91%, 65.22% and 40.57-49.16% for Cd, Pb and other metals (viz. Co, Cr, Cu, Ni and Zn), respectively as compared to outside FAD. These led to 14.72-55.39% reduction in the heavy metal pollution indices inside the FAD surface water. The fish species inside the FADs were also found less contaminated (24.07-25.07% reduction) with lower health risk indices. The study signifies the valuable contribution of natural floating island as FADs in ameliorating the effect of heavy metals pollution emphasizing the tremendous role of the natural floating islands in sustainable maintenance of freshwater wetlands for better human health and livelihood.

Enhanced fixation of dissolved inorganic carbon by algal-bacterial aerobic granular sludge during treatment of low-organic-content wastewater

The microalgae-based wastewater treatment technologies are believed to contribute to carbon neutrality. This study investigated the inorganic carbon fixation performance in the algal-bacterial aerobic granular sludge (A-BAGS) process under cultivation at different concentrations of organic carbon (OC) and inorganic carbon (IC). The results indicated that A-BAGS in treating wastewater containing organics of 77 mg-C/L contributed little to the fixation of inorganic carbon, while the highest inorganic carbon removal efficiency of 50 % was achieved at the influent IC of 100 mg/L and OC of 7 mg/L. This high IC condition contributed to enhanced biomass growth rate and enhanced extracellular polymeric substances, while it did not affect the granular stability and nitrification efficiency. The microbial diversity was also largely enhanced. The results demonstrated the great potential of A-BAGS for simultaneous resource recovery in wastewater and inorganic carbon fixation, while operation conditions need to be further optimized.

Pontederia sagittata and Cyperus papyrus contribution to carbon storage in floating treatment wetlands established in subtropical urban ponds

Carbon sequestration is considered an ecosystem service of regulation provided by diverse ecosystems, including wetlands. It has been widely evaluated in the soil of natural wetlands while in constructed wetlands, there is scanty information. In Floating Treatment Wetlands (FTW) there is none. Previously, our research group reported the efficient performance of FTW in an urban polluted pond for two years. As a follow up, the aim of this work was to investigate the contribution of Cyperus papyrus and Pontederia sagittata to carbon storage (CS) in four FTW established in eutrophic urban ponds in a subtropical region. Plant growth, productivity, and CS were assessed in the aboveground biomass of C. papyrus and P. sagittata and the belowground biomass (root mix from C. papyrus and P. sagittata), throughout 26 months in 2 FTW with an area of 17.5 m² (FTW1) and 33 m² (FTW2) and throughout 19 months in 2 FTW with an area of 25 m² (FTW3) and 33 m² (FTW4), respectively. The macrophyte growth depended on various factors, such as the season, the plant species, and the location of the FTW. High relative growth rate values were found for both species (0.125 and 0.142 d^-1 for P. sagittata and C. papyrus, respectively), especially during summer and early autumn. The highest values of productivity were 337 ± 125 g_dw m^-2d^-1 for the aboveground biomass of C. papyrus in FTW2, 311 ± 96.90 g_dwm^-2d^-1 for the aboveground of P. sagittata in FTW1, and 270 ± 107 g_dw m^-2d^-1 for the belowground biomass in FTW2. The mean values of CS for P. sagittata found in FTW1 were 1.90 ± 0.94 kg m^-2, while for C. papyrus in FTW2 they were 4.09 ± 0.73 kg m^-2. The contribution of the belowground biomass to CS was also significant in FTW2 (4.58 ± 0.59 kg m^-2).

Contribution of periphytic biofilm of paddy soils to carbon dioxide fixation and methane emissions

Rice paddies are major contributors to anthropogenic greenhouse gas emissions via methane (CH₄) flux. The accurate quantification of CH₄ emissions from rice paddies remains problematic, in part due to uncertainties and omissions in the contribution of microbial aggregates on the soil surface to carbon fluxes. Herein, we comprehensively evaluated the contribution of one form of microbial aggregates, periphytic biofilm (PB), to carbon dioxide (CO₂) and CH₄ emissions from paddies distributed across three climatic zones, and quantified the pathways that drive net CH₄ production as well as CO₂ fixation. We found that PB accounted for 7.1%-38.5% of CH₄ emissions and 7.2%-12.7% of CO₂ fixation in the rice paddies. During their growth phase, PB fixed CO₂ and increased the redox potential, which promoted aerobic CH₄ oxidation. During the decay phase, PB degradation reduced redox potential and increased soil organic carbon availability, which promoted methanogenic microbial community growth and metabolism and increased CH₄ emissions. Overall, PB acted as a biotic converter of atmospheric CO₂ to CH₄, and aggravated carbon emissions by up to 2,318 kg CO₂ equiv ha^-1 season^-1. Our results provide proof-of-concept evidence for the discrimination of the contributions of surface microbial aggregates (i.e., PB) from soil microbes, and a profound foundation for the estimation and simulation of carbon fluxes in a potential novel approach to the mitigation of CH₄ emissions by manipulating PB growth.