The Use of Urea and Kelp Waste Extract is A Promising Strategy for Maximizing the Biomass Productivity and Lipid Content in Chlorella sorokiniana

The decline in fossil fuel reserves has forced researchers to seek out alternatives to fossil fuels. Microalgae are considered to be a promising feedstock for sustainable biofuel production. Previous studies have shown that urea is an important nitrogen source for cell growth and the lipid production of microalgae. The present study investigated the effect of different concentrations of urea combined with kelp waste extract on the biomass and lipid content of Chlorella sorokiniana. The results revealed that the highest cell density, 20.36 × 107 cells-1, and maximal dry biomass, 1.70 g/L, were achieved in the presence of 0.5 g/L of urea combined with 8% kelp waste extract. Similarly, the maximum chlorophyll a, b and beta carotenoid were 10.36 mg/L, 7.05, and 3.01 mg/L, respectively. The highest quantity of carbohydrate content, 290.51 µg/mL, was achieved in the presence of 0.2 g/L of urea and 8% kelp waste extract. The highest fluorescence intensity, 40.05 × 107 cells-1, and maximum total lipid content (30%) were achieved in the presence of 0.1 g/L of urea and 8% kelp waste extract. The current study suggests that the combination of urea and kelp waste extract is the best strategy to enhance the biomass and lipid content in Chlorella sorokiniana.

Incorporating functional traits to enhance multimetric index performance and assess land use gradients

Taxonomic-based multimetric indices (MMIs) have been widely employed for assessing ecosystem status, particularly through the use of stream macroinvertebrate assemblages. However, the functional diversity and composition of assemblages is also important for maintaining stream ecosystem condition. Nonetheless, aquatic insect functional diversity and composition have not commonly been included in MMIs. Our goal was to advance our understanding of the performance and ecological interpretation of an MMI that potentially combined functional and taxonomic metrics. We sampled aquatic insects and natural and land-use variables at 74 temperate Chinese streams. We selected a candidate set of 36 functional and 20 taxonomic metrics that were screened by range tests, natural variation, responsiveness to anthropogenic disturbance, and redundancy for subsequent inclusion in MMIs. We determined if natural variation adjustments improved the performance of a functional-taxonomic MMI. Finally, we evaluated the degree to which the functional-taxonomic MMI served as an early-warning indicator of land use intensity. Natural variation explained between 19.62% and 71.02% of metric variability, indicating that functional metrics changed systematically along natural gradients. The final functional-taxonomic MMI adjusted for natural variation incorporated multiple aspects of assemblage characteristics: functional richness, Rao's quadratic entropy, abundance-weighted frequency of soft bodies, abundance-weighted frequency of predators, and number of Diptera taxa. In contrast to the natural variation unadjusted MMI, the functional-taxonomic adjusted MMI clearly distinguished least-disturbed sites from most-disturbed sites, exhibited high precision and low bias, and showed a significant negative response to land uses. The slope of a linear regression relative to 0-10% urban and 0-20% agriculture was significantly steeper for the functional-taxonomic adjusted MMI than that of the taxonomic adjusted MMI. We conclude that functional-taxonomic adjusted MMIs are more effective indicators of ecological condition and risks to biota from human pressures than are purely taxonomic unadjusted MMIs because functional-taxonomic MMIs are more sensitive to subtle anthropogenic pressures.