Spatio-temporal variability of phytoplankton assemblages and its controlling factors in spring and summer in the Subei Shoal of Yellow Sea, China

The Subei Shoal is a special coastal area with complex physical oceanographic properties in the Yellow Sea.In the present study,the distribution of phytoplankton and its correlation with environmental factors were studied during spring and summer of 2012 in the Subei Shoal of the Yellow Sea.Phytoplankton species composition and abundance data were accomplished by Utermohl method.Diatoms represented the greatest cellular abundance during the study period.In spring,the phytoplankton cell abundance ranged from 1.59×10^3 to 269.78×10^3 cell/L with an average of 41.80×10^3 cell/L,and Skeletonema sp.and Paralia sulcata was the most dominant species.In summer,the average phytoplankton cell abundance was 72.59×10^3 cell/L with the range of 1.78×10^3 to 574.96×10^3 cell/L,and the main dominant species was Pseudo-nitzschia pungens,Skeletonema sp.,Dactyliosolen fragilissima and Chaetoceros curvisetus.The results of a redundancy analysis(RDA)showed that turbidity,temperature,salinity,pH,dissolved oxygen(DO),the ratio of dissolved inorganic nitrogen to silicate and SiO4-Si(DIN/SiO4-Si)were the most important environmental factors controlling phytoplankton assemblages in spring or summer in the Subei Shoal of the Yellow Sea.

Distribution and controlling factors of phytoplankton assemblages associated with mariculture in an eutrophic enclosed bay in the East China Sea

The distribution of phytoplankton and its correlation with environmental factors were studied monthly during August 2012 to July 2013 in the Yantian Bay. A total of 147 taxa of phytoplankton were identified, and the average abundance was in the range of 0.57×10~4 to 7.73×10~4 cell/L. A total of 19 species dominated the phytoplankton assemblages, and several species that are widely reported to be responsible for microalgae blooms were the absolutely dominant species, such as Skeletonema costatum, Navicula sp., Thalassionema nitzschioides,Pleurosigma sp., and Licmophora abbreviata. The monthly variabilities in phytoplankton abundance could be explained by water temperature, dissolved oxygen, salinity, dissolved inorganic nitrogen（DIN）, and suspended solids. The results of a redundancy analysis showed that p H and nutrients, including DIN and silicate（SiO_4）, were the most important environmental factors controlling phytoplankton assemblages in specific months. It was found that nutrients and pH levels that were mainly influenced by mariculture played a vital role in influencing the variation of phytoplankton assemblages in the Yantian Bay. Thus, a reduction of mariculture activities would be an effective way to control microalgae blooms in an enclosed and intensively eutrophic bay.

Calculation of photosynthetically available radiation using multispectral data in the Arctic

Photosynthetically Available Radiation（PAR） is an important bio-optical parameter related to marine primary production.PAR is usually measured by a broadband sensor and can also be calculated by multispectral data.When the PAR is calculated by multispectral data in polar region,four factors are possible error sources.PAR could be overestimated as the wavelengths of multispectral instrument are usually chosen to evade main absorption zones of atmosphere. However,both PARs calculated by hyperspectral and multispectral data are consistent with an error less than 1%.By the fitting function proposed here,the PAR calculated by multispectral data could attain the same accuracy with that by hyperspectral data.To calculate the attenuation rate of the PAR needs PAR_0, the PAR just under the surface.Here,an approach is proposed to calculate PAR_0 by the best fit of the irradiance profile of 1-5 m with a content attenuation coefficient under surface.It is demonstrated by theory and observed data in different time at same location that the attenuation coefficient of PAR is independent of the intensity of radiation.But under sea ice,the attenuation coefficient of PAR is a little bit different,as the spectrum of the light has been changed by selective absorption by the sea ice.Therefore,the difference of inclusions inside the sea ice will result in different PAR,and impact on the attenuation of PAR.By the results of this paper,PAR can be calculated reliably by multispectral data.

Water Use in Sugar and Ethanol Industry in the State of Sao Paulo(Southeast Brazil)

Brazil is the largest producer of ethanol from sugarcane in the world. While the ethanol industry is economically important to Brazil for several reasons, it also has a significant impact on the environment. Here we analyze the water consumptive use in the transformation of the feedstock (sugarcane) into ethanol and the impact of industrial byproduct effluents on water resources of the state of Sao Paulo, Brazil. Our estimates indicated that in the 2007-2008 harvest, 700 million m3 was withdrawn mainly from rivers and streams by 140 mills, and of this total 440 million m3 was consumed which yielded a water use of approximately 1.53 m3 ·water·tonˉ1 sugarcane or approximately 18 L·water·L-ˉ1 ethanol. At the same time, a total of 120 million m3 of vinasse by-product was produced in the state, equivalent to an organic load of approximately 3 billion kg·BOD during the harvest season or approximately 8 million kg·BOD·dˉ1. Although the water used by sugarcane mills has decreased in recent decades, it is still possible to further decrease the amount of water used by ethanol production. This would decrease the pressure on 1st order streams of the state from which most water is withdrawn. In addition, the enormous volume of vinasse production must be reduced because it exerts constant pressure on aquatic ecosystems, soil and groundwater due to the constant increase in the potassium (K) concentration in areas where it is used as a fertilizer.

Resilience indicators support valuation of estuarine ecosystem restoration under climate change

Economic valuation of ecological restoration most often encompasses only the most tangible ecosystem service benefits,thereby omitting many difficult-to measure benefits,including those derived from enhanced reliability of ecosystem services.Because climate change is likely to impose novel ecosystem stressors,a typical approach to valuing benefits may fail to capture the contribution of ecosystem resilience to sustaining long-term benefits.Unfortunately,we generally lack predictive probabilistic models that would enable measurement and valuation of resilience.Therefore,alternative measures are needed to complement monetary values and broaden understanding of restoration benefits.We use a case study of Chesapeake Bay restoration(total maximum daily load)to show that ecosystem service benefits that are typically monetized leave critical information gaps.To address these gaps,we review evidence for ecosystem services that can be quantified or described,including changes in harmful algal bloom risks.We further propose two integrative indicators of estuarine resilience-the extent of submerged aquatic vegetation and spatial distribution of fish.Submerged aquatic vegetation extent is indicative of qualities of ecosystems that promote positive feedbacks to water quality.Broadly distributed fish populations reduce risk by promoting diverse responses to spatially heterogeneous stresses.Our synthesis and new analyses for the Chesapeake Bay suggest that resilience metrics improve understanding of restoration benefits by demonstrating how nutrient and sediment load reductions will alleviate multiple sources of stress,thereby enhancing the system’s capacity to absorb or adapt to extreme events or novel stresses.

Stressing over the Complexities of Multiple Stressors in Marine and Estuarine Systems

Aquatic ecosystems are increasingly threatened by multiple human-induced stressors associated with climate and anthropogenic changes,including warming,nutrient pollution,harmful algal blooms,hypoxia,and changes in CO_(2) and pH.These stressors may affect systems additively and synergistically but may also counteract each other.The resultant ecosystem changes occur rapidly,affecting both biotic and abiotic components and their interactions.Moreover,the complexity of interactions increases as one ascends the food web due to differing sensitivities and exposures among life stages and associated species interactions,such as competition and predation.There is also a need to further understand nontraditional food web interactions,such as mixotrophy,which is the ability to combine photosynthesis and feeding by a single organism.The complexity of these interactions and nontraditional food webs presents challenges to ecosystem modeling and management.Developing ecological models to understand multistressor effects is further challenged by the lack of sufficient data on the effects of interactive stressors across different trophic levels and the substantial variability in climate changes on regional scales.To obtain data on a broad suite of interactions,a nested set of experiments can be employed.Modular,coupled,multitrophic level models will provide the flexibility to explore the additive,amplified,propagated,antagonistic,and/or reduced effects that can emerge from the interactions of multiple stressors.Here,the stressors associated with eutrophication and climate change are reviewed,and then example systems from around the world are used to illustrate their complexity and how model scenarios can be used to examine potential future changes.