Chlorophyll budget in a productive tropical pond: algal production,sedimentation, and grazing by microzooplankton and rotifers

Chlorophyll a and pheopigment standing stocks and fluxes were used during a two weeks colonization experiment in a productive tropical pond (Layo, Côte d'Ivoire) in order to establish a chlorophyll budget. The experiment started from an azoïc state (the pond was dried, limed and progressively filled with ground water). Algal production was the only input to the phytoplanktonic system, while grazing and algal sedimentation were the main outputs. Chlorophyll a reflected the algal biomass, and degradation pigments were considered as an index of grazing by zooplankton (here, protozoans and rotifers). An estimation of the input through the algal growth rate was performed for the two main biological events observed during the study. The first algal bloom, with a large picoplankton participation, was mainly regulated by microzooplankton (increase of the peak) and rotifers (decrease of the peak). The second bloom (exclusively nanoplankton) was regulated by rotifers (increase) and by sedimentation of living cells (decrease). This last process was related to a sudden exhaustion of ammonia in the water column. Because of the time-lag between algal proliferation and zooplanktonic bloom, the phytoplanktonic biomass was able to be adjusted according to the availability of nutrients. This self-regulation took the form of sinking of active algal cells, resulting in a transient reduction of the food available for rotifers. This process had drastic consequences in these shallow waters, since a major part of the phytoplankton produced was removed from the pelagic system. For an optimal exploitation of the natural resources of an aquaculture pond, a study of the equilibrium nutrients-phytoplankton-zooplankton would provide a basis for artificial intervention, with a view to limit the impact of this mode of natural regulation.     

Forecasting of environmental risk maps of coastal algal blooms

We present the elements of an algal bloom risk forecast system which aims to provide a scientific prognosis of the likelihood of an algal bloom occurrence as a function of: (a) the nutrient concentration; and (b) the forecasted wind and tide-induced vertical mixing relative to the critical value defined by the environmental and algal growth conditions. The model is validated with high frequency field observations of algal blooms in recent years and only requires the input of readily available field measurements of water column transparency, nutrient concentration, representative maximum algal growth rate, and a simple estimate of vertical mixing as a function of tidal range, wind speed, and density stratification. The forecasted region-wide risk maps successfully predicted the observed algal bloom occurrences in Hong Kong waters over the past 20 years, with a correct prognosis rate of 87%. It is shown that algal blooms are to a large extent controlled by the interaction of physical and biological processes. This work provides a general framework to interpret the complex spatial and temporal dynamics of observed algal blooms, and paves the way for the development of real time algal bloom risk forecast systems.     

Australia's marine biogeography revisited: Back to the future?

The recognition of broad biogeographic provinces provides an important framework for ecological and conservation biological research. Marine biologists have long recognized distinct biogeographic provinces in southern Australia, primarily on the basis of qualitative differences in intertidal species assemblages. Here we provide an a priori test for these traditional eastern (Peronian), western (Flindersian) and south‐eastern (Maugean) provinces. Specifically, we analyse distributional data for approximately 1500 algal species using the newly available Australian Virtual Herbarium, an online database of herbarium specimens. Our quantitative algal analyses across southern Australia identify three distinct biogeographic assemblages, consistent with traditional qualitative provinces. We argue that these broad provinces provide a highly effective framework for understanding and managing Australia's marine biodiversity. In particular, biogeographic provinces provide a regional framework for integrating the ongoing discovery of biological variation at finer scales. More broadly therefore we recommend that biologists undertake quantitative analyses to test provincial biogeographic boundaries around the globe.     

不同类型生物土壤结皮覆盖下风沙土的入渗特征及模拟

干旱荒漠区广泛分布的生物土壤结皮(BSCs)对土壤水分入渗过程有重要影响。以古尔班通古特沙漠南缘的BSCs为研究对象,基于野外采样与室内模拟实验等方法,探究藓类、地衣和藻等3种类型BSCs覆盖下沙土的入渗特征。结果表明:与无结皮覆盖的风沙土对照,3种类型BSCs均显著降低了沙土初渗速率,藓类结皮、地衣结皮、藻结皮覆盖下初渗速率降低幅度依次为36.10%、46.42%、50.39%;藓类结皮、地衣结皮(P0.05)和藻结皮(P0.05)均明显降低了沙土稳渗速率,降低幅度依次为16.50%、33.98%和35.92%;3种类型BSCs均限制了湿润锋在沙土的推进过程,表现为:藓类结皮、地衣结皮、藻结皮的渗漏时间分别为裸沙对照的2.13、3.04和2.98倍;各类型BSCs均减小了沙土累积入渗量,阻碍了沙土水分入渗,与裸沙对照相比,藓类结皮、地衣结皮、藻结皮的1 h累积入渗量分别降低16.10%、28.56%和26.56%。在实验条件下,Kostiakov模型最适用于模拟不同类型BSCs覆盖下土壤水分入渗过程,Horton模型模拟效果次之。     

环境水体藻毒素生物处理技术研究进展

近年来,随着水体富营养化程度加剧,蓝藻水华现象时有发生,蓝藻及其释放的藻毒素对生态环境和人类健康构成严重威胁.本文概述了常见藻毒素的分类及其主要理化性质,总结了生物接触氧化、生物滤池和生物-生态耦合等工艺对藻毒素的去除性能与机制,分析了生物处理工艺的反应条件(温度、pH和水力停留时间)、原水性质及营养限制等影响因素,并对藻毒素去除机理、新工艺研发等方面进行了展望.     

OPTICAL MONITORING AND FORECASTING SYSTEMS FOR HARMFUL ALGAL BLOOMS: POSSIBILITY OR PIPE DREAM?

Monitoring programs for harmful algal blooms (HABs) are currently reactive and provide little or no means for advance warning. Given this, the development of algal forecasting systems would be of great use because they could guide traditional monitoring programs and provide a proactive means for responding to HABs. Forecasting systems will require near real-time observational capabilities and hydrodynamic/biological models designed to run in the forecast mode. These observational networks must detect and forecast over ecologically relevant spatial/ temporal scales. One solution is to incorporate a multiplatform optical approach utilizing remote sensing and in situ moored technologies. Recent advances in instrumentation and data-assimilative modeling may provide the components necessary for building an algal forecasting system. This review will outline the utility and hurdles of optical approaches in HAB detection and monitoring. In all the approaches, the desired HAB information must be isolated and extracted from the measured bulk optical signals. Examples of strengths and weaknesses of the current approaches to deconvolve the bulk optical properties are illustrated. After the phytoplankton signal has been isolated, species-recognition algorithms will be required, and we demonstrate one approach developed for Gymnodinium breve Davis. Pattern-recognition algorithms will be species-specific, reflecting the acclimation state of the HAB species of interest.Field data will provide inputs to optically based ecosystem models, which are fused to the observational networks through data-assimilation methods. Potential model structure and data-assimilation methods are reviewed.     

藻类快速鉴定研究进展

综述了传统形态学方法和生物化学法、分子生物学法在藻类鉴定中的应用及其原理,系统阐述了以上方法的研究进展。在藻类鉴定中,生物化学法和分子生物学法是新兴技术,其中的分子鉴定技术,是根据物种的基因差异来定性分类物种,可以快速稳定地鉴定藻类。分子生物学法在水华藻类快速鉴定方面具有很大的发展潜力,有望得到广泛应用。     

Predicting local biological characteristics in streams: a comparison of landscape classifications

1. Landscape classifications group tracts of land based on similar physico‐chemical attributes that may affect the biological characteristics of streams at local scales. We tested the ability of five landscape models to account for variation in algal and macroinvertebrate biomass, brook trout (Salvelinus fontinalis) growth and macroinvertebrate community composition from 132 riffles in 15 catchments in the Big Horn Mountains, Wyoming. 2. A model created by the U.S. Forest Service (FS) combined catchment and ecoregion approaches to classify the landscape. Our model used digital elevations to create a landscape classification for streams (DEM). The last three models were based on: (1) standard ecoregions (Ecoregion), (2) the type of underlying bedrock (Geology) and (3) the geographical distance between sites (Site Proximity model). 3. Overall, the Ecoregion and Geology models performed better than the two catchment models (FS and DEM) in predicting local biological characteristics. The Geology model was best at predicting differences in algal and macroinvertebrate biomass, the Site Proximity and Ecoregion models were best at predicting patterns of similarity in macroinvertebrate community composition, and the Site Proximity, Ecoregion, Geology, and FS models, in order from best to worst, accounted for significant variation in brook trout growth. The Site Proximity model performed well because of the effects of spatial autocorrelation. The DEM was consistently one of the worst models at predicting local biological characteristics because it failed to include important attributes (e.g. dominant geology). Calcareous geology was positively associated with greater macroinvertebrate biomass and faster brook trout growth, but it was inversely related to algal biomass. 4. None of the models accounted for a large amount of variation in local biological characteristics. Single‐scale, landscape classifications may never accurately predict variation in local biological characteristics because: (1) landscapes show a high degree of spatial heterogeneity, (2) local effects are stronger than landscape attributes and (3) there are too many intervening levels between landscape and local scales in the nested hierarchy of streams. However, landscape classifications did account for significant variation in biological characteristics. Thus, they would be a valuable management tool as part of a multi‐scale, hierarchical technique for classifying stream ecosystems.     

Algal photosynthetic aeration increases the capacity of bacteria to degrade organics in wastewater

Wastewater treatment is an energy-intensive process and a net emitter of greenhouse gas emissions. A large fraction of these emissions is due to intensive aeration of aerobic bacteria to facilitate break-down of organic compounds. Algae can generate dissolved oxygen at levels in excess of saturation, and therefore hold the potential to partially displace or complement mechanical aeration in wastewater treatment processes. The objective of this study was to develop an internally consistent experimental and modeling approach to test the hypothesis that algal photosynthetic aeration can speed the removal of organic constituents by bacteria. This framework was developed using a simplified wastewater treatment process consisting of a model bacteria (Escherichia coli), a model algae (Auxenochlorella protothecoides), and a single carbon source that was consumable by bacteria only. This system was then tested both with and without the presence of algae. A MATLAB model that considered mass transfer and biological kinetics was used to estimate the production and consumption of O₂ and CO₂ by algae and bacteria. The results indicated that the presence of algae led to 18–66% faster removal of COD by bacteria, and that roughly one-third of biochemical oxygen demand was offset by algal photosynthetic aeration.     

Algae as indicators of environmental change

Despite an increased awareness by governments and the general public of the need for protecting all types of aquatic habitats, human impacts continue to impair the services that these ecosystems provide. Increased monitoring activities that locus on all major biological compartments are needed to quantify the present condition of Earth's aquatic resources and to evaluate the effectiveness of regulations designed to rehabilitate damaged ecosystems. Algae are an ecologically important group in most aquatic ecosystems but are often ignored as indicators of aquatic ecosystem change. We attribute this situation both to an underappreciation of the utility of algal indicators among non-phycologists and to a lack of standardized methods for monitoring with algae.Because of their nutritional needs and their position at the base of aquatic foodwebs, algal indicators provide relatively unique information concerning ecosystem condition compared with commonly used animal indicators. Algae respond rapidly and predictably to a wide range of pollutants and, thus, provide potentially useful early warning signals of deteriorating conditions and the possible causes. Algal assemblages provide one of the few benchmarks for establishing historical water quality conditions and for characterizing the minimally impacted biological condition of many disturbed ecosystems. Preliminary comparisons suggest that algal indicators are a cost-effective monitoring tool as well.Based on available evidence from field studies, we recommend development of taxonomic indicators based on diatoms (Bacillariophyceae) as a standardized protocol for monitoring ecosystem change. Both population- and community-level indices have inherent strengths, and limitations and information from both levels of biological organization should be utilized in tandem. However, further information concerning species tolerances to a variety of anthropogenic stressors is needed if autecological indices are to be used routinely for monitoring purposes. While functional measures (e.g. productivity) may also prove useful as monitoring tools, further investigation is required to characterize the reliability of alternative methodologies and to assess the consistency of these indicators under varying field conditions.Author for correspondence     

A suggested standardised method for testing photocatalytic inactivation of aeroterrestrial algal growth on TiO2-coated glass

Aeroterrestrial green algae form conspicuous biofilms on man-made surfaces. The self-cleaning properties of photocatalytic coatings prevent their growth and can probably replace biocides. The aim of this study was to develop a laboratory method to investigate the efficiency of photocatalytic materials against algal growth. Two algal isolates (“Chlorella” luteoviridis, SAG 2196, and Coccomyxa sp., SAG 2040) functioned well as model organisms because they grew on almost all test specimens at 100% humidity and low UVA radiation. With these species, we examined algal growth prevention using photocatalytic glass. No effects on algal growth were detected, although the coated surfaces were photocatalytically active and degraded methylene blue. Because their cells are protected well against photocatalytically generated hydroxyl radicals, aeroterrestrial algae survive various stress factors. Nevertheless, the newly developed experimental design may be useful for assessing the biological function of other photocatalytic materials or stress factors.     

Disruption-free imaging by Raman spectroscopy reveals a chemical sphere with antifouling metabolites around macroalgae

Investigations of the surface chemistry of marine organisms are essential to understand their chemically mediated interactions with fouling organisms. In this context, the concentration of natural products in the immediate vicinity of algal surfaces, as well as their biological activity, are of particular importance. However, due to lack of appropriate methods, the distribution of compounds within the chemical sphere around marine algae is unknown. This study demonstrates the suitability of confocal resonance Raman microspectroscopy for the determination of metabolites around algal surfaces with a micrometer resolution. The spatial distribution of carotenoids in the diffusion boundary layer of the brown alga Fucus vesiculosus and the green alga Ulva sp. was determined using the disruption-free optical method. A gradient of carotenoids was determined within 0 to 150 μm from the surface of the algae, thereby demonstrating the release of the non-polar metabolites involved in antifouling processes. The differences in the carotenoid composition of the brown and green algae were reflected in the spectra. Resonance Raman microspectroscopy also allowed visualization of the lateral distribution of fucoxanthin on the algal surface and localization of concentration maxima within a 50 × 50 μm(2) area. The results from this work show clearly that established dipping techniques suitable for the extraction of the diffusion boundary layer of macroalgae only provide an average of the local strongly variable concentrations of metabolites on algal surfaces.     

Improved Biomass and Hydrocarbon Productivity of Botryococcus braunii by Periodic Ultrasound Stimulation

Ultrasonic treatment was firstly found to accelerate both biomass and hydrocarbon productivities of Botryococcus braunii algal cells cultured in the shake flasks. The most effective sonication strategy was to subject the cells to three 5-min ultrasonic treatments at a 4-day interval using a fixed frequency of 40 kHz and power of 240 W, and the ultrasound-treated algal cells showed the highest biomass productivity of 0.043 g L^?1 day^?1 and the highest hydrocarbon productivity of 13.1 mg L^?1 day^?1 among all ultrasound treatments tested. The improved productivity was proved to be mainly due to the enhancement of both endogenous indole-3-acetic acid (IAA) biosynthesis and membrane permeability in the ultrasound-stimulated algal cells. The efficient ultrasonic stimulation strategy also showed good performance for the algal culture in a 2-L airlift bioreactor. Together, these results not only illustrate the immense potential for an enhanced understanding on ultrasound-stimulated algal cells but also as provide a powerful process intensification method to improve the biomass and hydrocarbon productivity of B. braunii in practice.     

氮、磷对镍在食物链上传递的影响

采用放射性同位素示踪法,研究氮或磷添加对镍在东海原甲藻(Prorocentrum donghaienseLu)和中肋骨条藻(Skeletonema costatum)胞内累积的影响;并将其分别投喂中华哲水蚤(Calanus sinicus)后,探讨镍在桡足类体内的吸收和生理周转。结果表明,经过24h暴露后,氮或磷显著影响这两种藻类对镍的吸收,且高浓度氮或磷均能促进镍在这两种藻类细胞内的累积,因而促进镍在中华哲水蚤体内的吸收;而镍在中华哲水蚤体内的生理周转率却不受氮或磷浓度的影响,似乎更受动物个体的生理状态影响;中华哲水蚤对镍的吸收率与藻类细胞内镍含量呈极显著相关(p<0.001),证明了"桡足类只吸收饵料细胞内的水相金属库"的假说。由此可见,近海富营养化可促进浮游植物对镍的吸收,进而影响该金属在浮游生物食物链上的传递。     

Combining model structure identification and hybrid modelling for photo-production process predictive simulation and optimisation

Integrating physical knowledge and machine learning is a critical aspect of developing industrially focused digital twins for monitoring, optimisation, and design of microalgal and cyanobacterial photo-production processes. However, identifying the correct model structure to quantify the complex biological mechanism poses a severe challenge for the construction of kinetic models, while the lack of data due to the time-consuming experiments greatly impedes applications of most data-driven models. This study proposes the use of an innovative hybrid modelling approach that consists of a simple kinetic model to govern the overall process dynamic trajectory and a data-driven model to estimate mismatch between the kinetic equations and the real process. An advanced automatic model structure identification strategy is adopted to simultaneously identify the most physically probable kinetic model structure and minimum number of data-driven model parameters that can accurately represent multiple data sets over a broad spectrum of process operating conditions. Through this hybrid modelling and automatic structure identification framework, a highly accurate mathematical model was constructed to simulate and optimise an algal lutein production process. Performance of this hybrid model for long-term predictive modelling, optimisation, and online self-calibration is demonstrated and thoroughly discussed, indicating its significant potential for future industrial application.     

BioCO2 - a multidisciplinary, biological approach using solar energy to capture CO2 while producing H2 and high value products

Many areas of algae technology have developed over the last decades, and there is an established market for products derived from algae, dominated by health food and aquaculture. In addition, the interest for active biomolecules from algae is increasing rapidly. The need for CO(2) management, in particular capture and storage is currently an important technological, economical and global political issue and will continue to be so until alternative energy sources and energy carriers diminish the need for fossil fuels. This review summarizes in an integrated manner different technologies for use of algae, demonstrating the possibility of combining different areas of algae technology to capture CO(2) and using the obtained algal biomass for various industrial applications thus bringing added value to the capturing and storage processes. Furthermore, we emphasize the use of algae in a novel biological process which produces H(2) directly from solar energy in contrast to the conventional CO(2) neutral biological methods. This biological process is a part of the proposed integrated CO(2) management scheme.     

赤潮过程中“藻-菌”关系研究进展

微生物对促进海洋物质循环,维持水生环境的生态平衡具有重要作用。在赤潮事件中,基于微生物(尤其是细菌)的多样性和重要性,它们与藻类之间的相互关系成为了研究的热点。过去20年里,人们从不同角度对"藻-菌"间的关系进行了探索,包括物理学过程、生物学过程、环境过程以及化学过程。就化学过程而言,它作为一种较早出现的技术,在以往的研究中带给人们许多认识藻菌关系的方法。随着学科的渗透,化学法有了拓展与延伸,为人们认识藻菌关系带来了新的契机。从化学生态学领域来梳理"藻-菌"关系中涉及的现象和行为,包括菌对藻的有益面、菌对藻的有害面、以及藻类应答细菌行为的化学途径;并从信号语言(群体感应、化感作用)的角度来阐释两者之间的互生或克生关系。通过文献综述的方式来解读藻菌关系的互作过程和机理,为认识赤潮的发生和防控方法提供借鉴。     

Review of advances in biological CO<Subscript>2</Subscript> mitigation technology

CO₂ fixation by microalgae has emerged as a promising option for CO₂ mitigation. Intensive research work has been carried out to develop a feasible system for removing CO₂ from industrial exhaust gases. However, there are still several challenging points to overcome in order to make the process more practical. In this paper, recent research activities on three key technologies of biological CO₂ fixation, an identification of a suitable algal strain, development of high efficient photobioreactor and utilization of algal cells produced, are described. Finally the barriers, progress, and prospects of commercially developing a biological CO₂ fixation process are summarized.     

Life cycle analysis of algae biodiesel

Background, aim, and scope  

Algae biomass has great promise as a sustainable alternative to conventional transportation fuels. In this study, a well-to-pump life cycle assessment (LCA) was performed to investigate the overall sustainability and net energy balance of an algal biodiesel process. The goal of this LCA was to provide baseline information for the algae biodiesel process.