太湖湖岸带浮游植物初级生产力特征及影响因素

利用高频溶解氧监测,估算了太湖梅梁湾湖岸带浮游植物初级生产力的高频变化特征。结合同步气象监测及浮游植物、浮游动物和营养盐的周年逐周观测数据,分析了气象和环境条件对富营养化湖泊浮游植物初级生产力的影响。结果发现,高频溶解氧监测估算的初级生产力变化与浮游藻类生物量的变化一致,能够反映出浮游植物生产力的昼夜变化、季节变化等规律。统计分析表明,气温对太湖这一富营养化湖泊初级生产力影响很大;氮的供给与浮游动物的选择性牧食也是影响浮游植物初级生产力的重要因素。湖岸带的水华堆积过程对初级生产力影响巨大,气象、水文过程又加剧了蓝藻水华初级生产力的变化幅度,反映出富营养化湖泊初级生产力可能存在极大的时空不均一性。研究表明,溶解氧高频监测法估算初级生产力能够捕捉到湖泊初级生产力的快速变化过程,可以用于富营养化湖泊初级生产力监测、蓝藻水华灾害预警中。     

全球气候变化下的海洋浮游植物多样性

理解全球气候变化对地球生态系统的影响是全世界广泛关注的问题, 而相比于陆地生态系统, 海洋生态系统对全球气候变化更为敏感。全球气候变化对海洋的影响主要表现在海洋暖化、海洋酸化、大洋环流系统的改变、海平面上升、紫外线辐射增强等方面。浮游植物是海洋生态系统最重要的初级生产者, 同时对海洋碳循环起到举足轻重的作用, 其对全球气候变化的响应主要体现在物种分布、初级生产力、群落演替、生物气候学等方面。具体表现在以下方面: 暖水种的分布范围在扩大, 冷水种分布范围在缩小; 浮游植物全球初级生产力降低; 浮游植物群落会向细胞体积更小的物种占优势的方向转变; 浮游植物水华发生的时间提前、强度增强; 一些有害物种水华的发生频率也会增加; 海洋表层海水的酸化会影响浮游植物特别是钙化类群的生长和群落多样性; 紫外辐射增强对浮游植物的生长起到抑制作用; 厄尔尼诺、拉尼娜、降水量的增加通常抑制浮游植物生长。浮游植物生长和分布的变化会体现在多样性的各个层面上。对于浮游植物在全球变化各种驱动因子下的生理生态学和长周期变动观测等是今后研究的重要方向, 也将为理解全球变化下的浮游植物-多样性-生态系统响应与反馈机制提供基本信息。     

盐碱池塘浮游植物初级生产力的研究

根据黑白瓶测氧法测定 ,山东省高青县赵店渔场盐碱池塘鱼类生长期内 (4— 9月 )浮游植物初级生产力为9 42± 4 2 1gO2 (m2 ·d) ,日P/B系数平均 0 2 4± 0 18,浮游植物对太阳有效辐射的利用率平均 1 5 3%。无鱼对照池浮游植物初级生产力显著低于养鱼池。回归分析表明 ,浮游植物现存量、透明度、水温、盐度是决定盐碱池塘浮游植物初级生产力的主要生态因子。营养盐中磷比氮的限制作用大。文中探讨了养鱼池初级生产力在能量转化中的生态学效率。     

全球CO2 水平升高对浮游植物生理和生态影响的研究进展

工业革命以来由于化石燃料的大量燃烧,大气CO₂水平不断增加,预计在21世纪末将增至现有水平的两倍,达到750 μL/L。作为全球初级生产力的重要贡献者,浮游植物应对CO₂水平升高的生理生态响应必然会对水生生态系统和碳、氮等元素的生物地球化学循环产生重要影响。全球CO₂水平的升高将显著改变水体的碳化学环境,淡水生态系统(湖泊和河流)由于容量小变化比海洋更为显著。水体碳化学环境的改变首先会影响浮游植物个体,在高CO₂水平下,浮游植物的细胞会有变小的趋势,并且细胞的光合作用强度也会有不同程度的增加,其中细胞较小或者不具有碳浓缩机制(CCM)的浮游植物增加较多,此外浮游植物细胞的化学元素计量值也将显著改变。随后浮游植物个体水平上的变化会进一步影响水生生态系统,例如水体初级生产力水平的提高,浮游植物、浮游动物群落结构组成以及水体微食物网结构的变化等。此外浮游植物对CO₂水平升高的生理生态响应程度还与水体的营养水平有关。总结了大气CO₂水平升高对浮游植物生理生态影响的研究方法,展望了未来可能的研究方向。     

海洋微型浮游动物对浮游植物和初级生产力的摄食压力

综述了国际上研究微型浮游动物对浮游植物和初级生产力摄食的方法,并重点介绍了稀释法的理论和在实践中遇到的问题。各种方法的微型浮游动物对浮游植物和初级生产力摄食压力的估计表明,微型浮游动物在海洋生态系统中的扮演重要角色。     

基于MODIS和CASA模型的伊春市森林植被NPP变化特征及其影响因子分析

植被净初级生产力(net primary productivity,NPP)是判定生态系统质量状况和碳汇的重要因子,反映了植被群落的生产能力和生态过程,对调节全球碳平衡、增强生态服务功能具有重要的意义.本文基于MODIS卫星遥感资料和改进的CASA模型,利用2000-2019年MOD17A3HGF的NPP年际数据和气象...     

海水中叶绿素的测定

海洋浮游植物生物量及其变化,在很大程度上决定着海洋水域生产力的盛衰。为要了解海洋生物资源的蕴藏量,查找能为人类提供大量食品的高生产力区,首先必须对海洋水域中的浮游植物生产量及其变化作定量研究,亦即进行海洋初级生产力的研究。近些年,国际     

赤潮过程浮游植物与营养物质时间变化率研究

利用2000年大亚湾澳头海域赤潮定点连续调查资料及其多年现场调查资料,采用灰色回归模型,综合分析赤潮发生过程水体中浮游植物细胞密度与营养物质(NO3-、NH4+、PO4^3-、SiO3^2-、Fe)的时间变化率关系,分析了叶绿素a含量与浮游植物细胞密度相互关系．结果表明,预测值与实测基值本一致,复相关系数范围在0．51～0．83．当水体叶绿素浓度为5．8μg·dm-3,预示可能发生赤潮,通过采样分析水体叶绿素a含量或利用水色卫星遥感资料反演水体叶绿素浓度,计算浮游植物细胞密度,为赤潮的预测预报提供简便有效的方法．此外．本水域初级生产力由磷控制．     

遥感GPP模型在中亚干旱区4个典型生态系统的适用性评价

总初级生产力(GPP)是全球生态系统碳循环的重要组成部分,对全球气候变化有重要影响。目前有多种遥感模型可以模拟总初级生产力,比较不同遥感模型在中亚干旱区上的适用性对推进全球干旱区碳收支估算具有重要意义。基于涡度协相关技术观测的四个地面站数据验证MOD17、VODCA2、VPM、TG、SANIRv五种模型的模拟精度。结果表明：(1)基于光能利用率理论的MOD17、VPM模型模拟咸海荒漠植被和阜康荒漠植被GPP的精度最高(R²分别为0.52和0.80),但在模拟草地、农田生态系统生产力时存在较明显的低估(RE>20%);基于植被指数的遥感模型TG模型、SANIRv模型模拟巴尔喀什湖草地生态系统和乌兰乌苏农田生态系统GPP的精度最高(R²分别为0.91和0.81),同时模拟值与实测值的相对误差也较低;基于微波的VODCA2模型模拟各生态系统生产力的效果最差。(2)水分亏缺是限制植被GPP的主要因素,因此是否合理考虑水分胁迫是影响GPP模型在中亚干旱区适用性的重要因素。研究揭示了遥感GPP模型在中亚干旱区的应用潜力,为推进全球植被碳通量的准确估...     

珊瑚礁生态系统初级生产力研究进展

珊瑚礁生态系统由珊瑚礁生物群落及其周围的海洋环境共同组成。该生态系统具有很高的生产力和生物多样性而引起科学家的重视 ,特别是高初级生产力。初级生产力的贡献者包括底栖植物、浮游植物、共生藻和自养细菌等。初级生产力的测定方法较多 ,各有利弊 ,通常采用 1 4C同位素法。在初级生产力中 ,新生产力更引起科学界关注。对于新生产力的测定 ,主要应用 1 5N示踪法 ,采用“f”比或 Redfield比值来估算。为了减少误差 ,一般同时使用几种方法。光是影响初级生产力的主要因素 ,而对新生产力构成限制的主要因素是氮源。珊瑚礁生态系统初级生产力研究较多 ,但新生产力却很少。未来科学界研究重点在于珊瑚礁生态系统初级生产力和新生产力的动力学效应     

陆地植被净初级生产力计算模型研究进展

植被净初级生产力(NPP)研究是全球变化与陆地生态系统的核心内容之一。在回顾NPP模型研究的基础上,综合分析了气候模型、生态生理过程模型、光能利用率模型各自的优缺点,并对NPP模型研究做出展望。生态生理过程模型是当前陆地NPP估算研究的主要手段,而区域尺度转换则是它所面临的关键问题。近年来光能利用率模型已成为NPP估算的一种全新手段,它利用遥感所获得的全覆盖数据,使区域及全球尺度的NPP估算成为可能,但其生态学机理还有待于进一步研究。已有研究表明,“生态一遥感耦合模型”将是陆地NPP估算的主要发展方向,它融合了生态生理过程模型和光能利用率模型的优点,增强了NPP模型估算的可靠性和可操作性。     

Phytoplankton decline in the eastern North Pacific transition zone associated with atmospheric blocking

Global climate change can significantly influence oceanic phytoplankton dynamics, and thus biogeochemical cycles and marine food webs. However, associative explanations based on the correlation between chlorophyll‐a concentration (Chl‐a) and climatic indices is inadequate to describe the mechanism of the connection between climate change, large‐scale atmospheric dynamics, and phytoplankton variability. Here, by analyzing multiple satellite observations of Chl‐a and atmospheric conditions from National Center for Environmental Prediction/National Center for Atmospheric Research reanalysis datasets, we show that high‐latitude atmospheric blocking events over Alaska are the primary drivers of the recent decline of Chl‐a in the eastern North Pacific transition zone. These blocking events were associated with the persistence of large‐scale atmosphere pressure fields that decreased westerly winds and southward Ekman transport over the subarctic ocean gyre. Reduced southward Ekman transport leads to reductions in nutrient availability to phytoplankton in the transition zone. The findings describe a previously unidentified climatic factor that contributed to the recent decline of phytoplankton in this region and propose a mechanism of the top‐down teleconnection between the high‐latitude atmospheric circulation anomalies and the subtropical oceanic primary productivity. The results also highlight the importance of understanding teleconnection among atmosphere–ocean interactions as a means to anticipate future climate change impacts on oceanic primary production.     

遥感在森林地上生物量估算中的应用

生物量是地表C循环研究的重要组成部分,生物量研究有助于深入认识区域乃至全球的C平衡。森林作为地球最重要的陆地生态系统,区域乃至全球尺度的森林地上生物量估算一直是生态学研究的难点之一。在大的空间尺度上,遥感技术是估算森林地上生物量的有效手段。TM、AVHRR、SAR等数据以及多源数据的融合在森林生物量估算方面广泛应用,并取得了显著效果。运用遥感技术进行森林生物量估算时,所采用的数据源不同,分析方法也不相同,主要分析方法有:相关分析、多元回归分析、神经网络和数学模型模拟等。随着测定不同空间、时间和波谱分辨率的各种传感器的广泛使用,以及生物量遥感估算模型的进一步发展和完善,大尺度森林生物量的遥感估算研究必将向前迈进一大步。     

玉米农田冠层光合参数的多光谱遥感反演

冠层光合参数的准确定量遥感反演是生态系统遥感模型的核心与关键。基于2011年玉米(Zea mays)整个生长发育期的冠层光谱反射率、生态系统CO₂通量、微气象因子以及玉米光合生理生态指标的观测数据, 开展了玉米农田生态系统冠层光合能力(P_max, 最大光合速率)与光合效率(ε_N, 净CO₂通量交换/吸收光合有效辐射(NEE_CO2/APAR); ε_G, 总初级生产力/吸收光合有效辐射(GPP/APAR); α, 表观量子效率)参数的多光谱遥感反演能力评估研究。结果表明, P_max和α在整个生长季呈现单峰型变化趋势, 分别于7月底、8月初达到峰值, 而光合效率参数ε_N和ε_G在玉米营养生长早期数值较高, 随着玉米生长发育迅速降低, 而后呈现单峰型的变化趋势, 峰值出现时间基本与P_max最大值发生时间一致。基于两波段任意组合的遥感植被指数NDVI (normalized difference vegetation index)、RVI (ratio vegetation index)、WDRVI (wide dynamic range vegetation index)、EVI2 (2-band enhanced vegetation index)和CI (chlorophyll index)与玉米冠层4个光合参数的统计分析表明, EVI2对冠层光合效率与光合能力参数的反演与表征效果最佳。研究表明, 多光谱遥感信息对玉米生态系统冠层光合参数的变异具有较强的敏感性, 可以用来监测玉米冠层光合作用的季节动态变化以及准确定量评估作物生产力和生态系统CO₂交换能力。     

From silk to satellite: half a century of ocean colour anomalies in the Northeast Atlantic

Changes in phytoplankton dynamics influence marine biogeochemical cycles, climate processes, and food webs, with substantial social and economic consequences. Large‐scale estimation of phytoplankton biomass was possible via ocean colour measurements from two remote sensing satellites – the Coastal Zone Colour Scanner (CZCS, 1979–1986) and the Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS, 1998–2010). Due to the large gap between the two satellite eras and differences in sensor characteristics, comparison of the absolute values retrieved from the two instruments remains challenging. Using a unique in situ ocean colour dataset that spans more than half a century, the two satellite‐derived chlorophyll‐a (Chl‐a) eras are linked to assess concurrent changes in phytoplankton variability and bloom timing over the Northeast Atlantic Ocean and North Sea. Results from this unique re‐analysis reflect a clear increasing pattern of Chl‐a, a merging of the two seasonal phytoplankton blooms producing a longer growing season and higher seasonal biomass, since the mid‐1980s. The broader climate plays a key role in Chl‐a variability as the ocean colour anomalies parallel the oscillations of the Northern Hemisphere Temperature (NHT) since 1948.     

南海北部表层硝酸盐浓度反演研究

研究首次利用南海北部船基观测数据资料建立硝酸盐和海表温度的关系, 然后通过MODIS-SST资料与现场海表温度比较后进行了订正。利用订正后的数据表明南海北部的表层硝酸盐和海表温度之间存在显著的负相关关系(R²=0.7126)。结合海表硝酸盐和海表温度的关系式, 利用遥感海表温度的8 d平均值和月平均值估测了南海北部的表层硝酸盐浓度, 8 d平均海表硝酸盐浓度值范围为0～3.3167 μM, 月平均值为0～2.0590 μM, 该值与现场监测数据及历史资料均一致。     

Individual and interactive effects of ocean acidification,global warming,and UV radiation on phytoplankton

Rising carbon dioxide (CO₂) concentrations in the atmosphere result in increasing global temperatures and ocean warming (OW). Concomitantly, dissolution of anthropogenic CO₂ declines seawater pH, resulting in ocean acidification (OA) and altering marine chemical environments. The marine biological carbon pump driven by marine photosynthesis plays an important role for oceanic carbon sinks. Therefore, how ocean climate changes affect the amount of carbon fixation by primary producers is closely related to future ocean carbon uptake. OA may upregulate metabolic pathways in phytoplankton, such as upregulating ß-oxidation and the tricarboxylic acid cycle, resulting in increased accumulation of toxic phenolic compounds. Ocean warming decreases global phytoplankton productivity; however, regionally, it may stimulate primary productivity and change phytoplankton community composition, due to different physical and chemical environmental requirements of species. It is still controversial how OA and OW interactively affect marine carbon fixation by photosynthetic organisms. OA impairs the process of calcification in calcifying phytoplankton and aggravate ultraviolet (UV)-induced harms to the cells. Increasing temperatures enhance the activity of cellular repair mechanisms, which mitigates UV-induced damage. The effects of OA, warming, enhanced exposure to UV-B as well as the interactions of these environmental stress factors on phytoplankton productivity and community composition, are discussed in this review.     

A phytoplankton absorption-based primary productivity model for remote sensing in the Southern Ocean

Recent global environmental changes such as an increase in sea surface temperature (SST) are likely to impact primary productivity of phytoplankton in the Southern Ocean. However, models to estimate net primary production using satellite data use SST and uncertain estimation of chlorophyll a (chl-a) concentration. A primary productivity model for satellite ocean color data from the Southern Ocean, which is based on the light absorption coefficient of phytoplankton to reduce uncertainties of sea surface chl-a estimations and bias in optimal values of chl-a normalized productivity derived from SST, has been developed. The new model was able to estimate net primary productivity in the water column (PP _eu) without dependency on temperature when in the range of −2 to 25°C, and it explained 51% of the observed variability in PP _eu with a root mean square error (RMSE) of 0.15. Application of the model revealed that the SST dependent model has overestimated PP _eu in warmer waters around the Subtropical Front, and underestimated PP _eu in colder waters poleward of the Sub-Antarctic Front. This absorption-based primary productivity model contributes to a study of the relationship among spatio-temporal variations in the physical environment, and biogeochemical cycles in the Southern Ocean.     

Improved monitoring of HABs using autonomous underwater vehicles (AUV)

Blooms of toxic algae are increasing in magnitude and frequency around the globe, causing extensive economic and environmental impacts. On the west coast of Florida, blooms of the toxic dinoflagellate Karenia brevis (Davis) have been documented annually for the last 30 years causing respiratory irritation in humans, fish kills, and toxin bioaccumulation in shellfish beds. As a result, methods need to be established to monitor and predict bloom formation and transport to mitigate their harmful effects on the surrounding ecosystems and local communities. In the past, monitoring and mitigation efforts have relied on visual confirmation of water discoloration, fish kills, and laborious cell counts, but recently satellite remote sensing has been used to track harmful algal blooms (HABs) along the Florida coast. Unfortunately satellite ocean color is limited by cloud cover, lack of detection below one optical depth, and revisit frequency, all of which can lead to extended periods without data. To address these shortcomings, an optical phytoplankton discriminator (OPD) was developed to detect K. brevis cells in mixed phytoplankton assemblages. The OPD was integrated into autonomous underwater vehicle (AUV) platforms to gather spatially and temporally relevant data that can be used in collaboration with satellite imagery to provide a 3D picture of bloom dynamics over time. In January 2005, a Remote Environmental Monitoring UnitS (REMUS) AUV with an OPD payload was deployed on the west coast of Florida to retrieve a similarity index (SI), which indicates when K. brevis dominates the phytoplankton community. SI was used to monitor a K. brevis bloom in relation to temperature, salinity, chlorophyll, and ocean currents. Current speed, SI, temperature, salinity, and chlorophyll a from the AUV were used to quantify a 1 km displacement of the K. brevis bloom front that was observed over the deployment period. The ability to monitor short term bloom movement will improve monitoring and predictive efforts that are used to provide warnings for local tourism and fishing industries. In addition, understanding the fine scale environmental conditions associated with bloom formation will increase our ability to predict the location and timing of K. brevis bloom formation. This study demonstrates the use of one autonomous platform and provides evidence that a nested array of AUVs and moorings equipped with new sensors, combined with remote sensing, can provide an early warning and monitoring system to reduce the impact of HABs.     

127 Climate Variability and Phytoplankton Production in PNW Coast Estuaries

The west coast of North America receives strong forcing from climate modes such as El Niño-Southern Oscillation and the Pacific Decadal Oscillation. Estuaries are poised at a sensitive interface because estuarine biota and habitat will be affected by variability in properties and processes associated with the ocean, the watershed, and the local weather. Observations from the Washington coast and Willapa Bay illustrate these three arenas of influence. Variation in ocean upwelling and ocean thermocline depth associated with the 1997–98 El Niño versus the 1999 La Niña affected temperature and nutrient availability in Willapa Bay. Variation in river flow associated with the 2000–01 drought affected estuarine circulation and residence time. And, variation in prevailing wind direction and/or cloudiness was highly correlated with phytoplankton biomass. This situation is responsible for the complexity of understanding climate impacts on estuarine systems. In order to help evaluate which mechanisms, remote oceanic processes or local watershed/estuarine characteristics, most affected Willapa Bay's phytoplankton production, several phytoplankton species were used as indicators of water mass origin and compared with primary productivity data to assess whether phytoplankton blooms were dominated by endemic or imported species. Our analysis resolved that the highest primary production (and the appearance of Pseudo-nitzschia spp.) was associated with oceanic intrusions of phytoplankton biomass into Willapa Bay. This result underscores the dominant role that variation in ocean and climate play in controlling Pacific Northwest estuarine production. However, while the largest blooms were oceanic in origin, numerous medium-sized production events were from either oceanic or estuarine sources, indicating a complex picture.