Abstract Abiotic variables subject to global change are known to affect plankton biomasses, and these effects can be species-specific. Here, we investigate the environmental drivers of annual biomass using plankton data from the Gulf of Finland in the northern Baltic Sea, spanning years 1993–2016. We estimated annual biomass time-series of 31 nanoplankton and microplankton species and genera from day-level data, accounting for the average phenology and wind. We found wind effects on day-level biomass in 16 taxa. We subsequently used state-space models to connect the annual biomass changes with potential environmental drivers (temperature, salinity, stratification, ice cover and inorganic nutrients), simultaneously accounting for temporal trends. We found clear environmental effects influencing the annual biomasses of Dinobryon faculiferum, Eutreptiella spp., Protoperidinium bipes, Pseudopedinella spp., Snowella spp. and Thalassiosira baltica and indicative effects in 10 additional taxa. These effects mostly concerned temperature, salinity or stratification. Together, these 16 taxa represent two-thirds of the summer biomass in the sampled community. The inter-annual variability observed in salinity and temperature is relatively low compared to scenarios of predicted change in these variables. Therefore, the potential impacts of the presented effects on plankton biomasses are considerable.

中文翻译：

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驱动年度浮游生物生物量物种和属水平变化的环境变量

摘要 已知受全球变化影响的非生物变量会影响浮游生物生物量，这些影响可能是物种特异性的。在这里，我们使用来自波罗的海北部芬兰湾 1993 年至 2016 年的浮游生物数据调查年度生物量的环境驱动因素。我们从日级数据估计了 31 种纳米浮游生物和微型浮游生物物种和属的年度生物量时间序列，考虑了平均物候和风。我们在 16 个分类群中发现了风对日水平生物量的影响。我们随后使用状态空间模型将年度生物量变化与潜在的环境驱动因素（温度、盐度、分层、冰盖和无机营养物）联系起来，同时考虑了时间趋势。我们发现明显的环境影响影响 Dinobryon faculiferum 的年生物量，Eutreptiella spp., Protoperidinium bipes, Pseudomedinella spp., Snowella spp. 和 Thalassiosira baltica 以及其他 10 个分类群的指示性影响。这些影响主要与温度、盐度或分层有关。这 16 个分类群共同代表了采样群落中夏季生物量的三分之二。与这些变量的预测变化情景相比，在盐度和温度方面观察到的年际变化相对较低。因此，所呈现的影响对浮游生物生物量的潜在影响是相当大的。这 16 个分类群代表了采样群落夏季生物量的三分之二。与这些变量的预测变化情景相比，在盐度和温度方面观察到的年际变化相对较低。因此，所呈现的影响对浮游生物生物量的潜在影响是相当大的。这 16 个分类群代表了采样群落夏季生物量的三分之二。与这些变量的预测变化情景相比，在盐度和温度方面观察到的年际变化相对较低。因此，所呈现的影响对浮游生物生物量的潜在影响是相当大的。