Dataset Information

Environmental variables driving species and genus level changes in annual plankton biomass.

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.

SUBMITTER: Forsblom L

PROVIDER: S-EPMC6946087 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Environmental variables driving species and genus level changes in annual plankton biomass.

Forsblom Louise L Engström-Öst Jonna J Lehtinen Sirpa S Lips Inga I Lindén Andreas A

Journal of plankton research 20191101 6

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 ...[more]

PMID: 31920210

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Project description:The desert ecosystem is an important part of the terrestrial ecosystem. Accurate estimations of the biomass and species richness of desert plants are of great value for maintaining ecosystem stability; however, current assessments remain a challenge due to the large spatial heterogeneity in biomass and species richness and difficulties posed by time-consuming field surveys, particularly in remote areas. In the present study, There were 527 sampling sites, and each sampling site contained approximately 9 quadrats. Approximately 4500 quadrats in total were taken from the Junggar Desert of northern Xinjiang, and the spatial distribution and factors driving the biomass and species richness of the desert ecosystem were quantitatively analyzed. The results showed that the average aboveground biomass, belowground biomass, litter, and the Patrick index of the Junggar Desert in northern Xinjiang were 115.42 gm-2, 924.77 gm-2, 13.06 gm-2, and 63, with values ranging from 2-708.12 gm-2, 120.25-3537.3 gm-2, 2-56.46 gm-2, and 0-377, respectively, The mean of the variation coefficient was 56.19%, 41.16%, 62.16% and 73.83%, suggesting moderate variation. The result is affected by the differences between the desert environment and climate. Climate factors had a relatively large impact on species richness, and the variation coefficient of species richness was large, indicating a large degree of dispersion of species richness. The direct influence of environmental and climatic factors on underground biomass (BGB) is relatively small, and its coefficient of variation is small. The spatial distribution of biomass and species richness in northern Xinjiang gradually decreased from west to east. Redundancy analysis showed that climate was the main factor driving desert biomass and species richness in northern Xinjiang, with an average independent explanatory power of 20.38% and 18.57%, respectively. Structural equation modeling indicated that climate factors, elevation, and community coverage had a direct positive effect on the aboveground biomass of the desert plants in northern Xinjiang and a direct negative effect on the belowground biomass. Moreover, climate factors and biological factors showed a direct positive effect on the species richness in northern Xinjiang.

Dataset Information

Environmental variables driving species and genus level changes in annual plankton biomass.

Publications

Environmental variables driving species and genus level changes in annual plankton biomass.

Similar Datasets

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