Climate change effects on phytoplankton depend on cell size and food web structure

We investigated the effects of warming on a natural phytoplankton community from the Baltic Sea, based on six mesocosm experiments conducted 2005–2009. We focused on differences in the dynamics of three phytoplankton size groups which are grazed to a variable extent by different zooplankton groups. While small-sized algae were mostly grazer-controlled, light and nutrient availability largely determined the growth of medium- and large-sized algae. Thus, the latter groups dominated at increased light levels. Warming increased mesozooplankton grazing on medium-sized algae, reducing their biomass. The biomass of small-sized algae was not affected by temperature, probably due to an interplay between indirect effects spreading through the food web. Thus, under the higher temperature and lower light levels anticipated for the next decades in the southern Baltic Sea, a higher share of smaller phytoplankton is expected. We conclude that considering the size structure of the phytoplankton community strongly improves the reliability of projections of climate change effects

BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series

Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL

Phenological Changes of Blooming Diatoms Promoted by Compound Bottom-Up and Top-Down Controls

Understanding phytoplankton species-specific responses to multiple biotic and abiotic stressors is fundamental to assess phenological and structural shifts at the community level. Here, we present the case of Thalassiosira curviseriata, a winter-blooming diatom in the Bahía Blanca Estuary, Argentina, which displayed a noticeable decrease in the past decade along with conspicuous changes in phenology. We compiled interannual field data to assess compound effects of environmental variations and grazing by the invasive copepod Eurytemora americana. The two species displayed opposite trends over the period examined. The diatom decreased toward the last years, mainly during the winters, and remained relatively constant over the other seasons, while the copepod increased toward the last years, with an occurrence restricted to winter and early spring. A quantitative assessment by structural equation modeling unveiled that the observed long-term trend of T. curviseriata resulted from the synergistic effects of environmental changes driven by water temperature, salinity, and grazing. These results suggest that the shift in the abundance distribution of T. curviseriata toward higher annual ranges of temperature and salinity—as displayed by habitat association curves—constitutes a functional response to avoid seasonal overlapping with its predator in late winters. The observed changes in the timing and abundance of the blooming species resulted in conspicuous shifts in primary production pulses. Our results provide insights on mechanistic processes shaping the phenology and structure of phytoplankton blooms

Mesozooplankton structure and seasonal dynamics in three coastal systems of Argentina: Bahía Blanca Estuary, Nuevo Gulf and Ushuaia Bay

Mesozooplankton communities in coastal ecosystems have successfully adapted to a wide range of environments. However, the current rate of coastal modification is challenging the survival of resident species. In this chapter, we describe the structure and annual dynamics of the mesozooplankton community in recent years for three coastal systems in Argentina that are subject to human disturbance: (1) Bahía Blanca Estuary, (2) Pirámide Bay in Nuevo Gulf and (3) Ushuaia Bay in the Beagle Channel. The seasonal dynamics of mesozooplankton abundance in Bahía Blanca Estuary during 2009-2010 exhibited a unimodal pattern with an increase during the warm seasons, while organism abundance increased linearly with both salinity and turbidity. In Nuevo Gulf, research on the seasonal dynamics of mesozooplankton conducted during 2014-2015 exhibited a bimodal abundance pattern with peaks in late summer and spring. No significant relationships between mesozooplankton and the environmental variables included in Nuevo Gulf were found. The seasonal dynamics of mesozooplankton in Ushuaia Bay in the years 2006-2008 exhibited a bimodal abundance pattern with peaks in summer and early autumn; this pattern was mainly driven by the concentration of chlorophyll a. In Bahía Blanca Estuary, a gradual decrease in species richness was observed throughout the last four decades, while changes in species composition were also observed, suggesting that some species have the ability to acclimate to higher salinity and turbidity as well as to pollution. In Nuevo Gulf, the mesozooplankton community showed no significant modifications over time, which may be related to the low anthropogenic pressure. Although no profound shifts in mesozooplankton were observed in Ushuaia Bay, eutrophication may have an impact in the future through its effect on primary producers.Fil: Berasategui, Anabela Anhi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: López Abbate, María Celeste. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: D'agostino, Valeria Carina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; ArgentinaFil: Presta, María Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Biodiversidad y Biología Experimental y Aplicada. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Biodiversidad y Biología Experimental y Aplicada; ArgentinaFil: Uibrig, Román Armando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: García, Tami Mailén. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: Nahuelhual, Eugenia Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: Chazarreta, Carlo Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: Dutto, María Sofía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: Garcia, Maximiliano Darío. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: Capitanio, Fabiana Lia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Biodiversidad y Biología Experimental y Aplicada. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Biodiversidad y Biología Experimental y Aplicada; ArgentinaFil: Hoffmeyer, Monica Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Tecnológica Nacional. Facultad Regional Bahía Blanca; Argentin