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Abstract Temperature and biodiversity changes occur in concert, but their joint effects on ecological stability of natural food webs are unknown. Here, we assess these relationships in 19 planktonic food webs. We estimate stability as structural stability (using the volume contraction rate) and temporal stability (using the temporal variation of species abundances). Warmer temperatures were associated with lower structural and temporal stability, while biodiversity had no consistent effects on either stability property. While species richness was associated with lower structural stability and higher temporal stability, Simpson diversity was associated with higher temporal stability. The responses of structural stability were linked to disproportionate contributions from two trophic groups (predators and consumers), while the responses of temporal stability were linked both to synchrony of all species within the food web and distinctive contributions from three trophic groups (predators, consumers, and producers). Our results suggest that, in natural ecosystems, warmer temperatures can erode ecosystem stability, while biodiversity changes may not have consistent effects. 

Abstract Untangling causal links and feedbacks among biodiversity, ecosystem functioning, and environmental factors is challenging due to their complex and context-dependent interactions (e.g., a nutrient-dependent relationship between diversity and biomass). Consequently, studies that only consider separable, unidirectional effects can produce divergent conclusions and equivocal ecological implications. To address this complexity, we use empirical dynamic modeling to assemble causal networks for 19 natural aquatic ecosystems (N24 ◦ ~N58 ◦ ) and quantified strengths of feedbacks among phytoplankton diversity, phytoplankton biomass, and environmental factors. Through a cross-system comparison, we identify macroecological patterns; in more diverse, oligotrophic ecosystems, biodiversity effects are more important than environmental effects (nutrients and temperature) as drivers of biomass. Furthermore, feedback strengths vary with productivity. In warm, productive systems, strong nitrate-mediated feedbacks usually prevail, whereas there are strong, phosphate-mediated feedbacks in cold, less productive systems. Our findings, based on recovered feedbacks, highlight the importance of a network view in future ecosystem management. 

Abstract. Plankton form the base of the marine food web and are sensitive indicatorsof environmental change. Plankton time series are therefore an essentialpart of monitoring progress towards global biodiversity goals, such as theConvention on Biological Diversity Aichi Targets, and for informingecosystem-based policy, such as the EU Marine Strategy Framework Directive.Multiple plankton monitoring programmes exist in Europe, but differences insampling and analysis methods prevent the integration of their data,constraining their utility over large spatio-temporal scales. The PlanktonLifeform Extraction Tool brings together disparate European planktondatasets into a central database from which it extracts abundancetime series of plankton functional groups, called “lifeforms”, according toshared biological traits. This tool has been designed to make complexplankton datasets accessible and meaningful for policy, public interest, andscientific discovery. It allows examination of large-scale shifts inlifeform abundance or distribution (for example, holoplankton beingpartially replaced by meroplankton), providing clues to how the marineenvironment is changing. The lifeform method enables datasets with differentplankton sampling and taxonomic analysis methodologies to be used togetherto provide insights into the response to multiple stressors and robustpolicy evidence for decision making. Lifeform time series generated with thePlankton Lifeform Extraction Tool currently inform plankton and food webindicators for the UK's Marine Strategy, the EU's Marine Strategy FrameworkDirective, and for the Convention for the Protection of the MarineEnvironment of the North-East Atlantic (OSPAR) biodiversity assessments.The Plankton Lifeform Extraction Tool currently integrates 155 000 samples,containing over 44 million plankton records, from nine different planktondatasets within UK and European seas, collected between 1924 and 2017.Additional datasets can be added, and time series can be updated. The PlanktonLifeform Extraction Tool is hosted by The Archive for Marine Species andHabitats Data (DASSH) at https://www.dassh.ac.uk/lifeforms/ (last access: 22 November 2021, Ostle et al., 2021). The lifeform outputs are linked to specific, DOI-ed, versions of thePlankton Lifeform Traits Master List and each underlying dataset. 

ABSTRACT MotivationHere, 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 IncludedThe 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 GrainSampling 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 GrainThe 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 MeasurementThe database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Formatcsv and. SQL.