BioDeepTime : a database of biodiversity time series for modern and fossil assemblages

We thank the Paleosynthesis Project and the Volkswagen Stiftung for funding that supported this project (Az 96 796). M.C.R. acknowledges the German Research Foundation (DFG) for funding through the Cluster of Excellence ‘The Ocean Floor – Earth's Uncharted Interface’ (EXC 2077, grant no. 390741603). E.E.S. acknowledges funding from Leverhulme Trust grant RPG-201170, the Leverhulme Prize and the National Science Research Council grant NE/V011405/1. Q.J.L. and L.N. acknowledge support from the Youth Innovation Promotion Association (2019310) and the Chinese Academy of Sciences (CAS-WX2021SF-0205). A.M.P. acknowledges funding from the Leverhulme Trust through research grant RPG-2019-402. M.D. acknowledges funding from Leverhulme Trust through the Leverhulme Centre for Anthropocene Biodiversity (RC-2018-021) and a research grant (RPG-2019-402), and the European Union (ERC coralINT, 101044975). L. H. L. acknowledges funding from the European Research Council (macroevolution.abc ERC grant no. 724324). K.H.P acknowledges funding from the National Science Foundation Graduate Research Fellowship Program (DGE-2139841). H.H.M.H. acknowledges support from Peter Buck Postdoc Fellowship, Smithsonian Institution. A.T. acknowledges funding from the Slovak Research and Development Agency (APVV 22-0523) and the Slovak Scientific Grant Agency (VEGA 02/0106/23).Motivation We have little understanding of how communities respond to varying magnitudes and rates of environmental perturbations across temporal scales. BioDeepTime harmonizes assemblage time series of presence and abundance data to help facilitate investigations of community dynamics across timescales and the response of communities to natural and anthropogenic stressors. BioDeepTime includes time series of terrestrial and aquatic assemblages of varying spatial and temporal grain and extent from the present-day to millions of years ago. Main Types of Variables Included BioDeepTime currently contains 7,437,847 taxon records from 10,062 assemblage time series, each with a minimum of 10 time steps. Age constraints, sampling method, environment and taxonomic scope are provided for each time series. Spatial Location and Grain The database includes 8752 unique sampling locations from freshwater, marine and terrestrial ecosystems. Spatial grain represented by individual samples varies from quadrats on the order of several cm2 to grid cells of ~100 km2. Time Period and Grain BioDeepTime in aggregate currently spans the last 451?million years, with the 10,062 modern and fossil assemblage time series ranging in extent from years to millions of years. The median extent of modern time series is 18.7?years and for fossil series is 54,872?years. Temporal grain, the time encompassed by individual samples, ranges from days to tens of thousands of years. Major Taxa and Level of Measurement The database contains information on 28,777 unique taxa with 4,769,789 records at the species level and another 271,218 records known to the genus level, including time series of benthic and planktonic foraminifera, coccolithophores, diatoms, ostracods, plants (pollen), radiolarians and other invertebrates and vertebrates. There are to date 7012 modern and 3050 fossil time series in BioDeepTime. Software Format SQLite, Comma-separated values.Publisher PDFPeer reviewe

BioDeepTime:a database of biodiversity time series for modern and fossil assemblages

Motivation We have little understanding of how communities respond to varying magnitudes and rates of environmental perturbations across temporal scales. BioDeepTime harmonizes assemblage time series of presence and abundance data to help facilitate investigations of community dynamics across timescales and the response of communities to natural and anthropogenic stressors. BioDeepTime includes time series of terrestrial and aquatic assemblages of varying spatial and temporal grain and extent from the present-day to millions of years ago. Main Types of Variables Included BioDeepTime currently contains 7,437,847 taxon records from 10,062 assemblage time series, each with a minimum of 10 time steps. Age constraints, sampling method, environment and taxonomic scope are provided for each time series. Spatial Location and Grain The database includes 8752 unique sampling locations from freshwater, marine and terrestrial ecosystems. Spatial grain represented by individual samples varies from quadrats on the order of several cm2 to grid cells of ~100 km2. Time Period and Grain BioDeepTime in aggregate currently spans the last 451 million years, with the 10,062 modern and fossil assemblage time series ranging in extent from years to millions of years. The median extent of modern time series is 18.7 years and for fossil series is 54,872 years. Temporal grain, the time encompassed by individual samples, ranges from days to tens of thousands of years. Major Taxa and Level of Measurement The database contains information on 28,777 unique taxa with 4,769,789 records at the species level and another 271,218 records known to the genus level, including time series of benthic and planktonic foraminifera, coccolithophores, diatoms, ostracods, plants (pollen), radiolarians and other invertebrates and vertebrates. There are to date 7012 modern and 3050 fossil time series in BioDeepTime. Software Format SQLite, Comma-separated values

Efficient Non-Interactive Zero Knowledge Arguments for Set Operations ⋆

Abstract. We propose a non-interactive zero knowledge pairwise multiset sum equality test (PMSET) argument in the common reference string (CRS) model that allows a prover to show that the given committed multisets Aj for j ∈ {1, 2, 3, 4} satisfy A1 ⊎ A2 = A3 ⊎ A4, i.e., every element is contained in A1 and A2 exactly as many times as in A3 and A4. As a corollary to the PMSET argument, we present arguments that enable to efficiently verify the correctness of various (multi)set operations, for example, that one committed set is the intersection or union of two other committed sets. The new arguments have constant communication and verification complexity (in group elements and group operations, respectively), whereas the CRS length and the prover’s computational complexity are both proportional to the cardinality of the (multi)sets. We show that one can shorten the CRS length at the cost of a small increase of the communication and the verifier’s computation

Code and data used for the study: 'BioDeepTime: a database of biodiversity time series for modern and fossil assemblages'

The repository includes code and data to reproduce the results in the manuscript ‘BioDeepTime: a database of biodiversity time series for modern and fossil assemblages' by Smith et al. (analysis_biodeeptime.zip)

BioDeepTime: database and compilation code

The archive includes copies, compilation code, documentation and temporary data files for the BioDeepTime database. Deposited files: Relational database in SQLite format: biodeeptime_sqlite.zip. Denormalized database in zipped .csv format: biodeeptime_csv.zip Denormalized database in zipped .parquet (v1.0) format: biodeeptime_parquet.zip. Denormalized database in .rds (R version 4.0) format: biodeeptime.rds. Description of tables and columns: biodeeptime.md. Database schema: schema.pdf. Synonymy of sources: Synonymy of sources.xlsx. Change log and known issues: NEWS.md Compilation files: bdt_compilation.zip References in .csv format: references.csv Bchron ages calculated for Neotoma: neotoma_bchron.rds This repository accompanies the study BioDeepTime: a database of biodiversity time series for modern and fossil assemblages by Smith et al. (pending publication) and will be updated after a successful peer-review