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Rediscovering biodiversity: using big-data to trace taxonomic knowledge through time

Rediscovering biodiversity: using big-data to trace taxonomic knowledge through time

Objective

Few macroecologists would dispute the importance of taxonomy for their work. Yet most treat taxonomic classification as a static, although it is intrinsically dynamic and subject to periodic change. This inconsistency arises from the divergent objectives of both disciplines and hampers progress towards more robust estimates of species richness across biomes. TAXON-TIME aims to bridge the gap between taxonomy and macroecology. The project will scrutinize 250 years of botanical explorations in African and Amazonian rainforests and analyze the impacts of taxonomic reclassifications on the macroecological patterns of tree species abundance and richness. To this end, TAXON-TIME will apply cutting-edge methods of data-intensive research and integrate massive volumes of digital data of historical taxonomic discoveries and reclassifications that became available only recently. A probabilistic approach to data analysis will ensure the resulting biodiversity patterns account for the likelihood of taxonomic reclassifications across space and time. TAXON-TIME results can lead to a paradigm shift in macroecological research towards the adoption of a probabilistic, rather than deterministic, view of taxonomic reclassifications. The project is led by an Experienced Researcher (ER) with outstanding analytical and technical skills and relevant research experience on three continents. TAXON-TIME brings together an interdisciplinary team of leading scientists with complementary research skills in tropical ecology, macroecology and data-intensive research. Upon completion, TAXON-TIME will contribute to a paradigm shift in macroecology and provided the ER with an analytical toolbox tailored for the next generation of macroecologists, establishing the ER as a central actor in a unique cross-disciplinary research field, which has just began to emerge.
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Coordinator

AGENCIA ESTATAL CONSEJO SUPERIOR DEINVESTIGACIONES CIENTIFICAS

Address

Calle Serrano 117
28006 Madrid

Spain

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 172 932,48

Project information

Grant agreement ID: 843234

Status

Grant agreement signed

  • Start date

    1 October 2019

  • End date

    30 September 2021

Funded under:

H2020-EU.1.3.2.

  • Overall budget:

    € 172 932,48

  • EU contribution

    € 172 932,48

Coordinated by:

AGENCIA ESTATAL CONSEJO SUPERIOR DEINVESTIGACIONES CIENTIFICAS

Spain