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Valuing the information hidden in true long-term data for invasion science

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12520%2F23%3A43906384" target="_blank" >RIV/60076658:12520/23:43906384 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1007/s10530-023-03091-7" target="_blank" >https://doi.org/10.1007/s10530-023-03091-7</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s10530-023-03091-7" target="_blank" >10.1007/s10530-023-03091-7</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Valuing the information hidden in true long-term data for invasion science

  • Original language description

    Invasive species pose a significant threat to global biodiversity and human well-being. Despite the widespread use of long-term biomonitoring data in many natural science fields, the analysis of long-term time series with a focus on biological invasions is uncommon. To address this gap, we used twenty macroinvertebrate time series from the highly anthropogenically altered Rhine River, collected over 32 years from 1973 to 2005. We examined the adequacy of the data in capturing non-native species trends over time and explored trends in alpha, beta, and gamma diversity of non-native species with several climatic and site-specific predictors. Our findings revealed that the data adequately captured a saturating non-native species richness over time. Additionally, we observed an increase in both alpha and gamma diversity of both native and non-native species over time, with a recent dip in trends. Beta diversity trends were more complicated, but eventually increased, contrasting trends in native species beta diversity. Our applied models indicate that in this highly altered ecosystem, climatic shifts were insignificant, while time was the primarily driving factor. Proximity to anthropogenic structures and the distance to the outlet were the only site-specific predictors facilitating non-native species diversity. These findings highlight the value and importance of long-term time series for the study of invasive species, particularly long-term invasion dynamics and once again underline that naturality of ecosystems precede the effect of climate change.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10620 - Other biological topics

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Biological Invasions

  • ISSN

    1387-3547

  • e-ISSN

    1573-1464

  • Volume of the periodical

    25

  • Issue of the periodical within the volume

    8

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    10

  • Pages from-to

    2385-2394

  • UT code for WoS article

    000995729100001

  • EID of the result in the Scopus database

    2-s2.0-85160422749