Time series of freshwater macroinvertebrate abundances and site characteristics of European streams and rivers.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
07 Jun 2024
07 Jun 2024
Historique:
received:
13
12
2023
accepted:
29
05
2024
medline:
8
6
2024
pubmed:
8
6
2024
entrez:
7
6
2024
Statut:
epublish
Résumé
Freshwater macroinvertebrates are a diverse group and play key ecological roles, including accelerating nutrient cycling, filtering water, controlling primary producers, and providing food for predators. Their differences in tolerances and short generation times manifest in rapid community responses to change. Macroinvertebrate community composition is an indicator of water quality. In Europe, efforts to improve water quality following environmental legislation, primarily starting in the 1980s, may have driven a recovery of macroinvertebrate communities. Towards understanding temporal and spatial variation of these organisms, we compiled the TREAM dataset (Time seRies of European freshwAter Macroinvertebrates), consisting of macroinvertebrate community time series from 1,816 river and stream sites (mean length of 19.2 years and 14.9 sampling years) of 22 European countries sampled between 1968 and 2020. In total, the data include >93 million sampled individuals of 2,648 taxa from 959 genera and 212 families. These data can be used to test questions ranging from identifying drivers of the population dynamics of specific taxa to assessing the success of legislative and management restoration efforts.
Identifiants
pubmed: 38849407
doi: 10.1038/s41597-024-03445-3
pii: 10.1038/s41597-024-03445-3
doi:
Types de publication
Journal Article
Dataset
Langues
eng
Sous-ensembles de citation
IM
Pagination
601Informations de copyright
© 2024. The Author(s).
Références
Haase, P. et al. The recovery of European freshwater biodiversity has come to a halt. Nature 620, 582–588 (2023).
doi: 10.1038/s41586-023-06400-1
pubmed: 37558875
pmcid: 10432276
Vörösmarty, C. J. et al. Global threats to human water security and river biodiversity. Nature 467, 555–561 (2010).
doi: 10.1038/nature09440
pubmed: 20882010
Steffen, W. et al. Planetary boundaries: guiding human development on a changing planet. Science 347, 1259855 (2015).
doi: 10.1126/science.1259855
pubmed: 25592418
United States. Federal Water Pollution Control Act Amendments. Public Law 92–500 (1972).
European Union. Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for community action in the field of water policy. Community, European vol. Directive 2000/60/EC 1–72 (2000).
European Environment Agency. Air quality in Europe — 2018 report., (2018).
Birk, S. et al. Impacts of multiple stressors on freshwater biota across spatial scales and ecosystems. Nat Ecol Evol 4, 1060–1068 (2020).
doi: 10.1038/s41559-020-1216-4
pubmed: 32541802
Whelan, M. J. et al. Is water quality in British rivers “better than at any time since the end of the Industrial Revolution”? Sci Total Environ 843, 157014 (2022).
doi: 10.1016/j.scitotenv.2022.157014
pubmed: 35772542
Vaughan, I. P. & Gotelli, N. J. Water quality improvements offset the climatic debt for stream macroinvertebrates over twenty years. Nat Commun 10, 1956 (2019).
doi: 10.1038/s41467-019-09736-3
pubmed: 31028258
pmcid: 6486586
van Klink, R. et al. Meta-analysis reveals declines in terrestrial but increases in freshwater insect abundances. Science 368, 417–420 (2020).
doi: 10.1126/science.aax9931
pubmed: 32327596
Bowler, D. E. et al. Winners and losers over 35 years of dragonfly and damselfly distributional change in Germany. Divers and Distrib 27, 1353–1366 (2021).
doi: 10.1111/ddi.13274
Dornelas, M. et al. BioTIME: A database of biodiversity time series for the Anthropocene. Glob Ecol Biogeogr 27, 760–786 (2018).
doi: 10.1111/geb.12729
pubmed: 30147447
pmcid: 6099392
Zoological Society of London and the World Wildlife Fund. Living Planet Index database. 2022 (2022).
Jeliazkov, A. et al. A global database for metacommunity ecology, integrating species, traits, environment and space. Sci Data 7, 6 (2020).
doi: 10.1038/s41597-019-0344-7
pubmed: 31913312
pmcid: 6949231
Statzner, B., Bonada, N. & Dolédec, S. Conservation of taxonomic and biological trait diversity of European stream macroinvertebrate communities: a case for a collective public database. Biodivers Conserv 16, 3609–3632 (2007).
doi: 10.1007/s10531-007-9150-1
Leigh, C. et al. IRBAS: An online database to collate, analyze, and synthesize data on the biodiversity and ecology of intermittent rivers worldwide. Ecol Evol 7, 815–823 (2017).
doi: 10.1002/ece3.2679
pubmed: 28168018
pmcid: 5288254
Comte, L. et al. RivFishTIME: A global database of fish time-series to study global change ecology in riverine systems. Glob Ecol Biogeogr 30, 38–50 (2021).
doi: 10.1111/geb.13210
Grigoropoulou, A. et al. The global EPTO database: Worldwide occurrences of aquatic insects. Glob Ecol Biogeogr 32, 642–655 (2023).
doi: 10.1111/geb.13648
van Klink, R. et al. InsectChange: a global database of temporal changes in insect and arachnid assemblages. Ecology 102, e03354 (2021).
doi: 10.1002/ecy.3354
pubmed: 33797755
Rumschlag, S. L. et al. Density declines, richness increases, and composition shifts in stream macroinvertebrates. Sci Adv 9, eadf4896 (2023).
doi: 10.1126/sciadv.adf4896
pubmed: 37134169
pmcid: 10156106
Sinclair, J. S. et al. Multi-decadal improvements in the ecological quality of European rivers are not consistently reflected in biodiversity metrics. Nat Ecol Evol 8, 430–441 (2024).
doi: 10.1038/s41559-023-02305-4
pubmed: 38278985
Sexton, A. N. et al. Inland navigation and land use interact to impact European freshwater biodiversity. Nat Ecol Evol 1–11, https://doi.org/10.1038/s41559-024-02414-8 (2024).
Welti, E. & Haase, P. TREAM: Time series of freshwater macroinvertebrate abundances and site characteristics of European streams and rivers. Knowledge Network for Biocomplexity https://doi.org/10.5063/F1NG4P4R (2023).
Schmidt-Kloiber, A. & Hering, D. – An online tool that unifies, standardises and codifies more than 20,000 European freshwater organisms and their ecological preferences. Ecol Indic 53, 271–282, www.freshwaterecology.info (2015).
doi: 10.1016/j.ecolind.2015.02.007
Amatulli, G. et al. Hydrography90m: a new high-resolution global hydrographic dataset. Earth Syst Sci Data 14, 4525–4550 (2022).
doi: 10.5194/essd-14-4525-2022
Neteler, M. & Mitasova, H. Open Source GIS: A GRASS GIS Approach. (Springer, New York, NY, 2007).
Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci Data 5, 170191 (2018).
doi: 10.1038/sdata.2017.191
pubmed: 29313841
pmcid: 5759372
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. (2023).
Bürkner, P.-C. Bayesian item response modeling in R with brms and Stan. J. Stat. Soft. 100 (2021).
European Space Agency. Land Cover CCI Product User Guide Version 2. Tech. Rep. (2017).
Lehner, B. et al. Global reservoir and dam database, Version 1 (GRanDv1). Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC) https://doi.org/10.7927/H4N877QK (2011).
Schürz, M. et al. hydrographr: An R package for scalable hydrographic data processing. Methods in Ecology and Evolution 14, 2953–2963 (2023).
doi: 10.1111/2041-210X.14226