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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Code and data: Understanding temporal variability across trophic levels and spatial scales in freshwater ecosystems

Authors: Siqueira, Tadeu; Hawkins, Charles P.; Olden, Julian; Tonkin, Jonathan; Comte, Lise; Saito, Victor S.; Anderson, Thomas L.; +24 Authors

Code and data: Understanding temporal variability across trophic levels and spatial scales in freshwater ecosystems

Abstract

Acknowledgments. T.S. was supported by grants #19/04033-7 and #21/00619-7, São Paulo Research Foundation (FAPESP), and by grant #309496/2021-7, Brazilian National Council for Scientific and Technological Development (CNPq). Participation by CPH was supported, in part, by US National Science Foundation grant IOS-1754838. CPH thanks the PacFish/InFish Biological Opinion Monitoring Program (administered by the US Forest Service) for use of their long-term macroinvertebrate monitoring data. JDT is supported by a Rutherford Discovery Fellowship administered by the Royal Society Te Apārangi (RDF-18-UOC-007), and Bioprotection Aotearoa and Te Pūnaha Matatini, both Centres of Research Excellence funded by the Tertiary Education Commission, New Zealand. VS was supported by a FAPESP grant #2019/06291-3 during the writing of this manuscript. The FEHM (Freshwater Ecology, Hydrology and Management) research group is funded by the "Agència de Gestió d'Ajuts Universitaris i de Recerca" (AGAUR) at the "Generalitat de Catalunya" (2017SGR1643). CCB thanks PELD-PIAP/CNPq for support. M.C. was supported by a Ramón y Cajal Fellowship (RYC2020-029829-I) and the Serra Hunter programme (Generalitat de Catalunya). GAG was supported by #DEB-2025982, NTL LTER. PH received financial support from the eLTER PLUS project (Grant Agreement #871128). JMH was supported by the Federal Aid in Sport Fish Restoration Program (F-69-P, Fish Management in Ohio), administered jointly by the United States Fish and Wildlife Service and the Division of Wildlife, Ohio Department of Natural Resources (projects FADR65, FADX09, and FADB02). KLH and RP thank the Oulanka Research Station. MBF thanks over 300 students, staff, and faculty that have participated in the Kentucky Lake Long-Term Monitoring Program at Hancock Biological Station, Murray State University, Murray, KY. MJJ thanks the Northumberland Wildlife Trust for site access. IISD-ELA zooplankton samples were counted and identified primarily by Willy Findlay and Alex Salki. Field collections within IISD-ELA were overseen by Mark Lyng and Ken Sandilands. Funding for most of the IISD-ELA data was provided by Fisheries and Oceans Canada. PP and MS were supported by the Czech Science Foundation (P505-20-17305S). LCR is grateful to the Núcleo de Pesquisas em Limnologia, Ictiologia e Aquicultura (Nupélia) at Universidade Estadual de Maringá for logistic support; CNPq/ PELD for financial support and CNPq for a scholarship. AR was supported by NSF CAREER #2047324 and by UC Berkeley new faculty funds. We thank countless colleagues at all partner institutes for their help with collecting the time series data.

Code and data to reproduce the results in Siqueira et al. (submitted) published as a Preprint (https://doi.org/10.32942/osf.io/mpf5x) The full set of results, including those made available as supplementary material, can be reproduced by running five scripts in the R_codes folder following this sequence: 01_Dataprep_stability_metrics.R 02_SEM_analyses.R 03_Stab_figs.R 04_Stab_supp_m.R 05_Sensit_analysis.R and using the data available in the Input_data folder. The original raw data made available include the abundance (individual counts, biomass, coverage area) of a given taxon, at a given site, in a given year. See details here https://doi.org/10.32942/osf.io/mpf5x However, this is a collaborative effort and not all authors are allowed to share their raw data. One data set (LEPAS), out of 30, was not made available due to data sharing policies of The Ohio Division of Wildlife (ODOW). So, in code "01_Dataprep_stability_metrics.R" all data made available are imported, except the LEPAS data set. For this specific data set, code "01_Dataprep_stability_metrics.R" imports variability and synchrony components estimated using the methods described in Wang et al. (2019 Ecography; doi/10.1111/ecog.04290), diversity metrics (alpha and gamma diversity), and some variables describing the data set. A protocol for requesting access to the LEPAS data sets can be found here: https://ael.osu.edu/researchprojects/lake-erie-plankton-abundance-study-lepas Dataset owner: Ohio Department of Natural Resources – Division of Wildlife, managed by Jim Hood, Dept. of Evolution, Ecology, and Organismal Biology, The Ohio State University. Email: hood.211@osu.edu Anyone who wants to reproduce the results described in the preprint can just download the whole R project (that includes code and data) and run codes from 01 to 05. I am making the whole R project folder (with everything needed to reproduce the results) available as a compressed file.

Keywords

compensatory dynamics; International long term ecological research (ILTER); metacommunities; mobile consumers; Moran effect; portfolio effect; spatial synchrony; temporal variability

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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