Cover Image

Saved in:
Bibliographic Details
Main Authors: Paquette, Cindy, Gagné, Stéphanie, Fugère, Vincent
Format: Recurso digital
Language:
Published: Zenodo 2025
Online Access:https://doi.org/10.5281/zenodo.17916222
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866901922049425408
author Paquette, Cindy
Gagné, Stéphanie
Fugère, Vincent
author_facet Paquette, Cindy
Gagné, Stéphanie
Fugère, Vincent
contents <p><strong><span lang="EN-CA">Data sets for the results shown in <em>Fish and zooplankton co-responses to environmental gradients under different climate change scenarios</em>.</span></strong></p> <p><strong><span lang="EN-CA">FishPA_156lakes.xlsx</span></strong><span lang="EN-CA"><br>This file contains presence–absence data for 67 fish species across 156 lakes sampled through various monitoring programs of the Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs (MELCCFP). The dataset includes species occurrences from standardized monitoring surveys (described in <em>Service de la faune aquatique</em> 2011), bycatch from these surveys, observations from non-standardized surveys, and sport fishing records. Because the sampling protocols were not designed to verify true absences, zeros in the dataset should be interpreted with caution. MELCCFP kindly requests to be informed of any future uses of this dataset in order to better track and guide its use in research contexts <span lang="FR">(</span><span><a href="mailto:dpefa@environnement.gouv.qc.ca"><span lang="FR">dpefa@environnement.gouv.qc.ca</span></a></span><span lang="FR">)</span>.</span></p> <p><strong><span lang="EN-CA">FishTraits.xlsx</span></strong><span lang="EN-CA"><br>This file contains functional and physiological traits for the 67 fish species, including trophic level, classified into primary consumers, secondary consumers, and top predators (FishBase; </span><span lang="EN-CA">Froese</span> and Pauly 2025)<span lang="EN-CA">, maximum body length, oral gape position (MoBd ratio; categorized into bottom feeders, generalists, or surface feeders) from the FishMorph database (Su et al. 2021), and critical thermal maxima (CTmax) from Comte and Olden (2017). Missing CTmax values were imputed using family means.</span></p> <p><strong><span lang="EN-CA">ZooPA_156lakes.xlsx</span></strong><span lang="EN-CA"><br>This file contains presence–absence data for 53 zooplankton species across the same 156 lakes. Samples originate from the MELCCFP fish monitoring program (n = 120), the MELCCFP Biodiversity Monitoring Network (BdQc; n = 23), and the NSERC Canadian LakePulse Network (Huot et al. 2019; n = 13). Zooplankton were collected at each lake’s deepest point during the summer stratification period.</span></p> <p><strong><span lang="EN-CA">ZooTraits.xlsx</span></strong><span lang="EN-CA"><br>This file includes zooplankton functional traits, specifically mean body length, feeding type, habitat, and trophic group, following the trait classifications of Barnett et al. (2007) and Paquette et al. (2021).</span></p> <p><strong><span lang="EN-CA">Env_156Lakes.xlsx</span></strong><span lang="EN-CA"><br>This file contains environmental variables and metadata for the 156 lakes sampled by the MELCCFP monitoring programs. Morphometric characteristics and watershed population density were retrieved from the LakeAtlas database (v1.0; Lehner et al. 2022). Water quality variables (physical and chemical properties) were measured in situ or analyzed following MELCCFP protocols (<em>Service de la faune aquatique</em> 2011). Baseline climate variables were obtained from WorldClim version 2.1. </span></p> <p><strong><span lang="EN-CA">FutureClim_156lakes.xlsx</span></strong><span lang="EN-CA"><br>This file contains projected climate variables for the 2081–2100 period under three shared socio-economic pathways (SSP1-2.6, SSP3-7.0, and SSP5-8.5). Climate projections were extracted from WorldClim version 2.1 and averaged across six global climate models: MIROC6, MPI, IPSL, MRI, ACCESS, and UKESM.</span></p> <p> </p> <p><span lang="EN-CA">REFERENCES</span></p> <p><span lang="EN-CA">Barnett, A., K. Finlay, and B. Beisner. 2007. Functional diversity of crustacean zooplankton communities: Towards a trait-based classification. Freshw. Biol. <strong>52</strong>: 796–813. doi:10.1111/j.1365-2427.2007.01733.x</span></p> <p><span lang="EN-CA">Comte, L., and J. D. Olden. 2017. Climatic vulnerability of the world’s freshwater and marine fishes. Nat. Clim. Chang. <strong>7</strong>: 718–722. doi:https://doi.org/10.1038/nclimate3382</span></p> <p><span lang="EN-CA">Froese, R., and D. Pauly. 2025. FishBase. Available at: www.fishbase.org.</span></p> <p><span lang="EN-CA">Lehner, B., M. L. Messager, M. C. Korver, and S. Linke. 2022. Global hydro-environmental lake characteristics at high spatial resolution. Sci. Data <strong>9</strong>: 1–19. doi:10.1038/s41597-022-01425-z</span></p> <p><span lang="EN-CA">Paquette, C., I. Gregory-Eaves, B. E. Beisner, I. Gregory‐Eaves, and B. E. Beisner. 2021. Multi-scale biodiversity analyses identify the importance of continental watersheds in shaping lake zooplankton biogeography. J. Biogeogr. <strong>48</strong>: 2298–2311.</span></p> <p><span lang="EN-CA">Service de la faune aquatique. 2011. Guide de normalisation des méthodes d’inventaire ichtyologique en eaux intérieures, Tome I, Acquisition de données. Ministère des Ressources naturelles et de la Faune. 153p. Québec, Québec.</span></p> <p><span lang="EN-CA">Su, G., M. Logez, J. Xu, S. Tao, S. Villéger, and S. Brosse. 2021. Human impacts on global freshwater fish biodiversity. Science. <strong>371</strong>: 835–838.</span></p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_17916222
institution Zenodo
language
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Datasets for Fish and zooplankton co-responses to environmental gradients under different climate change scenarios
Paquette, Cindy
Gagné, Stéphanie
Fugère, Vincent
<p><strong><span lang="EN-CA">Data sets for the results shown in <em>Fish and zooplankton co-responses to environmental gradients under different climate change scenarios</em>.</span></strong></p> <p><strong><span lang="EN-CA">FishPA_156lakes.xlsx</span></strong><span lang="EN-CA"><br>This file contains presence–absence data for 67 fish species across 156 lakes sampled through various monitoring programs of the Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs (MELCCFP). The dataset includes species occurrences from standardized monitoring surveys (described in <em>Service de la faune aquatique</em> 2011), bycatch from these surveys, observations from non-standardized surveys, and sport fishing records. Because the sampling protocols were not designed to verify true absences, zeros in the dataset should be interpreted with caution. MELCCFP kindly requests to be informed of any future uses of this dataset in order to better track and guide its use in research contexts <span lang="FR">(</span><span><a href="mailto:dpefa@environnement.gouv.qc.ca"><span lang="FR">dpefa@environnement.gouv.qc.ca</span></a></span><span lang="FR">)</span>.</span></p> <p><strong><span lang="EN-CA">FishTraits.xlsx</span></strong><span lang="EN-CA"><br>This file contains functional and physiological traits for the 67 fish species, including trophic level, classified into primary consumers, secondary consumers, and top predators (FishBase; </span><span lang="EN-CA">Froese</span> and Pauly 2025)<span lang="EN-CA">, maximum body length, oral gape position (MoBd ratio; categorized into bottom feeders, generalists, or surface feeders) from the FishMorph database (Su et al. 2021), and critical thermal maxima (CTmax) from Comte and Olden (2017). Missing CTmax values were imputed using family means.</span></p> <p><strong><span lang="EN-CA">ZooPA_156lakes.xlsx</span></strong><span lang="EN-CA"><br>This file contains presence–absence data for 53 zooplankton species across the same 156 lakes. Samples originate from the MELCCFP fish monitoring program (n = 120), the MELCCFP Biodiversity Monitoring Network (BdQc; n = 23), and the NSERC Canadian LakePulse Network (Huot et al. 2019; n = 13). Zooplankton were collected at each lake’s deepest point during the summer stratification period.</span></p> <p><strong><span lang="EN-CA">ZooTraits.xlsx</span></strong><span lang="EN-CA"><br>This file includes zooplankton functional traits, specifically mean body length, feeding type, habitat, and trophic group, following the trait classifications of Barnett et al. (2007) and Paquette et al. (2021).</span></p> <p><strong><span lang="EN-CA">Env_156Lakes.xlsx</span></strong><span lang="EN-CA"><br>This file contains environmental variables and metadata for the 156 lakes sampled by the MELCCFP monitoring programs. Morphometric characteristics and watershed population density were retrieved from the LakeAtlas database (v1.0; Lehner et al. 2022). Water quality variables (physical and chemical properties) were measured in situ or analyzed following MELCCFP protocols (<em>Service de la faune aquatique</em> 2011). Baseline climate variables were obtained from WorldClim version 2.1. </span></p> <p><strong><span lang="EN-CA">FutureClim_156lakes.xlsx</span></strong><span lang="EN-CA"><br>This file contains projected climate variables for the 2081–2100 period under three shared socio-economic pathways (SSP1-2.6, SSP3-7.0, and SSP5-8.5). Climate projections were extracted from WorldClim version 2.1 and averaged across six global climate models: MIROC6, MPI, IPSL, MRI, ACCESS, and UKESM.</span></p> <p> </p> <p><span lang="EN-CA">REFERENCES</span></p> <p><span lang="EN-CA">Barnett, A., K. Finlay, and B. Beisner. 2007. Functional diversity of crustacean zooplankton communities: Towards a trait-based classification. Freshw. Biol. <strong>52</strong>: 796–813. doi:10.1111/j.1365-2427.2007.01733.x</span></p> <p><span lang="EN-CA">Comte, L., and J. D. Olden. 2017. Climatic vulnerability of the world’s freshwater and marine fishes. Nat. Clim. Chang. <strong>7</strong>: 718–722. doi:https://doi.org/10.1038/nclimate3382</span></p> <p><span lang="EN-CA">Froese, R., and D. Pauly. 2025. FishBase. Available at: www.fishbase.org.</span></p> <p><span lang="EN-CA">Lehner, B., M. L. Messager, M. C. Korver, and S. Linke. 2022. Global hydro-environmental lake characteristics at high spatial resolution. Sci. Data <strong>9</strong>: 1–19. doi:10.1038/s41597-022-01425-z</span></p> <p><span lang="EN-CA">Paquette, C., I. Gregory-Eaves, B. E. Beisner, I. Gregory‐Eaves, and B. E. Beisner. 2021. Multi-scale biodiversity analyses identify the importance of continental watersheds in shaping lake zooplankton biogeography. J. Biogeogr. <strong>48</strong>: 2298–2311.</span></p> <p><span lang="EN-CA">Service de la faune aquatique. 2011. Guide de normalisation des méthodes d’inventaire ichtyologique en eaux intérieures, Tome I, Acquisition de données. Ministère des Ressources naturelles et de la Faune. 153p. Québec, Québec.</span></p> <p><span lang="EN-CA">Su, G., M. Logez, J. Xu, S. Tao, S. Villéger, and S. Brosse. 2021. Human impacts on global freshwater fish biodiversity. Science. <strong>371</strong>: 835–838.</span></p>
title Datasets for Fish and zooplankton co-responses to environmental gradients under different climate change scenarios
url https://doi.org/10.5281/zenodo.17916222

Similar Items