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Enregistrement W4393877905 · doi:10.5281/zenodo.6591419

Code and data: Ecological stability propagates across spatial scales and trophic levels in freshwater ecosystems

2022· dataset· en· W4393877905 sur OpenAlexaff
Tadeu Siqueira, Charles P. Hawkins, Julian D. Olden, Jonathan D. Tonkin, Lise Comte, Victor S. Saito, Thomas L. Anderson, Gedimar Pereira Barbosa, Núria Bonada‬‬‬‬‬‬‬‬‬‬‬, Cláudia Cósta Bonecker, Miguel Cañedo‐Argüelles, Thibault Datry, Michael B. Flinn, Pau Fortuño, Gretchen A. Gerrish, Peter Haase, Matthew J. Hill, James M. Hood, Kaisa‐Leena Huttunen, Michael Jeffries, Timo Muotka, Daniel R. O’Donnell, Riku Paavola, Petr Pařil, Michael J. Paterson, Christopher J. Patrick, Gilmar Perbiche‐Neves, Luzia Cleide Rodrigues, Susanne C. Schneider, Michal Straka, Albert Ruhí

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2022
Typedataset
Langueen
DomaineEnvironmental Science
ThématiqueFish Ecology and Management Studies
Établissements canadiensInternational Institute for Sustainable Development
Organismes subventionnairesnon disponible
Mots-clésTrophic levelEcologyCode (set theory)Stability (learning theory)EcosystemEnvironmental scienceGeographyComputer scienceBiologyMachine learning

Résumé

récupéré en direct d'OpenAlex

The files listed below include data and code used to produce the results, including those made available as supplementary material, described in Siqueira et al. (https://ecoevorxiv.org/mpf5x), "Ecological stability propagates across spatial scales and trophic levels in freshwater ecosystems". The full set of results can be reproduced by running four R codes following this sequence: - 01_Siqueira_etal_dataprep_stability_metrics.R - 02_Siqueira_etal_SEM_analyses.R - 03_Siqueira_etal_stab_figs.R - 04_Siqueira_etal_stab_supp_m.R To run the first R code (“01_Siqueira_etal_dataprep_stability_metrics.R”), 3 .csv files are needed. "data_stab_analysis_except_lepas.csv" has 151404 rows and 17 columns. Rows represent the abundance (individual counts, biomass, coverage area) of a given taxon, at a given site, in a given year. Some abundance values were generated by interpolation (see details in the Methods section of the paper and supplementary material). The 17 columns include "Data_set_ID": a numerical vector describing 34 of the 35 independent metacommunity data sets. For the 35th data set, see below. "Metacom": a character vector describing 34 of the 35 independent metacommunity data sets. This column was kept for the sake of preserving the original identity of each data set. "Sample_id": a vector representing a unique combination of data set ID, site ID, and time step. "Site": a vector describing the ID of the site where the sample was taken. "Year": a vector describing the year when the sample was taken. "Frequency": a vector describing the frequency interval at which the samples were taken. This variable has only one state (“Inter_annual”) and was kept because some of the data originally gathered (before filtering) included also intra-annual sampling (these were discarded). "Time_step": a vector describing the time step a sample was taken, considering the whole number of years included in that data set. "Lat": a vector describing the latitude of the sampling site in decimal degrees. "Long": a vector describing the latitude of the sampling site in decimal degrees. "Datum": a vector describing the datum used by the person who collected the sample. "Coord_system": a vector describing the coordinate system used in this data set after data cleaning. "Bio_gr": a vector describing the major biological groups in the data set (e.g., macroinvertebrates, fish). "Ecosys": a vector describing the two ecosystem types in the data set (streams and lakes). "Species": a vector describing the species or genus names. "Abundance": a vector describing species or genus abundance, density, or coverage. "Trophic_gr": a vector describing 3 broad trophic groups (producers, consumers that are invertebrates, and consumers that are vertebrates). "New_tr_g": a vector describing 5 trophic levels used in the analysis (producers, primary consumers secondary consumers, tertiary consumers). The following files were made available separately due to the data sharing policies of The Ohio Division of Wildlife (ODOW). Thus, we made them available not in the format of raw numbers, but as pre-processed variables that we used in our models (e.g., stability and diversity metrics, trophic groups, etc.). "lepas_site_stab_metrics.csv" has 8 rows and 14 columns. Rows represent sites sampled for a given trophic level. Columns include "Lat", "Long", "Metacom", "Sample_id", "Site", "Bio_gr", "Ecosys", and "New_tr_g" as described above and: "Site_troph": a vector representing a combination of site ID and trophic level. This was used to identify sites that include more than one trophic level. "Simp": a vector describing the Simpson diversity index of a sampled site. "synchrony_comm_site": a vector describing species population synchrony within a sampled site. "mean_cv_species_site": a vector describing the average coefficient of variation of species sampled in a site. "cv_comm_site": a vector describing local temporal variability of aggregated community abundance. "S": a vector describing species richness in a sampled site. "lepas_meta_stab_metrics.csv" has 1 row and 21 columns. The row represents the LEPAS metacommunity. Columns include "Metacom", "Freq", "Time_step", "Bio_gr", "Trophic_gr", "New_tr_g", and "Ecosys" as described above and: "Meta_troph": a vector representing a combination of metacommunity ID and trophic level. This was used to differentiate metacommunities that include more than one trophic level. "Simp": a vector describing the Simpson diversity index averaged across sites within the metacommunity. "S": a vector describing the species richness averaged across sites within the metacommunity. "nSites": a vector describing the number of sampled sites in the metacommunity. "CV_S_L": a vector describing population temporal variability (sensu Wang et al. 2019) within metacommunity. "CV_C_L": a vector describing community temporal variability (sensu Wang et al. 2019) within metacommunity. "CV_S_R": a vector describing metapopulation temporal variability (sensu Wang et al. 2019) within metacommunity. "CV_C_R": a vector describing metacommunity temporal variability (sensu Wang et al. 2019). "phi_S_L2R": a vector describing species-level spatial synchrony (sensu Wang et al. 2019) within metacommunity. "phi_C_L2R": a vector describing community-level spatial synchrony (sensu Wang et al. 2019) within metacommunity. "phi_S2C_L": a vector describing local-scale species synchrony (sensu Wang et al. 2019) within metacommunity. "phi_S2C_R": a vector describing regional-scale species synchrony (sensu Wang et al. 2019) within metacommunity. "Simp_gamma": a vector describing Simpson gamma diversity in the metacommunity. "S_gamma": a vector describing regional richness in the metacommunity. To run the second R code (“02_Siqueira_etal_SEM_analyses.R”), two groups of files are needed – one group of files prepared with the first code and the following two .csv files: "site_env_preds.csv" has 735 rows and 3 columns. Rows represent climatic data extracted from each of the sites used in analyses. The 3 columns include: "Site_troph": a vector representing a combination of site ID and trophic level. This was used to identify sites that include more than one trophic level. "bio4": a numerical vector describing seasonality in temperature in each site. "bio15": a numerical vector describing seasonality in precipitation in each site. "meta_env_spa_preds.cs" has 59 rows and 4 columns. Rows represent each of the sites used in analyses. The 4 columns include: "Meta_troph": a vector representing a combination of metacommunity ID and trophic level. This was used to differentiate metacommunities that include more than one trophic level. "Tmax_sync ": a numerical vector describing synchrony in maximum temperature within the metacommunity. "Tmin_sync ": a numerical vector describing synchrony in minimum temperature within the metacommunity. "Precip_sync ": a numerical vector describing synchrony in precipitation within the metacommunity. To run the third and fourth R codes (“03_Siqueira_etal_stab_figs.R”; “04_Siqueira_etal_stab_supp_m.R”), one needs the same files described above.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,045
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,390
Score d'incertitude au seuil0,870

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,045
Méta-épidémiologie (sens strict)0,0040,003
Méta-épidémiologie (sens large)0,0020,004
Bibliométrie0,0040,004
Études des sciences et des technologies0,0020,001
Communication savante0,0050,004
Science ouverte0,0040,004
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,3900,227

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,057
Tête enseignante GPT0,271
Écart entre enseignants0,214 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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