Diversity and Structure of the Prokaryotic Community in Tropical Monomictic Reservoir.
Provisional — an automated or curator check raised a specific concern and points reviewers here. This is NOT a final assessment and not a determination about the authors.
The main result did not reproduce in this reproduction attempt. Where our recomputation produced values that differ from the published ones, those discrepancies are listed below. This is a single automated attempt — not peer review and not a finding of error or misconduct — and differences can also arise from data access, undocumented parameters or the computing environment. The verdict can be contested via “report an error”.
- Nothing in this column.
- 🔴Could not use the authors’ exact input data
- 🔴Reported values were only indirectly comparable
- 🟡A deviation arose in the data or preprocessing
- 🔴A deviation was attributed to the published material
- 🔴Reported values were not (fully) derivable from the shared data
- 🔴The deviation was non-trivial in magnitude
- 🔴The central claim did not (fully) hold under reproduction
- 🔴Overall, the reproduction showed a material discrepancy
This paper has a computational component, but its primary data is legally or ethically access-restricted — identifiable patient cohorts, rare-disease genomes, or controlled-access biobanks that cannot be openly shared. The reproduction therefore could not be attempted. That is a neutral verdict: it does not mean the result is wrong or that the authors fell short — only that, for legitimate privacy reasons, it cannot be independently checked from public data. We deliberately do NOT assign a 0–100 score here, because a low number would wrongly read as a failed reproduction.
▸Reproduction agent’s raw note
PARTIAL. PMID 40072582 is a 16S V4 QIIME2 amplicon study (q2-demux -> DADA2 -> MAFFT/FastTree -> q2-feature-classifier SILVA-138 515-806 nb); the pipeline and target numbers are well described and all claims are pre-pinned. The QIIME2/DADA2 pipeline itself CANNOT be reproduced: BioProject PRJNA1191546 (BioSamples SAMN45085681-685) is registered but NOT public (re-verified 2026-06-22 = identical to 2026-06-16: NCBI esearch Count 0 for bioproject/sra/all 5 biosamples, ENA 404, 0 read_run rows), and no ASV feature table was deposited. So no «our HPC» compute was possible (no inputs). NEW vs the prior drop: the article is open-access and its supplement (MOESM1 DOCX) Table S1 lists per-sample raw/filtered/non-chimeric/ASV counts for all 50 samples -- summing these reproduces the reported aggregates EXACTLY (raw 2,938,646; filtered 1,679,973; non-chimeric 1,471,484; min 13,077; max 73,881), an internal-consistency anti-fabrication check that PASSES (not an independent pipeline run). CCA r2 in-text claims (SRP 0.7669, DO 0.6987) match supplement Table S4 exactly. TWO data discrepancies flagged: (1) data_public_claim mismatch -- the asserted public deposition is false; (2) biosamples_vs_samples mismatch -- only 5 BioSamples registered for a 50-sample (depth x date) study. NOT a fabrication finding on the science, but a data-availability + deposit-completeness problem. DID NOT attempt: diversity/taxonomy/CCA recomputation (no feature table, no raw reads). Re-attempt warranted if PRJNA1191546 is released. Verdict provisional -- a human signs off.
These records describe the outcome of reproduction attempts carried out autonomously by brainbox using large language models (LLMs). They are not peer review, not an audit, and not a determination of error or misconduct by any author. A verdict reflects what one attempt could or could not reproduce — which may depend on data access, undocumented parameters, the computing environment, or the depth of effort — and not a judgement of the people who did the work. We can be wrong, and we correct mistakes quickly: every record carries a “report an error” button.
Assessment versions
Every reproduction run is kept as an immutable version — anchored to the data as it stood, with a tamper-evident chain hash. A rerun (e.g. after an author updates a deposit) adds a new version; the previous one stays on record.
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v1 current initial assessmentassessed: 2026-06-16 ⛓ 847bc5238a56
✎ I am an author of this paper
Updated or fixed a deposit, or is there an erratum? Ask us to re-run the metrics. We verify by email first; the new result is published as a new version with full history — nothing is overwritten.
Provenance — full disclosure
When this reproduction was carried out, which methodology version was used, and by whom — so the record can be audited and checked independently.
- Reproduced
- 2026-06-22
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-16no human curator yet
- Last updated
- 2026-08-05
Provisional, curator- or AI-assessed, and independently checkable. A reproduction outcome states what one attempt could reproduce — not a judgement of the authors.
Deep full-text extraction
Model: sonnetThe study aims to characterize the prokaryotic (Bacteria and Archaea) community of the tropical monomictic Valle de Bravo reservoir across an annual circulation-stratification hydrodynamic cycle during a low-water-level fluctuation period, and to associate the spatio-temporal distribution of these microorganisms with the hydrogeochemical conditions (DO, nutrients) of the water column.
- ★ Diversity and structure of the prokaryotic community exhibit spatio-temporal variations driven by the annual circulation-stratification hydrodynamic cycle. finding
- ★ Prokaryotic community structure is significantly correlated with dissolved oxygen (DO), soluble reactive phosphorus (SRP), and dissolved inorganic nitrogen (DIN) concentrations. finding
- ★ During heterotrophic circulation, breakdown of the thermal gradient homogenizes nutrient distribution, and DO presence promotes dominance of aerobic/facultative heterotrophic bacteria such as Bacteroidota, Actinobacteriota, and Verrucomicrobiota. finding
- ★ Autotrophic circulation is characterized by increased DO and NO3- concentrations with abundant Cyanobacteria. finding
- ★ During stratification, prokaryotes associated with methane metabolism are detected mainly in the hypolimnion, along with taxa related to sulfate reduction and nitrification. finding
- 16S rRNA gene metabarcoding combined with spatio-temporal physicochemical/biogeochemical monitoring provides a useful approach to understand biogeochemical dynamics in reservoirs. method
- Valle de Bravo reservoir was in a eutrophic state during the studied low-water-level fluctuation period. finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| 16S rRNA gene survey (metabarcoding, V4 region, primers 515F/806R) | water column samples, central monitoring station, Valle de Bravo reservoir | none (natural spatio-temporal/hydrodynamic variation) | prokaryotic community composition and relative abundance (ASVs) | Illumina MiSeq (Yale Center for Genome Analysis) |
| Sequence quality filtering, denoising, chimera removal, taxonomic assignment | 16S rRNA amplicon sequence data | none | filtered non-chimeric sequences, ASVs, taxonomy | QIIME2 with DADA2, MAFFT, FastTree, Silva 138 classifier |
| Water physicochemical profiling (temperature, pH, dissolved oxygen) | vertical water column profile, central station, Valle de Bravo reservoir | none | temperature, pH, DO concentration/saturation by depth and time | In-Situ Aqua TROLL 500 multiparameter sonde |
| Nutrient analysis (TN, TP, NO3-, NO2-, NH4+, SRP, SRSi) | water samples from multiple depths, Valle de Bravo reservoir | none | concentrations of nitrogen, phosphorus, and silica species | Skalar San Plus segmented-flow auto-analyzer, spectrophotometry |
| Chlorophyll a determination | water samples from multiple depths, Valle de Bravo reservoir | none | Chl-a concentration | spectrophotometry, acetone extraction |
| Secchi depth measurement | water column, Valle de Bravo reservoir | none | water transparency/depth | — |
- – 2,938,646 raw sequences obtained (~250 bp), resulting in 1,471,484 filtered non-chimeric sequences with a minimum of 13,077 sequences per sample
- – During well-established stratification (Sep 2018), epilimnion DO was oversaturated (>7.02 mg L-1 = 100% DO saturation), DIN and SRP nearly depleted; hypolimnion accumulated NH4+ and SRP with depleted DO
- – During heterotrophic circulation (Dec 2018), sub-oxic conditions (30–58% DO saturation) with SRP (0.28 µmol-P L-1) and NH4+ (21.3 µmol-N L-1) present throughout water column, NO3- depleted (0.52 µmol-N L-1) 0.28 µmol-P L-1 SRP; 21.3 µmol-N L-1 NH4+; 0.52 µmol-N L-1 NO3-
- – During early stratification (Apr 2019), NO3- became dominant DIN species in metalimnion/hypolimnion, highest at 12–20 m; NH4+ nearly depleted except at bottom
- – During late stratification (Sep 2019), anoxic hypolimnion rich in NH4+ and SRP, NO3- almost depleted
- – During autotrophic circulation (Jan 2020), slight sub-oxygenation (73–78% DO saturation), NO3- dominant among DIN species (13.77 µmol-N L-1), NH4+ depleted (1.02 µmol-N L-1) 13.77 µmol-N L-1 NO3-; 1.02 µmol-N L-1 NH4+
- count 2,938,646 raw sequences (total raw 16S rRNA sequences obtained via Illumina MiSeq)
- count 1,471,484 filtered non-chimeric sequences (sequences after DADA2 quality filtering and chimera removal)
- count minimum of 13,077 sequences per sample (sequencing depth adequacy per sample)
- other >7.02 mg L-1 = 100% DO saturation (epilimnion DO oversaturation threshold during well-established stratification)
- other 30–58% DO saturation (sub-oxic conditions during heterotrophic circulation (Dec 2018))
- mean 0.28 µmol-P L-1 SRP; 21.3 µmol-N L-1 NH4+; 0.52 µmol-N L-1 NO3- (nutrient concentrations during heterotrophic circulation)
- other 73–78% DO saturation (sub-oxygenation during autotrophic circulation (Jan 2020))
- mean 13.77 µmol-N L-1 NO3-; 1.02 µmol-N L-1 NH4+ (DIN species concentrations during autotrophic circulation)
Statistical methods review
Model: sonnetA neutral, descriptive read of the statistical approach — what was done, and (for shared learning, not as criticism) what could also have been done.
The study used a spatio-temporal 16S rRNA gene metabarcoding design (5 sampling campaigns across one annual hydrodynamic cycle, multiple water-column depths at a single central station) to characterize prokaryotic communities in a tropical reservoir. Alpha diversity (observed ASVs, Shannon, Simpson) and beta diversity (PCoA-UniFrac, PERMANOVA, betadisper) were calculated within a phyloseq/vegan framework in R. Community–environment relationships were assessed via canonical correspondence analysis (CCA) with envfit-based variable selection (p < 0.05), and physicochemical data were summarized with PCA. Taxon relative abundances and diversity metrics were visualized in GraphPad Prism.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| PERMANOVA (vegan::permutest after betadisper) | Differences in prokaryotic community composition among water-column compartments (epilimnion/metalimnion/hypolimnion) and sampling times | — | not stated |
| betadisper (homogeneity of multivariate dispersions) | Pre-test for PERMANOVA, checking dispersion equality among compartment groups | — | not stated |
| Principal Coordinate Analysis with UniFrac distances (PCoA-UniFrac) | Beta diversity ordination of prokaryotic communities across samples | — | na |
| Canonical Correspondence Analysis (CCA) with envfit permutation test (p < 0.05) | Relating prokaryotic assemblage structure to physicochemical/biogeochemical variables (DO, SRP, DIN, etc.) | — | not stated |
| Principal Component Analysis (PCA) | Clustering samples by physicochemical and biogeochemical characteristics | — | not stated |
| Alpha diversity indices (observed ASVs, Shannon index, Simpson index) | Within-sample diversity across water-column depths and sampling times | — | na |
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Beta diversity was visualized with PCoA using phylogenetic (UniFrac) distances↳ Could also: NMDS ordination on Bray-Curtis dissimilarity of Hellinger-transformed relative abundances could also be used — Bray-Curtis/NMDS does not require a phylogenetic tree and is robust to the high sparsity typical of ASV tables; Hellinger transformation down-weights rare ASVs and linearizes the species–environment relationship, making it complementary to phylogenetic approaches
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Community–environment relationships were assessed with CCA, which assumes a unimodal (Gaussian) species response to environmental gradients↳ Could also: Redundancy Analysis (RDA) on Hellinger-transformed abundances could also be used, which assumes linear species responses — For short environmental gradients (< 2 SD units, often the case in a single reservoir), linear methods such as RDA tend to perform well and are directly comparable to PCA; the appropriate choice can be guided by a preliminary detrended correspondence analysis (DCA) to estimate gradient length
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Multiple envfit permutation tests were run to select physicochemical variables, each at p < 0.05, without a stated correction for the family of tests↳ Could also: Benjamini-Hochberg FDR correction or Bonferroni correction across the set of tested environmental variables could also be applied — When several environmental variables are simultaneously tested for significance, adjusting the threshold reduces the probability of identifying spurious associations by chance; this is a commonly applied step in multivariate ecological analyses
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ASVs (100% nucleotide identity) were used as the unit of diversity↳ Could also: OTU clustering at 97% similarity could also be used, or denoising with an alternative tool such as Deblur — ASVs offer finer resolution and reproducibility across studies, while OTUs have a longer baseline of published comparison data; Deblur provides an alternative ASV-level denoising strategy that can be compared to DADA2 outputs as a sensitivity check
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All sampling was conducted at a single central monitoring station, treating depths as the spatial dimension↳ Could also: Sampling at multiple spatially distributed stations across the reservoir surface and littoral zones could also be incorporated — A single-station design efficiently captures vertical (depth) and temporal variation but cannot partition horizontal spatial variability; multiple stations would allow formal spatial autocorrelation analyses (e.g., Mantel tests, spatial distance-decay) and distinguish basin-wide patterns from local dynamics
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Alpha diversity was summarized with Shannon and Simpson indices and observed ASV richness, without rarefaction↳ Could also: Rarefaction to a common sequencing depth, or phylogenetic alpha diversity (Faith's PD), could also be used — Rarefaction standardizes unequal sequencing effort before richness comparisons; Faith's PD incorporates evolutionary branch-length information and can reveal diversity patterns not captured by richness or evenness indices alone, particularly relevant when the study reports a phylogenetic tree already used for UniFrac
Citation network
Where this publication sits in the reproducibility-weighted citation graph — what it is built on, and what is built on it. Citation data from OpenAlex.
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What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-40072582
Paper: Barjau-Aguilar et al. (2025) "Diversity and Structure of the Prokaryotic Community in Tropical Monomictic Reservoir." Microb Ecol. PMID 40072582 / PMCID PMC11903632 / DOI 10.1007/s00248-025-02508-1.
Pipeline (from Methods)
16S rRNA gene amplicon study, V4 region, primers 515F/806R, Illumina MiSeq (paired-end, ~250 bp), Yale Center for Genome Analysis. Bioinformatics in QIIME2:
- Demultiplex + quality-visualize with q2-demux (this is the "code" link in the brief — a generic QIIME2 plugin, not authors' own code; P16 third-party tool).
- Denoise / merge / chimera-removal with DADA2 (bimera removal via Needleman-Wunsch). → ASV table (100% identity).
- Align reps with MAFFT, build tree with FastTree.
- Taxonomy via q2-feature-classifier, SILVA v138 99% 515-806 naive-Bayes classifier (
silva-138-99-515-806-nb-classifier.qza, Nov/2020). - Remove chloroplast + mitochondria.
- Downstream: alpha diversity (Shannon, inverse Simpson), beta diversity (PCoA), CCA vs physico-chemistry, taxonomic composition per depth/date.
In scope (pipeline-derived, would be attempted)
- Total raw sequences: 2,938,646
- DADA2 filtered non-chimeric sequences: 1,471,484; minimum 13,077 / sample
- Number of ASVs
- Alpha diversity: Shannon avg 4.17 (Dec.2018) / 4.40 (Jan.2020)
- Inverse Simpson: 0.9539 / 0.9676
- Dominant phylum relative abundances per period (Bacteroidota, Actinobacteriota, Cyanobacteria, Planctomycetota, Proteobacteria classes, Verrucomicrobiota, etc.)
- Archaeal composition (Nanoarchaeota up to 17.4%, Woesearchaeales, methanogens ~0.3%)
- Beta-diversity / CCA significance (PCoA p=0.004; SRP r²=0.7669; DO r²=0.6987)
Out of scope (wet-lab / manual / external)
- Field sampling, limnology (temperature, DO, SRP, etc. measured in situ)
- Sequencing itself (MiSeq run at Yale)
BLOCKER — data not obtainable
The Data Availability statement asserts the sequences are "in a publicly accessible repository … BioProject PRJNA1191546" (BioSamples SAMN45085681–SAMN45085685). As of 2026-06-16 the data is NOT public:
- NCBI BioProject page returns: "The following ID is not public in BioProject: 1191546"
- NCBI esearch db=bioproject and db=sra (PRJNA1191546[BioProject]): Count 0
- ENA browser API: HTTP 404 for PRJNA1191546
- ENA filereport read_run: 0 runs for the project and for each of the 5 BioSamples
Evidence: reproduction/logs/availability_check_20260616T160413Z.txt.
No raw reads + no barcode/metadata mapping ⇒ no pipeline output can be regenerated (every in-scope number requires the raw sequences). No «our HPC» compute was submitted because there is nothing to download. → pipeline = drop: data_unavailable (registered but embargoed/not released; contradicts the paper's "publicly accessible" claim).
UPDATE 2026-06-22 (re-run) — overall outcome upgraded to PARTIAL
Re-verified availability: still not public (evidence
reproduction/logs/availability_recheck_20260622T132628Z.txt), so the QIIME2/DADA2
pipeline still cannot be run. BUT the article is open access and ships supplement
248_2025_2508_MOESM1_ESM.docx:
- Table S1 = per-sample raw/filtered/non-chimeric/ASV counts for all 50 samples.
Summing reproduces the reported aggregates EXACTLY (raw 2,938,646; filtered 1,679,973;
non-chimeric 1,471,484; min 13,077; max 73,881) — internal-consistency / anti-fabrication
check PASSED (not an independent pipeline run). Evidence:
reproduction/outputs/tableS1_consistency_check.txt. - Tables S4/S5 = CCA r² per period; in-text claims (SRP 0.7669, DO 0.6987) match exactly.
- Table S3 = hydrochemistry (env data for CCA). No ASV feature table deposited → diversity/taxonomy/CCA cannot be recomputed.
- Discrepancy: Data Availability lists only 5 BioSamples for a 50-sample study. → Status partial: pipeline drop (data_unavailable) + verified supplement audit + 2 data-availability/deposit-completeness mismatches. Se
Assessments & scoring basis
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Automated reproduction checks whether a published result can be regenerated from the paper’s described methods and shared data. When something does not reproduce, that is not a claim of error or misconduct — most often it reflects under-described methods, software or environment differences, or gaps in data access, and some of the pre-print papers in the queue may carry issues their authors had no part in. The goal is shared awareness that rigorous, fully-described methods help everyone — never a judgement of any author.
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Reproduction footprint
claude-opus-4-8Measured resources invested to assess this paper — sanitised (machine class only, no job ids/paths). Compute = HPC accounting (SLURM); tokens = the AI agent's session.