Occurrence dataset of reptiles and amphibians from two old-growth forest localities along the Las Piedras River, Tambopata Province, Peru
Bibliographic record
Abstract
Background: This study presents the first watershed-wide checklist and geo-referenced dataset of amphibians and reptiles from two primary forest localities along the Las Piedras River, Madre de Dios, Peru. Compiled from pitfall traps, quadrats, transects and opportunistic observations between 2004 and 2024, the dataset contains 2,327 records across 165 species, including several new distribution records from the central basin near the Huascar River. The Madre de Dios region in south-eastern Peru is renowned for its biodiversity and old-growth rainforests, hosting diverse flora and fauna. Protected areas like the Tambopata National Reserve and Manu National Park are vital refuges for wildlife and research hubs. The region faces threats from deforestation and illegal mining, necessitating urgent conservation efforts. Despite being one of the most diverse regions for herpetofauna globally, biogeography reports from the Las Piedras River are limited. Notably, sixty non-volant mammal species and 144 fish species have been documented, along with 59 frog and 11 reptile species at the Las Piedras Biodiversity Station (LPBS). However, a comprehensive review of reptile diversity in the watershed is lacking. This study presents a survey and occurrence dataset for reptile and amphibian species at LPBS and the Amazon Research and Conservation Centre (ARCC), including opportunistic records to provide complete taxonomic coverage. Furthermore, we review and compile other reported occurrences. This dataset and review offer detailed species and geographical information, supporting further research on herpetofauna biogeography and ecology and aiding conservation efforts on the Las Piedras River. New information: This list of reptile and amphibian species from the Las Piedras River in Peru includes new records from the basin's central area, near the Huascar River's confluence. It unifies data from early efforts to find herpetofauna at the Las Piedras Biodiversity Station spanning more than ten years. Over a decade of sampling, combined with opportunistic records, comprehensive taxonomic coverage of herpetofauna on the tributary has been provided. Our dataset contains 2,327 distinct geo-referenced records, categorised into Anura (1788), Crocodilia (10), Gymnophiona (1), Squamata (517) and Testudines (11). These records span 165 identified species, along with one entry recorded at the genus level (Chironius). This dataset was structured and managed using Microsoft Excel, where geo-referenced species occurrence data were organised into standardised formats compatible with GBIF publishing requirements. The dataset was subsequently validated and formatted as a Darwin Core Archive (DwC-A), the standard format for biodiversity data sharing, using GBIF's Integrated Publishing Toolkit (IPT). This structured approach ensures interoperability and compliance with global biodiversity informatics standards, supporting its integration into herpetofauna biogeography and conservation efforts. This dataset also includes new records from the central basin of the Las Piedras River near the Huascar River confluence. By offering 2,327 distinct geo-referenced records, this dataset (https://doi.org/10.15468/sa8m3q) supports ongoing research into herpetofauna biogeography and conservation efforts in a region under increasing pressure from deforestation and other human activities.Based on our dataset and an accompanying review of historical records and publications, we document a total of 175 herpetofauna species in the Las Piedras River watershed. This total includes 96 reptile species (ARCC = 70, LPBS = 76) and 79 amphibian species (ARCC = 64, LPBS = 69), from both geo-referenced and literature-confirmed sources.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".