Occurrence dataset of reptiles and amphibians from two old-growth forest localities along the Las Piedras River, Tambopata Province, Peru
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».