Diversity of geometrid moths (Lepidoptera: Geometroidea) from northernmost Western Ghats of Maharashtra, India, with notes on range extension.

データ レコード

この オカレンス（観察データと標本) リソース内のデータは、1 つまたは複数のデータ テーブルとして生物多様性データを共有するための標準化された形式であるダーウィン コア アーカイブ (DwC-A) として公開されています。 コア データ テーブルには、277 レコードが含まれています。

この IPT はデータをアーカイブし、データ リポジトリとして機能します。データとリソースのメタデータは、 ダウンロード セクションからダウンロードできます。 バージョン テーブルから公開可能な他のバージョンを閲覧でき、リソースに加えられた変更を知ることができます。

バージョン

次の表は、公にアクセス可能な公開バージョンのリソースのみ表示しています。

引用方法

研究者はこの研究内容を以下のように引用する必要があります。:

Gurule S A, Rajput J A, Shere-Kharwar A S (2025). Diversity of geometrid moths (Lepidoptera: Geometroidea) from northernmost Western Ghats of Maharashtra, India, with notes on range extension.. Version 1.1. Gokhale Education Society. Occurrence dataset. https://cloud.gbif.org/asia/resource?r=geometridae&v=1.1

権利

研究者は権利に関する下記ステートメントを尊重する必要があります。:

パブリッシャーとライセンス保持者権利者は Gokhale Education Society。 This work is licensed under a Creative Commons Attribution Non Commercial (CC-BY-NC 4.0) License.

GBIF登録

このリソースをはGBIF と登録されており GBIF UUID: 129dd4e0-6453-43de-ad3f-174929e772a0が割り当てられています。   Participant Node Managers Committee によって承認されたデータ パブリッシャーとして GBIF に登録されているGokhale Education Society が、このリソースをパブリッシュしました。

キーワード

Occurrence; Diversity; Moths; Geometroidea; Western Ghats; Range extension

連絡先

地理的範囲

The dataset covers a geographic range extending from the northernmost point at 20.3911° N, 73.9167° E to the southernmost point at 19.5290° N, 73.7500° E, and from the easternmost point at 20.3817° N, 74.0300° E to the westernmost point at 20.1036° N, 73.3883° E.

生物分類学的範囲

説明がありません

時間的範囲

プロジェクトデータ

We present the first comprehensive checklist of geometrid moths from the northernmost Western Ghats of Maharashtra, India a biogeographically significant yet underexplored region. Surveys conducted across eight localities between 2022 and 2024 recorded 286 individuals representing 77 species and 9 genus-level morphotypes within the superfamily Geometroidea. These taxa span 46 genera, 20 tribes, and 7 subfamilies under two families, namely Geometridae (73 species) and Uraniidae (4 species). Sampling was carried out across an elevational gradient of 309–1243 m asl using non-invasive light-sheet methods supplemented with opportunistic photographic observations. The most species-rich subfamilies were Ennominae (29 species), Sterrhinae (22 species), and Geometrinae (17 species). Genera such as Scopula, Chiasmia, and Comibaena were frequently encountered, indicating ecological generalism and strong phototactic behavior. Notably, three species—Idaea protensa, Cleora cornaria, and Ophthalmitis herbidaria—are reported for the first time from Peninsular India, thus extending their known distributional ranges. In addition, range extensions of eight species to the northernmost Western Ghats in Maharashtra and a total of thirty species to the northern Western Ghats were recorded.

プロジェクトに携わる要員:

収集方法

Random sampling was carried out between July 2021 and February 2024 across 10 sites in the northernmost Western Ghats of Maharashtra (309–1243 m asl). Moths were primarily sampled using a non-invasive light-sheet method (mercury vapor and UV lights), supplemented by opportunistic photographic observations. Randomized temporal and habitat-based sampling ensured broad representation of species diversity with minimal collection bias.

Method step description:

1. Step 1: The moth was collected from multiple sites based on habitat variation and accessibility i.e Kalmuste, Belgaon Dhaga, Saptashrungi Vani, Kalsubai, Kasara, Peth, Waghere Harsul, for morphological and molecular (DNA barcoding) studies for biodiversity assessment.
2. Step 2: Light traps, LepiLed, and sweep nets was used for nocturnal moth collection.
3. Step 3: Moths were captured in bottles, and each specimen was labelled with locality, date, and collection code.
4. Step 4: Specimens were spread, and preserved using entomological pins, and stored in insect boxes to maintain and to avoid contamination or degradation naphthalene balls were placed for identification purpose.
5. Step 5: Each specimen had detailed metadata: Locality, Date, time of collection Environmental conditions (temperature, humidity, weather), Collector’s name or team, for accurate analysis.
6. Step 6: Meta Data All metadata and specimen information were entered into a excels sheet. Repeated entries and errors were checked for statistical analysis or publication.

追加のメタデータ