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A georeferenced dataset of nocturnal macrolepidoptera: A tool for forest management and biodiversity conservation

In this paper we provide a georeferenced dataset of raw data concerning occurrence and abundance of nocturnal macrolepidoptera, an insect group largely recognized as a good ecological indicator of forest ecosystems. Data have been collected by using light traps located in 15 beech and 20 Calabrian b...

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Detalles Bibliográficos
Autores principales: Scalercio, Stefano, Di Marco, Carlo, Puletti, Nicola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818905/
https://www.ncbi.nlm.nih.gov/pubmed/35146097
http://dx.doi.org/10.1016/j.dib.2022.107882
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author Scalercio, Stefano
Di Marco, Carlo
Puletti, Nicola
author_facet Scalercio, Stefano
Di Marco, Carlo
Puletti, Nicola
author_sort Scalercio, Stefano
collection PubMed
description In this paper we provide a georeferenced dataset of raw data concerning occurrence and abundance of nocturnal macrolepidoptera, an insect group largely recognized as a good ecological indicator of forest ecosystems. Data have been collected by using light traps located in 15 beech and 20 Calabrian black pine forest lots, 20 of which included in Natura 2000 sites. The sampling was carried out monthly lasting from May to late October 2019 and 2020 in order to cover the entire period during which favourable conditions for adult monitoring occurred, and to encompass phenological changes occurring across seasons in moth diversity. The dataset is composed by a total of 42,834 individuals belonging to 363 species. Due to the relatively small attractive radius of used light traps (about 25 m), georeferenced lepidopteran data can be easily correlated to any kind of spatial environmental variables and forest attributes and to their temporal variations being useful to quantify also the effects of long-term ecological drivers.
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spelling pubmed-88189052022-02-09 A georeferenced dataset of nocturnal macrolepidoptera: A tool for forest management and biodiversity conservation Scalercio, Stefano Di Marco, Carlo Puletti, Nicola Data Brief Data Article In this paper we provide a georeferenced dataset of raw data concerning occurrence and abundance of nocturnal macrolepidoptera, an insect group largely recognized as a good ecological indicator of forest ecosystems. Data have been collected by using light traps located in 15 beech and 20 Calabrian black pine forest lots, 20 of which included in Natura 2000 sites. The sampling was carried out monthly lasting from May to late October 2019 and 2020 in order to cover the entire period during which favourable conditions for adult monitoring occurred, and to encompass phenological changes occurring across seasons in moth diversity. The dataset is composed by a total of 42,834 individuals belonging to 363 species. Due to the relatively small attractive radius of used light traps (about 25 m), georeferenced lepidopteran data can be easily correlated to any kind of spatial environmental variables and forest attributes and to their temporal variations being useful to quantify also the effects of long-term ecological drivers. Elsevier 2022-01-28 /pmc/articles/PMC8818905/ /pubmed/35146097 http://dx.doi.org/10.1016/j.dib.2022.107882 Text en © 2022 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Scalercio, Stefano
Di Marco, Carlo
Puletti, Nicola
A georeferenced dataset of nocturnal macrolepidoptera: A tool for forest management and biodiversity conservation
title A georeferenced dataset of nocturnal macrolepidoptera: A tool for forest management and biodiversity conservation
title_full A georeferenced dataset of nocturnal macrolepidoptera: A tool for forest management and biodiversity conservation
title_fullStr A georeferenced dataset of nocturnal macrolepidoptera: A tool for forest management and biodiversity conservation
title_full_unstemmed A georeferenced dataset of nocturnal macrolepidoptera: A tool for forest management and biodiversity conservation
title_short A georeferenced dataset of nocturnal macrolepidoptera: A tool for forest management and biodiversity conservation
title_sort georeferenced dataset of nocturnal macrolepidoptera: a tool for forest management and biodiversity conservation
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818905/
https://www.ncbi.nlm.nih.gov/pubmed/35146097
http://dx.doi.org/10.1016/j.dib.2022.107882
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