Hindawi Publishing Corporation Dataset Papers in Science Volume 2014, Article ID 176471, 8 pages http://dx.doi.org/10.1155/2014/176471

Dataset Paper New Distributional Data of Butterflies in the Middle of the : An Area Very Sensitive to Expected Climate Change

Stefano Scalercio

Consiglio per la Ricerca e la Sperimentazione in Agricoltura, Unita` di Ricerca per la Selvicoltura in Ambiente Mediterraneo, Contrada Li Rocchi-Vermicelli, , 87036 ,

Correspondence should be addressed to Stefano Scalercio; [email protected]

Received 6 November 2013; Accepted 6 March 2014; Published 12 May 2014

Academic Editors: P. Nowicki, B. Qian, and B. Schatz

Copyright © 2014 Stefano Scalercio. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Butterflies are known to be very sensitive to environmental changes. Species distribution is modified by climate warming with latitudinal and altitudinal range shifts, but also environmental perturbations modify abundance and species composition of communities. Changes can be detected and described when large datasets are available, but unfortunately only for few Mediterranean countries they were created. The butterfly fauna of the Mediterranean Basin is very sensitive to climate warming and there is an urgent need of large datasets to investigate and mitigate risks such as local extinctions or new pest outbreaks. The fauna of , the southernmost region of peninsular Italy, is composed also of European species having here their southern range. The aim of this dataset paper is to increase and update the knowledge of butterfly distribution in a region very sensitive to climate warming that can become an early-warning area.

1. Introduction only few data are available for , an area with a fauna very sensitive to climate changes [5]. In order to Large and updated datasets are fundamental tools for investi- detect changes, it is important to investigate the distribution gating the effects of climatic changes and environmental of both common and rare species, but bibliographic sources perturbations on , mainly of sensitive taxa such only rarely provide punctual and useful data of the former as butterflies [1]. Butterflies are known to react to climate causing an important lack of information. Many data can warming with latitudinal and altitudinal range shifts2 [ ], but be collected within private and public collections. This is an these changes are detectable only if distributional datasets expensive procedure, but interesting data can be obtained on are available. In Europe, some countries (Belgium, Finland, the past distribution of common species. Germany, Ireland, The Netherlands, Sweden, Switzerland, In Italy, the first attempt toward a knowledge of the and UK) adopted a standardized butterfly monitoring scheme distribution of the fauna at a national scale is represented by from several years [3],butintheMediterraneanareasonlythe the Checklist of the Italian Fauna [6], with the distribution Catalan Butterfly Monitoring Scheme (http://www.cata- of species only generalized to large areas (North, South, Sar- lanbms.org/) and the Suivi Temporel des Rhopaloceres` dinia, and ). Successively, the project CKmap supported de France (http://vigienature.mnhn.fr/page/suivi-temporel- the mapping of 10.000 species of animals at a national level des-rhopaloceres-de-france)areworking. in a UTM grid square [7]. Among them, the distribution of Models of species distribution in face of changes due to all butterflies species known for Italy was mapped and the climate warming [4]arebasedontheactualdistributionof localities georeferenced [8]. These localities were obtained species and future scenarios can be distorted when a model from private and public collections, from private datasets, and is based on few data. The southern range of the European from bibliographic resources, but very few were collected in distribution of butterflies is largely underinvestigated and the southern regions, where large territories are not explored. 2 Dataset Papers in Science

The localities were individuated by two toponyms: the 50 first is the most precise and the second is the most easily recognizable on maps. Latitude and longitude were provided 40 for all localities and grouped in territorial units with similar 1 ecological, geomorphological, and biogeographic features in 1000 km 30 9 order to facilitate the individuation of areas that need further 7 0102030 investigations. The territorial units individuated are nine [11]: Pollino- Mountains, Catena Costiera Moun- 2 tains, Sila Mountains, Marchesato Area, Serre Mountains, Aspromonte Mountains, Crati Valley, Tyrrhenian Coast, and 3 4 Ionian Coast (Figure 1). Data of localities are summarized in Table 1. Species lists were compiled as shown in Dataset Items 1, 2, 3, 4, and 5 (Tables).

Tyrrhenian Sea 3. Dataset Description The dataset associated with this Dataset Paper consists of 5 8 5 items which are described as follows.

Dataset Item 1 (Table). Species list for the different localities of the Pollino-Orsomarso Mountains. Data presented in this (km) table were based on the presence (1) or absence (0) of a 6 050 butterfly species.

Column 1: Family Column 2: Species Figure 1: Study area. It is located in the middle of the Mediter- Column 3: Bosco Pollinello ranean Basin. Territorial units are indicated as follows: 1: Pollino- OrsomarsoMountains;2:CatenaCostieraMountains;3:SilaMoun- Column 4: Campo Tenese tains; 4: Marchesato Area; 5: Serre Mountains; 6: Aspromonte Column 5: Mountains; 7: Crati Valley; 8: Tyrrhenian Coast; 9: Ionian Coast. Column 6: Civita Column 7: Cozzo del Pellegrino Column 8: Fagosa The Calabria is the southernmost region of Italian Penin- sula, located in the middle of the Mediterranean Basin. The Column 9: Fiume Argentino regional fauna includes European species, having here their Column 10: La Calvia southern range limit, particularly sensitive to the risk of local Column 11: Monte Moschereto extinctions as a consequence of the expected climate change. Column 12: Monte Palanuda Papers devoted to the Calabrian fauna of Lepidoptera are very scarce and only in last few decades the studies were Column 13: Monte Pollino intensified5 [ , 9, 10]. Anyway, data are largely insufficient to Column 14: Orsomarso study changes on a regional scale and data are strictly needed Column 15: Piani del Pollino for detecting and mitigating risks such as local extinctions or Column 16: new pest outbreaks. Theaimofthisdatasetpaperistoprovidenewdistribu- Column 17: Petrosa tional data and georeferenced datasets useful for the study Column 18: Serra del Prete of dynamics linked to changes on large spatial and temporal Column 19: Serra Dolcedorme scales in the Mediterranean Basin, a region very sensitive to Column 20: Timpa San Lorenzo climate changes that can become an early-warning area [5].

Dataset Item 2 (Table). Species list for the different localities 2. Methodology of the Catena Costiera Mountains. Data presented in this In this dataset paper, all unpublished records of butterflies table were based on the presence (1) or absence (0) of a of the author are reported. Data were collected during the butterfly species. years 2005–2012, mainly in the Cosenza Province, covering Column 1: Family all the seasons of butterflies’ activity. Species are named according to the online database of the European Fauna Column 2: Species (http://www.faunaeur.org/). Column 3: Acquafredda Dataset Papers in Science 3 E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 11 31 13 15 17 23 11 17 21 23 03 35 55 15 19 50 25 44 21 24 40 14 06 41 31 53 02 58 21 56 30 24 38 27 22 22 05 47 00 33 09 48 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 5 11 11 21 11 13 13 14 05 13 10 11 15 23 13 15 15 17 15 08 13 07 14 18 08 08 10 14 14 45 0 14 12 24 56 07 06 56 04 54 34 08 06 ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ 16 N16 N16 N N16 N16 N16 N16 N16 N16 N15 N16 N16 N16 N15 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N15 N16 N16 N16 N16 N16 N17 N16 N16 N16 N16 N16 N16 N16 N16 N16 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 11 31 17 18 13 10 35 52 10 39 31 18 17 21 58 50 45 29 07 54 50 44 21 50 00 33 48 39 57 43 24 36 27 19 38 30 09 20 48 06 󸀠 09 04 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 11 17 15 19 10 16 20 11 11 01 12 15 17 07 23 16 14 09 21 12 10 10 13 58 09 40 10 41 05 23 29 09 37 06 45 36 26 07 20 07 24 06 ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ Table 1: Description of collecting localities. Ionian Coast 15 39 Cosenza Catena Costiera Mountains 800 39 Cosenza Catena Costiera Mountains 540 39 Cosenza Catena Costiera Mountains 1540 39 Cosenza Catena Costiera Mountains 590 39 Cosenza Catena Costiera Mountains 460 39 Cosenza Catena Costiera Mountains 810 39 Cosenza Ionian Coast 30 39 Cosenza Catena Costiera Mountains 270 39 Cosenza Catena Costiera Mountains 625 39 Cosenza Catena Costiera Mountains 1080 39 Cosenza Catena Costiera Mountains 480 39 Cosenza Crati Valley 200 39 Cosenza Catena Costiera Mountains 985 39 Cosenza Crati Valley 250 39 Cosenza Catena Costiera Mountains 320 39 Cosenza Crati Valley 60 39 Cosenza Catena Costiera Mountains 1000 39 Cosenza Crati Valley 230 39 Cosenza Catena Costiera Mountains 740 39 Cosenza Catena Costiera Mountains 1200 39 CosenzaCosenza Catena Costiera Mountains 630 Crati Valley 39 110 39 Cosenza Catena Costiera Mountains 150 39 Cosenza Catena Costiera Mountains 700 39 Cosenza Catena Costiera Mountains 530 39 Cosenza Catena Costiera Mountains 560 39 Cosenza Catena Costiera Mountains 800 39 Cosenza Catena Costiera Mountains 890 39 Cosenza Catena Costiera Mountains 1000 39 Cosenza Crati Valley 140 39 Cosenza Catena Costiera Mountains 1190 39 Cosenza Ionian Coast 70 39 Cosenza Catena Costiera Mountains 300 39 Cosenza Catena Costiera Mountains 780 39 Cosenza Catena Costiera Mountains 400 39 Catanzaro Ionian Coast 40 38 Reggio Calabria Aspromonte Mountains 485 38 Reggio Calabria Ionian Coast 2 37 Reggio Calabria Ionian Coast 110 38 Reggio Calabria Aspromonte Mountains 1400 38 Reggio Calabria Aspromonte Mountains 1045 38 Administrative Province Territorial Unit Altitude (m a.s.l.) Latitude Longitude ı ` Lago Lago Lago Lago Lago Lago Rende Malito Malito Malito Belsito Stallet San Fili Cardeto Crotone Cosenza Caulonia Grimaldi Grimaldi Cittanova Mendicino Laurignano Laurignano Municipality Aiello Calabro (or nearest locality) TerranovadaSibari TerranovadaSibari Brancaleone Marina Roccaforte del Greco Locality Cittanova Lago di Tarsia Potame Contrada Salerno Passo dello Scalone Cozzo Cervello Tessano Fiera di San Vito Giardini del Signore Caselle Fiume Licetto Torrente Brittone Cozzo di Monte Caulonia Monte Cocuzzo Rancilla Torrente Menta Mendicino Pucchiello San Fili Capo Colonna Acquafredda Scannelle Cariati Ponte Nuovo Passo Crocetta Contrada Manche Cozzo Caselle TerranovadaSibari Monte Serratore Casino Feraudo Carolei Brancaleone Marina Fiume Jassa Iassa Arcavacata Fontana del Conte Cosenza Monte Ulis Petrarizzo Copanello Laurignano 4 Dataset Papers in Science E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 11 14 31 13 11 12 14 21 22 23 53 55 32 02 30 01 38 57 49 49 25 22 30 54 40 56 35 37 58 38 57 46 13 07 29 50 45 45 20 46 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 11 12 32 01 33 12 12 45 12 51 57 22 17 47 13 18 16 10 18 14 52 46 23 23 01 55 24 33 45 33 55 59 09 50 47 04 54 54 45 54 ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ N15 N16 N16 N16 N16 N16 N16 N16 N15 N16 N16 N16 N16 N16 N16 N16 N15 N16 N16 N16 N16 N16 N16 N15 N16 N16 N16 N16 N15 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 17 01 51 01 18 38 53 37 05 34 55 39 39 23 59 22 27 38 20 49 00 36 35 47 48 23 46 39 02 41 38 46 07 50 04 09 47 36 42 30 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 15 55 51 54 14 10 36 14 33 40 46 52 53 22 53 55 47 53 52 50 45 33 26 27 26 07 34 47 54 45 37 49 06 44 08 48 54 44 49 06 ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ Table 1: Continued. Crotone Marchesato Area 630 39 Crotone Marchesato Area 280 39 Crotone Marchesato Area 310 39 Crotone Marchesato Area 115 39 Crotone Marchesato Area 285 39 Crotone Marchesato Area 350 39 Crotone Marchesato Area 280 39 Cosenza Ionian Coast 90 39 Cosenza Ionian Coast 5 39 Cosenza Pollino-Orsomarso Mountains 1760 39 Cosenza Pollino-Orsomarso Mountains 1850 39 Cosenza Pollino-Orsomarso Mountains 190 39 Cosenza Pollino-Orsomarso Mountains 2100 39 Cosenza Pollino-Orsomarso Mountains 1000 39 Cosenza Pollino-Orsomarso Mountains 1600 39 Cosenza Pollino-Orsomarso Mountains 1300 39 Cosenza Pollino-Orsomarso Mountains 400 39 Cosenza Pollino-Orsomarso Mountains 1850 39 Cosenza Pollino-Orsomarso Mountains 770 39 Cosenza Pollino-Orsomarso Mountains 2267 39 Cosenza Ionian Coast 3 39 Cosenza Pollino-Orsomarso Mountains 1800 39 Cosenza Pollino-Orsomarso Mountains 120 39 Cosenza Pollino-Orsomarso Mountains 1200 39 CosenzaCosenza Pollino-Orsomarso Mountains Pollino-Orsomarso Mountains 750 2200 39 39 Cosenza Pollino-Orsomarso Mountains 180 39 Cosenza Pollino-Orsomarso Mountains 330 39 Cosenza Ionian Coast 65 39 Catanzaro Ionian Coast 370 38 Catanzaro Ionian Coast 360 38 Catanzaro Ionian Coast 120 38 Catanzaro Ionian Coast 100 38 Catanzaro Ionian Coast 190 38 ViboValentia SerreMountains 700 38 ViboValentia SerreMountains 400 39 Vibo ValentiaVibo Valentia Serre Mountains Serre Mountains 1000 1000 38 38 Reggio Calabria Ionian Coast 150 38 Reggio Calabria Serre Mountains 450 38 Administrative Province Territorial Unit Altitude (m a.s.l.) Latitude Longitude ı ı ı ` ` ` Civita Civita Crosia Crosia Stalett Stalett Stalett Cerenzia Squillace Caulonia Caulonia Catanzaro Papasidero Orsomarso Orsomarso Orsomarso Orsomarso Brognaturo Castrovillari Castrovillari Castrovillari Castrovillari Municipality Nardodipace Nardodipace Morano Calabro Morano Calabro Morano Calabro (or nearest locality) San Lorenzo Bellizzi San Nicola da Crissa ı ` Locality Fiumara Trionto Mirto San Nicola La Calvia Cozzo del Pellegrino Papasidero Serra del Prete Cerenzia Campo Tenese San Todaro Stalett Fagosa Monte Palanuda Civita Piani del Pollino Petrosa San Mauro Marchesato Serra Dolcedorme San Nicola da Crissa Gattarella Grave Grubbo Campoli Macchia della Bura Strange Squillace Bosco Pollinello Santa Maria del Mare Vetere Presso Grotta del Palombaro Orsomarso Santa Severina Altilia Scandale Gagliano Timpa di San Lorenzo Monte Moschereto Monte Pollino Fiume Argentino Castrovillari Lacina Nardodipace Dataset Papers in Science 5 E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 23 11 17 19 15 14 14 41 50 32 58 03 54 02 37 01 05 29 󸀠 54 49 50 56 22 08 09 24 04 56 46 05 04 53 22 43 02 39 07 50 42 56 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 25 33 19 17 25 17 31 18 25 18 18 30 27 17 15 21 22 29 35 35 33 28 32 35 22 27 23 22 25 36 36 22 22 ∘ 34 23 24 24 24 28 44 ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 N16 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 19 12 53 16 16 02 53 52 57 29 50 13 48 19 49 07 03 22 50 43 20 24 44 47 56 49 06 40 09 20 22 56 50 54 54 48 06 40 37 27 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 11 14 11 10 33 23 25 10 19 14 10 10 09 16 10 10 29 29 32 23 22 22 25 08 06 27 03 05 29 07 25 24 04 05 06 06 20 09 06 09 ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ Table 1: Continued. Cosenza Sila Mountains 1630 39 Cosenza Sila Mountains 910 39 Cosenza Sila Mountains 1120 39 Cosenza Sila Mountains 935 39 Cosenza Sila Mountains 1050 39 Cosenza Sila Mountains 780 39 Cosenza Sila Mountains 1320 39 Cosenza Sila Mountains 960 39 Cosenza Sila Mountains 750 39 Cosenza Sila Mountains 1020 39 Cosenza Sila Mountains 890 39 Cosenza Sila Mountains 740 39 Cosenza Sila Mountains 680 39 Cosenza Sila Mountains 1540 39 Cosenza Sila Mountains 505 39 Cosenza Sila Mountains 530 39 Cosenza Sila Mountains 734 39 Cosenza Sila Mountains 180 39 Cosenza Sila Mountains 570 39 Cosenza Sila Mountains 1215 39 Cosenza Sila Mountains 1160 39 Cosenza Sila Mountains 730 39 Cosenza Sila Mountains 1290 39 Cosenza Sila Mountains 1000 39 Cosenza Sila Mountains 550 39 Cosenza Sila Mountains 790 39 Cosenza Sila Mountains 1300 39 Cosenza Sila MountainsCosenza 1550 Sila Mountains 39 1150 39 Cosenza Sila Mountains 590 39 Cosenza Sila Mountains 1100 39 Cosenza Sila Mountains 1620 39 Cosenza Sila Mountains 1250 39 Cosenza Sila Mountains 1160 39 Cosenza Sila Mountains 1230 39 Cosenza Sila Mountains 550 39 Cosenza Sila Mountains 400 39 Catanzaro Sila Mountains 900 39 ViboValentia SerreMountains 850 38 Reggio Calabria Serre Mountains 420 38 Administrative Province Territorial Unit Altitude (m a.s.l.) Latitude Longitude Acri Marzi Marzi Lorica Trenta Parenti Parenti Parenti Parenti Bianchi Bianchi Rossano Rogliano Rogliano Rogliano Caulonia Colosimi Longobucco Longobucco Longobucco Longobucco Longobucco Pedivigliano Municipality Serra San Bruno Soveria Mannelli Donnici Inferiore Spezzano della Sila (or nearest locality) Camigliatello Silano Camigliatello Silano Santo Stefano di Rogliano Locality Serra San Bruno Colle dell’Esca Ponte della Castagna Mascari Soveria Mannelli Cicciardi Pianoro di Macchialonga Pittarella Monte Colonnina Acri Lago Cecita Confluenza Savuto-Bisirico Marzi Cupone Favali Saliano San Leo Lago Arvo Mauritanella Ponte della Tavoleria Fossiata Morachi Cozzo del Pupatolo Macrocioli Piano del Barone Torrente Savucchia Monte Scuro Colle dei Lupi Bocca di Piazza Coraci Lago Ariamacina Pietra di Pesco Lago Savuto Serra Castagna Versante Sud Monte Gabriele Fosso Cucolo ColdiVura Ursini Trenta Sant’Angelo 6 Dataset Papers in Science E E E E E E E E E E E E E E 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 52 15 03 39 00 20 20 02 47 08 46 45 48 32 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 51 52 02 25 52 00 05 29 53 47 04 30 54 06 ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ N15 N15 N15 N15 N16 N16 N16 N16 N16 N16 N16 N16 N15 N15 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 󸀠󸀠 11 11 12 12 13 18 37 59 49 50 00 55 57 06 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 󸀠 33 53 21 01 29 08 21 40 06 03 40 38 34 44 ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ ∘ Table 1: Continued. Cosenza Sila Mountains 1000 39 Cosenza Coast Tyrrhenian 10 39 Cosenza Coast Tyrrhenian 90 39 Cosenza Sila Mountains 780 39 Cosenza Tyrrhenian Coast 50 39 Cosenza Tyrrhenian Coast 160 39 Cosenza Sila Mountains 1180 39 Cosenza Coast Tyrrhenian 15 39 Cosenza Tyrrhenian Coast 2 39 Cosenza Tyrrhenian Coast 250 39 Catanzaro Tyrrhenian Coast 2 39 Vibo Valentia Tyrrhenian Coast 50 38 Vibo Valentia Tyrrhenian Coast 300 38 ViboValentia TyrrhenianCoast 350 38 Administrative Province Territorial Unit Altitude (m a.s.l.) Latitude Longitude Acri Paola Tropea Bianchi Spilinga Bonifati Amantea Cessaniti Municipality Nocera Terinese Spezzano della Sila (or nearest locality) Locality Trenta Coste Praia a Mare Tropea Foce Fiume Savuto Fiume Abatemarco Vallone Prunillo Paola Valle Capra Valle Ruffa Cittadella del Capo Amantea Monte Pellegrino Cessaniti Dataset Papers in Science 7

Column 4: Carolei Column 1: Family Column 5: Caselle Column 2: Species Column 6: Contrada Manche Column 3: Amantea Column 7: Cozzo Caselle Column 4: Cessaniti Column 8: Cozzo Cervello Column 5: Cittadella del Capo Column 9: Cozzo di Monte Column 6: Fiume Abatemarco Column 10: Fiume Jassa Column 7: Foce Fiume Savuto Column 11: Fiume Licetto Column 8: Monte Pellegrino Column 12: Fontana del Conte Column 9: Paola Column 13: Giardini del Signore Column 10: Praia a Mare Column 14: Iassa Column 11: Sangineto Column 15: Laurignano Column 12: Valle Ruffa Column 16: Mendicino Column 13: Tropea Column 17: Monte Cocuzzo Column 14: Brancaleone Marina Column 18: Monte Serratore Column 15: Capo Colonna Column 19: Passo Crocetta Column 16: Cariati Column 20: Passo dello Scalone Column 17: Casino Feraudo Column 21: Petrarizzo Column 18: Caulonia Column 22: Ponte Nuovo Column 19: Copanello Column 23: Potame Column 20: Fiumara Trionto Column 24: Pucchiello Column 21: Gagliano Column 25: Rancilla Column 22: Gattarella Column 26: San Fili Column 23: Macchia della Bura Column 27: Scannelle Column 24: Mirto Column 28: Tessano Column 25: San Nicola Column 26: Santa Maria del Mare Vetere Column 29: Torrente Brittone Column 27: Squillace Column 28: Stalett`ı Dataset Item 3 (Table). Species list for the different localities Column 29: Strange of the Sila Mountains. Data presented in this table were based on the presence (1) or absence (0) of a butterfly species. Dataset Item 5 (Table). Species list for the different localities Column 1: Family of Marchesato Area (Altilia, Cerenzia, Presso Grotta del Column 2: Species Palombaro, San Mauro Marchesato, Santa Severina, Scandale, Column 3: Acri and Grave Grubbo), Crati Valley (Arcavacata, Contrada Salerni, Cosenza, Fiera di San Vito, Lago di Tarsia, and Terra- . . nova da Sibari), Serre Mountains (Campoli, Lacina, Nardodi- pace, San Todaro, San Nicola da Crissa, Serra San Bruno, and Column 41: Trenta Coste Ursini), and Aspromonte Mountains (Cittanova, Monte Ulis, Column 42: Valle Capra and Torrente Menta). Data presented in this table were based Column 43: Vallone Prunillo on the presence (1) or absence (0) of a butterfly species.

Column 1: Family Dataset Item 4 (Table). Species list for the different localities Column 2: Species of the Tyrrhenian Coast (Amantea, Cessaniti, Cittadella del Column 3: Altilia Capo, Fiume Abatemarco, Foce Fiume Savuto, Monte Pelle- grino, Paola, Praia a Mare, Sangineto, Valle Ruffa, and Tropea) Column 4: Cerenzia and Ionian Coast (Brancaleone Marina, Capo Colonna, Column 5: Presso Grotta del Palombaro Cariati, Casino Feraudo, Caulonia, Copanello, Fiumara Tri- Column 6: San Mauro Marchesato onto, Gagliano, Gattarella, Macchia della Bura, Mirto, San Column 7: Santa Severina Nicola, Santa Maria del Mare Vetere, Squillace, Stalett`ı, and Strange). Data presented in this table were based on the Column 8: Scandale presence (1) or absence (0) of a butterfly species. Column 9: Grave Grubbo 8 Dataset Papers in Science

Column 10: Arcavacata [2]J.K.Hill,C.D.Thomas,R.Foxetal.,“Responsesofbutterflies Column 11: Contrada Salerni to twentieth century climate warming: implications for future ranges,” Proceedings of the Royal Society B: Biological Sciences, Column 12: Cosenza vol. 269, no. 1505, pp. 2163–2171, 2002. Column 13: Fiera di San Vito [3] C. A. M. Van Swaay, P. Nowicki, J. Settele, and A. J. Van Strien, Column 14: Lago di Tarsia “Butterfly monitoring in Europe: methods, applications and Column 15: perspectives,” Biodiversity and Conservation,vol.17,no.14,pp. 3455–3469, 2008. Column 16: Campoli [4]J.Settele,O.Kudrna,A.Harpkeetal.,Climatic Risk Atlas of Column 17: Lacina European Butterflies. BioRisk 1 (Special Issue),Pensoft,Sofia, Column 18: Nardodipace Bulgaria, 2008. [5] S. Scalercio, “On top of a Mediterranean Massif: Climate change Column 19: San Todaro and conservation of orophilous moths at the southern bound- Column 20: San Nicola da Crissa ary of their range (Lepidoptera: Macroheterocera),” European Column 21: Serra San Bruno Journal of Entomology,vol.106,no.2,pp.231–239,2009. [6] A. Minelli, S. Ruffo, and S. La Posta, Checklist Delle Specie Della Column 22: Ursini Fauna Italiana, Calderini, Fascicoli, Bologna, Italy, 1993–1995. Column 23: Cittanova [7] “Checklist and Distribution of the Italian Fauna. 10,000 ter- Column 24: Monte Ulis restrial and inland water species. 2nd and revised edition,” in Column 25: Torrente Menta Memorie Del Museo Civico Di Storia Naturale Di Verona, 2nd Series, Sezione Scienze Della Vita, S. Ruffo and F. Stoch, Eds., vol. 17, 2007. 4. Concluding Remarks [8] E. Balletto, S. Bonelli, and L. Cassulo, “Insecta Lepidoptera Papilionoidea,” in Checklist and Distribution of the Italian This Dataset Paper strongly increases the knowledge on the Fauna. 10,000 Terrestrial and Inland Water Species. 2nd and butterfly fauna of Calabria, the southernmost region of the Revised Edition, S. Ruffo and F. Stoch, Eds., vol. 17 of Memorie ItalianPeninsula,composedof135species[10]. New distri- del Museo Civico di Storia Naturale di Verona, 2nd series, Sezione butional data for 116 species of butterflies are provided, the Scienze della Vita,pp.257–261,2007. 86%ofthewholeregionalfauna.Thepresenceofspecieswas [9] S. Scalercio, “La fauna a Lepidotteri Ropaloceri della Sila recorded for 136 localities, for a total of 815 new distributional Greca (Italia meridionale) (Lepidoptera Hesperioidea e Papil- records. To date, the most data rich paper for this region ionoidea),” in Memorie Della Societa` Entomologica Italiana,vol. provided 745 distributional records for 44 localities [9]. 81, pp. 167–204, 2002. There is a heterogeneous distribution of sampled localities [10] P. Parenzan and F. Porcelli, “I macrolepidotteri italiani. Fauna on the regional territory. In fact, Sila and Catena Costiera Lepidopterorum Italiae (Macrolepidoptera),” Phytophaga,vol. Mountainsappeartobebettersampledthanothers. 15, no. 2005-2006, pp. 5–351, 2007. [11] S. Scalercio, “Nuovi dati di distribuzione dei macrolepidotteri Dataset Availability eteroceri della fauna calabrese (Insecta Lepidoptera),” Bollettino della Societa` Entomologica Italiana,2014. ThedatasetassociatedwiththisDatasetPaperisdedicatedto thepublicdomainusingtheCC0 waiver and is available at http://dx.doi.org/10.1155/2014/176471/dataset.

Disclosure The data presented here were collected by the author during several field trips and during several research activities of theauthorfrom2005to2012.Thedataareunpublishedand represent an important implementation of the knowledge on the butterfly fauna of Italy.

Conflict of Interests The author declares that there is no conflict of interests regarding the publication of this paper.

References

[1]M.S.Warren,J.K.Hill,J.A.Thomasetal.,“Rapidresponses of British butterflies to opposing forces of climate and habitat change,” Nature,vol.414,no.6859,pp.65–69,2001. International Journal of Peptides

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