We investigated possible correlations between climate-related factors and butterfly range restrictions by selecting a study case represented by four populations of Melitaea britomartis, which become ‘simultaneously’ extinct in NW Italy in 1976–1977 without any observable habitat change. To overcome difficulties related to the analysis of past extinctions and hypothesise causal factors, we applied the Optimal Interpolation method, a statistical method used to create a gridded climatological analysis of temperature and precipitation data, to a historical dataset containing all available information on the Italian butterfly fauna. We tested two different hypotheses: (1) the role of climate change, expressed as a general trend in temperature and precipitation data; (2) the role of extreme weather events, expressed as anomalous conditions during the years of extinctions. Our results show that long-term temperature and precipitation data do not present any clear trend at our study site, suggesting that they cannot be involved in the species’ extinction. On the opposite, 1976 and 1977 were climatologically critical for the study area. In particular, 1977 was characterized by the coldest summer in the entire historical dataset (1958–1977), with strong negative temperature anomalies. Moreover, both years experienced unusually many rainy days during spring and summer. The year 1977 in particular, was the wettest within the entire historical dataset. The years of M. britomartis populations’ extinction were characterised by many more cold and rainy days than usual during the species’ flight period. These results allow us to hypothesize a strong component of unfavourable weather in driving populations’ extinction.
Can the extinction of Melitaea britomartis in NW Italy be explained by unfavourable weather? An analysis by Optimal Interpolation
CERRATO, CRISTIANA;BONELLI, Simona;BALLETTO, Emilio
2014-01-01
Abstract
We investigated possible correlations between climate-related factors and butterfly range restrictions by selecting a study case represented by four populations of Melitaea britomartis, which become ‘simultaneously’ extinct in NW Italy in 1976–1977 without any observable habitat change. To overcome difficulties related to the analysis of past extinctions and hypothesise causal factors, we applied the Optimal Interpolation method, a statistical method used to create a gridded climatological analysis of temperature and precipitation data, to a historical dataset containing all available information on the Italian butterfly fauna. We tested two different hypotheses: (1) the role of climate change, expressed as a general trend in temperature and precipitation data; (2) the role of extreme weather events, expressed as anomalous conditions during the years of extinctions. Our results show that long-term temperature and precipitation data do not present any clear trend at our study site, suggesting that they cannot be involved in the species’ extinction. On the opposite, 1976 and 1977 were climatologically critical for the study area. In particular, 1977 was characterized by the coldest summer in the entire historical dataset (1958–1977), with strong negative temperature anomalies. Moreover, both years experienced unusually many rainy days during spring and summer. The year 1977 in particular, was the wettest within the entire historical dataset. The years of M. britomartis populations’ extinction were characterised by many more cold and rainy days than usual during the species’ flight period. These results allow us to hypothesize a strong component of unfavourable weather in driving populations’ extinction.File | Dimensione | Formato | |
---|---|---|---|
Cerrato et al 2014.pdf
Accesso riservato
Descrizione: MS
Tipo di file:
PDF EDITORIALE
Dimensione
1.65 MB
Formato
Adobe PDF
|
1.65 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
BRITOMARTIS.pdf
Open Access dal 11/04/2015
Descrizione: MS
Tipo di file:
POSTPRINT (VERSIONE FINALE DELL’AUTORE)
Dimensione
365.24 kB
Formato
Adobe PDF
|
365.24 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.