Distribution of the meadow lizard in Europe and its realized ecological niche model. Issue 29 (11th August 2018)

• Record Type: Journal Article
• Authors: Ćorović, Jelena; Popović, Miloš; Cogălniceanu, Dan; Carretero, Miguel A.; Crnobrnja-Isailović, Jelka
• Is Part Of: Journal of natural history. Volume 52:Issue 29/30(2018)
• Page Start: 1909
• Page End: 1925
• Publication Date: 2018-08-11
• Subjects: Darevskia praticola -- species range -- habitat suitability model -- species distribution model -- Maxent; Natural history -- Periodicals; 508
• DOI: 10.1080/00222933.2018.1502829
• Languages: English
• ISSNs: 0022-2933

Abstract

ABSTRACT: One of the most interesting but elusive members of the European herpetofauna is the meadow lizard ( Darevskia praticola ). It is a small, ground dwelling, predominantly forest living lacertid, for which many ecological and biological data are still missing. Moreover, at least for the western part of the species range (south-eastern Europe) its distribution and environmental associations are insufficiently known, likely due to difficulties in detection even with intensive field sampling. Here, we complemented the available literature records with our personal observations and explored the effects of environmental factors shaping the species ecological niche and distribution in Europe using the ecological niche modelling approach from Maxent software. The new records of the meadow lizard fill a gap in its known distribution. The most suitable habitats are in central and eastern Serbia, south-western Romania, and central, southern and south-western Bulgaria. Mean temperature of the coldest quarter, vegetation and slope had the strongest effect in defining the meadow lizard's ecological niche. Niche suitability increased with the increase in forest cover and slope, while the temperature showed a bell-shaped response with a rather narrow tolerance range for temperature. Contrary to expectations, precipitation seemed to have no contribution to the species occurrence. Ecological niche model performance increased with a higher resolution of predictor variables despite the lower number of available occurrence records, although the slope variable had a greater predictive power when calculated at a lower resolution. Interestingly, high resolution vegetation variables (30 m) were able to show some level of habitat fragmentation, which likely resulted from deforestation. Overall, our results epitomize the effects of limited sampling on the biogeography inference of elusive species while having significant repercussions on conservation priorities and management of the species.