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Published on: April 6, 2019
Cave morphology, microclimate and abundance of five cave predators from the Monte Albo (Sardinia, Italy)
Enrico Lunghi1,2,3, Claudia Corti2, Manuela Mulargia4
1Key Laboratory of the Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China Key Laboratory of the Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences Beijing China.
Background:
Systematic data collection on species and their exploited environments is of key importance for conservation studies. Within the less-known environments, the subterranean ones are neither easy to be studied, nor to be explored. Subterranean environments house a wide number of specialised organisms, many of which show high sensitivity to habitat alteration. Despite the undeniable importance to monitor the status of the subterranean biodiversity, standardised methodologies to record biotic and abiotic data in these environments are still not fully adopted, impeding therefore the creation of comparable datasets useful for monitoring the ecological condition in the subterranean environments and for conservation assessment of related species.
New Information:
In this work we describe a methodology allowing the collection of standardised abiotic and biotic data in subterranean environments. To show this, we created a large dataset including information on environmental features (morphology and microclimate) and abundance of five predators (one salamander, three spiders and one snail) occurring in seven caves of the Monte Albo (Sardinia, Italy), an important biodiversity hotspot. We performed 77 surveys on 5,748 m2 of subterranean environments througout a year, recording 1,695 observations of the five cave predators. The fine-scale data collection adopted in our methodology allowed us to record detailed information related to both morphology and microclimate of the cave inner environment. Furthermore, this method allows us to account for species-imperfect detection when recording presence/abundance data.
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