Over the last two decades there has been an exponential increase in the use of correlative species distribution models (SDMs) to address a variety of topics in ecology, biogeography, evolution, and conservation biology. Conversely, the use of these statistical methods to study the potential distribution of subterranean organisms has lagged behind, relative to their above-ground (epigean) counterparts. The reason for this is possibly related to a number of peculiarities of subterranean systems, which pose important limits, but also opportunities, for these correlative models. The aim of this forum is to explore the caveats that need to be made when generalizing these statistical techniques to caves and other subterranean habitats. We focus on the typical bias in spatial datasets of cave-dwelling species, and provide advice for selecting the model calibration area. In parallel, we discuss the potential use of different large scale surface variables to represent the subterranean condition. A more widespread adoption of these statistical techniques in subterranean biology is highly attractive and has great potential in broadening our knowledge on a variety of ecological topics, especially in the fields of climate change and biodiversity conservation. Their use would especially benefit the study of the biogeographic patterns of subterranean fauna and the impact of past and future climate change on subterranean ecosystems.

Applying species distribution models to caves and other subterranean habitats

Stefano Mammola;
2018-01-01

Abstract

Over the last two decades there has been an exponential increase in the use of correlative species distribution models (SDMs) to address a variety of topics in ecology, biogeography, evolution, and conservation biology. Conversely, the use of these statistical methods to study the potential distribution of subterranean organisms has lagged behind, relative to their above-ground (epigean) counterparts. The reason for this is possibly related to a number of peculiarities of subterranean systems, which pose important limits, but also opportunities, for these correlative models. The aim of this forum is to explore the caveats that need to be made when generalizing these statistical techniques to caves and other subterranean habitats. We focus on the typical bias in spatial datasets of cave-dwelling species, and provide advice for selecting the model calibration area. In parallel, we discuss the potential use of different large scale surface variables to represent the subterranean condition. A more widespread adoption of these statistical techniques in subterranean biology is highly attractive and has great potential in broadening our knowledge on a variety of ecological topics, especially in the fields of climate change and biodiversity conservation. Their use would especially benefit the study of the biogeographic patterns of subterranean fauna and the impact of past and future climate change on subterranean ecosystems.
2018
41
1194
1208
Mammola, Stefano; Boris, Leroy
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1653469
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