Abstract
Species occurrence data provide crucial information for biodiversity studies in the current context of global environmental changes. Such studies often rely on a limited number of occurrence data collected in the field and on pseudo-absences arbitrarily chosen within the study area, which reduces the value of these studies. To overcome this issue, we propose an alternative method of prospection using geo-located street view imagery (SVI). Following a standardised protocol of virtual prospection using both vertical (aerial photographs) and horizontal (SVI) perceptions, we have surveyed 1097 randomly selected cells across Spain (0.1x0.1 degree, i.e. 20% of Spain) for the presence of Arundo donax L. (Poaceae). In total we have detected A. donax in 345 cells, thus substantially expanding beyond the now two-centuries-old field-derived record, which described A. donax only 216 cells. Among the field occurrence cells, 81.1% were confirmed by SVI prospection to be consistent with species presence. In addition, we recorded, by SVI prospection, 752 absences, i.e. cells where A. donax was considered absent. We have also compared the outcomes of climatic niche modeling based on SVI data against those based on field data. Using generalized linear models fitted with bioclimatic predictors, we have found SVI data to provide far more compelling results in terms of niche modeling than does field data as classically used in SDM. This original, cost- and time-effective method provides the means to accurately locate highly visible taxa, reinforce absence data, and predict species distribution without long and expensive in situ prospection. At this time, the majority of available SVI data is restricted to human-disturbed environments that have road networks. However, SVI is becoming increasingly available in natural areas, which means the technique has considerable potential to become an important factor in future biodiversity studies.
Highlights
IntroductionSpecies occurrence data represent basic but indispensable information for research in conservation biology, biogeography, ecology, and evolution [1]
Species occurrence data represent basic but indispensable information for research in conservation biology, biogeography, ecology, and evolution [1]. These data provide guidance for sampling design, but they provide a basis for planning geographical areas for conservation policies [2], for studying spatial dynamics and risks of invasive species [3], or for defining biogeographical patterns according to environmental variables [4]
The 216 occurrences of A. donax derived from the field data were mainly located along the Mediterranean coast, from the coastline to about 100 km inland, with a deeper continental occurrence along the Ebro alluvial plain (NE Spain; Fig 2A)
Summary
Species occurrence data represent basic but indispensable information for research in conservation biology, biogeography, ecology, and evolution [1]. These data provide guidance for sampling design, but they provide a basis for planning geographical areas for conservation policies [2], for studying spatial dynamics and risks of invasive species [3], or for defining biogeographical patterns according to environmental variables [4]. Over the last 20 years, occurrence data have been increasingly valued with the development of species distribution models (SDM) as predictive tools in the context of global change [5, 6]. The main limitation of such large-scale data lies in the lack of information about the spatial sampling design and effort, and the unavailability of supported absence data
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