2019
DOI: 10.1111/jbi.13633
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Macroecology in the age of Big Data – Where to go from here?

Abstract: Recent years have seen an exponential increase in the amount of data available in all sciences and application domains. Macroecology is part of this “Big Data” trend, with a strong rise in the volume of data that we are using for our research. Here, we summarize the most recent developments in macroecology in the age of Big Data that were presented at the 2018 annual meeting of the Specialist Group Macroecology of the Ecological Society of Germany, Austria and Switzerland (GfÖ). Supported by computational adva… Show more

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Cited by 117 publications
(101 citation statements)
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“…Today, SDMs present the most widely used modelling tool for forecasting global change impacts on biodiversity (Guisan et al 2013, Ehrlén and Morris 2015, Ferrier et al 2016. This boom in SDM studies is likely related to the increasing availability of digital data (Jetz et al 2012, Franklin et al 2017, Wüest et al 2020 and easy-to-use software packages (Phillips et al 2006, Thuiller et al 2009, Brown 2014, Naimi and Araújo 2016, Golding et al 2018, Kass et al 2018 accompanied by detailed guides, manuals and textbooks (Elith et al 2008, Merow et al 2013, Guisan et al 2017. Despite their widespread use, SDM methods and results are often limited in their reproducibility because of a lack of reporting standards (Rodríguez-Castañeda et al 2012, Araújo et al 2019, Feng et al 2019, Hao et al 2019.…”
Section: Introductionmentioning
confidence: 99%
“…Today, SDMs present the most widely used modelling tool for forecasting global change impacts on biodiversity (Guisan et al 2013, Ehrlén and Morris 2015, Ferrier et al 2016. This boom in SDM studies is likely related to the increasing availability of digital data (Jetz et al 2012, Franklin et al 2017, Wüest et al 2020 and easy-to-use software packages (Phillips et al 2006, Thuiller et al 2009, Brown 2014, Naimi and Araújo 2016, Golding et al 2018, Kass et al 2018 accompanied by detailed guides, manuals and textbooks (Elith et al 2008, Merow et al 2013, Guisan et al 2017. Despite their widespread use, SDM methods and results are often limited in their reproducibility because of a lack of reporting standards (Rodríguez-Castañeda et al 2012, Araújo et al 2019, Feng et al 2019, Hao et al 2019.…”
Section: Introductionmentioning
confidence: 99%
“…Conservation research is restricted by the unavailability of data. Growing conservation knowledge evolves from an increasing quality and quantity of data (Wüest et al 2019).…”
Section: Next Generation Conservation Biogeographymentioning
confidence: 99%
“…Open information systems, data repositories, databases and data sets play a central role to foster global conservation research by the coming generations of conservation biogeographers. Varying quality, bias, noise and uncertainty within data require meta-data in order to efficiently harvest and analyse the data (Wohner et al 2019, Wüest et al 2019. Open-source software advances data analyses, their documentation, transparency and reproduction.…”
Section: Next Generation Conservation Biogeographymentioning
confidence: 99%
“…Publicly available data on species occurrences have some limitations [31,32]. Species occurrence data represent presence data and stem from different sources with varying monitoring efforts.…”
Section: Regional Species Pool: Use Of Geo-referenced Species Occurrementioning
confidence: 99%