Abstract
In an era of biodiversity crisis, arthropods have great potential to inform conservation assessment and test hypotheses about community assembly. This is because their relatively narrow geographic distributions and high diversity offer high-resolution data on landscape-scale patterns of biodiversity. However, a major impediment to the more widespread application of arthropod data to a range of scientific and policy questions is the poor state of modern arthropod taxonomy, especially in the tropics. Inventories of spiders and other megadiverse arthropods from tropical forests are dominated by undescribed species. Such studies typically organize their data using morphospecies codes, which make it difficult for data from independent inventories to be compared and combined. To combat this shortcoming, we offer cyberdiversity, an online community-based approach for reconciling results of independent inventory studies where current taxonomic knowledge is incomplete. Participating scientists can upload images and DNA barcode sequences to dedicated databases and submit occurrence data and links to a web site (www.digitalSpiders.org). Taxonomic determinations can be shared with a crowdsourcing comments feature, and researchers can discover specimens of interest available for loan and request aliquots of genomic DNA extract. To demonstrate the value of the cyberdiversity framework, we reconcile data from three rapid structured inventories of spiders conducted in Vietnam with an independent inventory (Doi Inthanon, Thailand) using online image libraries. Species richness and inventory completeness were assessed using non-parametric estimators. Community similarity was evaluated using a novel index based on the Jaccard replacing observed with estimated values to correct for unobserved species. We use a distance-decay framework to demonstrate a rudimentary model of landscape-scale changes in community composition that will become increasingly informative as additional inventories participate. With broader adoption of the cyberdiversity approach, networks of information-sharing taxonomists can more efficiently and effectively address taxonomic impediments while elucidating landscape scale patterns of biodiversity.