In recent decades, a lack of available knowledge about the magnitude, identity and distribution of biodiversity has given way to a taxonomic impediment where species are not being described as fast as the rate of extinction. Using Machine Learning methods based on seven different algorithms (LR, CART, KNN, GNB, LDA, SVM and RFC) we have created an automatic identification approach for odonate genera, through images of wing contours. The training population is composed of the collected specimens that have been […]

Read More from Are wing contours good classifiers for automatic identification in Odonata? A view from the Targeted Odonata Wing Digitization (TOWD) project

Species identification and description are two of the basic tasks in taxonomy, commonly known as alpha-taxonomy.

Read More from Species Identification and Description in Dragonflies & Damselflies: Model Organisms for Ecological and Evolutionary Research

The Odonata community has embraced the benefits afforded by the digital age to access specimens, promote and disseminate data, engage with an ever-growing community of enthusiasts, and answer big questions. Global databases offer the capacity to move beyond simple catalogs, link data and data providers, and create a unified and engaged community. There are millions of odonate specimens currently housed in institutional and private collections, with relatively few digitized and/or imaged. This chapter addresses approaches to data capture, including best […]

Read More from Odonata Collections and Databases in Dragonflies & Damselflies: Model Organisms for Ecological and Evolutionary Research

More than 1.2 million distribution records were used to create species distribution models for 402 Palaearctic species of dragonflies and damselflies.

Read More from Diversity of Palaearctic Dragonflies and Damselflies (Odonata)