Prediction of species distributions is central to diverse applications in ecology, evolution and conservation science. There is now increasing electronic access to vast sets of occurrence records in museums and herbaria all over the world, yet there has been little effective guidance on how best to use this information to model and predict species distributions.
A recent study in the journal Ecography by an international team of researchers now offers the by far most comprehensive model comparison ever made, comparing the performance of 16 methods over 226 species from 6 regions of the world. The study then takes the approach one step further and validates model-based predictions against data collected independently.
Along with well-established modelling methods, the team have explored novel approaches such as machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information that are typical of species occurrence data. The novel methods consistently outperformed more established methods. The results of the study hold great promise for the use of data from the Worlds museums and herbaria and will be invaluable for anyone wanting to analyse species distributions in years to come.
Jane Elith | EurekAlert!
Rutgers-led innovation could spur faster, cheaper, nano-based manufacturing
14.02.2018 | Rutgers University
New study from the University of Halle: How climate change alters plant growth
12.01.2018 | Martin-Luther-Universität Halle-Wittenberg
Animal photoreceptors capture light with photopigments. Researchers from the University of Göttingen have now discovered that these photopigments fulfill an...
On 15 March, the AWI research aeroplane Polar 5 will depart for Greenland. Concentrating on the furthest northeast region of the island, an international team...
The world’s second-largest ice shelf was the destination for a Polarstern expedition that ended in Punta Arenas, Chile on 14th March 2018. Oceanographers from...
At the 2018 ILA Berlin Air Show from April 25–29, the Fraunhofer Institute for Laser Technology ILT is showcasing extreme high-speed Laser Material Deposition (EHLA): A video documents how for metal components that are highly loaded, EHLA has already proved itself as an alternative to hard chrome plating, which is now allowed only under special conditions.
When the EU restricted the use of hexavalent chromium compounds to special applications requiring authorization, the move prompted a rethink in the surface...
At the ILA Berlin, hall 4, booth 202, Fraunhofer FHR will present two radar sensors for navigation support of drones. The sensors are valuable components in the implementation of autonomous flying drones: they function as obstacle detectors to prevent collisions. Radar sensors also operate reliably in restricted visibility, e.g. in foggy or dusty conditions. Due to their ability to measure distances with high precision, the radar sensors can also be used as altimeters when other sources of information such as barometers or GPS are not available or cannot operate optimally.
Drones play an increasingly important role in the area of logistics and services. Well-known logistic companies place great hope in these compact, aerial...
16.03.2018 | Event News
13.03.2018 | Event News
08.03.2018 | Event News
16.03.2018 | Earth Sciences
16.03.2018 | Physics and Astronomy
16.03.2018 | Life Sciences