Harnessing Deep Learning in Ecology: An Example Predicting Bark Beetle Outbreaks.

ABSTRACT: Addressing current global challenges such as biodiversity loss, global change, and increasing demands for ecosystem services requires improved ecological prediction. Recent increases in data availability, process understanding, and computing power are fostering quantitative approaches in ecology. However, flexible methodological frameworks are needed to utilize these developments towards improved ecological prediction. Deep learning is a rapidly evolving branch of machine learning, yet has received only little attention in ecology to date. It refers to the training of deep neural networks (DNNs), i.e. artificial neural networks consisting of many layers and a large number of neurons. We here provide a reproducible example (including code and data) of designing, training, and applying DNNs

SUBMITTER: Rammer W 

PROVIDER: S-EPMC6827389 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature