Computational Methods revolutionized life sciences a generation ago, but a large number of ecologists are yet to appreciate this shift, resulting in a gap between cultural and conceptual changes that needs bridging by funding bodies and academic institutions. Skilled computational ecologists are no longer service providers, but leaders of cutting-edge programs reflected in the large volume of data being generated and processed in the course of modern ecological research, both in the lab and in the field. Majority of ecology scholars across the globe, and specially in developing nations, are exceptional and dedicated, and good at fundamental knowledge, yet unable to make a cut in the real world after completing their degrees, often due to lack of basic computational skills. Timely training programs can help bridge this gap so that traditional ecologists may increase the probability of groundbreaking discoveries. The present CoronaVirus Pandemic emphasizes the role of trainers more than ever before, towards sustaining a zeal for research, and capacity building while working from home.
Results/Conclusions
In this talk, I shall present some of the algorithms we have developed over the past decade in ecology using simple coding methods and deploying these to make scientific breakthroughs, in areas like decision support systems, simulating extinction cascades, perturbation of species interaction networks and deep learning the phytochemical landscape. I will also share our experience with capacity building and training of youth in these methods by using open source tools like R, Cytoscape and NexCade. We have been training researchers in India and the U.K, and lately, we have begun a new series of online tutorials called "Protocols From Home" to help students and researchers gain new computational skills during the COVID lockdown. Sharing our experience, as well as challenges and opportunities with other trainers will enable global expansion of the ecology training network, and may pave the way to bring the power of coding to each and every ecologist.