title: Speeding up ecological and evolutionary computations in R; essentials of high performance computing for biologists.
abstract: Computation has become a critical component of research in biology. A risk has emerged that computational and programming challenges may limit research scope, depth, and quality. We review various solutions to common computational efficiency problems in ecological and evolutionary research. Our review pulls together material that is currently scattered across many sources and emphasizes those techniques that are especially effective for typical ecological and environmental problems. We demonstrate how straightforward it can be to write efficient code and implement techniques such as profiling or parallel computing. We supply a newly developed R package (aprof) that helps to identify computational bottlenecks in R code and determine whether optimization can be effective. Our review is complemented by a practical set of examples and detailed Supporting Information material (S1-S3 Texts) that demonstrate large improvements in computational speed (ranging from 10.5 times to 14,000 times faster). By improving computational efficiency, biologists can feasibly solve more complex tasks, ask more ambitious questions, and include more sophisticated analyses in their research.
authors: Departments of Experimental Plant Ecology and Animal Ecology & Ecophysiology, Radboud University Nijmegen, Nijmegen, The Netherlands; Program for Applied Ecology, Centre for Tropical Forest Science, Smithsonian Tropical Research Institute, Balboa, Ancón, Panamá, Republic of Panamá
authors: Marco D
authors: MD
authors: Visser
authors: Smithsonian Environmental Research Center, Edgewater, Maryland, United States of America.
authors: Sean M
authors: SM
authors: McMahon
authors: Smithsonian Environmental Research Center, Edgewater, Maryland, United States of America; Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, Connecticut, United States of America.
authors: Cory
authors: C
authors: Merow
authors: Department of Statistics, Iowa State University, Ames, Iowa, United States of America.
authors: Philip M
authors: PM
authors: Dixon
authors: Harvard University, Harvard Forest, Petersham, Massachusetts, United States of America; Bryn Mawr College, Bryn Mawr, Pennsylvania, United States of America.
authors: Sydne
authors: S
authors: Record
authors: Departments of Experimental Plant Ecology and Animal Ecology & Ecophysiology, Radboud University Nijmegen, Nijmegen, The Netherlands.
authors: Eelke
authors: E
authors: Jongejans
mesh_terms: D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D003205:Computing Methodologies; D004463:Ecology / Q000379:methods*; D005828:Genetics, Population / Q000379:methods*; D006801:Humans