A set of R functions for assessing extrapolation in density surface models
Density surface models (DSMs) are established as a method of choice for the analysis of cetacean line transect survey data, and are increasingly used to inform risk assessments in remote marine areas subject to rising anthropogenic impacts. Despite persistent skepticism about the validity of extrapolated models, more and more DSMs are being applied well beyond the boundaries of the study regions where field sampling originally took place. This leads to potentially uncertain and error-prone model predictions that may mislead on-the-ground management interventions and undermine conservation decision-making.
This repo contains user-friendly functions for quantifying, summarising and visualising various forms of extrapolation in multivariate environmental space a priori (ahead of model fitting).
These are designed to assist marine scientists, managers and policy agencies to (i) better interpret density surfaces and their associated uncertainty; (ii) refine model development and selection approaches; and (iii) optimise the allocation of future survey effort by identifying priority knowledge gaps, e.g. by delineating areas where model predictions are the least supported by data.
R functions are available from the model-extrapolation repository on Github. The associated vignette gives a step-by-step guide to conducting extrapolation assessments, based on data from both sperm whales (Physeter macrocephalus) and beaked whales (Ziphiidae spp) in the North Atlantic.
Note: An R package for extrapolation detection in density surface models is currently in development. Check this page for updates.
This code accompanies a technical report entitled ‘From here and now to there and then: Practical recommendations for extrapolating cetacean density surface models to novel conditions’ and is an output from the Living Marine Resources funded DenMod project at the University of St Andrews.
| Prof. Len Thomas | len.thomas@st-andrews.ac.uk |
| Dr. David L. Miller | dlm22@st-andrews.ac.uk |
| Dr. Phil J. Bouchet | pb282@st-andrews.ac.uk |