Marine plant dispersal and connectivity measures differ in their sensitivity to biophysical model parameters. (March 2022)

• Record Type: Journal Article
• Authors: Schlaefer, Jodie; Carter, Alexandra; Choukroun, Severine; Coles, Robert; Critchell, Kay; Lambrechts, Jonathan; Rasheed, Michael; Tol, Samantha; Grech, Alana
• Is Part Of: Environmental modelling & software. Volume 149(2022)
• Publication Date: 2022-03
• Subjects: Biophysical model -- Connectivity -- Dispersal -- Lagrangian particles -- Individual based models -- Seagrass; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2022.105313
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Biophysical models simulate dispersal and connectivity in marine environments by combining numerical models that represent water circulation with biological parameters that define the attributes of species. The effects of parameters, such as the number of particles released to simulate the trajectories of individual organisms, is potentially large but rarely tested. We present a framework to measure the optimal number of particles required to capture variability in dispersal and connectivity of the marine plants, seagrasses. We found that the number of optimal release particles per element (or grid cell) for dispersal estimates varied with seagrass habitat type, season, and physical parameters of the modelled propagules (i.e., wind drag). Connectivity metrics were comparatively much less sensitive, requiring lower particle numbers to achieve stable results. We provide guidance on important factors to consider when determining the optimal number of particles required to robustly predict dispersal and connectivity in biophysical models of marine plants. Highlights: Biophysical models simulate dispersal and connectivity in marine environments. Effects of model parameters on outputs is potentially large but rarely tested. We assess the optimal number of release particles in a seagrass biophysical model. Connectivity measures require less release particles than dispersal estimates. The disparity highlights the need to tailor sensitivity tests to research questions.