Marine plant dispersal and connectivity measures differ in their sensitivity to biophysical model parameters
Schlaefer, J.; Carter, A.; Choukroun, S.; Coles, R.; Critchell, K.; Lambrechts, J.; Rasheed, M.; Tol, S.; Grech, A. (2022). Marine plant dispersal and connectivity measures differ in their sensitivity to biophysical model parameters. Environ. Model. Softw. 149: 105313. https://dx.doi.org/10.1016/j.envsoft.2022.105313 In: Environmental Modelling & Software. Elsevier: Oxford. ISSN 1364-8152; e-ISSN 1873-6726, more |  |
| Keywords | | | Author keywords | Biophysical model; Connectivity; Dispersal; Lagrangian particles; Individual based models; Seagrass |
| Authors | | Top | - Schlaefer, J.
- Carter, A.
- Choukroun, S.
| - Coles, R.
- Critchell, K.
- Lambrechts, J., more
| - Rasheed, M.
- Tol, S.
- Grech, A.
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| 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. |
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