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Predicting the performance of cosmopolitan species: dynamic energy budget model skill drops across large spatial scales
Individual-based models are increasingly used by marine ecologists to predict species responses to environmental change on a mechanistic basis. Dynamic Energy Budget (DEB) models allow the simulation of physiological processes (maintenance, growth, reproduction) in response to variability in environmental drivers. High levels of computational capacity and remote-sensing technologies provide an opportunity to apply existing DEB models across global spatial scales. To do so, however, we must first test the assumption of stationarity, i.e., that parameter values estimated for populations in one location/time are valid for populations elsewhere. Using a validated DEB model parameterized for the cosmopolitan intertidal mussel Mytilus galloprovincialis, we ran growth simulations for native, Mediterranean Sea, populations and non-native, South African populations. The model performed well for native populations, but overestimated growth for non-native ones. Overestimations suggest that: (1) unaccounted variables may keep the physiological performance of non-native M. galloprovincialis in check, and/or (2) phenotypic plasticity or local adaptation could modulate responses under different environmental conditions. The study shows that stationary mechanistic models that aim to describe dynamics in complex physiological processes should be treated carefully when implemented across large spatial scales. Instead, we suggest placing the necessary effort into identifying the nuances that result in non-stationarity and explicitly accounting for them in geographic-scale mechanistic models.
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File | Pages | Size | Access | |
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Publisher's official version | 13 | 1 Mo | ||
Appendix S1. Mytilus galloprovincialis Dynamic Energy Budget (DEB) parameter values used to perform model simulations | 2 | 139 Ko | ||
Appendix S2. Linear regression coefficients from relationships between satellite-derived sea surface temperature and in situ measurements (data available in Appendix S5) | 1 | 118 Ko | ||
Appendix S3. Linear regression coefficients from relationship between weather station air temperature (www.weatherunderground.com/weather/api) and in situ measurements taken with aerially exposed “rob | 1 | 111 Ko | ||
Appendix S4. Dynamic Energy Budget (DEB) model scrip for Mytilus galloprovincialis | 9 | 179 Ko | ||
Appendix S5. Satellite-derived sea surface temperature and in situ measurements used to estimate submerged mussel body temperature | - | 114 Ko | ||
Appendix S6. Weather station air temperature and in situ “robomussels” measurements used to estimate aerially exposed mussel body temperature | - | 61 Ko | ||
Appendix S7. Site-specific environmental data used to run the DEB models. Columns are: region, site, local time (SAST or CEST), estimated body temperature in water (°C), estimated body temperature in | - | 8 Mo | ||
Author's final draft | 40 | 1 Mo |