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Understanding opposing predictions of Prochlorococcus in a changing climate
Vincent Bian1, Merrick Cai2, Christopher L Follett3
1Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA.
Nature Communications
|March 16, 2023
Summary
Species distribution models (SDMs) for Prochlorococcus, abundant phytoplankton, show limitations. A two-state model reveals SDMs struggle to predict changes where populations are already high, resolving conflicts with dynamical models.
Area of Science:
- Marine microbial ecology
- Phytoplankton population dynamics
- Climate change impacts on marine ecosystems
Background:
- Species distribution models (SDMs) are widely used for predicting ecological shifts due to climate change.
- For Prochlorococcus, the most abundant marine phytoplankton, existing SDMs conflict with dynamical models regarding future abundance predictions.
- This discrepancy highlights a need to critically evaluate SDM performance across scales.
Purpose of the Study:
- To investigate the reliability of statistically derived species distribution models (SDMs) for Prochlorococcus under changing environmental conditions.
- To resolve the conflict between established SDMs and dynamical models concerning Prochlorococcus abundance predictions.
- To assess the influence of spatial and temporal scales on SDM accuracy.
Main Methods:
- Analysis of SDMs at various spatial-temporal scales to identify drivers of Prochlorococcus abundance.
- Testing the explanatory power of light and temperature variables for temporal fluctuations and spatial transitions.
- Development and validation of a two-state model based on a temperature threshold.
Main Results:
- Light and temperature were found to be insufficient in explaining temporal fluctuations and sharp spatial transitions in Prochlorococcus abundance.
- Significant correlations between temperature changes and population abundance were observed only at very large spatial scales.
- A two-state model incorporating a temperature threshold successfully replicated the original SDM's predictions in surface waters.
Conclusions:
- The original SDM for Prochlorococcus has limited predictive power for areas with already high population densities.
- The study resolves the conflict between statistical and dynamical models by identifying scale-dependent limitations of SDMs.
- It is recommended that SDMs demonstrate efficacy across multiple spatial-temporal scales before being relied upon for predicting changes in dynamic ocean environments.
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