Predicting persistence in benthic marine species with complex life cycles: linking dispersal dynamics to redistribution potential and thermal tolerance limits
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Marine communities face continuing and accelerating climate change. Predicting which species will go extinct or persist in future climates requires assessing redistribution potential and tolerance to warming, both of which can depend on dispersal ability. We evaluated biophysical processes that could promote population persistence under changing climatic conditions by (1) promoting poleward dispersal in an Eastern Boundary Current region, where offshore currents flow predominantly equatorward, and (2) increasing the frequency of more thermotolerant phenotypes in marine populations. We paired intensive time-series observations (during 2014 and 2015) of recruitment and thermal tolerance limits for cohorts of marine mussels with simulated larval transport using a high-resolution, 3D coastal circulation model of the northeastern Pacific. We used the modeling results to predict the proportion of individuals in each recruiting cohort that originated from sources south or north of our study site on the USA west coast (45.50°N, 123.95°W) as well as the environmental conditions experienced in the water column. We found that the coastal upwelling index was related to origin of individuals within recruiting cohorts, with poleward recruitment predicted to increase under downwelling conditions. Furthermore, thermal tolerance limits were higher in cohorts predicted to experience higher and more variable temperatures during dispersal. These findings highlight complex links between demographic and physical transport processes as well as the potential for climate-driven changes in wind patterns to indirectly affect species’ abilities to cope with increasing temperatures.
We thank G. Bernatchez, G. McGann, L. Elsberry, M. Bracken, and F. Bracken-Sorte for their assistance with the fieldwork and tolerance limit assays. N. Banas, S. Maurel and B. Wu assisted with coding the particle tracking model. Members of the Sorte and Davis Labs gave helpful feedback on the project and manuscript. Funding was provided by the UCI Data Science Initiative (to LP) and via the Interdisciplinary Innovation Initiative (to KD and CS), with support from the UCI Henry Samueli School of Engineering, Department of Ecology and Evolutionary Biology, and School of Biological Sciences.
Compliance with ethical standards
This study was funded by the University of California, Irvine through the Data Science Initiative (to LP) and the Interdisciplinary Innovation Initiative (to KD and CS), with support from the UCI Henry Samueli School of Engineering, Department of Ecology and Evolutionary Biology, and School of Biological Sciences.
Conflict of interest
All authors declare that they have no conflicts of interest.
All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.
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