Non-additive effects of air and water warming on an intertidal predator–prey interaction
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Climate change alters multiple physical drivers that act concurrently on ecological communities. Evidence suggests widespread non-additive effects between multiple drivers; most of this evidence, however, is based on species-level responses, which is problematic because community responses to environmental change also depend on species interactions. To address this knowledge gap, this study experimentally manipulated two physical drivers and examined the responses of a predator–prey interaction. The two drivers tested are fundamental in intertidal systems: air and water temperatures. The two species were the intertidal dogwhelk, Nucella ostrina, and its barnacle prey, Balanus glandula. The objective was to test alternative hypotheses that air and water warming have additive vs. non-additive effects on the whelk-barnacle interaction. A 14-day mesocosm experiment was conducted in which animals were subjected to one of four temperature treatments: ambient (no temperature manipulation; water 12 °C, air 13 °C), warm water (15 °C), warm air (27 °C), or combined (water 15 °C, air 27 °C). There were two key findings. First, air and water warming non-additively affected interaction strength: warm water mitigated a 35% decrease in mean whelk feeding rate caused by warm air. Second, air warming had contrasting effects on individual growth rates of predator and prey. While whelk growth decreased by ~ 60% in warm air, barnacle growth increased by 47%. These findings suggest that combined air and water warming will benefit barnacle populations more than their whelk predators. This study highlights the value of integrating species performances and interactions to understand how multiple physical drivers may affect community structure.
Emily Carrington and the FHL maintenance crew lent essential equipment. Comments from Jennifer Ruesink, Hilary Hayford, Lauren Buckley, Megan Dethier, Eliza Heery, Alexander Lowe, Ryan Kelly, and two reviewers improved this and an earlier version of this manuscript. Animal collectors, button pressers, and troubleshooters included Fred Ellis, Matt Schlinger, Tom Campbell, Molly Roberts, Dara Yiu, Lyda Harris, Katie Dobkowski, and Sasha Seroy. This work was supported by FHL (Richard and Megumi Strathmann Fellowship and Patricia L. Dudley Fellowship); the University of Washington Department of Biology (Biology-Friday Harbor Labs Award); and the Pacific Northwest Shell Club (Trevor Roberts Award).
Compliance with ethical standards
All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. Animals were collected with permission of Friday Harbor Laboratories.
Conflict of interest
The authors declare no conflict of interest.
- Barnes M (2000) The use of intertidal barnacle shells. In: Oceanography and marine biology an annual review. pp 157–187Google Scholar
- Bertness MD, Schneider DE (1976) temperature relations of puget sound thaids in reference to their intertidal distribution. Veliger 19:47–58Google Scholar
- Faraway JJ (2006) Extending the linear model with R: generalized linear, mixed effects and nonparametric regression models. Chapman & Hall/CRC, LondonGoogle Scholar
- Gunderson AR, Armstrong EJ, Stillman JH (2016) Multiple stressors in a changing world: the need for an improved perspective on physiological responses to the dynamic marine environment. Annu Rev Mar Sci 8:357–378. https://doi.org/10.1146/annurev-marine-122414-033953 CrossRefGoogle Scholar
- Helmuth B, Broitman BR, Blanchette CA, Gilman S, Halpin P, Harley CDG, O’Donnell MJ, Hofmann GE, Menge B, Strickland D (2006b) Mosaic patterns of thermal stress in the rocky intertidal zone: implications for climate change. Ecol Monogr 76:461–479. https://doi.org/10.1890/0012-9615(2006)076[0461:MPOTSI]2.0.CO;2 CrossRefGoogle Scholar
- IPCC (2014) Climate change 2014: synthesis report. In: Core Writing Team, Pachauri RK, Meyer LA (eds) Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change. IPCC, Geneva, p 151Google Scholar
- Kuznetsova A, Brockhoff PB, Christensen RHB (2016) lmerTest: tests in linear mixed effects models. R package version 2.0-32. https://CRAN.R-project.org/package=lmerTest
- Palmer AR (1982) Growth in marine gastropods. A non-destructive technique for independently measuring shell and body weight. Malacologia 23:63–74Google Scholar
- R Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www.R-project.org/
- Russell BD, Harley CDG, Wernberg T, Mieszkowska N, Widdicombe S, Hall-Spencer JM, Connell SD (2012) Predicting ecosystem shifts requires new approaches that integrate the effects of climate change across entire systems. Biol Lett 8:164–166. https://doi.org/10.1098/rsbl.2011.0779 CrossRefPubMedGoogle Scholar
- Sala OE, Chapin FS, Iii Armesto JJ, Berlow E, Bloomfield J, Dirzo R, Huber-Sanwald E, Huenneke LF, Jackson RB, Kinzig A, Leemans R, Lodge DM, Mooney HA, Oesterheld M, Poff NL, Sykes MT, Walker BH, Walker M, Wall DH (2000) Global biodiversity scenarios for the year 2100. Science 287:1770–1774. https://doi.org/10.1126/science.287.5459.1770 CrossRefPubMedGoogle Scholar