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Tipping points, thresholds and the keystone role of physiology in marine climate change research
Monaco, C.J.; Helmuth, B. (2011). Tipping points, thresholds and the keystone role of physiology in marine climate change research. Adv. Mar. Biol. 60: 123-160.
In: Advances in Marine Biology. Academic Press: London, New York. ISSN 0065-2881; e-ISSN 2162-5875, meer
Peer reviewed article  

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  • Monaco, C.J.
  • Helmuth, B.

    The ongoing and future effects of global climate change on natural and human-managed ecosystems have led to a renewed interest in the concept of ecological thresholds or tipping points. While generalizations such as pole-ward range shifts serve as a useful heuristic framework to understand the overall ecological impacts of climate change, sophisticated approaches to management require spatially and temporally explicit predictions that move beyond these oversimplified models. Most approaches to studying ecological thresholds in marine ecosystems tend to focus on populations, or on non-linearities in physical drivers. Here we argue that many of the observed thresholds observed at community and ecosystem levels can potentially be explained as the product of non-linearities that occur at three scales: (a) the mechanisms by which individual organisms interact with their ambient habitat, (b) the non-linear relationship between organismal physiological performance and variables such as body temperature and (c) the indirect effects of physiological stress on species interactions such as competition and predation. We explore examples at each of these scales in detail and explain why a failure to consider these non-linearities - many of which can be counterintuitive - can lead to Type II errors (a failure to predict significant ecological responses to climate change). Specifically, we examine why ecological thresholds can occur well before concomitant thresholds in physical drivers are observed, i.e. how even small linear changes in the physical environment can lead to ecological tipping points. We advocate for an integrated framework that combines biophysical, ecological and physiological methods to generate hypotheses that can be tested using experimental manipulation as well as hindcasting and nowcasting of observed change, on a spatially and temporally explicit basis.

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