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Early warning signals detect critical impacts of experimental warming

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ABSTRACT

Earth's surface temperatures are projected to increase by ~1–4°C over the next century, threatening the future of global biodiversity and ecosystem stability. While this has fueled major progress in the field of physiological trait responses to warming, it is currently unclear whether routine population monitoring data can be used to predict temperature‐induced population collapse. Here, we integrate trait performance theory with that of critical tipping points to test whether early warning signals can be reliably used to anticipate thermally induced extinction events. We find that a model parameterized by experimental growth rates exhibits critical slowing down in the vicinity of an experimentally tested critical threshold, suggesting that dynamical early warning signals may be useful in detecting the potentially precipitous onset of population collapse due to global climate change.

No MeSH data available.


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Critical tipping point and example thermal performance curves. Hypothetical depiction of a critical tipping point and thermal performance curves with temperature warming. (A) The critical tipping point, or transcritical bifurcation, exists where the stabilities of two different fixed points switch, such that a stable equilibrium (N*) of a positive density is replaced by a stable equilibrium of zero density. Arrows indicate the direction of nearby trajectories, where they are attracted to stable (solid lines) equilibria and repelled by unstable (dashed lines) equilibria. Here, as demonstrated in plot (B) the critical tipping point is reached when rT < 0, which is determined by the temperature sensitivity of this key parameter, r (C) (but note that a critical tipping point can occur with any change in conditions that affects underlying parameters). When rT ≤ 0, the population cannot recover from a perturbation, and beyond this point, the carrying capacity is undefined and extinction is inevitable. The gray boxes in (A) and (C) indicate the conditions – after a threshold has been breached – where populations can no longer persist.
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ece32339-fig-0001: Critical tipping point and example thermal performance curves. Hypothetical depiction of a critical tipping point and thermal performance curves with temperature warming. (A) The critical tipping point, or transcritical bifurcation, exists where the stabilities of two different fixed points switch, such that a stable equilibrium (N*) of a positive density is replaced by a stable equilibrium of zero density. Arrows indicate the direction of nearby trajectories, where they are attracted to stable (solid lines) equilibria and repelled by unstable (dashed lines) equilibria. Here, as demonstrated in plot (B) the critical tipping point is reached when rT < 0, which is determined by the temperature sensitivity of this key parameter, r (C) (but note that a critical tipping point can occur with any change in conditions that affects underlying parameters). When rT ≤ 0, the population cannot recover from a perturbation, and beyond this point, the carrying capacity is undefined and extinction is inevitable. The gray boxes in (A) and (C) indicate the conditions – after a threshold has been breached – where populations can no longer persist.

Mentions: Early warning signals use a common dynamical property of equilibrium systems known as critical slowing down (Boettiger and Hastings 2013), whereby a system experiences a weak compensatory recovery toward equilibrium following perturbation. This characteristic is often indicative of an approach toward a local bifurcation, or critical tipping point that represents the boundary zone between population persistence and extinction (Fig. 1) (Wissel 1984; Hugget 2005; Scheffer et al. 2009; Drake and Griffen 2010; Veraart et al. 2012; Boettiger and Hastings 2013). Critical slowing down is accompanied by other related statistical signatures of an impending species loss or ecosystem collapse, namely increased degree of temporal autocorrelation and increasing variance in population densities over time (Dakos et al. 2012; Krkosek and Drake 2014). Delayed recovery yields greater similarities in population abundance between adjacent time steps (increased autocorrelation) and additive disturbance effects that may cause the population to deviate further from mean densities following perturbation (i.e., variance increases if the population is disturbed multiple times before it has recovered to its preperturbation state). Although the early warning signal approach has become more widespread (Drake and Griffen 2010; Carpenter et al. 2011; Veraart et al. 2012), it has not yet been used for predicting climate‐induced tipping points in populations, which one would predict due to the temperature dependence of key population traits and the perilous state of global warming (Brown et al. 2004; Englund et al. 2011).


Early warning signals detect critical impacts of experimental warming
Critical tipping point and example thermal performance curves. Hypothetical depiction of a critical tipping point and thermal performance curves with temperature warming. (A) The critical tipping point, or transcritical bifurcation, exists where the stabilities of two different fixed points switch, such that a stable equilibrium (N*) of a positive density is replaced by a stable equilibrium of zero density. Arrows indicate the direction of nearby trajectories, where they are attracted to stable (solid lines) equilibria and repelled by unstable (dashed lines) equilibria. Here, as demonstrated in plot (B) the critical tipping point is reached when rT < 0, which is determined by the temperature sensitivity of this key parameter, r (C) (but note that a critical tipping point can occur with any change in conditions that affects underlying parameters). When rT ≤ 0, the population cannot recover from a perturbation, and beyond this point, the carrying capacity is undefined and extinction is inevitable. The gray boxes in (A) and (C) indicate the conditions – after a threshold has been breached – where populations can no longer persist.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC5016634&req=5

ece32339-fig-0001: Critical tipping point and example thermal performance curves. Hypothetical depiction of a critical tipping point and thermal performance curves with temperature warming. (A) The critical tipping point, or transcritical bifurcation, exists where the stabilities of two different fixed points switch, such that a stable equilibrium (N*) of a positive density is replaced by a stable equilibrium of zero density. Arrows indicate the direction of nearby trajectories, where they are attracted to stable (solid lines) equilibria and repelled by unstable (dashed lines) equilibria. Here, as demonstrated in plot (B) the critical tipping point is reached when rT < 0, which is determined by the temperature sensitivity of this key parameter, r (C) (but note that a critical tipping point can occur with any change in conditions that affects underlying parameters). When rT ≤ 0, the population cannot recover from a perturbation, and beyond this point, the carrying capacity is undefined and extinction is inevitable. The gray boxes in (A) and (C) indicate the conditions – after a threshold has been breached – where populations can no longer persist.
Mentions: Early warning signals use a common dynamical property of equilibrium systems known as critical slowing down (Boettiger and Hastings 2013), whereby a system experiences a weak compensatory recovery toward equilibrium following perturbation. This characteristic is often indicative of an approach toward a local bifurcation, or critical tipping point that represents the boundary zone between population persistence and extinction (Fig. 1) (Wissel 1984; Hugget 2005; Scheffer et al. 2009; Drake and Griffen 2010; Veraart et al. 2012; Boettiger and Hastings 2013). Critical slowing down is accompanied by other related statistical signatures of an impending species loss or ecosystem collapse, namely increased degree of temporal autocorrelation and increasing variance in population densities over time (Dakos et al. 2012; Krkosek and Drake 2014). Delayed recovery yields greater similarities in population abundance between adjacent time steps (increased autocorrelation) and additive disturbance effects that may cause the population to deviate further from mean densities following perturbation (i.e., variance increases if the population is disturbed multiple times before it has recovered to its preperturbation state). Although the early warning signal approach has become more widespread (Drake and Griffen 2010; Carpenter et al. 2011; Veraart et al. 2012), it has not yet been used for predicting climate‐induced tipping points in populations, which one would predict due to the temperature dependence of key population traits and the perilous state of global warming (Brown et al. 2004; Englund et al. 2011).

View Article: PubMed Central - PubMed

ABSTRACT

Earth's surface temperatures are projected to increase by ~1&ndash;4&deg;C over the next century, threatening the future of global biodiversity and ecosystem stability. While this has fueled major progress in the field of physiological trait responses to warming, it is currently unclear whether routine population monitoring data can be used to predict temperature&#8208;induced population collapse. Here, we integrate trait performance theory with that of critical tipping points to test whether early warning signals can be reliably used to anticipate thermally induced extinction events. We find that a model parameterized by experimental growth rates exhibits critical slowing down in the vicinity of an experimentally tested critical threshold, suggesting that dynamical early warning signals may be useful in detecting the potentially precipitous onset of population collapse due to global climate change.

No MeSH data available.


Related in: MedlinePlus