Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.
School of Biological Sciences, University of Bristol, Bristol, UK.
J Anim Ecol. 2020 Feb;89(2):436-448. doi: 10.1111/1365-2656.13097. Epub 2019 Sep 18.
Environmental change can impact the stability of ecological systems and cause rapid declines in populations. Abundance-based early warning signals have been shown to precede such declines, but detection prior to wild population collapses has had limited success, leading to the development of warning signals based on shifts in distribution of fitness-related traits such as body size. The dynamics of population abundances and traits in response to external environmental perturbations are controlled by a range of underlying factors such as reproductive rate, genetic variation and plasticity. However, it remains unknown how such ecological and evolutionary factors affect the stability landscape of populations and the detectability of abundance and trait-based early warning signals. Here, we apply a trait-based demographic approach and investigate both trait and population dynamics in response to gradual and increasing changes in the environment. We explore a range of ecological and evolutionary constraints under which stability of a population may be affected. We show both analytically and with simulations that strength of abundance- and trait-based warning signals are affected by ecological and evolutionary factors. Finally, we show that combining trait- and abundance-based information improves our ability to predict population declines. Our study suggests that the inclusion of trait dynamic information alongside generic warning signals should provide more accurate forecasts of the future state of biological systems.
环境变化会影响生态系统的稳定性,并导致种群数量的迅速下降。基于丰度的早期预警信号已被证明先于这种下降,但在野生种群崩溃之前的检测一直收效甚微,这导致了基于与体型等与适应性相关特征的分布变化的预警信号的发展。种群丰度和特征对外部环境扰动的响应动力学受到一系列潜在因素的控制,如繁殖率、遗传变异和可塑性。然而,目前尚不清楚这些生态和进化因素如何影响种群的稳定性景观以及丰度和基于特征的早期预警信号的可检测性。在这里,我们应用了一种基于特征的人口统计方法,研究了特征和人口动态对环境逐渐和持续变化的响应。我们探讨了一系列生态和进化限制因素,在这些因素下,种群的稳定性可能会受到影响。我们通过分析和模拟表明,丰度和特征预警信号的强度受到生态和进化因素的影响。最后,我们表明,结合特征和丰度信息可以提高我们预测种群下降的能力。我们的研究表明,在通用预警信号之外,包括特征动态信息应该可以更准确地预测生物系统的未来状态。