Accounting for sources of uncertainty when forecasting population responses to climate change
Accounting for sources of uncertainty when forecasting population responses to climate change
复制标题
预测人口对气候变化的反应时考虑不确定性来源
DOI：
10.1111/1365-2656.13443
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发表时间：
2021
影响因子：
4.8
通讯作者：
Zipkin, Elise F.
中科院分区：
文献类型：
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作者：
Zylstra, Erin R.;Zipkin, Elise F.
焦点：Jaatinen, K.、Westerbom, M.、Norkko, A.、Mustonen, O. 和 Koons, D. N. (2021)。蓝贻贝依赖于密度的种群调节可能会加剧气候变化的不利影响。动物生态学杂志，90, 562–573，https://doi.org/10.1111/1365‐2656.13377。受威胁物种的保护策略越来越依赖于对人口对气候变化反应的预测。为了使此类预测准确，必须考虑多种不确定性来源，包括与未来气候情景预测相关的不确定性以及与用于描述人口动态的模型相关的不确定性。虽然许多种群预测纳入了非生物效应中的参数不确定性和与无法解释的时间变化相关的过程方差，但大多数预测忽视了评估种群模型本身结构中的不确定性的重要性。 Jaatinen 等人通过考虑蓝贻贝种群增长模型中的结构不确定性。 （2021）证明，密度依赖过程可能会加剧气候变化的不利影响并降低这一关键物种的种群生存能力。这些发现强调了将结构性未知因素纳入人口预测的重要性，以及考虑气候和模型不确定性多种来源的方法的价值。捕捉气候变化下一系列可能的人口轨迹的预测将有助于确保有限的保护资源的有效分配。
In Focus:Jaatinen, K., Westerbom, M., Norkko, A., Mustonen, O., & Koons, D. N. (2021). Detrimental impacts of climate change may be exacerbated by density‐dependent population regulation in blue mussels.Journal of Animal Ecology,90, 562–573, https://doi.org/10.1111/1365‐2656.13377. Conservation strategies for threatened species are increasingly dependent on forecasts of population responses to climate change. For such forecasts to be accurate, they must account for multiple sources of uncertainty, including those associated with projections of future climate scenarios and those associated with the models used to describe population dynamics. While many population forecasts incorporate parameter uncertainty in abiotic effects and process variance related to unexplained temporal variation, most forecasts overlook the importance of evaluating uncertainty in the structure of the population model itself. By accounting for structural uncertainties in a model of population growth for blue mussels, Jaatinen et al. (2021) demonstrated that density‐dependent processes are likely to exacerbate adverse effects of climate change and reduce population viability of this keystone species. These findings highlight the importance of incorporating structural unknowns in population forecasts and the value of approaches that account for multiple sources of climate and model uncertainties. Forecasts that capture a range of possible population trajectories under climate change will help ensure efficient allocation of limited conservation resources.