Evaluating ecosystem change as Gulf of Alaska temperature exceeds the limits of preindustrial variability
Evaluating ecosystem change as Gulf of Alaska temperature exceeds the limits of preindustrial variability
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评估阿拉斯加湾温度超过工业化前变化极限时的生态系统变化
DOI：
10.1016/j.pocean.2020.102393
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发表时间：
2020
影响因子：
4.1
通讯作者：
Fergusson, Emily
中科院分区：
文献类型：
--
作者：
Litzow, Michael A.;Hunsicker, Mary E.;Ward, Eric J.;Anderson, Sean C.;Gao, Jin;Zador, Stephani G.;Batten, Sonia;Dressel, Sherri C.;Duffy-Anderson, Janet;Fergusson, Emily
阿拉斯加湾在2014-2019年经历了极端温度，包括有史以来最热的四年。这项研究的目标是评估气候变暖事件在多个营养层和类群中的生态后果。我们测试了观测到的海表面温度(SST)异常不在自然气候变异性的范围内的证据，以评估新生态系统配置的风险。我们还使用动态因素分析(DFA)的贝叶斯实现，测试了气候(n=11)和生物(n=48)时间序列的共同趋势的状态变化。我们在2014-2019年测试了新的生态关系的证据。我们发现，2014-2019年连续3年的平均海温异常超出了CMIP5模式工业化前模拟的异常范围，表明变暖事件的规模和持续时间都超出了自然变率的范围。气候变异性的DFA模型还返回了2014-2019年期间处于前所未有水平的气候时间序列的共同趋势。然而，符合生物数据的DFA模型没有显示出前所未有的共同变异性趋势，符合气候和生物模型共同趋势的隐马尔可夫模型未能找到2014-2019年向新生态系统状态转变的证据。相反，我们确实发现了初步迹象，表明在经历了数十年的基本中性关系后，社区对SST变化的反应在2014-2019年期间有所加强。对共享变率的非平稳模式的测试表明，海温和其他具有生态重要性的气候变量之间的协方差仍然弱于20世纪70年代太平洋年代际涛动转移期间，这表明2014-2019年事件的生态反应可能会减弱。最后，我们发现，最近的群落变化模式似乎与20世纪70年代事件的相关模式非常不同，这表明新的社区状态可能会继续变暖。总而言之，我们没有发现2014-2019年大规模生态系统重组的证据，尽管气候和社区变量之间的非平稳关系表明，随着持续变暖，生态系统功能的新模式持续存在的可能性。
The Gulf of Alaska experienced extreme temperatures during 2014–2019, including the four warmest years ever observed. The goal of this study is to evaluate the ecological consequences of that warming event, across multiple trophic levels and taxa. We tested for evidence that observed sea surface temperature (SST) anomalies were outside the envelope of natural climate variability in order to evaluate the risk of novel ecosystem configurations. We also tested for state changes in shared trends of climate (n= 11) and biology (n= 48) time series, using a Bayesian implementation of Dynamic Factor Analysis (DFA). And we tested for evidence of novel ecological relationships during 2014–2019. We found that 3-year running mean SST anomalies during 2014–2019 were outside the range of anomalies from preindustrial simulations in CMIP5 models, indicating that the combined magnitude and duration of the warming event was outside the range of natural variability. A DFA model of climate variability also returned a shared trend in climate time series that was at unprecedented levels during 2014–2019. However, DFA models fit to biology data did not show shared trends of variability at unprecedented levels, and Hidden Markov Models fit to shared trends from the climate and biology models failed to find evidence of shifts to a new ecosystem state during 2014–2019. Conversely, we did find preliminary indications that community responses to SST variability strengthened during 2014–2019 after decades of a mostly neutral relationship. Tests for nonstationary patterns of shared variability suggest that covariance between SST and other ecologically-important climate variables remained weaker than during the 1970s Pacific Decadal Oscillation shift, suggesting the potential for muted ecological responses to the 2014–2019 event. Finally, we found that recent patterns of community variability appear to be highly dissimilar to those associated with the 1970s event, suggesting the potential for novel community states with continued warming. In summary, we find no evidence for wholesale ecosystem reorganization during 2014–2019, though nonstationary relationships among climate and community variables suggest the ongoing possibility of novel patterns of ecosystem functioning with continued warming.
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影响因子：
4.1
作者：
Kristin N. Marshall;J. Duffy‐Anderson;E. Ward;S. Anderson;M. Hunsicker;Benjamin C. Williams
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发表时间：
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期刊：
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DOI：
10.1016/j.envsoft.2018.03.021
发表时间：
2018-12
期刊：
Environ. Model. Softw.
影响因子：
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