Continental‐scale tree‐ring‐based projection of Douglas‐fir growth: Testing the limits of space‐for‐time substitution
Continental‐scale tree‐ring‐based projection of Douglas‐fir growth: Testing the limits of space‐for‐time substitution
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DOI：
10.1111/gcb.15170
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发表时间：
2020-05
影响因子：
11.6
通讯作者：
S. Klesse;R. DeRose;F. Babst;B. Black;L. Anderegg;J. Axelson;A. Ettinger;Hardy Griesbauer;Christopher H. Guiterman;G. Harley;Jill E Harvey;Yueh-Hsin Lo;A. Lynch;Christopher D. O’Connor;Christina M. Restaino;D. Sauchyn;J. Shaw;Dan Smith;Lisa J. Wood;J. Villanueva‐Díaz;M. Evans
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作者：
S. Klesse;R. DeRose;F. Babst;B. Black;L. Anderegg;J. Axelson;A. Ettinger;Hardy Griesbauer;Christopher H. Guiterman;G. Harley;Jill E Harvey;Yueh-Hsin Lo;A. Lynch;Christopher D. O’Connor;Christina M. Restaino;D. Sauchyn;J. Shaw;Dan Smith;Lisa J. Wood;J. Villanueva‐Díaz;M. Evans
全球变化研究的一个核心挑战是根据过去的观测结果预测系统的未来行为。在过去十年中，树木年轮数据越来越多地用于预测未来气候条件下的树木生长和森林生态系统脆弱性。但是，树木生长对过去气候变化的反应如何能预测未来，当未来看起来不像过去的时候？空间换时间替代（SFTS）是克服外推问题的一种方法：假设在未来变暖的给定位置的响应遵循今天变暖位置的响应。在这里，我们评估了SFTS的方法来预测未来的增长道格拉斯-冷杉（花旗松），一个物种，占据了一个非常大的环境空间在北美。我们拟合了一个分层混合效应模型，以捕捉响应气候时空变化的环宽变化。我们发现，在道格拉斯冷杉分布区的中纬度沿海地区，生产力和气候敏感性呈相反的梯度，生长率最高，对年际气候变化的反应最弱;半干旱内陆地区的年轮较窄，气候敏感性较强。环宽对空间与时间温度变化的响应是相反的，这表明由当地适应和其他缓慢过程引起的生产力的空间变化不能用来预测快速气候变化引起的生产力变化。因此，在预测未来树木生长时，我们仅用气候敏感性代替。预计道格拉斯冷杉分布区的大部分地区的生长量都会下降，美国内陆西部的相对下降幅度最大，太平洋西北部的相对下降幅度最小。我们进一步强调了混合效应建模的优势，以恢复树木生态学的概念基石，库克1987年的聚集生长模型，以及使用树轮网络和结果作为下一代植被模型的校准目标的巨大潜力。
A central challenge in global change research is the projection of the future behavior of a system based upon past observations. Tree‐ring data have been used increasingly over the last decade to project tree growth and forest ecosystem vulnerability under future climate conditions. But how can the response of tree growth to past climate variation predict the future, when the future does not look like the past? Space‐for‐time substitution (SFTS) is one way to overcome the problem of extrapolation: the response at a given location in a warmer future is assumed to follow the response at a warmer location today. Here we evaluated an SFTS approach to projecting future growth of Douglas‐fir (Pseudotsuga menziesii), a species that occupies an exceptionally large environmental space in North America. We fit a hierarchical mixed‐effects model to capture ring‐width variability in response to spatial and temporal variation in climate. We found opposing gradients for productivity and climate sensitivity with highest growth rates and weakest response to interannual climate variation in the mesic coastal part of Douglas‐fir's range; narrower rings and stronger climate sensitivity occurred across the semi‐arid interior. Ring‐width response to spatial versus temporal temperature variation was opposite in sign, suggesting that spatial variation in productivity, caused by local adaptation and other slow processes, cannot be used to anticipate changes in productivity caused by rapid climate change. We thus substituted only climate sensitivities when projecting future tree growth. Growth declines were projected across much of Douglas‐fir's distribution, with largest relative decreases in the semiarid U.S. Interior West and smallest in the mesic Pacific Northwest. We further highlight the strengths of mixed‐effects modeling for reviving a conceptual cornerstone of dendroecology, Cook's 1987 aggregate growth model, and the great potential to use tree‐ring networks and results as a calibration target for next‐generation vegetation models.