Time-lagged effects of weather on plant demography: drought and Astragalus scaphoides
Time-lagged effects of weather on plant demography: drought and Astragalus scaphoides
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天气对植物种群的时滞影响：干旱和舟状黄芪
DOI：
10.1002/ecy.2163
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发表时间：
2018
期刊：
影响因子：
4.8
通讯作者：
Tyre, Andrew J.
中科院分区：
文献类型：
--
作者：
Tenhumberg, Brigitte;Crone, Elizabeth E.;Ramula, Satu;Tyre, Andrew J.
温度和降水量决定了植物物种能够出现的条件。尽管其意义重大，但迄今为止，令人惊讶的是很少有人口实地研究考虑非生物驱动因素的影响。这是有问题的，因为预测全球气候变化对植物种群生存能力的影响需要了解天气变量如何影响种群动态。在人口研究中忽略天气变量影响的一个可能原因是难以检测生命率与环境驱动因素之间的紧密关联。在本文中，我们将函数线性模型（FLM）应用于多年生野花黄芪的长期人口统计数据，并探讨了结果对减少数据量的敏感性。我们比较了平均温度、总降水量或干旱强度综合测量（标准化降水蒸散指数，SPEI）对植物生命率影响的模型。我们发现，如果当年的冬季/春季潮湿（SPEI 的积极作用），那么当年的开花和补充的转变最高。与直觉相反，如果前一年春天潮湿，开花概率就会降低（SPEI 的负面影响）。从 t−1 到 t−1 的春季潮湿天气也会对营养植物的生存产生负面影响，对于大型植物来说，甚至 t−2 春季的潮湿天气也会产生负面影响。我们通过将 FLM 拟合到渐近增长率 log() 来评估所有生命率对生活史表现的综合影响。如果年份 − 1 的干燥条件随后是年份的潮湿条件，则 Log() 最高。总体而言，潮湿年份的积极影响超过了其消极影响，这表明干旱条件的增加会降低A. 种群的生存能力。 舟状骨。随着监测年数的减少，干旱信号减弱。用空间代替时间并不能恢复天气信号，可能是因为站点之间的天气变量变化不大。当分析包含 20 年监测的两个站点的数据（2 × 20 个观测值）时，我们检测到了 SPEI 信号，但在分析 10 年监测的四个站点的数据（4 × 10 个观测值）时，我们检测不到 SPEI 信号。
Temperature and precipitation determine the conditions where plant species can occur. Despite their significance, to date, surprisingly few demographic field studies have considered the effects of abiotic drivers. This is problematic because anticipating the effect of global climate change on plant population viability requires understanding how weather variables affect population dynamics. One possible reason for omitting the effect of weather variables in demographic studies is the difficulty in detecting tight associations between vital rates and environmental drivers. In this paper, we applied Functional Linear Models (FLMs) to long‐term demographic data of the perennial wildflower,Astragalus scaphoides, and explored sensitivity of the results to reduced amounts of data. We compared models of the effect of average temperature, total precipitation, or an integrated measure of drought intensity (standardized precipitation evapotranspiration index, SPEI), on plant vital rates. We found that transitions to flowering and recruitment in yeartwere highest if winter/spring of yeartwas wet (positive effect of SPEI). Counterintuitively, if the preceding spring of yeart− 1 was wet, flowering probabilities were decreased (negative effect of SPEI). Survival of vegetative plants fromt− 1 totwas also negatively affected by wet weather in the spring of yeart− 1 and, for large plants, even wet weather in the spring oft− 2 had a negative effect. We assessed the integrated effect of all vital rates on life history performance by fitting FLMs to the asymptotic growth rate, log(). Log() was highest if dry conditions in yeart − 1were followed by wet conditions in the yeart. Overall, the positive effects of wet years exceeded their negative effects, suggesting that increasing frequency of drought conditions would reduce population viability ofA. scaphoides. The drought signal weakened when reducing the number of monitoring years. Substituting space for time did not recover the weather signal, probably because the weather variables varied little between sites. We detected the SPEI signal when the analysis included data from two sites monitored over 20 yr (2 × 20 observations), but not when analyzing data from four sites monitored over 10 yr (4 × 10 observations).