首页> 外文期刊>Palaeogeography, Palaeoclimatology, Palaeoecology: An International Journal for the Geo-Sciences >Mean annual temperature estimation based on leaf morphology: a test from tropical South America
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Mean annual temperature estimation based on leaf morphology: a test from tropical South America

机译:基于叶片形态的年平均气温估算:来自南美热带地区的一项测试

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摘要

Are models that predict mean annual temperature (MAT) from leaf morphology applicable globally? Fifteen models that predict MAT from leaf morphology were tested on thirty floral samples from tropical South America to determine the degree to which models based on published data that are primarily from other regions are applicable to floras from tropical South America. The models included are based on regional data from North America, South America, and Asia. Of the fifteen models tested, five are simple linear regressions, six are multiple linear regressions, two are canonical correspondence analyses, and two are correspondence analyses followed by nearest neighbor analyses. For the seven modern floras with MAT ≤21 ℃, every model overestimates MAT. For the 23 modern floras with MAT > 21 ℃, all models produce variable results without a systematic error. The range of average model errors is 2.4-7.3 ℃, while the absolute extremes of error are 0 and 15.1 ℃. Average 95% predictive confidence intervals range from 1.6 to 6.9 ℃. Predicted MAT falls within the published standard error of the model for 0-67% of the South American test floras. Evaluating the seven sites with MAT ≤21 ℃ separately from the 23 sites with MAT > 21 ℃ shows that of equation accurately estimates MAT of the majority of low-temperature sites, but that four equations accurately estimate >50% of high-temperature sites. The results suggest that at least for sites of unknown or high elevation, mean annual temperature of fossil floras from tropical South America may be better predicted from models based on the leaf morphology of tropical South American floras.
机译:通过叶片形态预测年平均气温(MAT)的模型是否在全球范围内适用?在来自南美洲热带地区的30个花卉样本上测试了15个根据叶片形态预测MAT的模型,以确定基于主要来自其他地区的已发布数据的模型适用于南美洲热带地区植物区系的程度。包括的模型基于来自北美,南美和亚洲的区域数据。在测试的15个模型中,有5个是简单线性回归,有6个是多元线性回归,两个是典范对应分析,两个是对应分析,然后进行最近邻分析。对于MAT≤21℃的七个现代菌群,每个模型都高估了MAT。对于MAT> 21℃的23个现代菌群,所有模型均产生可变结果,而没有系统误差。平均模型误差范围为2.4-7.3℃,而误差的绝对最大值为0和15.1℃。平均95%的预测置信区间为1.6到6.9℃。预测的MAT在南美测试菌群的0-67%的模型的标准误差内。分别对MAT≤21℃的7个站点和MAT> 21℃的23个站点分别进行评估,可以发现方程式可以准确估计大多数低温站点的MAT,但四个方程式可以准确估计> 50%的高温站点。结果表明,至少对于未知或高海拔的地区,可以根据基于热带南美植物区系叶片形态的模型更好地预测热带南美植物区系化石的年平均温度。

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