A test of BIOME-BGC with dendrochronology for forests along the altitudinal gradient of Mt. Changbai in northeast China
A test of BIOME-BGC with dendrochronology for forests along the altitudinal gradient of Mt. Changbai in northeast China
复制标题
东北长白山海拔梯度森林BIOME-BGC树木年代学试验
DOI：
10.1093/jpe/rtw076
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发表时间：
2016-07
影响因子：
2.7
通讯作者：
Osbert Jianxin Sun
中科院分区：
文献类型：
--
作者：
Yulian Wu;Xiangping Wang;Shuai Ouyang;Kai Xu;Bradford A. Hawkins;Osbert Jianxin Sun
目标 基于过程的模型是预测森林碳对未来气候变化的响应的基本工具。这些模型通常针对森林生产力空间变化的预测进行测试，但预测时间变化的能力却少之又少。在这里，我们以 BIOME-BGC 为例，探索了用树木年轮测试模型的方法。方法利用长白山海拔梯度上五种主要森林类型采集的净初级生产力（NPP）数据和树木年轮来测试局部参数化BIOMEBGC模型。我们首先测试模型对生产率空间变化（测试 1）和时间变化（测试 2）的预测。然后，我们测试该模型是否能够检测历史气候变化期间限制森林生产力的气候因素，正如树木气候分析所揭示的那样（测试 3）。重要发现 我们的结果表明，BIOME-BGC 可以很好地模拟长白山五种森林类型的 NPP，沿海拔梯度的 17 个样地的模拟 NPP 与观测 NPP 之间的 r2 为 0.69（测试 1）。同时，模拟的 NPP 和年轮宽度指数相互关联，并显示出每种森林类型相似的时间趋势（测试 2）。虽然这些测试表明该模型对 NPP 时空变化的预测是可以接受的，但将模型 NPP 与气候变量的相关性与年轮宽度与气候的相关性联系起来的进一步测试（测试 3）表明，该模型没有很好地识别限制某些森林类型历史生产力动态的气候因素，因此无法可靠地预测其未来。树木年代学和BIOME-BGC均表明，由于树种和气候条件的差异，森林类型在限制生产力的气候因素上存在显着差异，从而对气候变化的响应也存在差异。我们的结果表明，空间 NPP 模式的成功预测并不能保证 BIOME-BGC 能够很好地模拟历史 NPP 动态。此外，模拟的 NPP 和树木年轮系列之间的相关性不能确保模型正确识别了生产力的限制气候因素。我们的结果表明有必要以更稳健的方式测试基于过程的模型的时间预测，并且树木年代学和生物地球化学模型的进一步整合可能有助于此目的。
Aims Process-based models are basic tools for predicting the response of forest carbon to future climate change. The models have commonly been tested for their predictions of spatial variation in forest productivity, but much less for their ability to predict temporal variation. Here, we explored methods to test the models with tree rings, using BIOME-BGC as an example. Methods We used net primary productivity (NPP) data and tree rings collected from five major forest types along the altitudinal gradient of Mt. Changbai, northeast China, to test local-parameterized BIOMEBGC model. We first test the model’s predictions of both spatial (Test 1) and temporal changes (Test 2) in productivity. Then we test if the model can detect the climatic factors limiting forest productivity during historical climate change, as revealed by dendroclimatic analyses (Test 3). Important Findings Our results showed that BIOME-BGC could well simulate NPP of five forest types on Mt. Changbai, with an r2 of 0.69 between modeled and observed NPP for 17 plots along the altitudinal gradient (Test 1). Meanwhile, modeled NPP and ring-width indices were correlated and showed similar temporal trends for each forest type (Test 2). While these tests suggest that the model’s predictions on spatial and temporal variation of NPP were acceptable, a further test that relate the correlations of modeled NPP with climate variables to the correlations of ring widths with climate (Test 3) showed that the model did not well identify the climatic factors limiting historical productivity dynamics for some forest types, and thus cannot reliably predict their future. Both dendrochronology and BIOME-BGC showed that forest types differed markedly in the climate factors limiting productivity because of differences in tree species and climate condition, and thus differed in responses to climate change. Our results showed that a successful prediction of spatial NPP patterns cannot assure that BIOME-BGC can well simulate historical NPP dynamics. Further, a correlation between modeled NPP and tree-ring series cannot assure that the limiting climatic factors for productivity have been correctly identified by the model. Our results suggest the necessity to test the temporal predictions of process-based models in a more robust way, and further integration of dendrochronology and biogeochemistry modeling may be helpful for this purpose.
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年轮宽度是西藏东南部色吉拉山高山杜鹃灌木净初级生产力变化的良好预测因子
影响因子：
1.7
作者：
Kong, Gaoqiang;Luo, Tianxiang;Liu, Xinsheng;Zhang, Lin;Liang, Eryuan
通讯作者：
Liang, Eryuan
影响因子：
64.8
作者：
Schimel, DS;House, JI;Wirth, C
通讯作者：
Wirth, C
DOI：
10.1007/s00468-015-1178-3
发表时间：
2015-03
期刊：
Trees
影响因子：
--
作者：
C. Sidor;I. Popa;R. Vlad;P. Cherubini
通讯作者：
C. Sidor;I. Popa;R. Vlad;P. Cherubini
影响因子：
5.9
作者：
Fang, Jingyun;Wang, Xiangping;Sanders, Nathan J.
通讯作者：
Sanders, Nathan J.
影响因子：
2.8
作者：
B. Zhu;Xiangping Wang;Jingyun Fang;S. Piao;Haihua Shen;Shuqing Zhao;C. Peng
通讯作者：
B. Zhu;Xiangping Wang;Jingyun Fang;S. Piao;Haihua Shen;Shuqing Zhao;C. Peng