一份新的数据驱动地图预测,亚马逊地区存在大量未记录的泥炭地。

A. Hastie, J. E. Householder, E. H. Honorio Coronado, C. G. Hidalgo Pizango, Rafael Herrera, O. Lähteenoja, Johan de Jong, R. S. Winton, Gerardo A. Aymard Corredor, José Reyna, Encarni Montoya, Stella Paukku, E. Mitchard, Christine M. Åkesson, Timothy R. Baker, Lydia Cole, C. J. Córdova Oroche, N. Dávila, Jhon del Águila, F. C. Draper, E. Fluet‐Chouinard, Julio Grández, John P. Janovec, David Reyna, Mathias W. Tobler, Dennis Del Castillo Torres, K. Roucoux, Charlotte E Wheeler, Maria Teresa Fernandez Piedade, J. Schöngart, Florian Wittman, Marieke van der Zon, I. Lawson
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引用次数: 0

摘要

热带泥炭地是有史以来碳密度最高的陆地生态系统之一。总的来说,泥炭地是全球碳循环中一个巨大但高度不确定的储库,其全球面积(441,025-1,700,000 平方公里)和地下碳储量(105-288 Pg C)的估计值差别很大。我们对泥炭地在一些关键地区(包括南美洲大部分热带地区)分布情况的了解仍存在巨大差距。在这里,我们汇编了亚马逊泥炭地及其周围的 2413 个地面参考点,并将它们与随机森林模型中的一系列遥感产品一起使用,生成了首个数据驱动的亚马逊盆地泥炭地分布模型。我们的模型预测亚马逊泥炭地总面积约为 251,015 平方公里(第 95 百分位数置信区间:128,671 至 373,359 平方公里),大于刚果盆地的泥炭地面积,但比最近通过模型估计的亚马逊泥炭地面积小 30%。该模型与定点观测结果相比表现良好,但地面参考数据集的空间差距意味着模型的不确定性仍然很高,尤其是在巴西和玻利维亚的部分地区。例如,我们预测秘鲁北部的泥炭地面积较大,可信度相对较高,而先前预测为坎皮纳拉纳或白沙森林的里约内格罗河流域和邻近的奥里诺科河流域西南部泥炭地面积较大,预测的不确定性较高。同样,我们预测玻利维亚会有大面积的开阔泥炭地,这在该国大部分地区气候季节性很强的情况下令人惊讶。在这些地区,可用于定量评估我们地图准确性的实地数据非常少。像这样的数据缺口应该成为新的实地采样工作的重中之重。这幅新地图有助于今后研究泥炭地在气候变化和人为影响下的脆弱性,而这种脆弱性在整个亚马逊流域可能存在空间差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new data-driven map predicts substantial undocumented peatland areas in Amazonia.
Tropical peatlands are among the most carbon-dense terrestrial ecosystems yet recorded. Collectively, they comprise a large but highly uncertain reservoir of the global carbon cycle, with wide-ranging estimates of their global area (441,025–1,700,000 km2) and below-ground carbon storage (105–288 Pg C). Substantial gaps remain in our understanding of peatland distribution in some key regions, including most of tropical South America. Here we compile 2,413 ground reference points in and around Amazonian peatlands and use them alongside a stack of remote sensing products in a random forest model to generate the first data-driven model of peatland distribution across the Amazon basin. Our model predicts a total Amazonian peatland extent of approximately 251,015 km2 (95th percentile confidence interval: 128,671 to 373,359), greater than that of the Congo basin, but around 30% smaller than a recent model-derived estimate of peatland area across Amazonia. The model performs well against point observations but spatial gaps in the ground reference dataset mean that model uncertainty remains high, particularly in parts of Brazil and Bolivia. For example, we predict significant peatland areas in northern Peru with relatively high confidence, while peatland areas in the Rio Negro basin and adjacent south-western Orinoco basin which have previously been predicted to hold Campinarana or white sand forests, are predicted with greater uncertainty. Similarly, we predict large areas of open peatlands in Bolivia, surprisingly given the strong climatic seasonality found over most of the country. Very little field data exists with which to quantitatively assess the accuracy of our map in these regions. Data gaps such as these should be a high priority for new field sampling. This new map can facilitate future research into the vulnerability of peatlands to climate change and anthropogenic impacts, which is likely to vary spatially across the Amazon basin.
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