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Old Forests in the Tropics Are Getting Younger and Losing Carbon

EOS - 9 hours 7 min ago

The towering trees of old forests store massive amounts of carbon in their trunks, branches, and leaves. When these ancient giants are replaced by a younger cohort after logging, wildfire, or other disturbances, much of this carbon stock is lost.

“We wanted to actually quantify what it means if an old forest becomes young.”

“We’ve known for a long time that forest age is a key component of the carbon cycle,” said Simon Besnard, a remote sensing expert at the GFZ Helmholtz Centre for Geosciences in Potsdam, Germany. “We wanted to actually quantify what it means if an old forest becomes young.”

The resulting study, published in Nature Ecology and Evolution, measured the regional net aging of forests around the world across all age classes between 2010 and 2020, as well as the impact of these changes on aboveground carbon.

To do this, the team developed a new high-resolution global forest age dataset based on more than 40,000 forest inventory plots, biomass and height measurements, remote sensing observations, and climate data. They combined this information with biomass data from the European Space Agency and atmospheric carbon dioxide observations.

The results point to large regional differences. While forests in Europe, North America, and China have aged during this time, those in the Amazon, Southeast Asia, and the Congo Basin were younger in 2020 than 10 years prior.

A number of recent studies have shown that forests are getting younger, but the new analysis quantifies the impact of this shift on a global level, said Robin Chazdon, a tropical forest ecologist at the University of the Sunshine Coast in Queensland, Australia, who was not involved in the study. “That’s noteworthy and a very important concept to grasp because this has global implications, and it points out where in the world these trends are strongest.”

Carbon Impact

The study identifies the tropics, home to some of the world’s oldest forests, as a key region where younger forests are replacing older ones.

In this image from 2020, old-growth forests are most evident in tropical areas in South America, Africa, and Southeast Asia. Credit: Besnard et al., 2021, https://doi.org/10.5194/essd-13-4881-2021, CC BY 4.0

On average, forests that are at least 200 years old store 77.8 tons of carbon per hectare, compared to 23.8 tons per hectare in the case of forests younger than 20 years old.

The implications for carbon sequestration are more nuanced, however. Fast-growing young forests, for instance, can absorb carbon much more quickly than old ones, especially in the tropics, where the difference is 20-fold. But even this rate of sequestration is not enough to replace the old forests’ carbon stock.

Ultimately, said Besnard, “when it comes to a forest as a carbon sink, the stock is more important than the sink factor.”

“It’s usually more cost-, carbon-, and biodiversity-effective to keep the forest standing than it is to try to regrow it after the fact.”

In the study, only 1% of the total forest area transitioned from old to young, primarily in tropical regions. This tiny percentage, however, accounted for more than a third of the lost aboveground carbon documented in the research— approximately 140 million out of the total 380 million tons.

“It’s usually more cost-, carbon-, and biodiversity-effective to keep the forest standing than it is to try to regrow it after the fact. I think this paper shows that well,” said Susan Cook-Patton, a reforestation scientist at the Nature Conservancy in Arlington, Va., who was not involved in the study. “But we do need to draw additional carbon from the atmosphere, and putting trees back in the landscape represents one of the most cost-effective carbon removal solutions we have.”

The increased resolution and details provided by the study can help experts better understand how to manage forests effectively as climate solutions, she said. “But forest-based solutions are not a substitute for fossil fuel emissions reductions.”

Open Questions

When carbon stored in trees is released into the atmosphere depends on what happens after the trees are removed from the forest. The carbon can be stored in wooden products for a long time or released gradually through decomposition. Burning, whether in a forest fire, through slash-and-burn farming, or as fuel, releases the carbon almost instantly.

“I think there is a research gap here: What is the fate of the biomass being removed?” asked Besnard, pointing out that these effects have not yet been quantified on a global scale.

Differentiating between natural, managed, and planted forests, which this study lumps together, would also offer more clarity, said Chazdon: “That all forests are being put in this basket makes it a little bit more challenging to understand the consequences not only for carbon but for biodiversity.”

She would also like to see future research on forest age transitions focus on issues beyond carbon: “Biodiversity issues are really paramount, and it’s not as easy to numerically display the consequences of that as it is for carbon.”

“We are only looking at one metric, which is carbon, but a forest is more than that. It’s biodiversity, it’s water, it’s community, it’s many things,” agreed Besnard.

—Kaja Šeruga, Science Writer

Citation: Šeruga, K. (2025), Old forests in the tropics are getting younger and losing carbon, Eos, 106, https://doi.org/10.1029/2025EO250369. Published on 2 October 2025. Text © 2025. The authors. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

机器学习模拟千年气候

EOS - 9 hours 8 min ago
Source: AGU Advances

This is an authorized translation of an Eos article. 本文是Eos文章的授权翻译。

近年来,科学家们发现,基于机器学习的天气模型可以比传统模型更快地做出天气预测,且使用更少的能耗。然而,许多这些模型无法准确预测未来15天以上的天气,并且到第 60 天时就会开始模拟出不切实际的天气。

深度学习地球系统模型(Deep Learning Earth System Model,简称DLESyM)建立在两个并行运行的神经网络上:一个模拟海洋,另一个模拟大气。在模式运行期间,对海洋状况的预测每四个模式日更新一次。由于大气条件演变得更快,对大气的预测每12个模式小时更新一次。

该模型的创建者Cresswell-Clay 等人发现,DLESyM 与过去观测到的气候非常吻合,并能做出准确的短期预测。以地球当前的气候为基准,它还可以在不到 12 小时的计算时间内,准确模拟 1000 年周期内的气候和年际变化。它的性能通常与基于耦合模式比对计划第六阶段(CMIP6)的模型相当,甚至优于后者,CMIP6目前在计算气候研究中被广泛使用。

DLESyM 模型在模拟热带气旋和印度夏季季风方面优于 CMIP6 模型。它至少与 CMIP6 模型一样准确地捕捉了北半球大气“阻塞”事件的频率和空间分布,而这些事件可能导致极端天气。此外,该模型预测的风暴也非常真实。例如,在 1000 年模拟结束时(3016 年)生成的东北风暴的结构与 2018 年观测到的东北风暴非常相似。

然而,新模型和CMIP6 模型都无法很好地描述大西洋飓风 的气候特征。此外,对于中期预报(即未来 15 天左右的预报),DLESyM 的准确性低于其他机器学习模型。尤其重要的是,DLESyM 模型仅对当前气候进行模拟,这意味着它没有考虑人类活动引起的气候变化。

作者认为,DLESyM模型的主要优势在于,它比运行CMIP6 模型所需的计算成本要低得多,这使得它比传统模型更容易使用。(AGU Advances, https://doi.org/10.1029/2025AV001706, 2025)

—科学撰稿人Madeline Reinsel

This translation was made by Wiley. 本文翻译由Wiley提供。

Read this article on WeChat. 在微信上阅读本文。

Text © 2025. AGU. CC BY-NC-ND 3.0
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The aftermath of the Matai’an landslide and dam breach in Taiwan

EOS - 14 hours 23 min ago

Good digital data is now being published that presents the scale of landscape change that occurred as a result of the Matai’an landslide hazard cascade. There is also interesting information about the root causes of the vulnerability of the town of Guangfu, where the fatalities occurred.

Some interesting information is now emerging about the Matai’an landslide and dam breach, much of it published in Taiwan in Mandarin. A very interesting post has appeared on the website of the Aerial Survey and Remote Sensing Branch that uses aerial imagery before and after the hazard cascade to analyse terrain changes. It is based upon this figure that they have published:-

Vertical elevation change before and after the Matai’an landslide and dam breach. Published by ASRS in Taiwan.

This uses LIDAR data from before and after the sequence of events, which has been turned into one metre Digital Elevation Model, which have then been digitally compared. Note this gives vertical change.

In the source area of the landslide, where the topography is extremely steep, there is over 300 metres of elevation reduction. Downslope and in the area of the dam and lake, the elevation change is over 200 m of accumulation – this is the landslide debris, whivch will now be mobilised in successive rain storm events. In the main channel, the river bed has aggraded (increased in elevation) by over ten metres, although the analysis shows that at point C this was 52 metres! This is going to cause very substantial issues in the future unless a large scale mitigation exercise is undertaken.

The cross-section through the landslide is fascinating:-

A cross-section showing vertical elevation change before and after the Matai’an landslide and dam breach. Published by ASRS in Taiwan.

This shows extremely well the rupture surface of the failure, which clearly had a rotational element, and the infilling of the bedrock topography by the landslide debris. Meanwhile, there is a good helicopter video on Facebook that shows the aftermath of the dam breach.

On a different matter, there is a huge amount of discussion in Taiwan as to why so little effort was made to mitigate the hazard associated with a breach of the Matai-an landslide dam. Writing in the Taipei Times, Michael Turton has a great article exploring the socio-political reasons why this disaster played out as it did. The bottom line is that Guangfu was built on a floodplain – a problem in so many places, but particularly acute in the almost uniquely dynamic physical geography of Taiwan. Levees were built to protect the town, which caused the river to aggrade even before the dam break event. And thus, the scene was set.

Hazards can be natural, disasters are not.

Return to The Landslide Blog homepage Text © 2023. The authors. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

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