China's current forest age structure will lead to weakened carbon sinks in the near future

Forests are chiefly responsible for the terrestrial carbon sink that greatly re duces the buildup of CO_(2)concentrations in the atmosphere and alleviates climate change.Current predictions of terrestrial carbon sinks in the future have so far ignored the variation of forest carbon uptake with forest age.Here,we predict the role of China's current forest age in future carbon sink capacity by generating a high-resolution(30 m)forest age map in 2019 over China's landmass using satellite and forest inventory data and deriving forest growth curves using measurements of forest biomass and age in 3,121 plots.As China's forests currently have large proportions of young and middle-age stands,we project that China's forests will maintain high growth rates for about 15 years.However,as the forests grow older,their net primary productivity will decline by 5.0%±1.4%in 2050,8.4%±1.6%in 2060,and 16.6%±2.8%in 2100,indicating weakened carbon sinks in the near future.The weakening of forest carbon sinks can be potentially mitigated by optimizing forest age structure through selective logging and implementing new or improved afforestation.This finding is important not only for the global carbon cycle and climate projections but also for developing forest management strategies to enhance land sinks by alleviating the age effect.

Phylogenetic context of a deep-sea clam(Bivalvia:Vesicomyidae) revealed by DNA from 1 500-year-old shells

DEAR EDITOR,Ancient DNA(a DNA) from mollusc shells is considered a potential archive of historical biodiversity and evolution.However, such information is currently lacking for mollusc shells from the deep ocean, especially those from acidic chemosynthetic environments theoretically unsuitable for longterm DNA preservation. Here, we report on the recovery of mitochondrial and nuclear gene markers by Illumina sequencing of a DNA from three shells of Archivesica nanshaensis – a hydrocarbon-seep vesicomyid clam previously known only from a pair of empty shells collected at a depth of 2626 m in the South China Sea.

Improved Fine-Scale Tropical Forest Cover Mapping for Southeast Asia Using Planet-NICFI and Sentinel-1 Imagery

The accuracy of existing forest cover products typically suffers from“rounding”errors arising from classifications that estimate the fractional cover of forest in each pixel,which often exclude the presence of large,isolated trees and small or narrow forest clearings,and is primarily attributable to the moderate resolution of the imagery used to make maps.However,the degree to which such high-resolution imagery can mitigate this problem,and thereby improve large-area forest cover maps,is largely unexplored.Here,we developed an approach to map tropical forest cover at a fine scale using Planet and Sentinel-1 synthetic aperture radar(SAR)imagery in the Google Earth Engine platform and used it to map all of Southeastern Asia’s forest cover.The machine learning approach,based on the Random Forests models and trained and validated using a total of 37,345 labels collected from Planet imagery across the entire region,had an accuracy of 0.937 and an F1 score of 0.942,while a version based only on Planet imagery had an accuracy of 0.908 and F1 of 0.923.We compared the accuracy of our resulting maps with 5 existing forest cover products derived from medium-resolution optical-only or combined optical-SAR approaches at 3,000 randomly selected locations.We found that our approach overall achieved higher accuracy and helped minimize the rounding errors commonly found along small or narrow forest clearings and deforestation frontiers where isolated trees are common.However,the forest area estimates varied depending on topographic location and showed smaller differences in highlands(areas>300 m above sea level)but obvious differences in complex lowland landscapes.Overall,the proposed method shows promise for monitoring forest changes,particularly those caused by deforestation frontiers.Our study also represents one of the most extensive applications of Planet imagery to date,resulting in an open,high-resolution map of forest cover for the entire Southeastern Asia region.

An Operational Assessment Framework for Near Real-time Cropland Dynamics:Toward Sustainable Cropland Use in Mid-Spine Belt of Beautiful China

Cropland monitoring is a crucial component for a broad user community from Land Use and Land Cover Change study to food security policy making.Faced with the rich natural ecological environment and variable agricultural production conditions of Mid-Spine Belt of Beautiful China(MSBBC),this study developed a novel operational assessment framework that combined the near real-time land cover mapping platform(i.e.,FROM-GLC Plus),the FAO Agricultural Stress Index System,and the land degradation monitoring method suggested by United Nations Convention to Combat Desertification for the timely monitoring of cropland extent change,cropland conditions,and cropland degradation.With integrated monitoring system,this framework can provide convenient access to high-spatiotemporalresolution cropland maps(30 m,dekadal)and instant(near real time)cropland dynamics.According to the monitoring results,we found that the abnormally high temperatures of summer 2022 adversely affected crop health in the southwest of MSBBC.Besides,our results suggested that China’s ecological restoration projects made remarkable achievement in MSBBC.The productivity of more than 70% of cropland in MSBBC has improved,and only~6% cropland(~3.69×104 km^(2))has degraded since 2000,mainly distributed in cropland with steep slope,insufficient precipitation,and intensive use.Site-specific measures,such as conservation tillage,improved tillage systems,and cropland ecological projects,should be adopted for sustainable cropland use and further increase in land carrying capacity of MSBBC to achieve balanced east-west development in China.

The land-sea interface mapping:China’s coastal land covers at 10 m for 2020

土地利用/覆盖分类是研究海岸带动态变化过程、理解滨海社会-生态系统作用机制和支持可持续发展的重要基础.中国海岸带土地覆盖复杂多样,以往全国海岸带土地覆盖遥感制图产品严重依赖人工目视解译,缺乏涵盖中国重要海岸带地物类型的标准化自动制图产品.结合多套中国海岸带地区公开发表的遥感数据产品,本研究建立了包含12个类型的中国海岸带土地覆盖样本库,基于谷歌地球引擎平台,采用2019~2021年哨兵主被动遥感数据构建光谱特征和纹理特征,联合基于像素和面向对象的分类方法得到10米分辨率的中国海岸带土地覆盖产品.分析结果表明,2020年中国海岸带土地覆盖遥感自动制图结果的总体精度达到79.3%,制图产品涵盖重要的中国滨海湿地类型且优于同期全球土地覆盖分类数据.本数据产品将为海岸带环境评估和监测提供重要依据,为中国海岸带综合保护和规划提供科学支持.

Urban Renewal Mapping:A Case Study in Beijing from 2000 to 2020

Understanding the distribution and land history of old urban areas(OUAs)and renewed urban areas(RUAs)has become the key point of urban management.However,it is hard to acquire adequate information for lack of pertinent detection methods.Here,we established a complete mapping framework on Google Earth Engine(GEE)platform to identify OUAs and RUAs and detect the temporal information of urban renewal,which was implemented in Beijing during 2000-2020.We used Landsat imagery and LandTrendr algorithm to fit the spectral trajectories of 14 bands/indices with specific segment attributes as the feature inputs for Random Forest classification.We produced the maps of OUAs and RUAs with an overall accuracy of 95.36%.On this basis,we further utilized LandTrendr to detect the start year,end year,and duration of urban renewal with the accuracies within the±5-year difference of 85.52%,80.97%,and 74.53%,respectively.These maps all present informative spatiotemporal patterns.Furthermore,the urban renewal process is likely to be influenced by major national or international events.The study answers the issues about urban renewal from multiple angles and provides scientific support for future urban planning.

Global impacts of COVID-19 on sustainable ocean development

The abrupt outbreak of coronavirus disease in 2019,also known as COVID-19,has led to an unprecedented global public healthcrisis.Current studies have paid immense attention to the impacts of COVID-19 posed to the atmosphere and the land-based sectors in areas such as air quality,carbon emission,economic senti ment,educational and social equality,etc.It is depicted that carbon emission had dropped about 8.8%in the first half of 2020 compared to 2019,'significant reduc-tion of air pollutants such as PM25 and NO2 were moreover reported at national,regional,and global levels.On the flip side,the amount of attention paid to the ocean during this pandemic has been nearly negligible despite its prominent functions of supporting livelihoods for 40%of the global population,absorbing~30%of anthropogenic CO_(2)emissions,and processing over 90%of excess heat in our climate system.Both direct and indirect effects of the pandemicare insufficiently understood in the ocean,which include their key roles in blue carbon sequestration,ocean-atmosphere and ocean-land interactions,sealevel changes,and their impacts to human beings.