1. 辽宁省沙地治理与利用研究所, 辽宁章古台科尔沁沙地生态系统国家定位观测研究站,辽宁,阜新,123000
2. 辽宁省水利事务服务中心,沈阳,110003
3. 辽宁省沙地治理与利用研究所, 国家农业环境彰武观测实验站,辽宁,阜新,123000
4. 辽宁省林业调查规划监测院,沈阳,110122
5. 内蒙古兴安盟林业科学研究所, 内蒙古 兴安盟,137400
6. 敖汉旗林业和草原局,内蒙古,赤峰,024399
[ "郎明翰(1995—),男,硕士,工程师,主要从事荒漠水文研究。E-mail:18804502009@163.com" ]
纸质出版:2024
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郎明翰, 张日升, 凡胜豪, 等. 科尔沁沙地南缘樟子松人工林碳汇及对气候因子的响应[J]. 水土保持学报, 2024,38(4):236-245.
LANG Minghan, ZHANG Risheng, FAN Shenghao, et al. Carbon Sequestration Function of[J]. 2024, 38(4): 236-245.
郎明翰, 张日升, 凡胜豪, 等. 科尔沁沙地南缘樟子松人工林碳汇及对气候因子的响应[J]. 水土保持学报, 2024,38(4):236-245. DOI: 10.13870/j.cnki.stbcxb.2024.04.030.
LANG Minghan, ZHANG Risheng, FAN Shenghao, et al. Carbon Sequestration Function of[J]. 2024, 38(4): 236-245. DOI: 10.13870/j.cnki.stbcxb.2024.04.030.
[目的] 以科尔沁沙地南缘不同初植密度沙地樟子松人工林为研究对象
旨在明晰不同初植密度林分碳储量、碳汇功能及其对气候的响应机制
以便于评估森林生态系统的固碳功能及其适应性管理。[方法] 利用林分胸高断面积估算樟子松人工林碳储量及固碳速率
结合气象因子分析其对温度、降水及蒸发的响应
利用GM(1
1)灰色预测模型对2030年林分碳储量进行预测。[结果] 不同初植密度樟子松人工林碳储量和固碳速率年际波动趋势基本一致
碳储量逐年增加
固碳速率曲线呈"U"形。初植密度过低或者过高均降低樟子松人工林碳汇能力;在林龄29年之前
碳汇强度最高林分初植密度为1 500~2 000株/hm2
31~42年林龄的林分最优密度为1 000~1 200株/hm2。林分碳储量随林分密度增加而增加
且二者拟合公式符合Logarithm方程。樟子松人工林固碳速率对降雨无响应。不同初植密度林分的气温对固碳速率响应模式不同
前一年8月及当年3
5
6
7月平均气温是限制高密度、极高密度樟子松人工林碳汇的主要气候因子;前一年8月及当年3
10月平均气温是限制低密度、中密度樟子松人工林碳汇的主要气候因子。由蒸发和密度林固碳速率相关分析可知
低密度樟子松人工林碳汇对蒸发的响应更为敏感。基于GM(1
1)灰色模型可知
过高或者过低初植密度均降低未来樟子松人工林固碳潜力
固碳速率最优初植林分密度为1 772 株/hm2。[结论] 林分初植密度对沙地樟子松林的碳储量和碳汇及其对气候响应存在明显影响
初植密度调整可能是气候变化下樟子松人工林适应管理的关键措施之一。
[Objective] This study aims to investigate the carbon storage
carbon sink function
and response mechanism to climate in Pinus sylvestris var. mongolica plantations with different initial planting densities on the southern edge of Horqin Sandy Land. The goal is to facilitate the assessment of the carbon sequestration function and adaptive management of forest ecosystems.[Methods] Estimating carbon storage and carbon sequestration rate of Pinus sylvestris plantations using stand height and cross-sectional area
and analyzing their responses to temperature
precipitation
and evaporation in conjunction with meteorological factors. The GM (1
1) grey prediction model was used to predict forest carbon storage in 2030. [Results] The carbon storage and sequestration rate of Pinus sylvestris plantations with different initial planting densities exhibited similar annual fluctuations
with an overall increase in carbon storage each year. The curve of the sequestration rate showed a "U" shape. Both thinly and excessive initial planting densities can reduce the carbon carbon sequestration capacity of Pinus sylvestris plantations. Before reaching 32 years old
the highest carbon sequestration intensity was observed in stands with initial planting densities of 1 500~2 000 tree/hm2
and for stands aged 35~46 years
the optimal density was 1 000~1 200 tree/hm2. The carbon storage increased logarithmically with increasing stand density.The response pattern of the planted Pinus sylvestris forests’carbon sequestration rate differed among stands with different initial planting densities regarding temperature but not precipitation. For high and extremely high-density Pinus sylvestris plantations
the average temperature in August of the previous year and in March
May
June and July of the current year were the main climatic factors limiting carbon sink. For low and medium-density plantations
the average temperature in August of the previous year and in March and October of the current year were the main climatic factors that constrain carbon sink. The correlation analysis between evapotranspiration and carbon sequestration rate in different planting density stands showed that carbon sink of low-density Pinus sylvestris plantations was more sensitive to evapotranspiration. Based on the GM (1
1) grey model
it was found that excessively high or low initial planting density would reduce the carbon sequestration potential of future Pinus sylvestris plantations. The optimal planting density for carbon sequestration rate was 1 772 tree/hm2. [Conclusion] The initial planting density of Pinus sylvestris has a significant impact on carbon storage and carbon sequestration
as well as their response to climate change in sandy areas. Adjusting the initial planting density may be one of the key adaptive management measures for Pinus sylvestris plantations under climate change.
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