阿根廷原生林中的土壤有机碳储量:气候多变情况下减缓和保护规划的有用替代物

IF 4.6 2区 环境科学与生态学 Q1 ECOLOGY
Pablo L. Peri, Juan Gaitán, Matías Mastrangelo, Marcelo Nosetto, Pablo E. Villagra, Ezequiel Balducci, Martín Pinazo, Roxana P. Eclesia, Alejandra Von Wallis, Sebastián Villarino, Francisco Alaggia, Marina González Polo, Silvina Manrique, Pablo A. Meglioli, Julián Rodríguez-Souilla, Martín Mónaco, Jimena E. Chaves, Ariel Medina, Ignacio Gasparri, Eugenio Alvarez Arnesi, María Paula Barral, Axel von Müller, Norberto M. Pahr, Josefina Uribe Echevarria, Pedro Fernández, Marina Morsucci, Dardo López, Juan Manuel Cellini, Leandro Alvarez, Ignacio Barberis, Hernán Colomb, Ludmila La Manna, Sebastián Barbaro, Cecilia Blundo, Ximena Sirimarco, Laura Cavallero, Gualberto Zalazar, Guillermo Martínez Pastur
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引用次数: 0

摘要

阿根廷在《巴黎协定》框架内提出的本国确定的贡献(NDC)与《联合国气候变化框架公约》(UNFCCC)中关于减少毁林和森林退化所致排放量以及森林碳保护(REDD+)的决定相一致。此外,气候变化是对森林生物多样性和生态系统服务的最大威胁之一。然而,由于缺乏相关信息,本地森林的土壤有机碳(SOC)储量尚未纳入森林参考排放水平计算和气候多变性下的保护规划。本研究的目标是(i) 以气候、地形和植被为预测变量,建立全国范围内 30 厘米原生林的 SOC 储量模型;(ii) 将 SOC 储量与时空遥感指数联系起来,以确定年际气候多变性威胁下的生物多样性保护问题。我们使用了 1040 个森林土壤样本(0-30 厘米),以约 200 米的空间分辨率对阿根廷原生森林的 SOC 进行了空间显式估算。我们选择了 52 个潜在的预测性环境协变量,它们代表了 SOC 空间分布的关键因素。所有协变量地图都上传到了谷歌地球引擎云计算平台,以便进行后续建模。为了确定年际气候高变率对生物多样性的威胁,我们采用了基于增强植被指数(EVI)和陆地卫星图像中的地表温度(LST)的时空卫星衍生指数。SOC 模型(0-30 厘米深度)预测结果占阿根廷整个原生林覆盖范围内该土壤属性变化的 69%。在 460,790 平方公里的总面积上,SOC 总储量的平均值达到 2.81 Pg C(2.71-2.84 Pg C,概率为 90%),其中查科森林占 SOC 总储量的 58.4%,其次是安第斯巴塔哥尼亚森林(16.7%)和埃斯皮纳森林(10.0%)。SOC 储量模型与对森林生态系统有重大影响的区域气候(包括降水量(年平均降水量和最暖季度降水量)和温度(白天地表温度、季节性、最暖月份最高温度、最高温度月份、夜间地表温度和每月最低温度))相关联。生物多样性受 SOC 水平和森林区域的影响。在《京都议定书》和 REDD+ 的框架下,本研究通过估算原始森林中的 SOC 得出的信息可纳入阿根廷年度国家清查报告,以协助提出森林管理建议。它还有助于深入了解如何提高本地森林的复原力,以减少生物多样性丧失的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Soil organic carbon stocks in native forest of Argentina: a useful surrogate for mitigation and conservation planning under climate variability
The nationally determined contribution (NDC) presented by Argentina within the framework of the Paris Agreement is aligned with the decisions made in the context of the United Nations Framework Convention on Climate Change (UNFCCC) on the reduction of emissions derived from deforestation and forest degradation, as well as forest carbon conservation (REDD+). In addition, climate change constitutes one of the greatest threats to forest biodiversity and ecosystem services. However, the soil organic carbon (SOC) stocks of native forests have not been incorporated into the Forest Reference Emission Levels calculations and for conservation planning under climate variability due to a lack of information. The objectives of this study were: (i) to model SOC stocks to 30 cm of native forests at a national scale using climatic, topographic and vegetation as predictor variables, and (ii) to relate SOC stocks with spatial–temporal remotely sensed indices to determine biodiversity conservation concerns due to threats from high inter-annual climate variability. We used 1040 forest soil samples (0–30 cm) to generate spatially explicit estimates of SOC native forests in Argentina at a spatial resolution of approximately 200 m. We selected 52 potential predictive environmental covariates, which represent key factors for the spatial distribution of SOC. All covariate maps were uploaded to the Google Earth Engine cloud-based computing platform for subsequent modelling. To determine the biodiversity threats from high inter-annual climate variability, we employed the spatial–temporal satellite-derived indices based on Enhanced Vegetation Index (EVI) and land surface temperature (LST) images from Landsat imagery. SOC model (0–30 cm depth) prediction accounted for 69% of the variation of this soil property across the whole native forest coverage in Argentina. Total mean SOC stock reached 2.81 Pg C (2.71–2.84 Pg C with a probability of 90%) for a total area of 460,790 km2, where Chaco forests represented 58.4% of total SOC stored, followed by Andean Patagonian forests (16.7%) and Espinal forests (10.0%). SOC stock model was fitted as a function of regional climate, which greatly influenced forest ecosystems, including precipitation (annual mean precipitation and precipitation of warmest quarter) and temperature (day land surface temperature, seasonality, maximum temperature of warmest month, month of maximum temperature, night land surface temperature, and monthly minimum temperature). Biodiversity was influenced by the SOC levels and the forest regions. In the framework of the Kyoto Protocol and REDD+, information derived in the present work from the estimate of SOC in native forests can be incorporated into the annual National Inventory Report of Argentina to assist forest management proposals. It also gives insight into how native forests can be more resilient to reduce the impact of biodiversity loss.
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来源期刊
Ecological Processes
Ecological Processes Environmental Science-Ecological Modeling
CiteScore
8.50
自引率
4.20%
发文量
64
审稿时长
13 weeks
期刊介绍: Ecological Processes is an international, peer-reviewed, open access journal devoted to quality publications in ecological studies with a focus on the underlying processes responsible for the dynamics and functions of ecological systems at multiple spatial and temporal scales. The journal welcomes manuscripts on techniques, approaches, concepts, models, reviews, syntheses, short communications and applied research for advancing our knowledge and capability toward sustainability of ecosystems and the environment. Integrations of ecological and socio-economic processes are strongly encouraged.
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