Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1111/gcb.14298 |
Unraveling past impacts of climate change and land management on historic peatland development using proxy-based reconstruction, monitoring data and process modeling | |
Heinemeyer, Andreas1; Swindles, Graeme T.2 | |
2018-09-01 | |
发表期刊 | GLOBAL CHANGE BIOLOGY
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ISSN | 1354-1013 |
EISSN | 1365-2486 |
出版年 | 2018 |
卷号 | 24期号:9页码:4131-4142 |
文章类型 | Article |
语种 | 英语 |
国家 | England |
英文摘要 | Peatlands represent globally significant soil carbon stores that have been accumulating for millennia under water-logged conditions. However, deepening water-table depths (WTD) from climate change or human-induced drainage could stimulate decomposition resulting in peatlands turning from carbon sinks to carbon sources. Contemporary WTD ranges of testate amoebae (TA) are commonly used to predict past WTD in peatlands using quantitative transfer function models. Here we present, for the first time, a study comparing TA-based WTD reconstructions to instrumentally monitored WTD and hydrological model predictions using the MILLENNIA peatland model to examine past peatland responses to climate change and land management. Although there was very good agreement between monitored and modeled WTD, TA-reconstructed water table was consistently deeper. Predictions from a larger European TA transfer function data set were wetter, but the overall directional fit to observed WTD was better for a TA transfer function based on data from northern England. We applied a regression-based offset correction to the reconstructed WTD for the validation period (1931-2010). We then predicted WTD using available climate records as MILLENNIA model input and compared the offset-corrected TA reconstruction to MILLENNIA WTD predictions over an extended period (1750-1931) with available climate reconstructions. Although the comparison revealed striking similarities in predicted overall WTD patterns, particularly for a recent drier period (1965-1995), there were clear periods when TA-based WTD predictions underestimated (i.e. drier during 1830-1930) and overestimated (i.e. wetter during 1760-1830) past WTD compared to MILLENNIA model predictions. Importantly, simulated grouse moor management scenarios may explain the drier TA WTD predictions, resulting in considerable model predicted carbon losses and reduced methane emissions, mainly due to drainage. This study demonstrates the value of a site-specific and combined data-model validation step toward using TA-derived moisture conditions to understand past climate-driven peatland development and carbon budgets alongside modeling likely management impacts. |
英文关键词 | carbon budgets carbon emissions MILLENNIA model peat accumulation peatland management peatlands testate amoebae water-table |
领域 | 气候变化 ; 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000441746900021 |
WOS关键词 | WATER-TABLE DEPTH ; BLANKET PEAT ; METHANE OXIDATION ; ORGANIC-CARBON ; BOG ; ACCUMULATION ; HOLOCENE ; SOIL ; UK ; DECOMPOSITION |
WOS类目 | Biodiversity Conservation ; Ecology ; Environmental Sciences |
WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/17593 |
专题 | 气候变化 资源环境科学 |
作者单位 | 1.Univ York, Stockholm Environm Inst, Environm Dept, York, N Yorkshire, England; 2.Univ Leeds, Sch Geog, Water Leeds, Leeds, W Yorkshire, England |
推荐引用方式 GB/T 7714 | Heinemeyer, Andreas,Swindles, Graeme T.. Unraveling past impacts of climate change and land management on historic peatland development using proxy-based reconstruction, monitoring data and process modeling[J]. GLOBAL CHANGE BIOLOGY,2018,24(9):4131-4142. |
APA | Heinemeyer, Andreas,&Swindles, Graeme T..(2018).Unraveling past impacts of climate change and land management on historic peatland development using proxy-based reconstruction, monitoring data and process modeling.GLOBAL CHANGE BIOLOGY,24(9),4131-4142. |
MLA | Heinemeyer, Andreas,et al."Unraveling past impacts of climate change and land management on historic peatland development using proxy-based reconstruction, monitoring data and process modeling".GLOBAL CHANGE BIOLOGY 24.9(2018):4131-4142. |
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