Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1111/gcb.13886 |
Detection of climate change-driven trends in phytoplankton phenology | |
Henson, Stephanie A.1; Cole, Harriet S.2; Hopkins, Jason3; Martin, Adrian P.1; Yool, Andrew1 | |
2018 | |
发表期刊 | GLOBAL CHANGE BIOLOGY |
ISSN | 1354-1013 |
EISSN | 1365-2486 |
出版年 | 2018 |
卷号 | 24期号:1页码:E101-E111 |
文章类型 | Article |
语种 | 英语 |
国家 | England; Scotland; USA |
英文摘要 | The timing of the annual phytoplankton spring bloom is likely to be altered in response to climate change. Quantifying that response has, however, been limited by the typically coarse temporal resolution (monthly) of global climate models. Here, we use higher resolution model output (maximum 5 days) to investigate how phytoplankton bloom timing changes in response to projected 21st century climate change, and how the temporal resolution of data influences the detection of long-term trends. We find that bloom timing generally shifts later at mid-latitudes and earlier at high and low latitudes by similar to 5 days per decade to 2100. The spatial patterns of bloom timing are similar in both low (monthly) and high (5 day) resolution data, although initiation dates are later at low resolution. The magnitude of the trends in bloom timing from 2006 to 2100 is very similar at high and low resolution, with the result that the number of years of data needed to detect a trend in phytoplankton phenology is relatively insensitive to data temporal resolution. We also investigate the influence of spatial scales on bloom timing and find that trends are generally more rapidly detectable after spatial averaging of data. Our results suggest that, if pinpointing the start date of the spring bloom is the priority, the highest possible temporal resolution data should be used. However, if the priority is detecting long-term trends in bloom timing, data at a temporal resolution of 20 days are likely to be sufficient. Furthermore, our results suggest that data sources which allow for spatial averaging will promote more rapid trend detection. |
英文关键词 | bloom initiation bloom timing climate model climate warming ocean monitoring RCP8.5 sustained observations |
领域 | 气候变化 ; 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000426506100009 |
WOS关键词 | LONG-TERM TRENDS ; PLANKTON PRODUCTION ; OCEAN ; CHLOROPHYLL ; IMPACT ; BLOOM ; SEASONALITY ; ECOSYSTEMS ; EXPORT ; MODEL |
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/17855 |
专题 | 气候变化 资源环境科学 |
作者单位 | 1.Natl Oceanog Ctr, Southampton, Hants, England; 2.Marine Scotland, Marine Lab, Aberdeen, Scotland; 3.Bigelow Lab Ocean Sci, East Boothbay, ME USA |
推荐引用方式 GB/T 7714 | Henson, Stephanie A.,Cole, Harriet S.,Hopkins, Jason,et al. Detection of climate change-driven trends in phytoplankton phenology[J]. GLOBAL CHANGE BIOLOGY,2018,24(1):E101-E111. |
APA | Henson, Stephanie A.,Cole, Harriet S.,Hopkins, Jason,Martin, Adrian P.,&Yool, Andrew.(2018).Detection of climate change-driven trends in phytoplankton phenology.GLOBAL CHANGE BIOLOGY,24(1),E101-E111. |
MLA | Henson, Stephanie A.,et al."Detection of climate change-driven trends in phytoplankton phenology".GLOBAL CHANGE BIOLOGY 24.1(2018):E101-E111. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论