DOI: 10.1111/gcb.13438
论文题名: Evaluating, predicting and mapping belowground carbon stores in Kenyan mangroves
作者: Gress S.K. ; Huxham M. ; Kairo J.G. ; Mugi L.M. ; Briers R.A.
刊名: Global Change Biology
出版年: 2017
卷: 23, 期: 1 起始页码: 224
结束页码: 234
语种: 英语
英文关键词: belowground carbon
; carbon loss
; coastal carbon stores
; mangrove sediment
; mapping
Scopus关键词: carbon sink
; climate change
; deforestation
; emission control
; forest management
; mangrove
; mapping
; Kenya
; Rhizophora
; Rhizophoraceae
; Vanga
英文摘要: Despite covering only approximately 138 000 km2, mangroves are globally important carbon sinks with carbon density values three to four times that of terrestrial forests. A key challenge in evaluating the carbon benefits from mangrove forest conservation is the lack of rigorous spatially resolved estimates of mangrove sediment carbon stocks; most mangrove carbon is stored belowground. Previous work has focused on detailed estimations of carbon stores over relatively small areas, which has obvious limitations in terms of generality and scope of application. Most studies have focused only on quantifying the top 1 m of belowground carbon (BGC). Carbon stored at depths beyond 1 m, and the effects of mangrove species, location and environmental context on these stores, are poorly studied. This study investigated these variables at two sites (Gazi and Vanga in the south of Kenya) and used the data to produce a country-specific BGC predictive model for Kenya and map BGC store estimates throughout Kenya at spatial scales relevant for climate change research, forest management and REDD+ (reduced emissions from deforestation and degradation). The results revealed that mangrove species was the most reliable predictor of BGC; Rhizophora muronata had the highest mean BGC with 1485.5 t C ha−1. Applying the species-based predictive model to a base map of species distribution in Kenya for the year 2010 with a 2.5 m2 resolution produced an estimate of 69.41 Mt C [±9.15 95% confidence interval (C.I.)] for BGC in Kenyan mangroves. When applied to a 1992 mangrove distribution map, the BGC estimate was 75.65 Mt C (±12.21 95% C.I.), an 8.3% loss in BGC stores between 1992 and 2010 in Kenya. The country-level mangrove map provides a valuable tool for assessing carbon stocks and visualizing the distribution of BGC. Estimates at the 2.5 m2 resolution provide sufficient details for highlighting and prioritizing areas for mangrove conservation and restoration. © 2016 John Wiley & Sons Ltd 资助项目: Gress, S.K.
; School of Life, Sport and Social Sciences, Edinburgh Napier University, Sighthill Campus, United Kingdom
; 电子邮件: selenagress@gmail.com
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/61201
Appears in Collections: 影响、适应和脆弱性
There are no files associated with this item.
作者单位: School of Life, Sport and Social Sciences, Edinburgh Napier University, Sighthill Campus, Edinburgh, United Kingdom; Kenya Marine and Fisheries Research Institute, P.O. Box 81651, Mombasa, Kenya
Recommended Citation:
Gress S.K.,Huxham M.,Kairo J.G.,et al. Evaluating, predicting and mapping belowground carbon stores in Kenyan mangroves[J]. Global Change Biology,2017-01-01,23(1)