Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot

Background The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C $ ha^{-1} $) than woody savanna (51 Mg C $ ha^{-1} $). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C $ ha^{-1} $ $ yr^{-1} $ (c. 2% of the stocks of carbon per year). Conclusions The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. The results imply that policy interventions could retain carbon stored in vegetation and likely successfully slow or reverse carbon emissions. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Willcock, Simon [verfasserIn] Phillips, Oliver L Platts, Philip J Balmford, Andrew Burgess, Neil D Lovett, Jon C Ahrends, Antje Bayliss, Julian Doggart, Nike Doody, Kathryn Fanning, Eibleis Green, Jonathan MH Hall, Jaclyn Howell, Kim L Marchant, Rob Marshall, Andrew R Mbilinyi, Boniface Munishi, Pantaleon KT Owen, Nisha Swetnam, Ruth D Topp-Jorgensen, Elmer J Lewis, Simon L

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2014

Schlagwörter:	Eastern Arc Mountains Tanzania IPCC Tier 3 REDD+ Forest Disturbance Degradation Ecosystem service

Anmerkung:	© Willcock et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (

Übergeordnetes Werk:	Enthalten in: Carbon balance and management - London : Biomed Central, 2006, 9(2014), 1 vom: 28. Apr.
Übergeordnetes Werk:	volume:9 ; year:2014 ; number:1 ; day:28 ; month:04

Links:	Volltext

DOI / URN:	10.1186/1750-0680-9-2

Katalog-ID:	SPR029478383

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245	1	0	\|a Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot
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520			\|a Background The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C $ ha^{-1} $) than woody savanna (51 Mg C $ ha^{-1} $). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C $ ha^{-1} $ $ yr^{-1} $ (c. 2% of the stocks of carbon per year). Conclusions The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. The results imply that policy interventions could retain carbon stored in vegetation and likely successfully slow or reverse carbon emissions.
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700	1		\|a Phillips, Oliver L \|4 aut
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700	1		\|a Marchant, Rob \|4 aut
700	1		\|a Marshall, Andrew R \|4 aut
700	1		\|a Mbilinyi, Boniface \|4 aut
700	1		\|a Munishi, Pantaleon KT \|4 aut
700	1		\|a Owen, Nisha \|4 aut
700	1		\|a Swetnam, Ruth D \|4 aut
700	1		\|a Topp-Jorgensen, Elmer J \|4 aut
700	1		\|a Lewis, Simon L \|4 aut
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allfields	10.1186/1750-0680-9-2 doi (DE-627)SPR029478383 (SPR)1750-0680-9-2-e DE-627 ger DE-627 rakwb eng Willcock, Simon verfasserin aut Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Willcock et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C $ ha^{-1} $) than woody savanna (51 Mg C $ ha^{-1} $). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C $ ha^{-1} $ $ yr^{-1} $ (c. 2% of the stocks of carbon per year). Conclusions The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. The results imply that policy interventions could retain carbon stored in vegetation and likely successfully slow or reverse carbon emissions. Eastern Arc Mountains (dpeaa)DE-He213 Tanzania (dpeaa)DE-He213 IPCC Tier 3 (dpeaa)DE-He213 REDD+ (dpeaa)DE-He213 Forest (dpeaa)DE-He213 Disturbance (dpeaa)DE-He213 Degradation (dpeaa)DE-He213 Ecosystem service (dpeaa)DE-He213 Phillips, Oliver L aut Platts, Philip J aut Balmford, Andrew aut Burgess, Neil D aut Lovett, Jon C aut Ahrends, Antje aut Bayliss, Julian aut Doggart, Nike aut Doody, Kathryn aut Fanning, Eibleis aut Green, Jonathan MH aut Hall, Jaclyn aut Howell, Kim L aut Marchant, Rob aut Marshall, Andrew R aut Mbilinyi, Boniface aut Munishi, Pantaleon KT aut Owen, Nisha aut Swetnam, Ruth D aut Topp-Jorgensen, Elmer J aut Lewis, Simon L aut Enthalten in Carbon balance and management London : Biomed Central, 2006 9(2014), 1 vom: 28. Apr. (DE-627)515824364 (DE-600)2243512-8 1750-0680 nnns volume:9 year:2014 number:1 day:28 month:04 https://dx.doi.org/10.1186/1750-0680-9-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2014 1 28 04
spelling	10.1186/1750-0680-9-2 doi (DE-627)SPR029478383 (SPR)1750-0680-9-2-e DE-627 ger DE-627 rakwb eng Willcock, Simon verfasserin aut Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Willcock et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C $ ha^{-1} $) than woody savanna (51 Mg C $ ha^{-1} $). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C $ ha^{-1} $ $ yr^{-1} $ (c. 2% of the stocks of carbon per year). Conclusions The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. The results imply that policy interventions could retain carbon stored in vegetation and likely successfully slow or reverse carbon emissions. Eastern Arc Mountains (dpeaa)DE-He213 Tanzania (dpeaa)DE-He213 IPCC Tier 3 (dpeaa)DE-He213 REDD+ (dpeaa)DE-He213 Forest (dpeaa)DE-He213 Disturbance (dpeaa)DE-He213 Degradation (dpeaa)DE-He213 Ecosystem service (dpeaa)DE-He213 Phillips, Oliver L aut Platts, Philip J aut Balmford, Andrew aut Burgess, Neil D aut Lovett, Jon C aut Ahrends, Antje aut Bayliss, Julian aut Doggart, Nike aut Doody, Kathryn aut Fanning, Eibleis aut Green, Jonathan MH aut Hall, Jaclyn aut Howell, Kim L aut Marchant, Rob aut Marshall, Andrew R aut Mbilinyi, Boniface aut Munishi, Pantaleon KT aut Owen, Nisha aut Swetnam, Ruth D aut Topp-Jorgensen, Elmer J aut Lewis, Simon L aut Enthalten in Carbon balance and management London : Biomed Central, 2006 9(2014), 1 vom: 28. Apr. (DE-627)515824364 (DE-600)2243512-8 1750-0680 nnns volume:9 year:2014 number:1 day:28 month:04 https://dx.doi.org/10.1186/1750-0680-9-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2014 1 28 04
allfields_unstemmed	10.1186/1750-0680-9-2 doi (DE-627)SPR029478383 (SPR)1750-0680-9-2-e DE-627 ger DE-627 rakwb eng Willcock, Simon verfasserin aut Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Willcock et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C $ ha^{-1} $) than woody savanna (51 Mg C $ ha^{-1} $). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C $ ha^{-1} $ $ yr^{-1} $ (c. 2% of the stocks of carbon per year). Conclusions The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. The results imply that policy interventions could retain carbon stored in vegetation and likely successfully slow or reverse carbon emissions. Eastern Arc Mountains (dpeaa)DE-He213 Tanzania (dpeaa)DE-He213 IPCC Tier 3 (dpeaa)DE-He213 REDD+ (dpeaa)DE-He213 Forest (dpeaa)DE-He213 Disturbance (dpeaa)DE-He213 Degradation (dpeaa)DE-He213 Ecosystem service (dpeaa)DE-He213 Phillips, Oliver L aut Platts, Philip J aut Balmford, Andrew aut Burgess, Neil D aut Lovett, Jon C aut Ahrends, Antje aut Bayliss, Julian aut Doggart, Nike aut Doody, Kathryn aut Fanning, Eibleis aut Green, Jonathan MH aut Hall, Jaclyn aut Howell, Kim L aut Marchant, Rob aut Marshall, Andrew R aut Mbilinyi, Boniface aut Munishi, Pantaleon KT aut Owen, Nisha aut Swetnam, Ruth D aut Topp-Jorgensen, Elmer J aut Lewis, Simon L aut Enthalten in Carbon balance and management London : Biomed Central, 2006 9(2014), 1 vom: 28. Apr. (DE-627)515824364 (DE-600)2243512-8 1750-0680 nnns volume:9 year:2014 number:1 day:28 month:04 https://dx.doi.org/10.1186/1750-0680-9-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2014 1 28 04
allfieldsGer	10.1186/1750-0680-9-2 doi (DE-627)SPR029478383 (SPR)1750-0680-9-2-e DE-627 ger DE-627 rakwb eng Willcock, Simon verfasserin aut Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Willcock et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C $ ha^{-1} $) than woody savanna (51 Mg C $ ha^{-1} $). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C $ ha^{-1} $ $ yr^{-1} $ (c. 2% of the stocks of carbon per year). Conclusions The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. The results imply that policy interventions could retain carbon stored in vegetation and likely successfully slow or reverse carbon emissions. Eastern Arc Mountains (dpeaa)DE-He213 Tanzania (dpeaa)DE-He213 IPCC Tier 3 (dpeaa)DE-He213 REDD+ (dpeaa)DE-He213 Forest (dpeaa)DE-He213 Disturbance (dpeaa)DE-He213 Degradation (dpeaa)DE-He213 Ecosystem service (dpeaa)DE-He213 Phillips, Oliver L aut Platts, Philip J aut Balmford, Andrew aut Burgess, Neil D aut Lovett, Jon C aut Ahrends, Antje aut Bayliss, Julian aut Doggart, Nike aut Doody, Kathryn aut Fanning, Eibleis aut Green, Jonathan MH aut Hall, Jaclyn aut Howell, Kim L aut Marchant, Rob aut Marshall, Andrew R aut Mbilinyi, Boniface aut Munishi, Pantaleon KT aut Owen, Nisha aut Swetnam, Ruth D aut Topp-Jorgensen, Elmer J aut Lewis, Simon L aut Enthalten in Carbon balance and management London : Biomed Central, 2006 9(2014), 1 vom: 28. Apr. (DE-627)515824364 (DE-600)2243512-8 1750-0680 nnns volume:9 year:2014 number:1 day:28 month:04 https://dx.doi.org/10.1186/1750-0680-9-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2014 1 28 04
allfieldsSound	10.1186/1750-0680-9-2 doi (DE-627)SPR029478383 (SPR)1750-0680-9-2-e DE-627 ger DE-627 rakwb eng Willcock, Simon verfasserin aut Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Willcock et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C $ ha^{-1} $) than woody savanna (51 Mg C $ ha^{-1} $). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C $ ha^{-1} $ $ yr^{-1} $ (c. 2% of the stocks of carbon per year). Conclusions The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. The results imply that policy interventions could retain carbon stored in vegetation and likely successfully slow or reverse carbon emissions. Eastern Arc Mountains (dpeaa)DE-He213 Tanzania (dpeaa)DE-He213 IPCC Tier 3 (dpeaa)DE-He213 REDD+ (dpeaa)DE-He213 Forest (dpeaa)DE-He213 Disturbance (dpeaa)DE-He213 Degradation (dpeaa)DE-He213 Ecosystem service (dpeaa)DE-He213 Phillips, Oliver L aut Platts, Philip J aut Balmford, Andrew aut Burgess, Neil D aut Lovett, Jon C aut Ahrends, Antje aut Bayliss, Julian aut Doggart, Nike aut Doody, Kathryn aut Fanning, Eibleis aut Green, Jonathan MH aut Hall, Jaclyn aut Howell, Kim L aut Marchant, Rob aut Marshall, Andrew R aut Mbilinyi, Boniface aut Munishi, Pantaleon KT aut Owen, Nisha aut Swetnam, Ruth D aut Topp-Jorgensen, Elmer J aut Lewis, Simon L aut Enthalten in Carbon balance and management London : Biomed Central, 2006 9(2014), 1 vom: 28. Apr. (DE-627)515824364 (DE-600)2243512-8 1750-0680 nnns volume:9 year:2014 number:1 day:28 month:04 https://dx.doi.org/10.1186/1750-0680-9-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2014 1 28 04
language	English
source	Enthalten in Carbon balance and management 9(2014), 1 vom: 28. Apr. volume:9 year:2014 number:1 day:28 month:04
sourceStr	Enthalten in Carbon balance and management 9(2014), 1 vom: 28. Apr. volume:9 year:2014 number:1 day:28 month:04
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Eastern Arc Mountains Tanzania IPCC Tier 3 REDD+ Forest Disturbance Degradation Ecosystem service
isfreeaccess_bool	true
container_title	Carbon balance and management
authorswithroles_txt_mv	Willcock, Simon @@aut@@ Phillips, Oliver L @@aut@@ Platts, Philip J @@aut@@ Balmford, Andrew @@aut@@ Burgess, Neil D @@aut@@ Lovett, Jon C @@aut@@ Ahrends, Antje @@aut@@ Bayliss, Julian @@aut@@ Doggart, Nike @@aut@@ Doody, Kathryn @@aut@@ Fanning, Eibleis @@aut@@ Green, Jonathan MH @@aut@@ Hall, Jaclyn @@aut@@ Howell, Kim L @@aut@@ Marchant, Rob @@aut@@ Marshall, Andrew R @@aut@@ Mbilinyi, Boniface @@aut@@ Munishi, Pantaleon KT @@aut@@ Owen, Nisha @@aut@@ Swetnam, Ruth D @@aut@@ Topp-Jorgensen, Elmer J @@aut@@ Lewis, Simon L @@aut@@
publishDateDaySort_date	2014-04-28T00:00:00Z
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language_de	englisch
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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Background The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C $ ha^{-1} $) than woody savanna (51 Mg C $ ha^{-1} $). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C $ ha^{-1} $ $ yr^{-1} $ (c. 2% of the stocks of carbon per year). Conclusions The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. 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author	Willcock, Simon
spellingShingle	Willcock, Simon misc Eastern Arc Mountains misc Tanzania misc IPCC Tier 3 misc REDD+ misc Forest misc Disturbance misc Degradation misc Ecosystem service Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot
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topic_title	Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot Eastern Arc Mountains (dpeaa)DE-He213 Tanzania (dpeaa)DE-He213 IPCC Tier 3 (dpeaa)DE-He213 REDD+ (dpeaa)DE-He213 Forest (dpeaa)DE-He213 Disturbance (dpeaa)DE-He213 Degradation (dpeaa)DE-He213 Ecosystem service (dpeaa)DE-He213
topic	misc Eastern Arc Mountains misc Tanzania misc IPCC Tier 3 misc REDD+ misc Forest misc Disturbance misc Degradation misc Ecosystem service
topic_unstemmed	misc Eastern Arc Mountains misc Tanzania misc IPCC Tier 3 misc REDD+ misc Forest misc Disturbance misc Degradation misc Ecosystem service
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title	Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot
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title_full	Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot
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author_browse	Willcock, Simon Phillips, Oliver L Platts, Philip J Balmford, Andrew Burgess, Neil D Lovett, Jon C Ahrends, Antje Bayliss, Julian Doggart, Nike Doody, Kathryn Fanning, Eibleis Green, Jonathan MH Hall, Jaclyn Howell, Kim L Marchant, Rob Marshall, Andrew R Mbilinyi, Boniface Munishi, Pantaleon KT Owen, Nisha Swetnam, Ruth D Topp-Jorgensen, Elmer J Lewis, Simon L
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title_sort	quantifying and understanding carbon storage and sequestration within the eastern arc mountains of tanzania, a tropical biodiversity hotspot
title_auth	Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot
abstract	Background The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C $ ha^{-1} $) than woody savanna (51 Mg C $ ha^{-1} $). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C $ ha^{-1} $ $ yr^{-1} $ (c. 2% of the stocks of carbon per year). Conclusions The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. The results imply that policy interventions could retain carbon stored in vegetation and likely successfully slow or reverse carbon emissions. © Willcock et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
abstractGer	Background The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C $ ha^{-1} $) than woody savanna (51 Mg C $ ha^{-1} $). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C $ ha^{-1} $ $ yr^{-1} $ (c. 2% of the stocks of carbon per year). Conclusions The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. The results imply that policy interventions could retain carbon stored in vegetation and likely successfully slow or reverse carbon emissions. © Willcock et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
abstract_unstemmed	Background The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C $ ha^{-1} $) than woody savanna (51 Mg C $ ha^{-1} $). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C $ ha^{-1} $ $ yr^{-1} $ (c. 2% of the stocks of carbon per year). Conclusions The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. The results imply that policy interventions could retain carbon stored in vegetation and likely successfully slow or reverse carbon emissions. © Willcock et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
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title_short	Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot
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author2	Phillips, Oliver L Platts, Philip J Balmford, Andrew Burgess, Neil D Lovett, Jon C Ahrends, Antje Bayliss, Julian Doggart, Nike Doody, Kathryn Fanning, Eibleis Green, Jonathan MH Hall, Jaclyn Howell, Kim L Marchant, Rob Marshall, Andrew R Mbilinyi, Boniface Munishi, Pantaleon KT Owen, Nisha Swetnam, Ruth D Topp-Jorgensen, Elmer J Lewis, Simon L
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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Background The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C $ ha^{-1} $) than woody savanna (51 Mg C $ ha^{-1} $). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C $ ha^{-1} $ $ yr^{-1} $ (c. 2% of the stocks of carbon per year). Conclusions The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. 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