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Assessment of climate impact on vegetation dynamics over East Africa from 1982 to 2015

Located across the equator, the East Africa region is among regions of Africa which have previously known the severe vegetation degradation. Some known reasons are associated with the climate change events and unprofessional agricultural practices. For this purpose, the Advanced Very High Resolution...

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Autores principales: Kalisa, Wilson, Igbawua, Tertsea, Henchiri, Malak, Ali, Shahzad, Zhang, Sha, Bai, Yun, Zhang, Jiahua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6856068/
https://www.ncbi.nlm.nih.gov/pubmed/31727960
http://dx.doi.org/10.1038/s41598-019-53150-0
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author Kalisa, Wilson
Igbawua, Tertsea
Henchiri, Malak
Ali, Shahzad
Zhang, Sha
Bai, Yun
Zhang, Jiahua
author_facet Kalisa, Wilson
Igbawua, Tertsea
Henchiri, Malak
Ali, Shahzad
Zhang, Sha
Bai, Yun
Zhang, Jiahua
author_sort Kalisa, Wilson
collection PubMed
description Located across the equator, the East Africa region is among regions of Africa which have previously known the severe vegetation degradation. Some known reasons are associated with the climate change events and unprofessional agricultural practices. For this purpose, the Advanced Very High Resolution Radiometer (AVHRR) version 3 NDVI (NDVI3g) and Climate Research Unit (CRU) datasets for precipitation and temperature were used to assess the impact of climate factors on vegetation dynamics over East Africa from 1982 to 2015. Pearson correlation of NDVI and climate factors were also explored to investigate the short (October - December) rainy seasons. The phenological metrics of the region was also extracted to understand the seasonal cycle of vegetation. The results show that a positive linear trend of 14.50 × 10(−4) for mean annual NDVI before 1998, where as a negative linear trend of −9.64 × 10(−4) was found after 1998. The Break Point (BP) was obtained in 1998, which suggests to nonlinear responses of NDVI to climate and non-climate drivers. ENSO-vegetation in El-nino years showed a weak teleconnection between ENSO and vegetation growth changes of croplands. Also, the analyzed correlations on NDVI data resulted to the higher correlation between NDVI and precipitation than that with temperature. The Hurst exponent result showed that about, 18.63% pixels exhibited a behavior, typical of random walk (H = 0.5) suggesting that NDVI growth changes may eventually persist, overturn or fluctuate randomly in the future depending on the drivers. Vegetation trends with sustainable (unsustainable) trends were 36.8% (44.6%). Strikingly, about 20% of the total vegetated area showed unsustainable trend from degradation to amelioration. More so, results reveal that the vegetation of the croplands (non-croplands) over East Africa changed insignificantly by 6.9 × 10(−5)/yr (5.16 × 10(−4)/yr), suggesting that non-croplands are fast getting reduced Nonetheless, the NDVI growth responses to monthly and seasonal changes in climate were adjudged to be complex and dynamic. Seasonally, the short rainy season showed the higher variability in NDVI than the long rainy season. Also, the DJF, MAM and SON seasons are strongly driven by precipitation variation effect of ENSO versus NDVI series.
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spelling pubmed-68560682019-11-19 Assessment of climate impact on vegetation dynamics over East Africa from 1982 to 2015 Kalisa, Wilson Igbawua, Tertsea Henchiri, Malak Ali, Shahzad Zhang, Sha Bai, Yun Zhang, Jiahua Sci Rep Article Located across the equator, the East Africa region is among regions of Africa which have previously known the severe vegetation degradation. Some known reasons are associated with the climate change events and unprofessional agricultural practices. For this purpose, the Advanced Very High Resolution Radiometer (AVHRR) version 3 NDVI (NDVI3g) and Climate Research Unit (CRU) datasets for precipitation and temperature were used to assess the impact of climate factors on vegetation dynamics over East Africa from 1982 to 2015. Pearson correlation of NDVI and climate factors were also explored to investigate the short (October - December) rainy seasons. The phenological metrics of the region was also extracted to understand the seasonal cycle of vegetation. The results show that a positive linear trend of 14.50 × 10(−4) for mean annual NDVI before 1998, where as a negative linear trend of −9.64 × 10(−4) was found after 1998. The Break Point (BP) was obtained in 1998, which suggests to nonlinear responses of NDVI to climate and non-climate drivers. ENSO-vegetation in El-nino years showed a weak teleconnection between ENSO and vegetation growth changes of croplands. Also, the analyzed correlations on NDVI data resulted to the higher correlation between NDVI and precipitation than that with temperature. The Hurst exponent result showed that about, 18.63% pixels exhibited a behavior, typical of random walk (H = 0.5) suggesting that NDVI growth changes may eventually persist, overturn or fluctuate randomly in the future depending on the drivers. Vegetation trends with sustainable (unsustainable) trends were 36.8% (44.6%). Strikingly, about 20% of the total vegetated area showed unsustainable trend from degradation to amelioration. More so, results reveal that the vegetation of the croplands (non-croplands) over East Africa changed insignificantly by 6.9 × 10(−5)/yr (5.16 × 10(−4)/yr), suggesting that non-croplands are fast getting reduced Nonetheless, the NDVI growth responses to monthly and seasonal changes in climate were adjudged to be complex and dynamic. Seasonally, the short rainy season showed the higher variability in NDVI than the long rainy season. Also, the DJF, MAM and SON seasons are strongly driven by precipitation variation effect of ENSO versus NDVI series. Nature Publishing Group UK 2019-11-14 /pmc/articles/PMC6856068/ /pubmed/31727960 http://dx.doi.org/10.1038/s41598-019-53150-0 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Kalisa, Wilson
Igbawua, Tertsea
Henchiri, Malak
Ali, Shahzad
Zhang, Sha
Bai, Yun
Zhang, Jiahua
Assessment of climate impact on vegetation dynamics over East Africa from 1982 to 2015
title Assessment of climate impact on vegetation dynamics over East Africa from 1982 to 2015
title_full Assessment of climate impact on vegetation dynamics over East Africa from 1982 to 2015
title_fullStr Assessment of climate impact on vegetation dynamics over East Africa from 1982 to 2015
title_full_unstemmed Assessment of climate impact on vegetation dynamics over East Africa from 1982 to 2015
title_short Assessment of climate impact on vegetation dynamics over East Africa from 1982 to 2015
title_sort assessment of climate impact on vegetation dynamics over east africa from 1982 to 2015
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6856068/
https://www.ncbi.nlm.nih.gov/pubmed/31727960
http://dx.doi.org/10.1038/s41598-019-53150-0
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