Abstract
There is a growing concern over change in vegetation dynamics and drought patterns with the increasing climate variability and warming trends in Africa, particularly in the semiarid regions of East Africa. Here, several geospatial techniques and datasets were used to analyze the spatio-temporal vegetation dynamics in response to climate (precipitation and temperature) and drought in Eritrea from 2000 to 2017. A pixel-based trend analysis was performed, and a Pearson correlation coefficient was computed between vegetation indices and climate variables. In addition, vegetation condition index (VCI) and standard precipitation index (SPI) classifications were used to assess drought patterns in the country. The results demonstrated that there was a decreasing NDVI (Normalized Difference Vegetation Index) slope at both annual and seasonal time scales. In the study area, 57.1% of the pixels showed a decreasing annual NDVI trend, while the significance was higher in South-Western Eritrea. In most of the agro-ecological zones, the shrublands and croplands showed decreasing NDVI trends. About 87.16% of the study area had a positive correlation between growing season NDVI and precipitation (39.34%, p < 0.05). The Gash Barka region of the country showed the strongest and most significant correlations between NDVI and precipitation values. The specific drought assessments based on VCI and SPI summarized that Eritrea had been exposed to recurrent droughts of moderate to extreme conditions during the last 18 years. Based on the correlation analysis and drought patterns, this study confirms that low precipitation was mainly attributed to the slowly declining vegetation trends and increased drought conditions in the semi-arid region. Therefore, immediate action is needed to minimize the negative impact of climate variability and increasing aridity in vegetation and ecosystem services.
Highlights
Climate is a prime driver of vegetation dynamics and it dictates the distributions of plant species and vegetation [1]
NDVI drought classification of different levels of the growing season from a maximum of 35% to a minimum of 0% was extracted for each year of the observation period (Table 1)
The Moist Lowland and Semi-Desert zones showed the highest decrease in NDVMI torsetnodfsth(Feiaggurroe-sec1obloagnidca5l bz)o;ntehsisofcEouriltdreba,eemxcaeipntlyfodr utheetSoutbheHiunmcriedazsionnge,asrhidoiwtyedordreeccruearsreinngt dmreoaunghNtDs VaIs trthenedrevsapluoenss.eThtoe McliomisattLeovwalrainadbleasndanSedmdi-eDfoerseesrttaztioonnesaschtiovwiteieds.theThhieghSeustbdHecuremaisde aingrNo-DeVcoIlotrgeincdals z(Foingeurloecsa1tbedanind t5hbe);EtahsistecronuEldscbaerpmmaeinnltysdhuowe teodthane iinnccrreeaassiinngg amriedaintyNorDrVeIcutrrerenndt, edvroiduegnhttlsy absectahuesreesthpeonessecatropmcliemnat theavsabreiaebnlepsroantedctdedefoarseastantaiotinonaacltipvaitrikess. iTnchee 2S0u0b6.HIunmthide apgarrok, ecological zone located in the Eastern Escarpment showed an increasing mean NDVI trend, because the escarpment has been protected as a national park since 2006
Summary
Climate is a prime driver of vegetation dynamics and it dictates the distributions of plant species and vegetation [1]. With increases in climate variability and a warming trend in Sub-Saharan Africa, and in East Africa, there have been changes towards extreme rainfall events, and an increase in seasonal mean temperature [3]. Such trends can bring about an impact on vegetation change and agricultural production, especially in countries like Eritrea, where the majority of its population depends on rain-fed agriculture. There is a need to develop proper drought monitoring methods in order to mitigate and adapt to climate change impacts. Drought monitoring usually has many aspects, such as hydrological, meteorological, and agricultural aspects, and analyzing vegetation dynamics and climate variables together can lead to a better understanding of interconnected and correlated drought-related parameters [4]
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