| 1. |
- Abdi, Hakim, et al.
(författare)
-
The El Niño – La Niña cycle and recent trends in supply and demand of net primary productivity in African drylands
- 2016
-
Ingår i: Climatic Change. - : Springer Science and Business Media LLC. - 0165-0009 .- 1573-1480. ; 138:1, s. 111-125
-
Tidskriftsartikel (refereegranskat)abstract
- Inter-annual climatic variability over a large portion of sub-Saharan Africa is under the influence of the El Niño-Southern Oscillation (ENSO). Extreme variability in climate is a threat to rural livelihoods in sub-Saharan Africa, yet the role of ENSO in the balance between supply and demand of net primary productivity (NPP) over this region is unclear. Here, we analyze the impact of ENSO on this balance in a spatially explicit framework using gridded population data from the WorldPop project, satellite-derived data on NPP supply, and statistical data from the United Nations. Our analyses demonstrate that between 2000 and 2013 fluctuations in the supply of NPP associated with moderate ENSO events average ± 2.8 g C m−2 yr.−1 across sub-Saharan drylands. The greatest sensitivity is in arid Southern Africa where a + 1 °C change in the Niño-3.4 sea surface temperature index is associated with a mean change in NPP supply of −6.6 g C m−2 yr.−1. Concurrently, the population-driven trend in NPP demand averages 3.5 g C m−2 yr.−1 over the entire region with densely populated urban areas exhibiting the highest mean demand for NPP. Our findings highlight the importance of accounting for the role ENSO plays in modulating the balance between supply and demand of NPP in sub-Saharan drylands. An important implication of these findings is that increase in NPP demand for socio-economic metabolism must be taken into account within the context of climate-modulated supply.
|
|
| 2. |
- Abdi, Hakim, et al.
(författare)
-
The supply and demand of net primary production in the Sahel
- 2014
-
Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 9:9, s. 11-094003
-
Tidskriftsartikel (refereegranskat)abstract
- Net primary production (NPP) is the principal source of energy for ecosystems and, by extension, human populations that depend on them. The relationship between the supply and demand of NPP is important for the assessment of socio-ecological vulnerability. We present an analysis of the supply and demand of NPP in the Sahel using NPP estimates from the MODIS sensor and agri-environmental data from FAOSTAT. This synergistic approach allows for a spatially explicit estimation of human impact on ecosystems. We estimated the annual amount of NPP required to derive food, fuel and feed between 2000 and 2010 for 22 countries in sub-Saharan Africa. When comparing annual estimates of supply and demand of NPP, we found that demand increased from 0.44 PgC to 1.13 PgC, representing 19% and 41%, respectively, of available supply due to a 31% increase in the human population between 2000 and 2010. The demand for NPP has been increasing at an annual rate of 2.2% but NPP supply was near-constant with an inter-annual variability of approximately 1.7%. Overall, there were statistically significant (p < 0.05) increases in the NPP of cropland (+6.0%), woodland (+6.1%) and grassland/savanna (+9.4%), and a decrease in the NPP of forests (−0.7%). On the demand side, the largest increase was for food (20.4%) followed by feed (16.7%) and fuel (5.5%). The supply-demand balance of NPP is a potentially important tool from the standpoint of sustainable development, and as an indicator of stresses on the environment stemming from increased consumption of biomass.
|
|
| 3. |
- Ahmed, Mohamed, et al.
(författare)
-
Dynamic response of NDVI to soil moisture variations during different hydrological regimes in the Sahel region
- 2017
-
Ingår i: International Journal of Remote Sensing. - : Informa UK Limited. - 1366-5901 .- 0143-1161. ; 38:19, s. 5408-5429
-
Tidskriftsartikel (refereegranskat)abstract
- Over the last few decades, the African Sahel has become thefocus of many studies regarding vegetation dynamics and theirrelationships with climate and people. This is because rainfalllimits the production of biomass in the region, a resource onwhich people are directly dependent for their livelihoods. In thisstudy, we utilized a remote-sensing approach to answering thefollowing two questions: (1) how does the dynamic relationshipbetween soil moisture and plant growth vary across hydrologi-cal regimes, and (2) are vegetation-type-dependent responsesto soil moisture availability detectable from satellite imagery? Inorder to answer these questions, we studied the relationshipbetween monthly modelled soil moisture as an indicator forwater availability and the remotely sensed normalized differ-ence vegetation index (NDVI) as a proxy for vegetation growthbetween a“recovery rainfall period”(1982 to 1997) and a“stable rainfall period”(1998 to 2013), at different time lagsacross the Sahel region. Using windowed cross-correlation, wefind a strong significant positive relationship between NDVI andsoil moisture at a concurrent time and at NDVI lagging behindsoil moisture by 1 month for grassland, cropland, and decid-uous shrubland vegetation–the dominant vegetation classes inthe Sahel. South of the Sahel (the Sudanian and Guinean areas),wefind longer optimal lags (soil moisture lagged by 1–3 months) in association with mixed forest and deciduousshrubland. Wefind no major significant change in optimal lagbetween the recovery and stable periods in the Sahelian region;however, in the Sudanian and Guinean areas, we observe atrend towards shorter time lags. This change in optimal lagsuggests a vegetation change, which may be a response to aclimatic shift or land-use change. This approach of identifyingspatiotemporal trends in optimal lag correlations between mod-elled soil moisture and NDVI could prove to be a useful tool formapping vegetation change and ecosystem behaviour, in turnhelping inform climate change mitigation approaches and agri-cultural planning
|
|
| 4. |
|
|
| 5. |
- Hickler, Thomas, et al.
(författare)
-
Precipitation controls Sahel greening trend
- 2005
-
Ingår i: Geophysical Research Letters. - 1944-8007. ; 32:21
-
Tidskriftsartikel (refereegranskat)abstract
- The Sahel region has been identified as a "hot spot'' of global environmental change, but understanding of the roles of different climatic and anthropogenic forcing factors driving change in the region is incomplete. We show that a process-based ecosystem model driven by climatic and atmospheric CO2 data alone closely reproduces the satellite-observed greening trend of the Sahel vegetation and its interannual variability between 1982 and 1998. Changes in precipitation were identified as the primary driver of the aggregated simulated vegetation changes. According to the model, the increasing carbon uptake through vegetation was associated with an increasing relative carbon sink; but integrated over the whole period, the Sahel was predicted to be a net source of carbon.
|
|
| 6. |
- Jamali, Sadegh, et al.
(författare)
-
Automated mapping of vegetation trends with polynomials using NDVI imagery over the Sahel
- 2014
-
Ingår i: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257. ; 141, s. 79-89
-
Tidskriftsartikel (refereegranskat)abstract
- Over the last few decades, increasing rates of change in the structure and function of ecosystems have been brought about by human modification of land cover, of which a major component is vegetation. Metrics derived from linear regression models applied to high temporal resolution satellite data are commonly used to estimate rates of vegetation change. This approach implicitly assumes that vegetation changes gradually and linearly, which may not always be the case. In order to account for non-linear change in annual observations of vegetation from satellites, we test and apply a polynomial fitting-based scheme to annual GIMMS (Global Inventory Modeling and Mapping Studies)–NDVI (Normalized Difference Vegetation Index) observations for North Africa (including the Sahel) for the period 1982–2006. The scheme divides vegetation change into cubic, quadratic, linear, and “concealed” trend behaviors, the latter indicating that while no net change in vegetation amount has occurred over the period, the curve exhibits at least one minimum or/and maximum indicating that the vegetation has undergone change during the elapsed time period. Our results show that just over half the study area (51.9%) exhibit trends that are statistically significant, with a dominance of positive linear trends (22.2%) that are distributed in an east-west band across the Sahel, thus confirming previous studies. Non-linear trends occur much less frequently and are more widely scattered. Nevertheless, they tend to cluster within or on the outskirts of zones of linear trend, underscoring their importance for detecting anomalous change features. We also show that the ratio of linear vs. non-linear trends tends to be associated with different land cover types/land cover change estimates, many of which reflect biome-level controls on vegetation dynamics. However, more local drivers related to direct human impact, such as urbanization, cannot be ruled out. Our change detection approach retains the more complex signatures embedded in long-term time series by preserving details about change rates, therefore allowing for a more subtle interpretation of change trajectories on a case-by-case basis. The fitting method is entirely automated and does not require the judicious selection of thresholds. However, while polynomials can give a better fit, they like linear models are based on assumptions, and may sometimes lead to oversimplification or miss short-term variations. Our method can help to contribute more accurate information to one of the major goals of the burgeoning field of land change science, namely to observe and monitor land changes underway throughout the world.
|
|
| 7. |
- Jamali, Sadegh, et al.
(författare)
-
Comparing parametric and non-parametric approaches for estimating trends in multi-year NDVI
- 2012
-
Konferensbidrag (refereegranskat)abstract
- The aim of this study is to systematically compare parametric and non-parametric techniques for analyzing trends in annual NDVI derived from NOAA AVHRR sensor in order to examine how trend type and departure from normality assumptions affect the accuracy of detecting long-term change. To generate annual data, the mean NDVI of a four-month long ‘green’ season was computed for fifteen sites (located in Africa, Spain, Italy, Sweden, and Iraq) from the GIMMS product for the periods 1982-2006. Trends in these time series were then estimated by Ordinary Least-Squares (OLS) regression (parametric) and the combined Mann-Kendall test with Theil-Sen slope estimator (non-parametric), and compared using slope value and statistical significance measures. We also estimated optimal polynomial model for the annual NDVI, by using Akaike Information Criterion (AIC), to determine the trend type at each site. Results indicate that slopes and their statistical significances obtained from the two approaches at sites with low degree polynomials (mostly linear) and steep monotonic (gradually increasing or decreasing) trends compare favourably with one another. At sites with weak linear slopes, the two approaches had similar results as well. Exceptions include sites with abrupt step-like changes resulting in departures from linearity and consequently high degree polynomials where the least-squares method outperformed the Mann-Kendall Theil-Sen method. In sum, we conclude that OLS is superior for detecting NDVI trends using annual data though further investigation using other techniques is recommended.
|
|
| 8. |
- Jamali, Sadegh, et al.
(författare)
-
Detecting changes in vegetation trends using time series segmentation
- 2015
-
Ingår i: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257 .- 1879-0704. ; 156:January, s. 182-195
-
Tidskriftsartikel (refereegranskat)abstract
- Although satellite-based sensors have made vegetation data series available for several decades, the detection of vegetation trend and change is not yet straightforward. This is partly due to the scarcity of available change detection algorithms suitable for identifying and characterizing both abrupt and non-abrupt changes, without sacrificing accuracy or computational speed. We propose a user-friendly program for analysing vegetation time series, with two main application domains: generalising vegetation trends to main features, and characterizing vegetation trend changes. This program, Detecting Breakpoints and Estimating Segments in Trend (DBEST) uses a novel segmentation algorithm which simplifies the trend into linear segments using one of three user-defined parameters: a generalisation-threshold parameter δ, the m largest changes, or a threshold β for the magnitude of changes of interest for detection. The outputs of DBEST are the simplified trend, the change type (abrupt or non-abrupt), and estimates for the characteristics (time and magnitude) of the change. DBEST was tested and evaluated using simulated Normalized Difference Vegetation Index (NDVI) data at two sites, which included different types of changes. Evaluation results demonstrate that DBEST quickly and robustly detects both abrupt and non-abrupt changes, and accurately estimates change time and magnitude. DBEST was also tested using data from the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI image time series for Iraq for the period 1982–2006, and was able to detect and quantify major change over the area. This showed that DBEST is able to detect and characterize changes over large areas. We conclude that DBEST is a fast, accurate and flexible tool for trend detection, and is applicable to global change studies using time series of remotely sensed data sets.
|
|
| 9. |
- Jamali, Sadegh, et al.
(författare)
-
Investigating temporal relationships between rainfall, soil moisture and MODIS-derived NDVI and EVI for six sites in Africa
- 2011
-
Konferensbidrag (refereegranskat)abstract
- This study investigates temporal relationships between vegetation growth, rainfall, and soil moisture for six sites located in sub-Saharan and southern Africa for the period 2005-2009. Specifically, seasonal components of time series of Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) composites from the Moderate Resolution Imaging Spectroradiometer (MODIS) and half-hourly in-situ rainfall and soil moisture data at different depths (5-200 cm) during the growing season were used in a lagged correlation analysis in order to understand how vegetation growth responds to rainfall and soil moisture across different sites. Results indicate that both vegetation indices are strongly related to soil moisture (EVI slightly stronger than NDVI) for the upper 1 m reaching maximum correlations when they lag soil moisture by 0-28 days. They respond to rainfall with a 24-32 day lag at the sub-Saharan sites, EVI slightly earlier than NDVI, but their response at the southern hemisphere sites is complex.
|
|
| 10. |
- Sallaba, Florian, et al.
(författare)
-
Future supply and demand of net primary production in the Sahel
- 2017
-
Ingår i: Earth System Dynamics. - : Copernicus GmbH. - 2190-4979 .- 2190-4987. ; 8:4, s. 1191-1221
-
Tidskriftsartikel (refereegranskat)abstract
- In the 21st century, climate change in combination with increasing demand, mainly from population growth, will exert greater pressure on the ecosystems of the Sahel to supply food and feed resources. The balance between supply and demand, defined as the annual biomass required for human consumption, serves as a key metric for quantifying basic resource shortfalls over broad regions.Here we apply an exploratory modelling framework to analyse the variations in the timing and geography of different NPP (net primary production) supply-demand scenarios, with distinct assumptions determining supply and demand, for the 21st century Sahel. We achieve this by coupling a simple NPP supply model forced with projections from four representative concentration pathways with a global, reduced-complexity demand model driven by socio-economic data and assumptions derived from five shared socio-economic pathways.For the scenario that deviates least from current socio-economic and climate trends, we find that per capita NPP begins to outstrip supply in the 2040s, while by 2050 half the countries in the Sahel experience NPP shortfalls. We also find that despite variations in the timing of the onset of NPP shortfalls, demand cannot consistently be met across the majority of scenarios. Moreover, large between-country variations are shown across the scenarios, in which by the year 2050 some countries consistently experience shortage or surplus, while others shift from surplus to shortage. At the local level (i.e. grid cell), hotspots of total NPP shortfall consistently occur in the same locations across all scenarios but vary in size and magnitude. These hotspots are linked to population density and high demand. For all scenarios, total simulated NPP supply doubles by 2050 but is outpaced by increasing demand due to a combination of population growth and the adoption of diets rich in animal products. Finally, variations in the timing of the onset and end of supply shortfalls stem from the assumptions that underpin the shared socio-economic pathways rather than the representative concentration pathways.Our results suggest that the UN sustainable development goals for eradicating hunger are at high risk for failure. This emphasizes the importance of policy interventions such as the implementation of sustainable and healthy diets, family planning, reducing yield gaps, and encouraging the transfer of resources to impoverished areas via trade relations.
|
|
