| 1. |
- Abdi, Hakim, et al.
(författare)
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The El Niño – La Niña cycle and recent trends in supply and demand of net primary productivity in African drylands
- 2016
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Ingår i: Climatic Change. - : Springer Science and Business Media LLC. - 0165-0009 .- 1573-1480. ; 138:1, s. 111-125
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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.
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| 2. |
- Ahmed, Mohamed, et al.
(författare)
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Dynamic response of NDVI to soil moisture variations during different hydrological regimes in the Sahel region
- 2017
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Ingår i: International Journal of Remote Sensing. - : Informa UK Limited. - 1366-5901 .- 0143-1161. ; 38:19, s. 5408-5429
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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
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| 3. |
- Eklund, Lina, et al.
(författare)
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Meteorological, agricultural and socioeconomic drought in the Duhok Governorate, Iraqi Kurdistan
- 2015
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Ingår i: Natural Hazards. - : Springer Science and Business Media LLC. - 0921-030X .- 1573-0840. ; 76:1, s. 421-441
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Tidskriftsartikel (refereegranskat)abstract
- Drought is a recurrent natural hazard that is expected to increase in the future due to anthropogenic climate change. The Middle East region witnessed a drought period between 2007 and 2009 that has been reported to have severe consequences for the population, especially in Syria and Iraq. This study seeks to assess the spatial and temporal characteristics of the drought in the Duhok Governorate in Northern Iraq, focusing on meteorological, agricultural and socio-economic drought at province and village level. Satellite based precipitation data, validated by station data, were used in a meteorological drought assessment. To estimate the decreased precipitation’s effects on vegetation, an agricultural drought assessment was performed using Enhanced Vegetation Index (EVI) from multi-temporal satellite data. Vegetation anomalies were studied at provincial level, and also at village level where the anomalies were compared with survey data showing the socio-economic susceptibility to drought. The study confirms that precipitation dropped by approximately 50%, leading to a negative anomaly in vegetation conditions for 62% of Duhok Governorate’s area in 2008. Out of 50 assessed villages, 46 experienced a negative vegetation anomaly during the drought year, and three of those experienced a strong negative anomaly. Reports of drought as a problem were frequently recorded in the exposed villages, but was also related to the level of agricultural involvement. This study emphasizes the importance of understanding drought from both physical and socio-economic perspectives. Moreover, discrepancies in the datasets make a multi-source approach essential to avoid erroneous interpretations.
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| 4. |
- Jamali, Sadegh, et al.
(författare)
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Detecting changes in vegetation trends using time series segmentation
- 2015
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Ingår i: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257 .- 1879-0704. ; 156:January, s. 182-195
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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.
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| 5. |
- Johansson, Emma Li, et al.
(författare)
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Green and blue water demand from large-scale land acquisitions in Africa
- 2016
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424. ; 113:41, s. 11471-11476
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Tidskriftsartikel (refereegranskat)abstract
- In the last decade, more than 22 million ha of land have been contracted to large-scale land acquisitions in Africa, leading to increased pressures, competition, and conflicts over freshwater resources. Currently, 3% of contracted land is in production, for which we model site-specific water demands to indicate where freshwater appropriation might pose high socioenvironmental challenges. We use the dynamic global vegetation model Lund-Potsdam-Jena managed Land to simulate green (precipitation stored in soils and consumed by plants through evapotranspiration) and blue (extracted from rivers, lakes, aquifers, and dams) water demand and crop yields for seven irrigation scenarios, and compare these data with two baseline scenarios of staple crops representing previous water demand. We find that most land acquisitions are planted with crops that demand large volumes of water (>9,000 m3·ha-1) like sugarcane, jatropha, and eucalyptus, and that staple crops have lower water requirements (<7,000 m3·ha-1). Blue water demand varies with irrigation system, crop choice, and climate. Even if the most efficient irrigation systems were implemented, 18% of the land acquisitions, totaling 91,000 ha, would still require more than 50% of water from blue water sources. These hotspots indicate areas at risk for transgressing regional constraints for freshwater use as a result of overconsumption of blue water, where socioenvironmental systems might face increased conflicts and tensions over water resources.
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| 6. |
- Johansson, Lars, et al.
(författare)
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Towards the modelling of pedestrian wind speed using high-resolution digital surface models and statistical methods
- 2016
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Ingår i: Theoretical and Applied Climatology. - : Springer Science and Business Media LLC. - 0177-798X .- 1434-4483. ; 124:1, s. 189-203
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Tidskriftsartikel (refereegranskat)abstract
- Wind is a complex phenomenon and a critical factor in assessing climatic conditions and pedestrian comfort within cities. To obtain spatial information on near-ground wind speed, 3D computational fluid dynamics (CFD) modelling is often used. This is a computationally intensive method which requires extensive computer resources and is time consuming. By using a simpler 2D method, larger areas can be processed and less time is required. This study attempts to model the relationship between near-ground wind speed and urban geometry using 2.5D raster data and variable selection methods. Such models can be implemented in a geographic information system (GIS) to assess the spatial distribution of wind speed at street level in complex urban environments at scales from neighbourhood to city. Wind speed data, 2 m above ground, is obtained from simulations by CFD modelling and used as a response variable. A number of derivatives calculated from high-resolution digital surface models (DSM) are used as potential predictors. A sequential variable selection algorithm followed by all-possible subset regression was used to select candidate models for further evaluation. The results show that the selected models explain general spatial wind speed pattern characteristics but the prediction errors are large, especially so in areas with high wind speeds. However, all selected models did explain 90 % of the wind speed variability (R2 ≈0.90). Predictors adding information on width and height ratio and alignment of street canyons with respect to wind direction are suggested for improving model performance. To assess the applicability of any derived model, the results of the CFD model should be thoroughly evaluated against field measurements.
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| 7. |
- Kross, Angela, et al.
(författare)
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Light use efficiency of peatlands: Variability and suitability for modeling ecosystem production
- 2016
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Ingår i: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257. ; 183, s. 239-249
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Tidskriftsartikel (refereegranskat)abstract
- Peatland net ecosystem production is a key variable to assess changes in the functional role of peatlands in the global carbon cycle. Light use efficiency (LUE) models in combination with satellite data have been used to estimate production for most major ecosystems, but peatlands have been largely ignored. The objectives of this study were: 1) to examine how the LUE parameter epsilon, ε (the amount of carbon fixed or converted to biomass per unit absorbed photosynthetically active radiation), varies between and within four different peatlands; 2) to examine how the variations in ε relate to variations in environmental conditions; and 3) to evaluate a LUE-based model for estimation of ε in peatlands. We achieve these objectives using a combination of eddy covariance flux measurements, climate data and satellite data and estimate ε using the LUE-based vegetation photosynthesis model (VPM). The results show that: 1) mean site-specific flux-derived ε values (± standard deviation) were split into three statistically different groups: lowest values at the two colder fens, Kaamanen and Sandhill (0.22 ± 0.18 and 0.23 ± 0.20 g C MJ− 1, respectively), highest values at the treed fen La Biche (0.47 ± 0.27 g C MJ− 1) and intermediate values at the bog, Mer Bleue (0.34 ± 0.18 g C MJ− 1); 2) Variations in monthly ε within sites related mainly to air temperature, while variations in annual ε within sites related mainly to wetness variables; 3) relative mean absolute errors of estimates of ε for the four sites ranged between 19% and 35%, with r2 values ranging between 72% and 93%. LUE models are appealing as they are relatively simple formulations of variables that are easily obtained from satellite data. Challenges associated with the use of satellite data derived input variables are further discussed in the paper.
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| 8. |
- Mechiche-alami, Altaaf, et al.
(författare)
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Transnational land acquisitions beyond the food and financial crises
- 2019
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Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 14:8
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Tidskriftsartikel (refereegranskat)abstract
- Large-scale land acquisitions (LSLA) in resource-rich countries came to global attention after the food and financial crises of 2008. Previous research has assessed the magnitude of these land investments in terms of land areas acquired. In this study, we analyze the trends in the evolution of LSLA by framing the latter as virtual land trade network with land transactions occurring between 2000 and 2015, in order to shed light on the development and evolution of this system. Based on an index we introduce to represent both the number of countries and size of deals, we discover three main phases of trade activity: a steady increase from 2000 until 2007 (Phase 1) followed by a peak coinciding with the food and financial crises between 2008 and 2010 (Phase 2) and concluded by a decline from 2011 to 2015 (Phase 3). We identify 73 countries that remained active in land trading during all three phases and form a core of land traders much larger than previously thought. Using network analysis methods, we group countries with similar trade patterns into categories of competitive, preferential, diversified, and occasional importers or exporters. Finally, in exploring the changes in investors and their interests in land throughout the phases, we attribute the evolution of LSLA to the different stages in the globalization and financialization of different industries. By showing that land investments seem fully integrated as investment strategies across industries we argue for the urgency of better regulation of LSLA so that they also benefit local populations without damaging the environment regardless of their primary purpose.
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| 9. |
- Sallaba, Florian, et al.
(författare)
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A rapid NPP meta-model for current and future climate and CO2 scenarios in Europe
- 2015
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Ingår i: Ecological Modelling. - : Elsevier BV. - 0304-3800. ; 302, s. 29-41
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Tidskriftsartikel (refereegranskat)abstract
- Net primary production (NPP) is the difference in gross photosynthetic assimilation of carbon and carbon loss due to autotrophic respiration, and is an important ecosystem variable that facilitates understanding of climate change impacts on terrestrial ecosystem productivity and ecosystem services. The aim of this study is to rapidly estimate the NPP of European potential natural vegetation for current and future climate and carbon-dioxide scenarios (CO2). A NPP meta-model was developed and evaluated based on the dynamic global vegetation model LPJ-GUESS. LPJ-GUESS was used to simulate NPP under current and future climate change as well as CO2 scenarios. The NPP dataset produced from these simulations was used to determine the empirical relationships between NPP and driving climate variables (maximum temperature, minimum temperature, summer precipitation, winter precipitation) along with CO2 concentration. The climate variables’ relationships were combined in a synergistic function including CO2 relationships to estimate NPP. The meta-model was compared with randomly chosen NPP data originated from LPJ-GUESS. Furthermore, the meta-model's performance was evaluated on the European level with LPJ-GUESS simulations. The meta-model performed reasonably well with regard to estimating total NPP while performances for species-specific NPP were poor. For total NPP, the meta-model generated an agreement of R2 = 0.68 and RMSE = 0.06 at CO2 = 350 ppm in comparison to LPJ-GUESS simulations. The consideration of all CO2 concentration scenarios yielded R2 = 0.62 and RMSE = 0.08. A rapid synergistic approach is suggested that enables interactions between climate variables and their intra-annual variability to estimate NPP. This is a useful alternative to traditional empirical models that control NPP with the most limiting climate variable. The meta-model performed reasonably well for estimating total NPP for future climate change and CO2 scenarios. However, species-specific NPP estimates were unsatisfactory, implying that the synergistic approach cannot account for species specific dynamics. Comparison between the meta-model and LPJ-GUESS at the European scale showed that additional environmental variables (e.g. solar radiation) would be necessary to improve the meta-model.
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| 10. |
- Sallaba, Florian, et al.
(författare)
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Future supply and demand of net primary production in the Sahel
- 2017
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Ingår i: Earth System Dynamics. - : Copernicus GmbH. - 2190-4979 .- 2190-4987. ; 8:4, s. 1191-1221
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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.
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