| 41. |
- Ardö, Jonas
(författare)
-
Soil carbon sequestration and climate change in semi-arid Sudan
- 2015
-
Ingår i: Sudan Academy of Sciences Journal-Special Issue (Climate Change). - 1816-8272. ; 11, s. 140-163
-
Tidskriftsartikel (refereegranskat)abstract
- Climate change poses risk for natural and human systems in Africa. Increasing temperatures and changes in precipitation patterns is likely to affect agriculture, pastoralism and forestry. Mitigation of increasing atmospheric concentration of CO2 through soil carbon sequestration in semi-arid ecosystems may be beneficial to soil properties and cultivation. This paper describes and discusses soil carbon sequestration in relation to climate change in semi-arid regions, with special attention to the Sudan. It is anticipated that adaptation to climate changes is a more reasonable way to cope with future climate change than mitigation through soil carbon sequestration, especially for low emitting countries in Africa such as the Sudan.
|
|
| 42. |
- Ardö, Jonas, et al.
(författare)
-
Soil carbon sequestration in traditional farming in Sudanese dry lands
- 2004
-
Ingår i: Environmental Management. - : Springer Science and Business Media LLC. - 0364-152X .- 1432-1009. ; 33, s. 318-329
-
Tidskriftsartikel (refereegranskat)abstract
- Do altered land management practices offer possibilities to sequester carbon in the soil and thereby mitigate increasing atmospheric CO2 as well as improve local soil fertility? This study investigates the impact of fallow periods on soil organic carbon in semiarid subsistence agroecosystems on sandy and poor soils in Kordofan, Sudan. The area is characterized by low-input cultivation of millet and sorghum in combination with livestock grazing. Recently, cultivation intensity has increased and the fallow periods have been shortened. Soil carbon contents were assessed for sites that have been under various cultivation intensities, ranging from 30 years of fallow to 30 years of continuous cultivation. Soil organic carbon showed a significant negative relationship with cultivation intensity. Measurements indicate a mean increase of approximately 4 g soil organic carbon (SOC) per square meter per year during fallow periods. The possibilities of increasing soil organic carbon by land management were also estimated through simulations using the Century model. Modeling suggested that reverting an intensely cropped millet site to permanent grassland would sequester approximately 1-2 g SOC/m(2)/yr, with higher rates during the early part of the period. Continuous intense cultivation could decrease the currently low soil carbon levels even further. These results indicate that altered land management could contribute to transforming degraded semiarid agroecosystems from a source to a weak sink for atmospheric CO2. Possible data improvements and uncertainties are discussed.
|
|
| 43. |
|
|
| 44. |
|
|
| 45. |
|
|
| 46. |
- Boke-Olén, Niklas, et al.
(författare)
-
Analyzing savannah vegetation phenology with remotely sensed data, lagged time-series models and phenopictures
- 2016
-
Konferensbidrag (refereegranskat)abstract
- It is predicted that savannah regions will see changes in precipitation patterns due to current climate change pro-jections. The change will most likely affect leaf phenology which controls net primary production. It is thereforeimportant to; 1) study those changes and its drivers, 2) to be able to correctly model the changes to vegetationphenology due to climate change. To our knowledge there is no existing global savannah phenology model thatcan capture both the phenological events and the vegetation state between the events. We therefore, investigate howday length, mean annual precipitation and soil moisture affects and controls the vegetation phenology of savannahs(using MODIS NDVI as a proxy for phenological state) with a lagged time series model for global application. Wefurthermore use phenological pictures (phenopictures) to investigate savannah tree and grass phenology. Phenopic-tures are pictures taken with a digital time-lapse camera with the purpose of recording and studying phenologicalevents. We used climate data from 15 flux towers sites located in 4 continents together with normalized differencevegetation index from MODIS for the model development. Two of the sites located in Africa were further ana-lyzed using phenopictures. The developed model identified all three considered variables as usable for modellingof savannah leaf phenology but showed some inconsistent result for some of the sites indicating the difficultiesin creating a simple common model that works equally well across sites. We attribute some of these difficultiesto site specific differences (e.g. grazing or tree and grass ratio) that the simplified model did not consider. Butwe expect it to on average give the cross-validated result (r2= 0.6, RMSE = 0.1) when applied to other savannahareas. The preliminary analysis of the phenological pictures with respect to tree and grass to some extent supportthis by showing differences in the start of the leaves development in the beginning of the season. However, thisdiffered between the two studied sites which further highlights the difficulties in creating a common model thatworks equally well for individual sites.
|
|
| 47. |
- Boke-Olén, Niklas, et al.
(författare)
-
Estimating and analyzing savannah phenology with a lagged time series model
- 2016
-
Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:4
-
Tidskriftsartikel (refereegranskat)abstract
- Savannah regions are predicted to undergo changes in precipitation patterns according to current climate change projections. This change will affect leaf phenology, which controls net primary productivity. It is of importance to study this since savannahs play an important role in the global carbon cycle due to their areal coverage and can have an effect on the food security in regions that depend on subsistence farming. In this study we investigate how soil moisture, mean annual precipitation, and day length control savannah phenology by developing a lagged time series model. The model uses climate data for 15 flux tower sites across four continents, and normalized difference vegetation index from satellite to optimize a statistical phenological model. We show that all three variables can be used to estimate savannah phenology on a global scale. However, it was not possible to create a simplified savannah model that works equally well for all sites on the global scale without inclusion of more site specific parameters. The simplified model showed no bias towards tree cover or between continents and resulted in a cross-validated r2 of 0.6 and root mean squared error of 0.1. We therefore expect similar average results when applying the model to other savannah areas and further expect that it could be used to estimate the productivity of savannah regions.
|
|
| 48. |
- Boke-Olén, Niklas, et al.
(författare)
-
Estimating Grazing Potentials in Sudan Using Daily Carbon Allocation in Dynamic Vegetation Model
- 2018
-
Ingår i: Rangeland Ecology and Management. - : Elsevier BV. - 1550-7424. ; 71:6, s. 792-797
-
Tidskriftsartikel (refereegranskat)abstract
- Livestock production is important for local food security and as a source of income in sub-Saharan Africa. The human population of the region is expected to double by 2050, and at the same time climate change is predicted to negatively affect grazing resources vital to livestock. Therefore, it is essential to model the potential grazing output of sub-Saharan Africa in both present and future climatic conditions. Standard tools to simulate plant productivity are dynamic vegetation models (DVMs). However, as they typically allocate carbon to plant growth at an annual time step, they have a limited capability to simulate grazing. Here, we present a novel implementation of daily carbon allocation for grasses into the DVM Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) and apply this to study the grazing potential for the Kordofan region in Sudan. The results show a latitudinal split in grazing resources, where the northern parts of Kordofan are unexploited and southern parts are overused. Overall, we found that the modeled grazing potential of Kordofan is 16% higher than the livestock usage reported in the Food and Agricultural Organization of the United Nations, indicating a mitigation potential in the form of a spatial relocation of the herds.
|
|
| 49. |
- Boke-Olén, Niklas, et al.
(författare)
-
Remotely sensed soil moisture to estimate savannah NDVI
- 2018
-
Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 13:7
-
Tidskriftsartikel (refereegranskat)abstract
- Satellite derived normalized difference vegetation index (NDVI) is a common data source for monitoring regional and global ecosystem properties. In dry lands it has contributed to estimation of inter-annual and seasonal vegetation dynamics and phenology. However, due to the spectral properties of NDVI it can be affected by clouds which can introduce missing data in the time series. Remotely sensed soil moisture has in contrast to NDVI the benefit of being unaffected by clouds due to the measurements being made in the microwave domain. There is therefore a potential in combining the remotely sensed NDVI with remotely sensed soil moisture to enhance the quality and estimate the missing data. We present a step towards the usage of remotely sensed soil moisture for estimation of savannah NDVI. This was done by evaluating the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture and three of its individual products with respect to their relative performance. The individual products are from the advance scatterometer (ASCAT), Soil Moisture and Ocean Salinity (SMOS), and the Land Parameter Retrieval Model-Advanced Microwave Scanning Radiometer-Earth Observing System (LPRM-AMSR-E). Each dataset was used to simulate NDVI, which was subsequently compared to remotely sensed NDVI from MODIS. Differences in their ability to estimate NDVI indicated that, on average, CCI soil moisture differs from its individual products by showing a higher average correlation with measured NDVI. Overall NDVI modelled from CCI soil moisture gave an average correlation of 0.81 to remotely sensed NDVI which indicates its potential to be used to estimate seasonal variations in savannah NDVI. Our result shows promise for further development in using CCI soil moisture to estimate NDVI. The modelled NDVI can potentially be used together with other remotely sensed vegetation datasets to enhance the phenological information that can be acquired, thereby, improving the estimates of savannah vegetation phenology.
|
|
| 50. |
- Cai, Zhanzhang, et al.
(författare)
-
Modelling Daily Gross Primary Productivity with Sentinel-2 Data in the Nordic Region-Comparison with Data from MODIS
- 2021
-
Ingår i: Remote Sensing. - : MDPI. - 2072-4292. ; 13:3
-
Tidskriftsartikel (refereegranskat)abstract
- The high-resolution Sentinel-2 data potentially enable the estimation of gross primary productivity (GPP) at finer spatial resolution by better capturing the spatial variation in a heterogeneous landscapes. This study investigates the potential of 10 m resolution reflectance from the Sentinel-2 Multispectral Instrument to improve the accuracy of GPP estimation across Nordic vegetation types, compared with the 250 m and 500 m resolution reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS). We applied linear regression models with inputs of two-band enhanced vegetation index (EVI2) derived from Sentinel-2 and MODIS reflectance, respectively, together with various environmental drivers to estimate daily GPP at eight Nordic eddy covariance (EC) flux tower sites. Compared with the GPP from EC measurements, the accuracies of modelled GPP were generally high (R-2 = 0.84 for Sentinel-2; R-2 = 0.83 for MODIS), and the differences between Sentinel-2 and MODIS were minimal. This demonstrates the general consistency in GPP estimates based on the two satellite sensor systems at the Nordic regional scale. On the other hand, the model accuracy did not improve by using the higher spatial-resolution Sentinel-2 data. More analyses of different model formulations, more tests of remotely sensed indices and biophysical parameters, and analyses across a wider range of geographical locations and times will be required to achieve improved GPP estimations from Sentinel-2 satellite data.
|
|
