Modelling gross primary production in semi-arid regions: effects on carbon uptake of intensive agriculture in southern Kenya

Abstract

Background and aim: Gross primary production (GPP) is the largest global carbon (C) flux and an important component for counteracting anthropogenic CO2 emissions, understanding vegetation dynamics, and sustaining universal human standards. Africa plays a prominent role in the global C cycle, though our understanding of GPP dynamics is largely hampered by a paucity of ground-based observations. By using flux data from a newly installed eddy covariance (EC) flux tower in southern Kenya and high-resolution Sentinel-2 satellite data, the aims of this thesis were to i) determine the net C flux and climatic factors governing GPP at a high-intensively cropped dryland farm, ii) use the dataset to test different remote sensing driven GPP models and the MOD17 GPP product (collection 6), and iii) assess the difference in annual GPP among croplands and shrublands, grasslands and open forests.

Results: The studied cropland had a net ecosystem exchange (NEE) of 170 g C m-2 between March and December 2019, thus acting as a source of C during the measurement period. Climatic factors governing GPP were vapour pressure deficit (VPD), soil moisture and air temperature (Tair). Using the 2-band enhanced vegetation index (EVI2), VPD and Tair as input in a multiple linear regression yielded the best results to in situ GPP (R2=0.65, RMSE = 2.02 g C m-2 d-1). Croplands had a higher mean annual GPP compared to grasslands, shrublands and open forest in the sub-humid to semi-arid agro-climatic zone, and a similar annual GPP to open forest in the semi-arid agro-climatic zones. The studied field at the Ausquest farm had however a considerably lower GPP compared to both natural lands and other croplands.

Conclusion: Based on these results, land cover changes occurring over the vast savannah landscape in southern Kenya are not likely to reduce GPP in the region, however, more data is needed to make a more robust assessment. The studied cropland at the Ausquest farm emitted considerable amounts of C during the measurement period, indicating the importance of accounting for respiration in land-cover change studies. The ambiguity of the GPP models can be attributed to the persistent cloud cover during the growing season, as well as difficulties in accounting for the influence of anthropogenic effects on GPP, and to little ground-based data for calibration and validation.

Popular Abstract

Gross primary production (GPP) describes the uptake of carbon (C) from the atmosphere by plants through the process of photosynthesis. As such, plants store a large proportion of C while removing C from the atmosphere. Since human activities increase C emissions to the atmosphere, ultimately resulting in a global warming of Earth, understanding GPP is important to counteract climate change. Furthermore, as GPP describes photosynthesis, GPP is also valuable for understanding how vegetation responds to climate and other external factors. The African continent plays a prominent role in the global C cycle and has a large seasonal variability in GPP, yet, due to low data accessibility and a large uncertainty on how to model GPP especially over dry regions, the scientific community has not a full understanding on how GPP changes in Africa.

Data on C uptake and release by ecosystems from so-called eddy covariance (EC) flux towers are often used to measure C uptake (GPP) and C release (respiration) on the ground. The net flux of C is called the net ecosystem exchange (NEE). By using a new EC dataset from southern Kenya and satellite data with a high resolution, thus capturing small changes on the ground, the aims of this thesis were to i) determine if the studied intense agricultural cropland farm was taking up or releasing C and what climatic factors regulate GPP, ii) use the EC tower dataset to test different self-developed remote-sensing driven GPP models and a commercial GPP product called the MOD17 GPP product (collection 6), and iii) assess the difference in annual GPP among croplands and shrublands, grasslands and open forests to see the potential effects of agriculture expansion on C uptake.

The studied cropland had a NEE of 170 g C m-2 between March and December 2019, thus releasing C during the measurement period. The climatic factors governing GPP were vapour pressure deficit (VPD), which describes the dryness of the air, soil moisture and air temperature (Tair). Using an index derived from satellite data, called the 2-band enhanced vegetation index (EVI2), and the climate variables VPD and Tair as input in a multiple linear regression was found to be the best method to model GPP (R2=0.65, RMSE = 2.02 g C m-2 d-1). The model shows that croplands had a higher C uptake compared to natural grasslands, shrublands and open forest in the relatively dry climate zone. In the even drier zone, however, cropland and open forest have a similar annual GPP.

Since croplands had a higher or similar GPP compared to the natural vegetation, croplands are not likely to reduce the C uptake in the region, but rather to increase C uptake. However, more data would be needed to make a more robust assessment. The studied cropland where the EC tower was located emitted considerable amounts of C during the measurement period, indicating the importance of accounting for respiration in land-cover change studies. The ambiguity of the remote-sensing GPP models can be attributed to the persistent cloud cover during the growing season, which disturbed the images, as well as difficulties in accounting for the influence of human activities on GPP, and to the too little ground-based data available.

• author: Ahlbäck, Malin
• supervisor: Lars Eklundh
• organization: Dept of Physical Geography and Ecosystem Science
• course: NGEM01 20201
• year: 2020
• type: H2 - Master's Degree (Two Years)
• subject: Earth and Environmental Sciences
• keywords: Physical Geography, Ecosystem Analysis, GPP, Africa, Kenya, Land cover changes, Cropland, Remote sensing, Sentinel-2
• publication/series: Student thesis series INES
• report number: 522
• language: English
• id: 9021653
• date added to LUP: 2020-06-23 15:29:27
• date last changed: 2020-06-23 15:29:27