Spatially distributed modelling and mapping of soil organic carbon and total nitrogen stocks in the Eastern Mau Forest Reserve, Kenya

doi:10.1007/s11442-016-1257-4

Abstract

Abstract:

Detailed knowledge about the estimates and spatial patterns of soil organic carbon (SOC) and total nitrogen (TN) stocks is fundamental for sustainable land management and climate change mitigation. This study aimed at: (1) mapping the spatial patterns, and (2) quantifying SOC and TN stocks to 30 cm depth in the Eastern Mau Forest Reserve using field, remote sensing, geographical information systems (GIS), and statistical modelling approaches. This is a critical ecosystem offering essential services, but its sustainability is threatened by deforestation and degradation. Results revealed that elevation, silt content, TN concentration, and Landsat 8 Operational Land Imager band 11 explained 72% of the variability in SOC stocks, while the same factors (except silt content) explained 71% of the variability in TN stocks. The results further showed that soil properties, particularly TN and SOC concentrations, were more important than that other environmental factors in controlling the observed patterns of SOC and TN stocks, respectively. Forests stored the highest amounts of SOC and TN (3.78 Tg C and 0.38 Tg N) followed by croplands (2.46 Tg C and 0.25 Tg N) and grasslands (0.57 Tg C and 0.06 Tg N). Overall, the Eastern Mau Forest Reserve stored approximately 6.81 Tg C and 0.69 Tg N. The highest estimates of SOC and TN stocks (hotspots) occurred on the western and northwestern parts where forests dominated, while the lowest estimates (coldspots) occurred on the eastern side where croplands had been established. Therefore, the hotspots need policies that promote conservation, while the coldspots need those that support accumulation of SOC and TN stocks.

Key words: soil organic carbon, total nitrogen, carbon sequestration, climate change, digital soil mapping, Eastern Mau

WERE Kennedy, Ram SINGH Bal, Bjarne DICK Øystein. Spatially distributed modelling and mapping of soil organic carbon and total nitrogen stocks in the Eastern Mau Forest Reserve, Kenya[J].Journal of Geographical Sciences, 2016, 26(1): 102-124.

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Variables	Data format	Date	Source	Scale	Soil-forming factor
Target variables
1. SOC stocks	Points	2012	Field work
2. TN stocks	Points	2012	Field work
Predictor variables
1. SOC concentration	Raster	2012	Interpolated field data	30 m	S
2. TN concentration	Raster	2012	Interpolated field data	30 m	S
3. Magnesium	Raster	2012	Interpolated field data	30 m	S
4. Potassium	Raster	2012	Interpolated field data	30 m	S
5. Calcium	Raster	2012	Interpolated field data	30 m	S
6. Clay content	Raster	2012	Interpolated field data	30 m	S
7. Silt content	Raster	2012	Interpolated field data	30 m	S
8. Sand content	Raster	2012	Interpolated field data	30 m	S
9. pH	Raster	2012	Interpolated field data	30 m	S
10. Elevation	Raster	-	ASTER GDEM http://gdem.ersdac.jspacesystems.or.jp/	30 m	R
11. Slope	Raster	-	ASTER GDEM	30 m	R
12. Aspect	Raster	-	ASTER GDEM	30 m	R
13. Curvature	Raster	-	ASTER GDEM	30 m	R
14. CTI	Raster	-	ASTER GDEM	30 m	S
15. Temperature	Raster	1950-2000	www.worldclim.org	1 km	C
16. Rainfall	Raster	1950-2000	www.worldclim.org	1 km	C
17. Surface reflectance & thermal emission	Raster	30.05.2013	Landsat 8 OLI (bands 2, 3, 4, 5, 6, 7, 10 & 11) http://earthexplorer.usgs.gov/	30 m	C, S
18. NDVI	Raster	30.05.2013	Landsat 8 OLI (bands 4 & 5)	30 m	O
19. PC bands	Raster	30.05.2013	Landsat 8 OLI (bands 2, 3, 4, 5, 6 & 7)	30 m	S
20. Land cover	Raster	17.01.2011	Landsat 5 TM; Were et al. (2013)	30 m	O

Variable	n	Mean	Median	SD	CV (%)	Min.	Max.	Range	Skewness	Kurtosis
SOC_st	220	102.7	103.2	24.6	23.9	42.0	193.4	151.4	0.39	0.97
TN_st	220	10.3	10.3	2.4	23.8	4.2	19.1	14.9	0.28	0.76

Variables	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15
1. SOC stock	1.00
2. TN stock	0.99	1.00
3. TN content	0.84	0.85	1.00
4. SOC content	0.85	0.84	0.99	1.00
5. Silt	-0.41	-0.42	-0.56	-0.55	1.00
6. Magnesium	0.35	0.35	0.44	0.44	-0.36	1.00
7. Clay	0.28	0.29	0.40	0.39	-0.61	0.08	1.00
8. Temperature	-0.50	-0.50	-0.63	-0.63	0.28	-0.04	-0.34	1.00
9. Rainfall	0.44	0.45	0.56	0.55	-0.23	0.25	0.10	-0.61	1.00
10. Elevation	0.51	0.51	0.65	0.65	-0.30	0.06	0.35	-0.99	0.65	1.00
11. Aspect	0.22	0.23	0.18	0.17	-0.08	0.01	0.02	-0.16	0.16	0.16	1.00
12. NDVI	0.30	0.30	0.39	0.39	-0.25	0.07	0.24	-0.50	0.25	0.50	0.11	1.00
13. Land cover	-0.48	-0.48	-0.54	-0.53	0.31	0.00	-0.41	0.83	-0.46	-0.84	-0.16	-0.56	1.00
14. PC1	-0.48	-0.48	-0.52	-0.52	0.15	-0.03	-0.23	0.71	-0.50	-0.73	-0.28	-0.32	0.74	1.00
15. Landsat 8 OLI band 11	-0.58	-0.58	-0.65	-0.65	0.35	-0.09	-0.37	0.81	-0.56	-0.84	-0.29	-0.63	0.89	0.82	1.00

Parameter	SOC stocks model					TN stocks model
Parameter	Estimate	SE	t value	Pr (>\|t\|)	VIF	Estimate	SE	t value	Pr (>\|t\|)	VIF
Intercept	143.502	50.757	2.827	0.0053^**	-	16.741	5.131	3.263	0.0013**	-
Silt	0.443	0.202	2.191	0.0298^*	1.531	-	-	-	-	-
Band 11	-0.003	0.001	-2.360	0.0194^*	3.511	-0.000	0.000	-2.475	0.0143^*	3.489
Elevation	-0.022	0.009	-2.503	0.0133^*	3.613	-0.002	0.001	-2.305	0.0223^*	3.558
TN	178.200	12.269	14.524	0.0000^***	2.471	-	-	-	-	-
SOC	-	-	-	-	-	1.597	0.106	15.103	0.0000^***	1.807
Adjusted R²	0.72					0.71
RMSE	13.07					1.33
Moran’s I	0.11					0.08

Parameter	SOC stocks model					TN stocks model
Parameter	Mean	SD	Min.	Max.	Range	Mean	SD	Min.	Max.	Range
Intercept	129.525	31.412	50.031	199.881	149.851	14.790	4.771	8.037	26.423	18.387
Silt	0.436	0.115	0.203	0.614	0.411	-	-	-	-	-
Band 11	-0.003	0.001	-0.004	-0.001	0.004	-0.000	0.000	-0.000	-0.000	0.000
Elevation	-0.021	0.007	-0.041	-0.004	0.037	-0.002	0.001	-0.005	-0.001	0.004
TN	177.230	23.072	142.790	238.558	95.768	-	-	-	-	-
SOC	-	-	-	-	-	1.576	0.197	1.087	1.899	0.812
Global adjusted R²	0.73					0.72
Global RMSE	12.86					1.29
Moran’s I	0.06					0.02