Silva Fennica

Fig. 1. The location and topography of the study area map.

Fig. 2. Rainfall and temperature climatology of the GIAHS site based on observed data for the Amaghouz station for the period 1983–2022. Globally Important Agricultural Heritage Systems (GIAHS).

Fig. 3. Flowchart of the adopted methodology for assessing Drought and vegetation dynamics dynamics in GIAHS site. Globally Important Agricultural Heritage Systems (GIAHS), The spectral indices used include the Soil-Adjusted Vegetation Index (SAVI), Normalized Difference Built-up Index (NDBI), and Normalized Difference Water Index (NDWI). The classification was carried out using the Random Forest (RF) algorithm implemented in Google Earth Engine (GEE). LULC – Land Use and Land Cover; SAVI – Soil-Adjusted Vegetation Index; NDBI – Normalized Difference Built-up Index; NDWI – Normalized Difference Water Index; RF – Random Forest; OA – Overall Accuracy; Kappa – Kappa coefficient.

Table 1. Classification of land cover types based on NDVI values for the GIAHS site.
NDVI Values	Class description
NDVI < 0.03	Bare land
0.03 < NDVI < 0.3	Low-density vegetation
0.3 < NDVI < 0.4	Moderate-density Vegetation
NDVI > 0.4	High-density Vegetation
NDVI: Normalized Difference Vegetation Index; GIAHS: Globally Important Agricultural Heritage Systems (GIAHS).

Fig. 4. Climatology of annual (a) precipitation and (b) temperature, in the GIAHS site from 1983–2020. Globally Important Agricultural Heritage Systems (GIAHS).

Fig. 5. Spatial-temporal changes in precipitation in the GIAHS site during 1983–2020. (A1–A4) show the seasonal spatial trends in precipitation (unit: mm/year) derived using the Linear Regression Method (LRM), while (Y1–Y4) represent the corresponding interannual variation and linear trends. Seasons are as follows: (1) Winter, (2) Spring, (3) Summer, and (4) Autumn. Globally Important Agricultural Heritage Systems (GIAHS). View larger in new window/tab.

Fig. 6. Spatial-temporal changes in temperature in the GIAHS site during 1983–2020. (K1–K4) illustrate the seasonal spatial trends in temperature (unit: °C/year) using the Linear Regression Method (LRM), and (G1–G4) show the corresponding interannual variation and trends. Seasons are as follows: (1) Winter, (2) Spring, (3) Summer, and (4) Autumn. Globally Important Agricultural Heritage Systems (GIAHS). View larger in new window/tab.

Fig. 7. Time series of changes in SPEI at the seasonal scale (SPEI-6) and annual scale (SPEI-12) from 1983 to 2020 in the GIAHS site. The Standardized Precipitation-Evapotranspiration Index (SPEI).

Table 2. Confusion matrix and accuracy assessment of (LULC) classification for the GIAHS site.
Year		Ground truth
1995	Classes	Agriculture	Woodland	Bare land	Built-up	Producer’s accuracy
	Agriculture	83.33	0.67	0.07	0.00	99.12
	Woodland	0.00	87.33	0.21	19.35	81.72
	Bare land	16.67	4.67	99.49	16.13	72.63
	Build up	0.00	7.33	0.24	64.52	89.51
	User’s accuracy	83.33	87.33	99.48	64.52
	OA = 83.66; KI = 0.82
2000	Classes	Agriculture	Woodland	Bare land	Built-up	Producer’s accuracy
	Agriculture	88.24	2.40	0.11	14.29	84.01
	Woodland	0.00	91.62	0.17	7.14	92.62
	Bare land	11.76	4.79	99.49	14.29	76.33
	Build up	0.00	1.20	0.23	64.29	97.82
	User’s accuracy	88.24	91.61	99.49	64.28
	OA = 85.90; KI = 0.86
2005	Classes	Agriculture	Woodland	Bare land	Built-up	Producer’s accuracy
	Agriculture	93.75	2.08	0.00	0.00	97.83
	Woodland	6.25	97.92	0.00	0.00	94.00
	Bare land	0.00	0.00	99.73	8.33	92.30
	Build up	0.00	0.00	0.27	91.67	99.71
	User’s accuracy	93.75	97.92	99.73	91.67
	OA = 95.77; KI = 0.90
2010	Classes	Agriculture	Woodland	Bare land	Built-up	Producer’s accuracy
	Agriculture	93.55	9.23	0.00	0.00	91.00
	Woodland	6.45	90.77	0.00	0.00	93.37
	Bare land	0.00	0.00	99.93	9.38	91.37
	Build up	0.00	0.00	0.07	90.63	99.92
	User’s accuracy	93.55	90.77	99.93	90.62
	OA = 93.72; KI = 0.93
2015	Classes	Agriculture	Woodland	Bare land	Built-up	Producer’s accuracy
	Agriculture	91.67	4.29	0.02	0	95.51
	Woodland	8.33	95.24	0	0	91.96
	Bare land	0	0.48	99.89	8.33	91.92
	Build up	0	0	0.09	91.67	99.90
	User’s accuracy	91.67	95.24	99.89	91.67
	OA = 95.62; KI = 0.95
2020	Classes	Agriculture	Woodland	Bare land	Built-up	Producer’s accuracy
	Agriculture	92.86	0.69	0	0	99.26
	Woodland	7.14	99.04	0.01	0	93.27
	Bare land	0	0	99.93	0.62	99.38
	Build up	0	0	0.07	99.38	99.93
	User’s accuracy	92.86	99.31	99.92	99.38
	OA = 97.87; KI = 0.96
LULC: land use/land cover; GIAHS: Globally Important Agricultural Heritage System.

Fig. 8. Spatio-temporal change of LULC over the period 1995–2020 within the Globally Important Agricultural Heritage System (GIAHS) site.

Table 3. Temporal variability in LULC Composition across Different Classes: 1995–2020.
Classes	1995 (%)	2000 (%)	2005 (%)	2010 (%)	2015 (%)	2020 (%)
Bare land	97.268	98.123	96.562	97.869	96.783	98.429
Woodland	1.902	1.789	3.082	1.995	3.149	1.079
Built-up	0.002	0.018	0.009	0.026	0.045	0.055
Agriculture	0.828	0.070	0.347	0.111	0.022	0.436
LULC: land use land cover (LULC).

Fig. 9. Area based change detection of LCLU in respective periods.

Fig. 10. Spatial patterns of NDVI rate of change in the Globally Important Agricultural Heritage System (GIAHS) site from 2000 to 2020.

Table 4. Percentage temporal variation of vegetation density classes: 1985–2020.
NDVI class	1985	1990	1995	2000	2005	2010	2015	2020
BL	0.63	2.76	2.55	2.55	2.16	1.22	0.68	1.57
LVD	98.57	96.65	96.78	94.72	96.50	97.38	92.8	96.38
MVD	0.55	0.39	0.45	0.45	0.98	1.1	5.22	1.52
HVD	0.25	0.20	0.22	0.30	0.36	0.30	1.30	0.53
BL, LDV, MVD, and HDV are acronyms for Bare Land, Low Vegetation Density, Moderate Vegetation Density, and High Vegetation Density, respectively.

Fig. 11. Annual NDVI trends among various crop types from 2000 to 2020. Cereal mixed with species cereals are cultivated together with other crops, such as legumes, maize and alfalfa (Medicago sativa).

Fig. 12. Seasonal NDVI trends among various crop types from 2000 to 2020.

Table 5. Mann-Kendall trend and Sen’s slope of remote sensing and drought index.
Variables	NDVI				SPEI-6	SPEI-12
Variables	Palm tree	Argan tree	Cereal	Cereal mixed with species	SPEI-6	SPEI-12
Z-score	1.11	0.09	–1.42	–2.99*	–3.95*	–4.52*
Sen’s slope	0.001	0.006	–0.002	–0.004	–0.001	–0.001
Tau	0.18	0.02	–0.23	–0.48	–0.12	–1.43
Variance	1096.6	1096.6	1096.6	1096.6	10158610	10158460
* Significant p-value at 99% confidence level; SPEI-6: Standardized Precipitation Evapotranspiration Index at 6 months; SPEI-12: Standardized Precipitation Evapotranspiration Index at 12 months.

Fig. 13. Pearson correlation coefficient matrix of drought indicators. Cereal mixed with species (cereals are cultivated together with other crops, such as legumes, maize and alfalfa (Medicago sativa)). SPEI-6: Standardized Precipitation Evapotranspiration Index at 6 months; SPEI-12: Standardized Precipitation Evapotranspiration Index at 12 months.

Fig. 14. Illustration of the impact of abandon on terraces: (a) soil loss and degraded terraces (b) Water erosion in the Southeast of the GIAHS. Credit: Moussa Ait El Kadi.

Fig. 15. Palm trees threatened by fire in Ait Mansour Oasis. Credit: Brahim Meskour.