Land use gradients
Land use structure and quantity in CYCC changed substantially from 1995 to 2018 (Figs. 2 and 3, Table S1). Among the six land use classes studied, land formerly under grass underwent the largest reduction (743.64 km2, or 48.47% of the total reduction in main land use types), followed by agricultural land (490.45 km2 or 31.97%) and forest land (300.22 km2 or 19.57%). Constructed land exhibited the largest increase (1354.09 km2, to double the area in 1995, representing 88.25% of the increase in main land use types), followed by open water (175.18 km2 or 11.42%) and unused land (5.03 km2 or 3.14%). This shows that expansion of built-up area due to large-scale, scattered agglomeration urbanization is the main driving force for changes of land use pattern and structure in CYCC.
Comparing the different annular rings, from 1995 to 2018 the proportion of forest land showed an obvious increasing trend from 35% in the core cohesion zone to more than 60% in the outermost concentric ring (ring 8), while there was an obvious downward trend in constructed land area from 22% in the core cohesion zone to less than 0.2% in the outermost ring. In the same period, the proportion of grass land showed an increasing trend, but with apparent and irregular fluctuations, from 20% in the core cohesion zone to 35% in the outermost ring, although the total area decreased strongly from 1995 to 2018. Agricultural land proportion showed a first rise (0–1 ring) and then a continuous decline trend, exceeding 20% for core cohesion zone from 1995 and 2005, while lower than 20% in 2015 and 2018. The proportions of open water and unused land both displayed a general decrease, although with indistinct and irregular fluctuations, along the urban-rural gradient from core to outermost ring from 1995 to 2018.
Ecosystem services gradient
At the entire CYCC scale, there was an increase in water yield (of 4.84×108 m3) from 1995 to 2018, while the other three ESs analyzed all experienced a general downward trend, with carbon storage decreasing by 4.81×106 tons, soil retention by 0.27×106 tons, and nitrogen export by 5.57×105 tons (Table 1).
The average values for the four ESs in CYCC differed along the urban-rural gradient from 1995 to 2018 (Fig. 5). Average carbon storage showed an irregular increasing trend from the core cohesion zone to the outermost concentric ring between 1995 and 2005 and then suddenly declined, while it showed a slight increase in 2015 and 2018. Water yield displayed an irregular W- shaped overall downward trend along the urban-rural gradient with a suddenly increased in the 7th ring, but remained lower in than the 4th ring across the study period. Soil retention showed a continuous increasing trend from core to outermost ring, although the increase between the 1st and 2nd rings was smaller during the study period. Nitrogen export first displayed a temporary increase, and then a continuous irregular decrease trend along the gradient from the core outwards, over the study period.
A noteworthy observation was that the average carbon storage and nitrogen export values showed a sudden surge in the 3rd concentric ring in 1995, 2005, 2015 and 2018, and also a sudden surge in the 5th concentric ring for carbon storage in 2015 and 2018, and a sudden surge in the 5th concentric ring for nitrogen export in all four years.
Table 1
Variation in total ecosystem services (ESs) supply in Central Yunnan City Cluster (CYCC) from 1995 to 2018
ESs
|
1995
|
2005
|
2015
|
2018
|
Variation
|
Rangeability
|
Carbon storage(106t)
|
891.87
|
891.74
|
891.14
|
887.06
|
-4.81
|
-0.54%
|
Water yield (108m)
|
256.94
|
257.32
|
258.78
|
261.77
|
4.84
|
1.88%
|
Soil retention (106t)
|
6920.48
|
6920.59
|
6920.95
|
6920.22
|
-0.27
|
-0.0039%
|
Nitrogen export (105t)
|
631.17
|
628.52
|
623.04
|
625.61
|
-5.57
|
-0.88%
|
Driving mechanism analysis of ESs changes
As mentioned above, land use change was one of the most important driving factors affecting ESs, and urbanization in particular changed regional land use in a large area and completely. Therefore, we analysed the impact of urbanization on regional ESs from the aspects of physical geography, economic and social factors. Specifically, a total of 11 factors (8 physical geographic factors and 5 economic and social factors) were selected to further study the influence and driving mechanism of CYCC urbanization process on regional ESs. 40,000 random points generated as section 2.2 were used to extract the intensity values of various ESs and the attribute values of the spatial layers of potential drivers made above (Table S6 in Supplementary Information), binary Logistic regression SPSS 26.0 (SPSS Inc., Chicago, IL, USA) was used in to analyze the correlation between the 4 representative ESs and 10 potential drivers factors one by one (Fig. 6).
For carbon storage change, the influential factors with stronger correlation in turn are: Distance to nearest town, NDVI and Night light index. Carbon storage was negative with distance to nearest town and night light index, positive with DIVI. The distance to towns and night light index is closely related to human activities. The demand for construction land is large in places close to towns (where night light index is always higher), and vast grassland, cropland and forests are converted into construction land, this resulted in decline of carbon storage. This is consistent with the previous analysis results, the carbon storage carbon storage decreasing by 4.81×106 tons during the study period (Table 1).
For water yield change, the influential factors with stronger correlation in turn are: distance to nearest town, distance to nearest road and slope. Water yield was negative with distance to nearest town and distance to nearest road, positive with slope. Areas close to towns and cities are highly disturbed by human activities. For example, the impervious surface of the ground is relatively high, resulting in increased water production in such areas. This is consistent with the previous analysis results; the water yield increased 4.84×108 m3 during the study period (Table 1).
For soil retention, the influential factors with stronger correlation in turn are: the distance to nearest town, NDVI and population density. The soil retention was positively correlated with the above former two factors, negative with population density. Because areas far from cities and towns are less vulnerable to human interaction (such areas tend to have high NDVI), they are more conducive to soil conservation. And the opposite is true in densely populated areas. With increasing human interaction in the CYCC, regional soil retention by 0.27×106 tons during the study period (Table 1).
For nitrogen export, the influential factors with stronger correlation in turn are: the distance to nearest road, the distance to nearest town and Population density. NDVI and population density. The nitrogen export was positively correlated with the above former two factors, negative with population density. This is because there are more frequent human activities around roads, towns and densely populated areas. For example, farmland is usually distributed around them, so nitrogen output near roads and towns is more serious due to agricultural non-point sources and surface runoff erosion.
In addition, the cumulative correlation coefficient was introduced in this study, that is, the correlation coefficient of the impact of the 10 driving factors on the 4 ESs was summed after the absolute value to judge the correlation between the above driving factors and ESs change. As shown in Fig. 6, the influential factors with stronger correlation in turn are: distance to nearest town, distance to nearest road and NDVI. It further indicates that the urban-rural development pattern and layout change in the process of CYCC urbanization is the main driving force of regional ESs change.
Trade-offs between ESs
Correlation between the ESs were investigated using Pearson correlation test (df = 39998). The results showed that, at the entire CYCC, scale carbon storage had an extremely highly significant negative correlation with water yield and a highly significant negative correlation with nitrogen export (p < 0.01), and a significant positive correlation with soil retention (p < 0.01) in 1995 and 2018 (Table 2). Water yield displayed a highly significant positive correlation with soil retention and nitrogen export across the study period. Soil retention showed a significant negative correlation with nitrogen export across the study period. This suggests that large-scale, scattered urbanization at city cluster scale in CYCC, with marked impacts on land use change, eventually lowers the regional ESs supply. Moreover, the correlations between ESs appear to persist for a long time under large-scale, scattered urbanization at city cluster scale.
Statistically significant ESs trade-offs were also found between adjacent rings along the gradient in CYCC (Paired samples t test; df = 1143, P < 0.01) (Fig. 7). Thus when one ESs tended to increase or decrease, the corresponding ESs in adjacent concentric circles followed the same trend. This was especially evident for carbon storage between concentric rings 0&1, 1&2, 2&3, 3&4, and 7&8; for water yield between rings 0&1, 1&2, 2&3, 3&4, 5&6, and 6&7; for soil retention between rings 1&2 and 6&7; and for nitrogen export between rings 0&1, 3&4, 5&6, and 6&7.
Table 2
Trade-offs among ecosystem services (ESs) in Central Yunnan City Cluster (CYCC) from 1995 to 2018.
Year
|
ESs
|
Carbon storage
|
Water yield
|
Soil retention
|
1995
|
Water yield
|
-0.712**
|
|
|
Soil retention
|
0.084**
|
-0.109**
|
|
Nitrogen export
|
-0.419**
|
0.377**
|
-0.026**
|
2005
|
Water yield
|
-0.712**
|
|
|
Soil retention
|
0.084**
|
-0.109**
|
|
Nitrogen export
|
-0.418**
|
0.376**
|
-0.026**
|
2015
|
Water yield
|
-0.711**
|
|
|
Soil retention
|
0.083**
|
-0.110**
|
|
Nitrogen export
|
-0.415**
|
0.368**
|
-0.025**
|
2018
|
Water yield
|
-0.704**
|
|
|
Soil retention
|
0.086**
|
-0.113**
|
|
Nitrogen export
|
-0.413**
|
0.360**
|
-0.027**
|
Note: n = 40,000 in the whole CYCC. **p < 0.01. |