Spatiotemporal simulation of sustainable development based on ecosystem services under climate change

less than the reductions of 232.79 km2 and 265.62 km2 seen in the SSP126 and SSP585 scenar- ios, respectively. Grassland experiences significant loss, with decreases of 287.11 km2, 310.53 km2, and 285.85 km2 under the SSP126, SSP245, and SSP585 scenarios, respectively. Unused land decreases the least under the SSP245 scenario, with a reduction of 20.56 km2 compared to 2020, which is lower than the 57.40 km2 and 35.91 km2 reductions under the SSP126 and SSP585 scenarios. Water area increases the most under the SSP126 scenario, with an increase of 537.63 km2, significantly higher than the 249.43 km2 and 302.69 km2 increases under the SSP245 and SSP585 scenarios. Build-up land increases the most under the SSP585 scenario, with an increase of 525.05 km2, slightly higher than the 503.10 km2 under the SSP245 scenario, and significantly higher than the 257.96 km2 under the SSP126 scenario. 3.2. Spatio-temporal evolution of ESs based on climate change Between 2000 and 2020, the study area’s water yield showed a pattern of higher levels in the southeast and lower levels in the northwest. By 2035, its spatial distribution remains akin to that of 2020 across different scenarios (Fig 4). When compared to 2020, the total water yield sees an increase in all three scenarios, with the SSP126 scenario experiencing the largest rise. The spatial distribution of carbon storage was dispersed from 2000 to 2020 and continues simi- larly in 2035 under various scenarios. Nonetheless, total carbon storage decreases across all

scenarios relative to 2020, with the SSP126 scenario exhibiting the least reduction. From 2000 to 2020, habitat quality displayed a pattern of better conditions in the south and poorer condi- tions in the north. In comparison to 2020, habitat quality sees a decline in all three scenarios, although the SSP126 scenario shows the smallest decrease. Soil retention between 2000 and 2020 also demonstrated a south-high, north-low trend, with high-value areas being less exten- sive and low-value areas more prevalent. Compared to 2020, soil retention increases across all scenarios, with the SSP126 scenario showing the most significant improvement. 3.3. Spatial correlation of ESs under climate change Using the entropy weight method, the weights for the four indicators were determined as fol- lows: carbon storage at 0.24, habitat quality at 0.27, soil retention at 0.24, and water yield at 0.25. By aggregating these normalized indicators, we derived the total ESs. From 2000 to 2020, the spatial distribution of ecosystem services showed a pattern of "low in the northeast and high in the southwest" (Fig 5). The Moran’s I index for ESs is greater than 0, indicating a cer- tain degree of spatial clustering. The Getis-Ord Gi* analysis revealed significant spatial differ- ences in hot and cold spots from 2000 to 2020, with cold spots gradually expanding towards the northwest. Hot spots were primarily located in the southern and eastern remote areas of Yunnan, and by 2020, the hot spots in the eastern region also increased. Table 3. LUC in southeast Yunnan under different scenarios in 2035.

Land use types 2020 year SSP126 SSP245 SSP585 Areas Change Areas Change Areas Change Farmland 13991.32 13773.04 -218.28 13759.24 -232.08 13750.96 -240.36 Forest 38543.17 38310.38 -232.79 38353.82 -189.35 38277.55 -265.62 Grassland 17895.12 17608.01 -287.11 17584.59 -310.53 17609.27 -285.85 Water 516.38 1054.01 537.63 765.81 249.43 819.07 302.69 Built-up land 904.95 1162.91 257.96 1408.05 503.1 1430 525.05 Unused land 76.87 19.47 -57.4 56.31 -20.56 40.96 -35.91 https://doi.org/10.1371/journal.pone.0316605.t003 PLOS ONE Sustainable development simulation under climate change: A spatiotemporal ecosystem services approach PLOS ONE | https://doi.org/10.1371/journal.pone.0316605 February 4, 2025 9 / 19