Trade-offs and synergies among ecosystem services are often subject to the scale effects in modern agriculture. But only a few studies have explored from the perspective of the optimal spatial scale, thereby limiting their applicability in policy making. Taking Zhangbei County, a representative Grain for Green areas in China, as a case study, two ecosystem services were quantitatively evaluated from 2000 to 2020, namely windbreak and sand fixation, and food production, both of which were essential to maintain the ecological stability and rural livelihoods in the ecologically fragile agro-pastoral transition zones. Spatial continuous wavelet transform was applied to determine the optimal spatial scale, at which the trade-offs and synergies were characterized for the spatiotemporal features. Ecological zoning was finally proposed under the differentiated regulation. The results showed that: 1) The two ecosystem services exhibited the opposing trends from 2000 to 2020. Windbreak and sand fixation services increased overall, while the food production services slightly declined. Spatially, there was the decrease in the windbreak and sand fixation services from the central to peripheral areas, indicating the close association with the regional topography, climatic conditions, and land-use pattern, whereas the food production services displayed a fragmented pattern that aligned well with the spatial distribution of cropland. 2) 1.2 km was identified as the optimal scale for the trade-offs and synergies between the two ecosystem services in the study area. There was the phased pattern over the 20 years, with the initial trade-offs, followed by synergies, and then a return to trade-offs. Spatially, the trade-offs were widely distributed in a patchy pattern in the county, with a continuous contraction. Synergies were concentrated in the eastern mountainous and hilly areas, exhibiting a strengthening trend. Structurally, the weak trade-offs increased rapidly, whereas the moderate and strong trade-offs declined significantly. In contrast, there was increase in the weak, moderate, and strong synergies. 3) According to the decision trees of the trade-offs and synergies, an ecological zoning decision tree was constructed to take the grid cells as the basic analytical units. Time series were adopted as the main analytical thread. The trade-offs and synergies patterns were identified as the hierarchical classification nodes. Four ecological zones were then classified, including subzone I, subzone II, subzone III, and subzone IV. The targeted strategies were optimized for each subzone. The findings can provide a methodological pathway for the interactions among ecosystem services, thereby enhancing the scientific basis for ecological zoning under the Grain for Green Program. The specific locality can be reduced after optimization. The approach can be extended into the similar regions for the sustainable development goals, such as SDGs 2 and 15. Future work should focus on the trade-offs and synergies among a broader set of ecosystem services, such as the carbon sequestration, water conservation, and soil retention. The optimal pathways can be identified for the coordinated multi-service development at the regional scale. In addition, the ecological and practical scale can balance the ecological zones and regional decision-making at the optimal spatial scale.

Forestland has been one of the most important ecological land and natural resources in modern agriculture. The quantity, type, spatial layout, and age structure of forestland can have a significant impact on its functional performance. There is a high demand to accurately and rapidly acquire forest information at a regional scale. Fortunately, a linear spectral mixture model can be expected to avoid the influence of mixed pixels on the spectral information. This study aims to carry out the fine classification of forestland and forest age mapping using a linear spectral mixture model combined with a random forest and logistic model. The study area was taken as the Zhangjiakou City, Hebei Province, China. Landsat series remote sensing images were also captured in 2020 using surface spectral endmember space. The results showed that: 1) The forestland was divided into five types: evergreen coniferous, deciduous shrub, deciduous small-leaved, deciduous broadleaved, and deciduous needle-leaf forest. The overall high accuracy of classification was 90.58%, and the Kappa coefficient was 0.89. Furthermore, there were significant differences in the area occupied by various forestland types and their distribution in the horizontal space. Among them, the deciduous shrub forest shared the widest distribution area in the study area, accounting for 31.25%. The second was deciduous broadleaved forest, accounting for 3792.80 km². The smallest distribution area was found in the deciduous needle-leaf forest, accounting for only 480.32 km². 2) The classification of forest age was validated to compare the field sample point data and high-resolution images from the Google Earth platform. The average absolute error and deviation of the forest age mapping were within two and three years, respectively, indicating the more effective mapping. There was a significant variation in the spatial distribution pattern of each age group. Forestland with an age of 20-30 years shared the largest distribution area among the five age groups, with an area of 3843.85 km². While the forestland with an age of more than 30 years had the smallest area, accounting for only 124.84 km². 3) The distribution areas of different forestland types showed a tendency to increase and then decrease with the increase in elevation and slope. Among them, the evergreen coniferous forest was primarily distributed at an elevation range of 1500-2000 m. Deciduous shrubs and deciduous needle-leaf forests were both concentrated within the elevation range of 1000-1500 m. Deciduous small-leaved and deciduous broadleaved forests were aggregated within the elevation ranges of 1000-1500 m and 1500-2 000 m, respectively. In terms of slope distribution, the deciduous small-leaved forest predominantly grew with a gradient of 2°-6°, while the rest were primarily concentrated on the gradients of 6°-15° and 15°-25°. As for different forest ages, the area of each age group reached the highest level in the elevation band of 1 000-1 500 m. The age groups of 5-10 years and 10-20 years shared the largest distribution area in the slope zone of 15°-25°. And the forest age of 20-30 years occupied the largest area in the slope zone of 6°-15°. The area of each age group was smaller than that in the flat land with a slope of <2°. This finding can provide a visual basis and technical support to the spatial distribution and age structure of regional forestlands. It was of great significance to optimize the forest resources and ecologically sustainable construction.

Ecological engineering can dominate the structure and function of ecosystems. The quantity and quality of ecological land can be directly related to the pattern and dynamics of regional ecosystem services. It is very necessary to identify the impacts of ecological engineering construction on regional ecosystem services, especially in agro-pastoral transitional zones. This study aims to explore the impact of the quantity and quality of ecological land on ecosystem services under ecological projects. A case study was taken in Zhangbei County, a typical county in an agro-pastoral transitional zone. The map of land use was then classified using a random forest model, according to the Landsat remote sensing images in 2000, 2010, and 2020. The linear spectral mixture model was also used to decompose the original image for the abundance values of typical endmembers. Three key ecosystem services were included soil conservation, water conservation as well as windbreak, and sand fixation. The evolutionary characteristics were quantitatively assessed using the InVEST model and ArcGIS. The correlation analysis was then applied to reveal the impact of the quantity and quality of ecological land on the key ecosystem services. The results showed that: 1) The distribution of forestland in Zhangbei County was expanded rapidly, with a total increase of 986.10 km² from 2000-2020. But the areas of arable land and grassland continued to shrink, thus decreasing by 802.86 and 307.43 km², respectively. There was some spatial overlap between the expansion of forestland and the shrinkage of arable land and grassland. An overall strengthening trend was found for soil conservation, water conservation, windbreak, and sand fixation as a whole. However, there was outstanding spatial heterogeneity in the specific distribution. 2) In the quantity of ecological land, the total area of ecological land has continuously increased by 687.67 km² over the past 20 years. Among them, the increases in the area of forestland, grassland, and their total area posed a significant effect on the soil conservation and water conservation services, while only the increase in the area of forestland shared the positive impact on the windbreak and sand fixation. In the quality of ecological land, the average abundance values of endmember elements in forestland declined by 0.108 during the 20-year period, indicating an overall decreasing trend. The average abundance values of endmember elements in grassland increased by 0.099, with an overall weakly increasing trend. The quality of forestland and grassland was enhanced the soil conservation, water conservation, windbreak, and sand fixation, whereas the windbreak and sand fixation were the most sensitive to changes in the quality of forestland and grassland. The findings can offer a promising perspective to explore the impact of ecological engineering construction on ecosystem services. The region-specific decision-making insights can also be provided for ecological restoration in the agro-pastoral transitional zone. The impact of fine classification of ecological land on ecosystem services should be further examined in future research. Additionally, it is necessary to incorporate the time-series data of climatic factors into vegetation ecological process models, in order to reveal the feedback effects of ecosystem services on climatic factors. This approach can be expected to distinguish the relative contributions of climatic factors and ecological engineering in regional ecosystem services.