Five restoration scenarios reveal competing stakes in China’s Qilian Mountains

Restoring a degraded mountain range is never a single decision but a cascade of them: where to act first, whether to plant trees or grasses, and whose priorities—villagers, provincial governments, or the global climate—should guide the budget. A new study of the Qilian Mountains, a roughly 193,300-square-kilometer ecological barrier on the northeastern edge of the Qinghai-Tibet Plateau, has now mapped those choices in unusually fine detail. The researchers assessed seven ecosystem services across the range, identified land degraded by human activity rather than climate, and then simulated five competing restoration scenarios, each prioritizing a different set of beneficiaries. Their model estimates show that a scenario emphasizing global benefits—carbon sequestration and habitat quality—delivered the highest total and per-unit ecosystem service value, while a scenario prioritizing regional soil conservation achieved the most balanced gains across services, leading the authors to recommend it as a benchmark strategy for the region.

The work arrives amid a vast national experiment in ecological restoration. China has rolled out integrated protection and restoration projects spanning mountains, rivers, forests, farmlands, lakes, grasslands, and deserts across 19 provinces, and between 2009 and 2019 alone these efforts were estimated to have increased the total value of ecosystem services by 2.53 trillion yuan, with more than 65 percent of that growth attributed to regulatory services such as water regulation and erosion control. Yet the study’s authors argue that macro-level spatial planning of such projects remains suboptimal, and that restoration strategies are often designed around single objectives or individual services rather than the full portfolio of benefits that mountain landscapes provide. The Qilian Mountains, they contend, offer an ideal testing ground for doing better, because the range supplies water to downstream basins, stores carbon in extensive forests and alpine grasslands, supports an agro-pastoral economy, and anchors one of China’s newest national parks.

The geography of the range makes any one-size-fits-all plan untenable. Elevations across most of the Qilian Mountains sit between 3,500 and 5,000 meters, and conditions swing from annual average temperatures as low as minus 16.3 degrees Celsius to as high as 6 degrees, with precipitation ranging from 67 to 758 millimeters per year. Vegetation cover, averaging 42.6 percent, thins from east to west. The warmer, wetter east supports croplands and forests and concentrates the region’s population and agriculture, while the cold, arid west is dominated by alpine grasslands, alpine deserts, and temperate deserts. Grassland covers 49.3 percent of the range, alpine desert 26.0 percent, temperate desert 9.9 percent, forest 7.0 percent, water bodies 4.7 percent, cropland 3.0 percent, and built-up areas just 0.3 percent. Decades of overgrazing, tourism development, and mineral and hydropower extraction have degraded ecosystems and weakened regional ecological security, even though restoration projects have been running in the area since 2000.

To quantify what is at stake, the team assessed seven services: food production and tourism as local benefits; water yield, soil conservation, and sand fixation as regional benefits; and carbon sequestration and habitat quality as global benefits. Each service was estimated with established models—the Revised Universal Soil Loss Equation for soil conservation, the Revised Wind Erosion Equation for sand fixation, the water balance equation for water yield, and the InVEST model for habitat quality—and then converted into monetary values so that gains under different scenarios could be compared on a common footing. To smooth out year-to-year climate variability, the researchers averaged water yield, soil conservation, sand fixation, and carbon sequestration estimates over 2018 to 2020. A principal component analysis of the resulting service maps revealed a striking structure: five independent factors together explained 86.7 percent of the variance, with food production and tourism rising and falling together, carbon sequestration and habitat quality moving in lockstep, and the three regional services each operating largely on their own.

Pinpointing where restoration should happen required disentangling human influence from climate. Using 30-meter-resolution vegetation cover data from 1990 to 2020, the team applied Theil-Sen trend estimation and Mann-Kendall significance testing to map where vegetation had changed. They then used multiple correlation analysis and residual analysis—regressing vegetation cover on temperature and precipitation, and treating the leftover deviation as the fingerprint of human activity—to separate climate-driven from human-driven change. Areas with significant human-caused vegetation decline, together with areas showing no significant recovery in a range that has generally greened under warming and wetting conditions, were flagged as potential restoration zones, on the reasoning that ecosystems failing to recover amid favorable trends may have low resilience or persistent degradation risks. Alpine deserts, existing forests, and other areas unsuitable or unnecessary for intervention were excluded, while adjacent bare land, sandy land, and cropland on slopes steeper than 15 degrees were added. A neural-network-based land use model, GeoSOS-FLUS, then classified the ecological suitability of these zones: 20.4 percent proved suitable for cropland, 21.0 percent for forest, 28.8 percent for shrubland, and 29.8 percent for grassland, with cropland-suitable areas clustered along the lower eastern edge and grassland-suitable areas concentrated at high elevations in the west.

With the map in hand, the researchers matched specific interventions to specific degradation states. Grassland restoration through reseeding, fertilization, and grazing management targets degraded pastures; conversion to cropland or artificial grassland establishes managed agro-ecosystems; shrub afforestation plants locally adapted species such as Hippophae rhamnoides and Lycium barbarum; tree afforestation uses species including Picea crassifolia and Sabina przewalskii; and returning cropland to grassland retires marginal farmland. These types were then ranked within each suitability zone under five scenarios: a local-priority scenario favoring food production and tourism, three regional scenarios each prioritizing water yield, soil conservation, or sand fixation, and a global-priority scenario favoring carbon sequestration and habitat quality. Priority scores were computed as equally weighted sums of the monetized service-value increments for each scenario’s target services, allowing restoration to proceed sequentially from highest to lowest priority.

The scenario comparisons produced clear winners and losers. Active restoration would cover 18,159 square kilometers under the local, water-yield, and sand-fixation scenarios, and 22,564 square kilometers under the soil-conservation and global scenarios, which additionally convert shrubland and non-degraded grassland in forest-suitable zones to afforestation. The global-priority scenario maximized both total and per-unit ecosystem service value, delivering substantial gains in carbon sequestration and habitat quality along with notable increases in soil conservation, sand fixation, and water yield—but it suppressed food production and tourism, because afforestation on cropland and grassland shrinks the forage base and the agricultural footprint. The soil-conservation scenario achieved its target and produced strong co-benefits for carbon and habitat, performing well on both total and per-unit value. The local-priority scenario boosted food production most but left other services largely unchanged and, notably, saw habitat quality decline. Perhaps most tellingly, the water-yield and sand-fixation scenarios, though they achieved the largest numerical gains in their focal services, delivered only modest absolute improvements, suggesting that prioritizing either service alone yields limited returns for the investment.

These trade-offs expose a deeper tension in who pays and who benefits. The stakeholders most directly affected by restoration in the Qilian Mountains are herders, farmers, and county-level governments, yet the benefits of enhanced carbon sequestration and habitat quality accrue largely to regional and global beneficiaries. Top-down policies already in force—grazing bans, seasonal grazing rest, fencing programs, ecological resettlement, and the establishment of the Qilian Mountains National Park—have substantially restricted traditional land use, imposing local livelihood costs for broadly shared gains. The authors argue that bridging this mismatch requires explicit benefit-sharing mechanisms: performance-based grassland subsidies tied to grazing compliance, value chains for yak and Tibetan sheep products, community-based ecotourism, and participatory co-management that delegates grazing regulation to local communities. Without such compensation, they warn, the global-priority scenario’s afforestation on grazing and cultivated lands risks low local acceptance, non-compliance, and weak on-the-ground effectiveness, whereas involving residents in monitoring and adaptive management can lower enforcement costs and improve durability.

Translating the results into policy, the authors propose a selective, performance-based regulatory framework rather than a uniform rollout. The local-priority scenario should not be the default; where it is used in agriculturally dependent eastern valleys, it should be paired with strict ecological redline protections and biodiversity offsets requiring habitat restoration to compensate any agricultural expansion. The water-yield and sand-fixation scenarios are not recommended as standalone strategies, since their focal gains are marginal; their measures would work better folded into the soil-conservation or global scenarios. The soil-conservation scenario is recommended as the benchmark for the range, supported by targeted subsidies for slope stabilization such as terracing and shrub afforestation in erosion-prone central and eastern mountains, and by mandatory co-benefit monitoring that could generate certified ecosystem service credits for green financing. The global-priority scenario fits best in areas of national or transboundary ecological security, such as the national park’s core zones, provided it includes transboundary ecological compensation, strict water-balance monitoring in afforestation areas to avoid downstream trade-offs, and phased implementation starting in non-agricultural alpine regions.

The authors are candid about the limits of their estimates. Because terrain, climate, and human activity cause ecosystem service values to vary even within the same land use state and suitability zone, the calculated before-and-after restoration values carry some bias. The study did not conduct a cost-benefit analysis, since restoration costs vary widely with terrain, distance from settlements and roads, and land compensation, making the economic feasibility of each scenario difficult to judge. Scenario design also did not account for potential land use conflicts, policy barriers, or socio-economic constraints on where restoration could actually proceed, nor did it differentiate management regimes inside and outside protected areas—an important refinement the authors flag for future work. Even so, the framework offers a template for a problem that extends well beyond one mountain range: as restoration budgets grow worldwide, deciding whose benefits count most, and making that decision transparently on a map, may matter as much as planting the right species in the right place.

Subject of Research: Spatial optimization of ecological restoration scenarios and ecosystem service trade-offs in the Qilian Mountains

Article Title: Optimizing ecological restoration patterns and types in the Qilian Mountains: Balancing local, regional, and global benefits

Article References: Teng, Y., Wang, C., Liu, H., Zhang, Y., Liu, H., & Zhan, J. (2026). Optimizing ecological restoration patterns and types in the Qilian Mountains: Balancing local, regional, and global benefits. Environmental and Sustainability Indicators, 32, Article 101588. https://doi.org/10.1016/j.indic.2026.101588

Image Credits: AI Generated

DOI: 10.1016/j.indic.2026.101588

Keywords: ecological restoration, ecosystem services, Qilian Mountains, Qinghai-Tibet Plateau, carbon sequestration, soil conservation, habitat quality, scenario analysis, land use optimization, trade-offs and synergies, stakeholder compensation, grassland degradation