**Background:** Forests cover approximately 31% of Earth's land surface and provide critical ecosystem services including water conservation, climate regulation, and pollution mitigation. Climate change and air pollution both impact forest development, but their combined effects—particularly in forests surrounding megacities—are poorly understood. The Miyun Reservoir Basin (MRB) is the major drinking water source for Beijing, located approximately 180 km from the city center. This study investigated how Pinus tabuliformis (Chinese pine), the dominant coniferous species in the MRB, responds to both global climate change and local air pollution along a spatial gradient.
**Methods:** Five sampling sites (S1–S5) were selected along a transect across the MRB, ranging in elevation from approximately 200 to 1300 m above sea level. S1 and S5 represented sites with lowest pollution impacts (high elevation, remote), while S2, S3, and S4 experienced moderate to intensive pollution exposure. Tree ring cores were collected from 4–9 trees per site (total 24–42 trees per site, ages 24–49 years). Ring width was converted to basal area increment (BAI). Stable carbon (δ¹³C) and nitrogen (δ¹⁵N) isotope analyses were performed on 3-year pooled wood samples. Intrinsic water-use efficiency (iWUE) was calculated as A/gₛ = (cₐ − cᵢ)/1.6. Historical climate data (precipitation, temperature) were derived from TerraClimate gridded data (validated against Fengning and Miyun meteorological stations). Pollutant concentrations (PM10, PM2.5, dust deposition, N deposition, S deposition) were reconstructed using the Environmental Kuznets Curve (EKC) theory based on per capita GDP of Beijing. Statistical analyses included Pearson correlations, one-way ANOVA, and multiple linear regression.
**Key Results:** (1) Pollutant concentrations were consistently high before approximately 1996, then decreased substantially. N deposition decreased from a near-constant level of 132.8 kg N ha⁻¹ (1966–1993 average) to approximately 60.4 kg N ha⁻¹ (2008–2014 average). (2) BAI showed overall increasing trends at all five sites but with varying rates. S1 and S5 had the highest growth rates, especially since the mid-1990s. S2 and S3 had significantly lower growth rates than the other three sites since the late 1990s. (3) iWUE increased similarly at all sites, with significant positive correlations with atmospheric CO₂ concentration (cₐ) (r = 0.790 to 0.951 across sites). (4) BAI was significantly positively correlated with cₐ at S1 (r = 0.947, p < 0.001), S4 (r = 0.888, p < 0.001), and S5 (r = 0.935, p < 0.001), but not at S2 and S3. (5) All pollutants (PM10, PM2.5, dust, N, S) showed significant negative correlations with iWUE at all sites. (6) Multiple regression showed cₐ explained 91.9% of BAI variation at S1, 79.3% at S4, and 94% at S5. At S2, dust, N, and S depositions together explained 74.5% of BAI variation. At S3, cₐ, temperature, iWUE, and pollutants together explained approximately 90% of BAI variation. (7) During high-pollution periods (pre-1996), δ¹³C at S2 and S3 was approximately 0.5–1‰ higher than at other sites (e.g., 1984: −25.10‰ at S2, −24.97‰ at S3 vs. −27.12‰ at S1 in 1993). (8) Tree ring δ¹⁵N peaks corresponded with rainfall extremes, suggesting N losses from denitrification and leaching during heavy rainfall events.
**Clinical Implications:** This study demonstrates that air pollution significantly suppresses tree growth in forests surrounding megacities, with effects varying by distance from pollution sources and elevation. The finding that P. tabuliformis shows adaptive capacity—with growth recovering after pollution reductions post-1996—suggests that air quality improvements can benefit forest health. The quadratic relationships between BAI and cₐ indicate potential tipping points (e.g., 415 ppm at S1, 414 ppm at S2, 371 ppm at S3, 518 ppm at S4) beyond which further CO₂ increases may not benefit tree growth. The study also validates tree ring δ¹⁵N as a tool for fingerprinting nitrogen deposition and nitrogen losses. These findings have implications for forest management and conservation planning in regions experiencing both climate change and air pollution, particularly for urban forests and water source protection areas.