Warming is making drought and heat co-occur more often, intensifying compound stress on cropland in northern China’s drylands, where water scarcity makes further irrigation expansion untenable. On the Guanzhong Plain, a major grain-producing region, it remains unclear which irrigation conditions buffer cropland carbon–water productivity—the carbon assimilated per unit of water consumed—against such events. Using growing-season (March–October) remote sensing for 2016–2024, we identified the 2022 compound drought–heat event pixel by pixel and classified cropland as stable rainfed, transitional/mixed, or stable high-coverage irrigation from the pre-event (2016–2020) irrigated-area fraction and its persistence. In 2022, 88.9% of cropland experienced at least one compound dry–hot day, with dry–hot overlap 2.4 times the independence expectation. After balancing climate, terrain, soil, spatial position, and subpixel cropland fraction, stable high-coverage irrigation held no advantage in event-year resistance, post-event recovery, or overall resilience. Carbon assimilation remained above its pre-event level while carbon–water productivity fell, so the event cost water-use efficiency rather than carbon. Event-period root-zone soil-moisture change ranked first, and irrigated-area fraction last, among twelve random-forest predictors of resistance. We flagged 6722.3 km² of cropland for water-use audits and 2418.1 km² for supplemental irrigation; limited water should be allocated by realized moisture status, exposure, and resilience, not by irrigability.

Biocrusts are critical yet threatened components of dryland ecosystems, and predicting their functional trait dynamics under future scenarios is essential for conservation planning. Using 129 occurrence localities and 84 trait sampling sites across three precipitation zones in China’s Mu Us Sandland, we combined MaxEnt habitat modeling with Random Forest regression to predict biocrust functional traits—including coverage, thickness, and total volume for both moss and cyanobacterial crusts—under current conditions and 12 future climate–land use scenarios (four SSPs × three time periods: 2050s–2090s). Soil nitrogen, annual precipitation, and soil potassium emerged as key environmental drivers of biocrust habitat distribution. Currently, moss crusts cover 7.63% of the study area (thickness: 10.56 mm) and cyanobacterial crusts cover 5.88% (thickness: 4.88 mm), with a total biocrust volume of 4629 × 10⁴ m³. Across the emission and policy gradient, functional traits exhibited contrasting responses: coverage showed scenario-dependent declines, while thickness remained relatively stable. Under SSP126, moss coverage declined by 3.32% and cyanobacterial coverage by 2.80% by the 2070s, with total volume decreasing by 2064.76 × 10⁴ m³; by the 2090s, moss coverage partially recovered (+0.26%). In contrast, SSP370 and SSP585 projected sustained losses without recovery. A striking divergence emerged: cyanobacterial thickness increased consistently (+0.02 to +0.23 mm) even as coverage declined, while moss thickness fluctuated within ±0.13 mm. Notably, high-precipitation transitional zones (362–434 mm) exhibited the greatest vulnerability, with moss coverage declining 3× more under SSP126 than SSP585 by the 2070s and volume losses persisting through the 2090s. These findings provide spatially explicit predictions of biocrust traits and quantitative baselines for prioritizing conservation in transitional zones facing accelerating environmental pressures.

Tropospheric NO₂ anomalies reflect meteorological, land-surface, and emission influences, yet whether greater anomaly activity indicates stronger associations with hydroclimatic extremes across landscapes remains unclear. We analyzed monthly TROPOMI NO₂ anomalies (2019–2025) at 10 km resolution across paddy, dryland, forest, and grassland backgrounds in Northeast China’s black soil region, where typical black soils mainly correspond to Phaeozems and Chernozems. We assessed anomaly activity, concurrent and lagged correlations, and regression-based heat- and precipitation-related associations with paired spatial-block bootstrap inference. Agricultural backgrounds exhibited greater anomaly magnitudes, high-anomaly frequencies, and growing-season variability than forest and grassland, with median high-anomaly frequencies of 32.9–34.8% versus 7.5–15.2%. During May–September, regional standardized total associations were positive for heat (0.163; 95% spatial-block CI: 0.116–0.211) and negative for precipitation (−0.063; −0.110 to −0.023). The regional heat association remained positive across robustness checks, but agricultural–non-agricultural heat contrasts were not supported by paired spatial-block confidence intervals, despite grid-cluster bootstrap intervals excluding zero for all four contrasts. Precipitation associations were generally more negative over agricultural backgrounds, although evidence for between-background differences depended on multiple-comparison adjustment. The regional precipitation estimate remained negative under coverage-covariate and minimum-valid-day checks but approached zero under a stringent common-coverage restriction (−0.0035; 95% CI: −0.0522 to 0.0402). These findings distinguish elevated NO₂ anomaly activity from evidence of stronger hydroclimatic associations, while documenting a comparatively stable regional heat association and greater coverage sensitivity of precipitation-related estimates. This distinction supports more careful interpretation of atmospheric NO₂ variability across heterogeneous agricultural and natural landscapes.