Understory intercropping may improve soils, but its effects on bacterial communities in Idesia polycarpa plantations remain unclear. Five patterns were established in the Yellow River floodplain: pure I. polycarpa and I. polycarpa intercropped with Astragalus membranaceus, Ipomoea batatas, Salvia rosmarinus, or Arachis hypogaea. Soil properties and bacterial communities were assessed using 16S rRNA gene sequencing, LEfSe, FAPROTAX, and redundancy analysis. Intercropping significantly affected soil electrical conductivity, water content, organic matter, alkali-hydrolyzable nitrogen, available phosphorus, and available potassium, but not pH or bulk density. Salvia rosmarinus intercropping had 14.3 g kg⁻¹ organic matter and 123 mg kg⁻¹ available potassium; Arachis hypogaea had 14.5 g kg⁻¹ organic matter and 81.3 mg kg⁻¹ alkali-hydrolyzable nitrogen; and Ipomoea batatas had 11.9% water content and 13.6 mg kg⁻¹ available phosphorus. Alpha diversity did not differ significantly. PCoA suggested differentiation, but PERMANOVA based on Bray–Curtis dissimilarity was nonsignificant (r² = 0.329, p = 0.083); LEfSe identified treatment-associated biomarkers. Chemoheterotrophy and aerobic chemoheterotrophy accounted for 42.6–45.7% and 20.4–26.2%, respectively. Alkali-hydrolyzable nitrogen was associated with genus-level variation (r² = 0.440, p = 0.031). Understory intercropping improved soil conditions and may influence bacterial composition and predicted functional potential.

Based on a balanced panel of nine provincial-level forest-park systems in the Yellow River Basin over 2013–2022 (90 province-year observations), this study measures the tourism eco-efficiency of forest parks and examines its spatiotemporal evolution and determinants. The unit of analysis is the aggregated forest-park system of each province (i.e., all registered forest parks within each province, aggregated to the provincial level), not individual parks. We combine a slacks-based super-efficiency (super-SBM) model—with four inputs, three desirable outputs, and three undesirable outputs—with the global Malmquist–Luenberger (GML) index, standard deviational ellipse (SDE) analysis, and a random-effects panel Tobit model. To remove price effects, monetary variables were deflated to constant 2012 prices; a small number of missing observations were completed by linear interpolation. The results show that: (1) Mean tourism eco-efficiency was 0.778, rising from 0.486 in 2013 to a peak of 1.077 in 2019, declining to 0.897–0.905 in 2020–2021 under the COVID-19 shock, and recovering to 1.143 in 2022. The mean GML index was 1.182, and mean technological change (TC) exceeded mean efficiency change (EC), suggesting that frontier shifts contributed more to measured productivity growth than efficiency change over the study period, although this conclusion rests on the pooled sample and is examined for robustness. (2) Eco-efficiency was spatially heterogeneous, with lower values in the upper reaches and higher values in the middle and lower reaches; the SDE was oriented east–west and its centroid shifted southeast-to-northwest by a modest distance. (3) At the 5–1% level, per capita GDP and tourism revenue share were positively associated with eco-efficiency and forest-park density negatively associated; highway mileage was positively associated only at the 10% level (p = 0.069); forest cover and employee density were not significant. Because the undesirable-output indicators are provincial industrial emissions allocated to forest parks by the tourism-revenue-to-GDP ratio, and because one regressor (tourism revenue share) is mechanically related to a desirable output, the associations reported here should be interpreted as observational, non-causal evidence. Policy implications are drawn accordingly.