Under the global Sustainable Development Goals initiative, the pursuit of well-being is gradually shifting from wealth to sustainable development. Re-examining the contribution of regional economic, ecological, and social development to the common creation of well-being, analyzing their deep connections, will help us understand the multidimensional concepts and processes of development, and provide ideas for further promoting the construction of a more equitable and sustainable world. China is moving from comprehensive prosperity to common prosperity, and the continuous improvement of sustainable well-being provides effective samples for our research. This study focuses on 46 counties in the Qinba Mountains region of China, and constructs a coupled performance indicator system for sustainable well-being in mountain villages. The Super SBM model is used to evaluate the matching performance of input and output factors, with Economic capital, Ecological capital, and Social capital as explanatory variables and Sustainable Happiness Index as the expected output. Research has found that: (1) There is a mismatch between the input and output factors of sustainable well-being in the Qinba Mountain area, and management techniques are a key factor hindering the improvement of the coupling performance level of sustainable well-being in the Qinba Mountain area; (2) The coupling performance level of sustainable happiness in the Qinba Mountain area is showing a downward trend, and only adjusting the input-output relationship by about 1.02% can achieve optimization and growth in performance level; (3) There is a significant shortage of input factors, with 87% of counties experiencing insufficient economic capital, about 76% experiencing insufficient arable land, and 41% experiencing insufficient social capital. To solve these problems, it is necessary to strengthen the sustainable management level of each county in terms of ecology, economy, and social integration, continue to promote capital investment in mountainous areas to improve economic level, strictly use arable land, optimize land use structure, strengthen social governance level, improve residents’ satisfaction level, and thus enhance sustainable happiness level. This will provide useful reference for achieving sustainable development goals in similar regions of the world.

Context or Problem: Soil constraints significantly impact crop productivity, however, the direct relationship between these constraints and crop yields remains unclear, creating a need for targeted soil management strategies to enhance agricultural output.Objective or Research Question: This study aims to clarify the influence of various soil constraints on crop productivity by examining soil indicators across distinct productivity zones on Queensland farms.Methods: Soil samples were collected from three productivity zones (consistently low, inconsistent, and consistently high) and five soil layers (D1-D5, 0-120 cm) on 21 farms in Queensland. We utilized the Constraint ID tool and applied mixed-effects models, principal component analysis, and machine learning model to soil chemical indicators including nitrate (NO3–), electrical conductivity (ECe), pH, Cl, exchangeable sodium percentage (ESP), exchangeable contents of Ca (ECa), K (EK), and Mg (EMg).Results: The results identified ECe, pH, Cl, and ESP as critical factors influencing soil fertility, particularly in the deeper layers (D3-D5, 30-120 cm), which indicate issues with salinity, alkalinity, and sodicity. However, subsoil constraints below 30 cm pose significant challenges for remediation, underscoring the importance of surface-level interventions and strategies that benefit the entire soil profile.Conclusions and Implications: This study highlights the importance of surface-level interventions that address the entire soil profile to improve soil health and crop productivity in Queensland’s agricultural systems. It underscores the need for site-specific management strategies to effectively mitigate soil constraints and optimize crop yields.