The global food trade network (FTN) is a critical infrastructure for achieving the Sustainable Development Goals (SDGs). The FTN’s vulnerability to geopolitical conflicts, public health crises, and climate change events directly impacts food security and the ability to meet the SDGs. This study aims to analyze the dynamic evolution of the vulnerability of FTN, focusing on the period from 2000 to 2022, to aim for strategies for enhancing the resilience and sustainability of the global food system. Based on complex network analysis, we examine the structural characteristics and evolution of FTN for four major crops: soybeans, wheat, rice, and maize. We identify a trend towards increased network density and regionalization, with a decline in average shortest path length (ASPL) and an increase in the average clustering coefficient (ACC). These changes indicate a shift towards a more interconnected and resilient FTN in response to various shocks, including the COVID-19 pandemic and the Russia–Ukraine conflict. The findings suggest that the global FTN has adapted to increase resilience, which is essential for achieving the SDGs related to food security and sustainable development. The study’s insights can guide policy interventions to further strengthen the network against future shocks and promote global food security.

Although irrigation systems are critical to the long-term viability of agriculture, they also contribute a significant amount of carbon dioxide emissions. This creates a conflict between reducing greenhouse gas emissions and promoting agricultural growth. Researchers may be able to gain a better understanding of the subject by looking at the connection between irrigation water efficiency (IWE) and agricultural carbon emissions (ACE). With data from 30 Chinese provinces collected between 2002 and 2019, this study examines the dynamic effect of IWE on ACE. According to the results, IWE has the potential to significantly raise ACE. The positive effects of IWE become more pronounced as ACE increases, according to the heterogeneity analysis. ACE in northern China is also more vulnerable to IWE than other ACE regions. Irrigation scales appear to be a significant channel through which IWE positively affects ACE, according to an investigation of possible mechanisms. However, the increased IWE causes the planting structure adjustments, which aids in the reduction of ACE. The results of this study have significant ramifications for public policy.

The new wave of reform of collective forestland tenure (NRCFT) in China is considered an important policy for achieving sustainable management of forest resources. The purpose of this study is to investigate the influence of NRCFT on forest fragmentation in the Beijing–Tianjin–Hebei region of China based on a fixed-effects model. The forest fragmentation was analyzed based on the remote sensing images of Landsat and landscape pattern indices in the Beijing–Tianjin–Hebei region from 2000 to 2018. The results showed that (1) The NRCFT has significantly contributed to reducing forest fragmentation. (2) The effect of economic growth on forest fragmentation showed an inverted U-shape. (3) The implementation of the Grain for Green Program (GGP) and the transformation of rural energy consumption significantly reduce the degree of forest fragmentation. This study has crucial implications for formulating policies, achieving good forest governance, and reducing forest fragmentation.

Population aging is a critical demographic trend in China, creating both challenges and opportunities for sustainable development. As aging alters the structure of the workforce and capital demand, understanding its effect on productivity is essential to managing demographic transitions in China. This study investigates the causal impact of population aging on labor productivity, with a focus on the mediating role of the capital–labor ratio and heterogeneities across industries, skill levels, and regions. Using data from Chinese listed firms between 2011 and 2018, this paper employs industry- and year-fixed effects regression models to control for unobservable heterogeneity and conducts a formal causal mediation analysis. The analysis reveals that population aging significantly enhances labor productivity. Specifically, a one-percentage-point increase in the old-age dependency ratio is associated with a 1.47% increase in firm-level labor productivity. The capital–labor ratio emerges as a critical mechanism, mediating the relationship between aging and productivity by incentivizing firms to increase capital intensity in response to labor shortages. Approximately 72.4% of the total effect is mediated through changes in capital intensity. The findings highlight notable heterogeneities. Labor-intensive firms and low-skilled worker segments experience stronger productivity gains from aging compared with their capital-intensive and high-skilled counterparts. At the regional level, the productivity effects are most pronounced in first- and second-tier cities, while third-tier cities show negligible impacts, reflecting resource and structural constraints. This study underscores the dual role of population aging as a challenge and an opportunity. Policy recommendations include (1) expanding targeted fiscal support for capital investment and automation in aging-intensive industries; (2) promoting vocational training programs tailored to older workers and digital skills development; and (3) strengthening infrastructure and institutional capacity in third-tier cities to better absorb productivity spillovers from demographic adjustment. By addressing these demographic and productivity linkages, the study contributes to achieving Sustainable Development Goals 8 (Decent Work and Economic Growth), 9 (Industry, Innovation, and Infrastructure), and 10 (Reduced Inequalities), by promoting inclusive productivity growth, enhancing industrial adaptation to demographic change, and reducing regional and skill-based disparities.These findings offer valuable insights for policymakers and businesses navigating the complexities of aging economies.

The United Nations Sustainable Development Goals (SDGs) emphasize enhancing agricultural productivity sustainably and strengthening the resilience of agricultural systems amidst rising economic uncertainties, escalating climate change risks, and geopolitical tensions. Amidst these challenges, the relentless progress of digital and information technologies heralds the digital economy as a potential game-changer for agricultural productivity. In 2023, the scale of China’s digital economy reached 7.64 trillion US dollars, accounting for 42.8% of China’s GDP, with the contribution of digital economy growth to GDP growth reaching 66.45%. As a nascent yet formidable force in the global economy, the digital economy is reshaping industries worldwide, particularly the agricultural sector. Food security and sustainability could potentially be affected by the digital economy, while agricultural productivity is a crucial element of food security and sustainability. The primary objective of this study is to investigate the extent to which the digital economy (DE) contributes to agricultural technical efficiency (ATE) in the context of China and to explore the mechanisms through which this impact is mediated and the implications for regional disparities. This study delves into the Chinese context, examining the empirical evidence of how the DE bolsters ATE utilizing provincial panel data. Key findings reveal the following: (1) DE exerts a significant and positive impact on ATE, demonstrating robust effects. (2) Marketization acts as a pivotal mediation mechanism in transmitting the positive influence of DE on ATE. (3) DE fosters convergence in ATE, narrowing regional disparities. Based on these insights, we propose strategic recommendations to mitigate agricultural production risks in agricultural productivity and propel food security and sustainability in China.