Geographical indication agricultural products (GIAPs) are characterized by their reputation, high quality, unique features, and distinct regional attributes. This study constructed a “description–measurement–attribution” analytical framework to identify the spatial pattern differentiation of GIAPs and the underlying mechanisms that influence them through a multi-method approach. In terms of description and measurement, the nearest-neighbor index was used to characterize the distribution pattern, Voronoi polygons were employed to partition spatial regions, and the Lorenz curve combined with the Dagum Gini coefficient was used to quantify the degree of concentration. In terms of attribution analysis, the geodetector and quantile regression model were used to identify the dominant factors and their interactions driving the spatial differentiation of GIAP types. The findings were as follows: (1) The number of GIAPs displayed a considerable upward trend. Bounded by the Hu Huanyong Line, a spatial pattern of “dense in the east and sparse in the west” was observed along with clustered distribution. Core clusters were concentrated in Shandong and Heilongjiang, while secondary clusters were distributed in Zhejiang, Jiangsu, Hubei, Shanxi, Henan, and other regions. Across product categories, different types of GIAPs, such as tea, fruits, and grains, exhibited distinct core–secondary core distribution patterns. (2) Based on a quantitative comparison of the concentration index I, the spatial agglomeration of various GIAPs was ranked as follows: aquaculture industry (0.556) > animal husbandry (0.386) > planting industry (0.281) > total GIAPs (0.272), indicating that the aquaculture industry had the most pronounced spatial concentration. (3) The spatial differentiation of the planting industry was mainly influenced by factors such as the employment scale in the primary industry, value added of the primary industry, and the level of agricultural mechanization. The key factors for animal husbandry were agricultural mechanization, rural residents’ income level, and value added of the primary industry. The spatial differentiation of the aquaculture industry was closely related to rural residents’ income level, regional per capita GDP, and annual precipitation.
Household grain security in agro-pastoral systems of the Qinghai-Tibet Plateau (QTP) depends not only on production capacity and land resources, but also on how staple crops are allocated among food, feed, storage, and market purposes. However, the spatial pattern and drivers of the QTP remain unclear, hindering regional food security assessment. Using multi-year household surveys, we analyzed wheat and highland barley utilization and grain-security pathways across three major agricultural regions on the QTP. Results revealed distinct spatial disparities in production capacity: with the Yarlung Zangbo-Lhasa River-Nyangqu River region (YLN) higher than the Hehuang Valley Region (HVR) and the Agro-Pastoral Ecotone of Qinghai (APE). Consumption strategies diverged: YLN exhibited a storage-oriented subsistence pattern, HVR displayed a food-feed dual structure, while APE was feed- and market-oriented with feed grain accounting for 29.4
Pakistan’s reliance on irrigation has intensified water scarcity, threatening food security, water sustainability, and economic development. Understanding the dynamics of water scarcity and its driving factors is essential for the synergistic development of the water-food-economy nexus in Pakistan. However, previous studies lacked a quantitative attribution of water scarcity variations across all agricultural regions. This study quantified the spatiotemporal changes in water availability, irrigation water demand (IWD), and the agricultural water scarcity index (WSI) across Pakistan (1990–2021), and employed the Logarithmic Mean Divisia Index decomposition to identify key drivers. The results showed that increased crop evapotranspiration and cropland expansion significantly raised national IWD (+0.73 billion m3/year), with the Punjab Province contributing 66
Identifying the drivers of urban carbon emissions and accurately projecting future trends are crucial for achieving China’s dual-carbon goals. However, further research is needed to incorporate recent emission reduction trends and policy developments into modeling analyses in order to identify optimal pathways for cities to achieve carbon peaking. This study addresses a gap in Beijing’s carbon reduction research by developing Logarithmic Mean Divisia Index (LMDI) and Low Emissions Analysis Platform (LEAP) models to simulate multiple policy scenarios aligned with the city’s emission reduction targets and to propose optimal decarbonization pathways. The results indicate that carbon emissions from the three major industries and the residential sector are primarily influenced by factors such as energy intensity, energy structure, industrial structure, and economies of scale. Scenarios emphasizing improvements in energy efficiency and transitions toward low-carbon energy sources under individual policy frameworks demonstrate substantial emission reduction effects. Under comprehensive mitigation measures, Beijing could achieve peak carbon emissions by 2027, reducing emissions by 12.84
Extensive research has demonstrated that urban green spaces play a vital role in promoting residents’ health. Meanwhile, growing evidence suggests that bird diversity may also contribute to human health; however, whether bird diversity mediates the relationship between urban green spaces and elderly health remains unclear. To address this knowledge gap, this study investigated 563 residential communities in the central districts of Shanghai by integrating citizen-science bird data and applying mediation analysis to examine the relationships among green space coverage, bird richness, and elderly health. The results revealed significant positive associations between green space coverage and bird richness, as well as between bird richness and elderly health. After incorporating bird richness as a mediating variable, the effect of green space coverage on elderly health decreased from 0.16 (p<0.001) to 0.12 (p<0.05) while remaining statistically significant, indicating a partial mediating effect of bird richness. Further analysis showed that the total effect of green space coverage on elderly health was 0.16, comprising a direct effect of 0.12 (p<0.05) and an indirect effect of 0.04 through bird richness, which accounted for 25.0
