The dynamic relationships between landscape structure and ecosystem services: An empirical analysis from the Wuhan metropolitan area, China.

Environmental managers have been striving to optimize landscape structure to achieve a sustained supply of ecosystem services (ESs). However, we still lack a full understanding of the relationships between landscape structure and ESs due to the absence of thorough investigations on the variability of these relationships in space and time. To fill this critical gap, we assessed landscape structure alongside four important ESs (agricultural production (AP), carbon sequestration (CS), soil conservation (SC), and water retention (WR)) in the Wuhan metropolitan area (WMA), and then analyzed the spatiotemporal impacts of landscape structure on ESs from 2000 to 2020 using Geographically and Temporally Weighted Regression. The results show only AP maintained a stable growth trend over the past two decades, while the other ESs fluctuated considerably with a noticeable decline in SC and WR. The importance of landscape structure in influencing ESs varies by time and place, depending on the local landscape composition and configuration. In general, landscape composition has a stronger and less temporally stable impact on ESs compared to configuration. Furthermore, increases in landscape diversity, as measured through Shannon's diversity index, and the percentage of woodlands were found to contribute to the simultaneous benefits of multiple ESs, but in most cases the effects of landscape structure on different ESs were different or even opposite, suggesting that trade-offs are critical in landscape management. The findings highlight the complex response of ESs to dramatically changing landscapes in the WMA and can guide decision-makers in precise spatial arrangement and temporal adjustments to improve current landscape management.

Dynamics and Determinants of the Grain Yield Gap in Major Grain-Producing Areas: A Case Study in Hunan Province, China.

Understanding the dynamics of the grain yield gap (YGAP) and its causative factors is essential for optimizing the layout of grain production and addressing the food crisis, especially in countries with a huge population and less cultivated land, such as China. In the study, a spatial analysis- and machine learning-based framework for YGAP analysis was developed, taking Hunan Province, China, as an application. The results showed that the average YGAP in Hunan Province gradually narrowed from 1990 to 2018, and the YGAPs narrowed in 116 counties. Of which, 26 counties narrowed by more than 4 t ha-1, 58 counties narrowed from 2-4 t ha-1, and 32 counties narrowed within 2 t ha-1. Additionally, we found that the GDP per capita (GDPPC), sunshine hours (SH), per capita annual net income of farmers (PCAI), and rural electricity consumption (REC) play a key role in YGAP change, and the importance of human investment to the YGAP decreased, while socioeconomic environment became the dominant factor that influenced grain production. Comprehensively, the relatively great potential for grain yield growth was generated in sixty-four counties, which are mainly located in the northern, central, and southern Hunan. The findings suggest that it is necessary to consider the trends of economic development in rural areas and population migration in agricultural management. This work provides insights into yield gap dynamics and may contribute to sustainable agricultural management in Hunan Province, China, and other similar regions.