The standardized FAO56 Penman-Monteith model, which has been the most reasonable method in both humid and arid climatic conditions, provides reference evapotranspiration (ETo) estimates for planning and efficient use of agricultural water resources. And sensitivity analysis is important in understanding the relative importance of climatic variables to the variation of reference evapotranspiration. In this study, a non-dimensional relative sensitivity coefficient was employed to predict responses of ETo to perturbations of four climatic variables in the Ejina oasis northwest China. A 20-year historical dataset of daily air temperature, wind speed, relative humidity and daily sunshine duration in the Ejina oasis was used in the analysis. Results have shown that daily sensitivity coefficients exhibited large fluctuations during the growing season, and shortwave radiation was the most sensitive variable in general for the Ejina oasis, followed by air temperature, wind speed and relative humidity. According to this study, the response of ETo can be preferably predicted under perturbation of air temperature, wind speed, relative humidity and shortwave radiation by their sensitivity coefficients.

Ecosystem service mapping (ESM) studies are receiving increasing attention due to the imbalance between the supply of and demand for ecosystem services (ES). Global scale ESM is still scarce, but the high computing power of the Google Earth Engine (GEE) cloud platform significantly increases the efficiency. Based on global-scale land cover datasets and the GEE, an ES matrix model based-expert is constructed in this paper to map the ES supply, demand, and relative budgets. The net primary productivity (NPP), enhanced vegetation index (EVI), nighttime light (NTL), and world population (Pop) were acquired, and the NPP and EVI and the NTL and Pop datasets were used to revise the supply of and demand for ESs, respectively. We discovered that the ES supply capacity exhibits a double-peaked distribution with latitude, and the peaks are located at the equator and 50° N. The global ESs have a high spatial heterogeneity and the global supply of ESs is 2.405 times higher than the demand; however, the demand exhibits an increasing trend of about 3.36% per decade, and only southern Asia has more ES demand than supply. The imbalance between the ES supply and demand produced a push-pull effect, that is, it forced humans to move closer to the ES surplus regions (ESSRs) and farther away from the ES deficit regions (ESDRs), and the destruction of the ecological environment promoted this phenomenon. The global terrestrial area is divided into eight ES sub-regions, and targeted land management, urban planning, and environmental remediation policies are proposed.

Innovation is the engine for the sustainable development of cities and regions, and an innovation perspective is used to study the collaborative innovation relationship between regional cities and the evolution mechanism of regional innovation network formation. Based on the social network analysis method and spatial analysis method, we explore the characteristics of the regional research cooperation network and its spatial pattern, as well as analyze the formation mechanism of the network using the exponential random graph model. The study finds that the scale of the regional innovation network is expanding, the overall network density is gradually increasing, but the nodes are loosely linked, and the regional innovation network is in the stage of deepening development. There is spatial heterogeneity in the regional innovation network, with a dumbbell-shaped distribution of “double-core dominance and central collapse”. During the formation of the regional innovation network, the endogenous structure of the innovation network is multi-connected under the path dependence, and the network development tends to be complicated; the economic strength and scientific research capability of cities and multi-dimensional proximity have a positive influence on the formation of the innovation network, and geographical proximity, social proximity and cognitive proximity can promote intra-regional innovation cooperation.

Constructing regional ecological security patterns (ESP) and enhancing carbon sequestration are essential for achieving China’s dual-carbon goals. However, rapid urbanization has intensified landscape fragmentation, disrupted ecosystem flows, and significantly altered urban ecological networks, weakening their carbon sink functions. Using the Chengdu metropolitan area (CMA) as a case study, a time-series ESP from 2000 to 2020 was constructed. Morphological Spatial Pattern Analysis (MSPA), the Minimum Cumulative Resistance (MCR) model, the gravity model, and complex network theory were employed to assess the spatiotemporal evolution and carbon sequestration capacity of the ecological network. Results revealed continuous declines in ecological sources and corridors, an initial rise then stabilization in resistance, and weakening connectivity, particularly in central and western subregions. Reductions in modularity and topological indices reflected lower ecological stability and greater vulnerability. Forest land served as the primary carbon sink, closely associated with multiple topological metrics; grassland sequestration correlated with clustering, while water bodies were positively linked to centrality measures. Adding 10 stepping-stone nodes and 45 corridors could enhance carbon sequestration by approximately 4156 Mg C yr⁻¹, with forests contributing 94.8% by 2020. This study provides scientific support for resilient regional ESP construction and dual-carbon strategy advancement.

The cultivation industry occupies a large proportion of greenhouse gas emissions in agriculture. Assessing greenhouse gas emissions from the cultivation industry is pivotal for mitigating emissions and promoting sustainable cultivation. Utilizing greenhouse gas emission calculation methods recommended by the Intergovernmental Panel on Climate Change (IPCC) and other methods, this work evaluated annual emissions and the emission structure of major crops from 2005 to 2021 in the Chengdu Plain, a significant agricultural region in Southwest China. We identified nitrogen fertilizer as the primary contributing factor to high emissions from cultivation production. Subsequently, we analyzed the trend and utilization of nitrogen fertilizer, which proposes essential strategies for reducing greenhouse gas emissions. The results showed that greenhouse gas (GHG) emissions from the cultivation industry in the Chengdu Plain exhibited a growth, fluctuation, and eventual decline trend from 2005 to 2021. The emissions increased from 5,148,900 t in 2005 to 6,289,700 t in 2009, representing a 22.16% increase, and subsequently decreased to 5,109,900 t in 2021, marking a 23.31% decrease. Nitrogen fertilizer application emerges as the primary source of GHG emissions, constituting approximately half of the total, with nitrogen fertilizer manufacturing contributing significantly as well, collectively amounting to about 70%. We also found that the proportion of greenhouse gas emissions attributed to cash crop cultivation has gradually increased over the last decade. Among these crops, vegetables exhibit the highest emissions, comprising nearly half of the total emissions from 2019 onwards. However, the nitrogen fertilizer use efficiency of cash crops is less than 30%, with higher nitrogen surplus, ammonia volatilization, and nitrogen leaching per unit area, and the total amount is higher than that of grain crops. Among cash crops, vegetables exhibit the highest amount of nitrogen surplus, ammonia volatilization, and nitrogen leaching, constituting nearly half of the total amount in the study area since 2019. Our findings significantly affect sustainable and low-carbon cultivation industry development in the study area.

Chengdu has experienced a rapid urbanization in the past two decades, and its land spatial pattern has undergone severe changes. It's meaningful to investigate the tempo-spatial evolution of land spatial pattern and then contribute to high-quality development in Chengdu. Based on the Landsat-series satellite imagery and land use/cover datasets, this paper investigates Chengdu's land function change concerning Production, Living and Ecological (PLE) land. The methods of land dynamics degree, landscape pattern index and Pearson correlation were be employed to analyzes the tempo-spatial evolution of landscape pattern in Chengdu, and some suggestions were finally made. We found that there were severe dynamic degree of PLE land in Chengdu and the production and ecological land were decrease obviously before 2015. Contrastingly, the dynamic degree is decrease after 2015, high dynamic degree regions are move to the northeast from 2000–2019. In addition, the change of production land is the main factor affecting the landscape pattern of Chengdu. In general, we put forward the macroscopic strategy and suggestions of “one core, two belts, four regions, and one direction” to support the high-quality development of Chengdu.