Gang-Jun Liu

Wetland restoration has become increasingly important for biodiversity conservation, ecosystem-function recovery, and climate resilience. However, global restoration evidence remains fragmented across geographical regions, wetland systems, restoration approaches, and ecological response domains, limiting the identification of broadly transferable restoration principles. This review conducted a systematic mapping review of global wetland ecological restoration research published between 2000 and 2024 by integrating evidence mapping, bibliometric analysis, and ecological interpretation of representative restoration studies. The global literature expanded substantially during the study period, but the evidence base remained unevenly distributed among regions, institutions, and wetland contexts. Differences among research participation, research leadership, and study locations indicated that patterns of scientific output were shaped not only by wetland distribution and restoration needs but also by research capacity, monitoring infrastructure, and institutional networks. Thematic development revealed a transition from intervention-oriented studies focusing on hydrological modification, habitat reconstruction, and pollution control toward broader consideration of biodiversity recovery, ecosystem functions, carbon dynamics, microbial processes, and nature-based solutions. Across wetland systems, restoration pathways varied according to ecological processes and degradation contexts, but common challenges emerged regarding the translation of structural improvements into durable ecological recovery. Improvements in habitat structure, vegetation, hydrological conditions, or physicochemical indicators did not necessarily indicate equivalent recovery of biodiversity, ecosystem functions, or resilience. These findings highlight the need for long-term, multidimensional restoration assessment, stronger evidence generation in underrepresented regions, and adaptive approaches that integrate ecological processes, monitoring, and local contexts to support durable wetland recovery.

A novel integration of retinal multispectral imaging (MSI), retinal oximetry, and laser speckle contrast imaging (LSCI) is presented for functional imaging of retinal blood vessels that could potentially allow early detection or monitoring of functional changes. This technology can rapidly acquire structural MSI images, retinal oximetry, and LSCI blood flow information in a simplified clinical workflow. Results from multiple modalities can be combined to provide structural‐functional information.Further details can be found in the article by Ximeng Feng, Yue Yu, Da Zou, Zi Jin, Chuanqing Zhou, Gangjun Liu, James G. Fujimoto, Changhui Li, Yanye Lu, Qiushi Ren (e202100285) image

Background & objectives: Weather and climate are directly linked to human health including the distribution and occurrence of vector-borne diseases which are of significant concern for public health. Methods: In this review, studies on spatiotemporal distribution of dengue, Barmah Forest Virus (BFV) and Ross River Virus (RRV) in Australia and malaria in Papua New Guinea (PNG) under the influence of climate change and/ or human society conducted in the past two decades were analysed and summarised. Environmental factors such as temperature, rainfall, relative humidity and tides were the main contributors from climate. Results: The Socio-Economic Indexes for Areas (SEIFA) index (a product from the Australian Bureau of Statistics that ranks areas in Australia according to relative socio-economic advantage and disadvantage) was important in evaluating contribution from human society. Interpretation & conclusion: For future studies, more emphasis on evaluation of impact of the El Niño-Southern Oscillation (ENSO) and human society on spatio-temporal distribution of vector borne diseases is recommended to highlight importance of the environmental factors in spreading mosquito-borne diseases in Australia and PNG.

The polyacrylonitrile/fly ash composite was synthesized through solution polymerization and was modified with NH₂OH·HCl. The amidoxime-modified polyacrylonitrile/fly ash composite demonstrated excellent adsorption capacity for Zn²⁺ in an aqueous medium. Fourier transform-Infrared spectroscopy, thermogravimetric analysis, nitrogen adsorption, X-ray diffraction, and scanning electron microscopy were used to characterize the prepared materials. The results showed that the resulting amidoxime-modified polyacrylonitrile/fly ash composite was able to effectively remove Zn²⁺ at pH 4–6. Adsorption of Zn²⁺ was hindered by the coexisting cations. The adsorption kinetics of Zn²⁺ by Zn²⁺ followed the pseudo-second order kinetic model. The adsorption process also satisfactorily fit the Langmuir model, and the adsorption process was mainly single layer. The Gibbs free energy ΔG⁰, ΔH⁰, and ΔS⁰ were negative, indicating the adsorption was a spontaneous, exothermic, and high degree of order in solution system.

The Yellow River Basin (YRB) plays an important role in China’s socioeconomic development and ecological security. From the perspective of recessive land use transition (RLUT), exploring the watershed food security (FS) coordination mechanism is of strategic significance to territorial space optimization and high-quality development. To this end, a coordinated evaluation system was built for analyzing the coupling coordination degree (CCD), spatiotemporal evolution characteristics, and driving mechanism between RLUT and FS of 74 cities in the YRB from 2003 to 2018, using methods such as the coupling coordination degree model, spatial autocorrelation analysis, and the geo-detector model. The results are as follows: (1) Spatial imbalance of RLUT and FS in the YRB is significant. RLUT has significant differences between east and west, and FS has significant differences between north and south. (2) From 2003 to 2018, the CCD between RLUT and FS increased from 0.6028 to 0.6148, maintaining a steady upward trend, and the cold and hot characteristics of spatial agglomeration are significant. (3) The CCD between RLUT and FS depends on population density, average annual temperature, and average elevation. The driving effect of natural factors is higher than the socioeconomic factors on the total basin scale, but the opposite is true on the sub-basin scale. Clarifying the spatiotemporal pattern, characteristics, and mechanism of the coupling and the coordination of RLUT and FS can provide a scientific basis for territorial space planning.

Land consolidation (LC) is an important measure taken to increase the quantity and productivity of farmland while reducing land fragmentation and ensuring food security. However, long-term land consolidation project (LCP) practices are rarely analyzed to assess the effectiveness for achieving current policy objectives of LC in China. Taking the practices of LCPs in Jiangsu Province from 2001 to 2017 as a case study, we used the spatial self-related analysis, the consistency analysis, and the redundant analysis (RDA), and found that the construction scale and the investment amount of LC in Jiangsu Province displayed varying trends, and that the newly increased farmland rate is clearly divided into three stages and gradually decreases. The newly increased farmland area, the investment funds, and reserved land resources for farmlands are not spatially synchronized in Jiangsu Province. Only the positive relationship between the LC rate and the Normalized Difference Vegetation Index (NDVI) growth rate continue to rise. The earlier stage of land consolidation projects (LCPs)’s practices is mainly affected by natural and social factors, and the late stage is mainly affected by economic and strategic factors. Finally, a new implementation scheme framework of LC planning has been proposed. This framework provides reference for top-level design, planning, and management of LC policies at the national level in China and other developing countries.

The rapid development of urbanization and industrialization in coastal China in the past 20 years has exerted a huge squeezing effect on agricultural land use. The phenomenon of non-grain production on cultivated land (NGP) is very common, seriously threatening the protection of high-quality arable land and national food security. In order to find out the overall situation regarding NGP on cultivated land in coastal China, this study revealed the spatial differentiation of NGP and its main driving factors by spatial autocorrelation analysis, multiple linear regression models and geographically weighted regression analysis (GWR). The results show that: (1) in 2018, the non-grain cultivated land area of 11 provinces along the coast of China was about 15.82 × 10⁶ hm², accounting for 33.65% of the total cultivated land area. (2) The NGP rate in 11 provinces gradually decreased from south to north, but the NGP area showed two peak centers in Guangxi province and Shandong province, then decreased gradually outwards. (3) The low economic benefit of the planting industry (per capita GDP and urban-to-rural disposable income ratio) was the most important driving force, leading to the spatial differentiation of NGP, while the number of rural laborers and land transfer areas also acted as the main driving factors for the spatial differentiation of NGP. However, the influence of each driving factor has obvious spatial heterogeneity. The non-grained area and the non-grain production rate at the municipal level were completely different from those at the provincial level, and the spatial heterogeneity was more prominent. In the future, the local government should control the disorganized spread of NGP, scientifically set the bottom line of NGP, reduce the external pressure of NGP, regulate multi-party land transfer behavior, and strengthen land-use responsibilities. This study can provide a scientific foundation for adjusting land-use planning and cultivated land protection policies in China and other developing countries.

Li-Xia-river Wetlands make up the biggest freshwater marsh in East China. Over the last decades, social and economic developments have dramatically altered the natural wetlands landscape. Mitigating land use conflict is beneficial to protect wetlands, maintain ecosystem services, and coordinate local socioeconomic development. This study employed multi-source data and GIS-based approaches to construct a composite index model with the purpose of quantitatively evaluating the intensity of land use conflict in Li-Xia-river Wetlands from 1978 to 2018. The results showed that the percentage of the wetlands’ area declined from 20.3% to 15.6%, with an overall reduction rate of 23.2%. The mean index of land use conflict increased from 0.15 to 0.35, which suggests that the conflict intensity changed from “no conflict” to “mild conflict.” The number of severe conflict units increased by about 25 times. A conspicuous spatial variation of land use conflict was observed across different periods, although taking land for agricultural activities was the overriding reason for wetlands reduction. However, in recent years, urban sprawl has posed the greatest threat to Li-Xia-river Wetlands. Coordinating land use conflict and formulating a practical strategy are the initial imperative steps to mitigate the threat to wetlands.

Understanding where, when, what type and why crashes are occurring can help determine the most appropriate initiatives to reduce road trauma. Spatial statistical analysis techniques are better suited to analysing crashes than traditional statistical techniques as they allow for spatial dependency and non-stationarity. For example, crashes tend to cluster at specific locations (spatial dependency) and vary from one location to another (non-stationarity). Several spatial statistical methods were used to examine crash clustering in metropolitan Melbourne, including Global Moran’s I statistic, Kernel Density Estimation and Getis-Ord Gi* statistic. The Global Moran’s I statistic identified statistically significant clustering on a global level. The Kernel Density Estimation method showed clustering but could not identify the statistical significance. The Getis-Ord Gi* method identified local crash clustering and found that 15.7 per cent of casualty crash locations in metropolitan Melbourne were statistically significant hot spots at the 95 per cent confidence level. The degree, location and extent of clustering was found to vary for different crash categories, with fatal crashes exhibiting the lowest level of clustering and bicycle crashes exhibiting the highest level of clustering. Temporal variations in clustering were also observed. Overlaying the results with land use and road classification data found that hot spot clusters were in areas with a higher proportion of commercial land use and with a higher proportion of arterial and sub-arterial roads. Further work should investigate network based hot spot analysis and explore the relationship between crash clusters and influencing factors using spatial techniques such as Geographically Weighted Regression.