Particulate matter (PM) is an essential source of atmospheric pollution in metropolitan areas since it has adverse effects on human health. However, previous research suggested wetlands can remove particulate matter from the atmosphere to land surfaces. This study was conducted in the Hanshiqiao Wetland National Nature Reserve in Beijing during 2016. The concentrations of PM₁₀ and PM_2.5 on a wetland and bare land in the park, as well as metrological data, were collected during the whole year. Based on the observed data, removal efficiency of each land use type was calculated by empirical models and the relationships between concentrations and metrological factors were also analyzed. The results indicated that: (1) In general, the PM₁₀ and PM_2.5 concentrations on the bare land surface were higher than those on the wetland surface, in both of which the highest value appeared at night and evening, while the lowest value appeared near noon. In terms of season, the average concentration of PM₁₀ was higher in winter (wetland: 137.48 μg·m⁻³; bare land: 164.75 μg·m⁻³) and spring (wetland: 205.18 μg·m⁻³; bare land: 244.85 μg·m⁻³) in general. The concentration of PM_2.5 on the wetland surface showed the same pattern, while that on the bare land surface was higher in spring and summer. (2) Concentrations of PM₁₀ and PM_2.5 were significantly correlated with the relative humidity (p < 0.01) and inversely correlated with wind speed (p < 0.05). The relationship between PM₁₀ and PM_2.5 concentrations and temperature was more complicated—it showed a significantly negative correlation (p < 0.01) between them in winter and spring, however, the correlation was insignificant in autumn. In summer, only the correlation between PM₁₀ concentration and temperature on the wetland surface was significant (p < 0.01). (3) The dry removal efficiency of PM₁₀ was greater than that of PM_2.5. The dry removal efficiencies of PM₁₀ and PM_2.5 followed the order of spring > winter > autumn > summer on the wetland. This study seeks to provide practical measures to improve air quality and facilitate sustainable development in Beijing.

Forest therapy bases are essential ecological recreational locations to promote mental and physical health while at the same time allowing people to enjoy and appreciate the forest. The article took Japan, where the development of forest therapy is in a mature stage, as the research object. Using multi-data and the methodologies of Kernel Density Analysis in ArcGIS and GeoDetector, the spatial distribution characteristics of Japan’s forest therapy bases were investigated, as well as the influencing factors. The results reveal that the spatial distribution of forest therapy bases in Japan is unbalanced, with an aggregated distribution in economically developed and densely populated areas. The spatial density of natural landscape resources, Gross Domestic Product (GDP), the spatial density of population, distance from three major metropolitan areas, rail transit ridership, and spatial density of tourism resources are factors influencing the distribution of forest therapy bases in Japan. The factors interact with each other, forming the spatial distribution pattern. Among these factors, GDP has the greatest explanatory power for the spatial distribution of forest therapy bases in Japan, followed by the distance from Japan’s three major metropolitan areas and spatial density of tourism resources, while the spatial density of population, spatial density of natural landscape resources, and rail transit ridership have a relatively weaker influence on forest therapy bases in Japan. The findings provide some insight into the macroscopic layout of forest therapy bases in various regions of different countries, demonstrating that excellent transportation facilities and good natural resources are the fundamental considerations for the location of forest therapy bases and that densely populated urban areas with a strong economic foundation are key areas for the development of forest therapy bases. Additionally, to take advantage of industrial agglomeration and synergize regional development, considerations for merging with existing resources, such as national parks, forest parks, and recreation forests, should be made.

Water isotope studies in alpine wetlands have revealed the dynamic characteristics of the hydrological cycle and evapotranspiration processes in the Zoige region through hydrogen and oxygen isotope ratios. However, the hydrological continuity between marshes, rivers, and lakes in wetlands is relatively understudied. The study found that the Zoige Alpine Wetland local meteoric water line (LMWL) is δD = 8.33δ¹⁸O + 14.52 (R² = 0.92) by using linear regression analysis to confirm the Craig temperature effect equation backwards. Comparison with the global and Chinese LMWLs revealed that the slope of the Zoige LMWL is significantly higher than those of the global and Chinese LMWLs, indicating that the oceanic warm and humid airflow and the southwest monsoon significantly influence this region. The δ¹⁸O ranges of rivers, lakes, and marshes in the Zoige wetland were −12.86‰ to −2.02‰, −12.9‰ to −2.22‰, and −15.47‰ to −7.07‰, respectively. In terms of δD, marshes had the lowest δD values, with a mean value of −89.58‰, while rivers and lakes had close δD values of about −72‰. Rivers had the most dramatic variation in d-excess values, ranging from −34.16‰ to 3.68‰, while marshes and lakes had more concentrated d-excess values, with particularly negative values in marshes. Regression analysis yielded a trend line of δD = 5.41δ¹⁸O − 29.57 for evaporation from the water bodies, further demonstrating the importance of evaporation effects in this region. By using the Rayleigh fractionation model and estimating the climatic conditions, we found that the lake water had the highest evaporation intensity (41%). Those of the river and marsh water were 40% and 36%, respectively. The results of this study provide new scientific insights into the hydrological connectivity, evaporation processes, and water source characteristics in the Zoige wetland. Future studies can shed more light on how climate change affects wetland hydrological systems and how they change over time and space. This will help to manage water resources in the region and protect the environment.

Bolboschoenus planiculmis (F.Schmidt) T.V.Egorova is a typical wetland plant in the species-rich Cyperaceae family. This species contributes prominently to carbon dynamics and trophic integration in wetland ecosystems. Previous studies have reported that the chromosomes of B. planiculmis are holocentric; i.e. they have kinetic activity along their entire length and carry multiple centromeres. This feature was suggested to lead to a rapid genome evolution through chromosomal fissions and fusions and participate to the diversification and ecological success of the Bolboschoenus genus. However, the specific mechanism remains uncertain, partly due to the scarcity of genetic information on Bolboschoenus. We present here the first chromosome-level genome assembly for B. planiculmis. Through the integration of high-quality long-read and short-read data, together with chromatin conformation using Hi-C technology, the ultimate genome assembly was 238.01 Mb with a contig N50 value of 3.61 Mb. Repetitive elements constituted 37.04% of the genome, and 18,760 protein-coding genes were predicted. The low proportion of long terminal repeat retrotransposons (∼9.62%) was similar to that reported for other Cyperaceae species. The K_s (synonymous substitutions per synonymous site) distribution suggested no recent large-scale genome duplication in this genome. The haploid assembly contained a large number of 54 pseudochromosomes with a small mean size of 4.10 Mb, covering most of the karyotype. The results of centromere detection support that not all the chromosomes in B. planiculmis have multiple centromeres, indicating more efforts are needed to fully reveal the specific style of holocentricity in cyperids and its evolutionary significance.

As a critical ecological security node in North China, the Baiyangdian Basin underpins regional water resources, biodiversity conservation, and environmental risk mitigation. Its ecological integrity is fundamental to the sustainable development of the Beijing–Tianjin–Hebei (BTH) megaregion. This study leveraged Google Earth Engine (GEE) to quantify spatiotemporal ecosystem dynamics within the Baiyangdian watershed from 1990 to 2023, utilizing the Remote Sensing Ecological Index (RSEI). The primary drivers influencing the watershed’s ecological and environmental quality were subsequently analyzed. The results show that the ecological quality of the Baiyangdian Basin showed fluctuating changes from 1990 to 2023. Overall, the northwestern part of the Baiyangdian Basin improved significantly, while the southeastern part was slightly degraded, and the intensity of the change between different RSEI grades was low, mainly fluctuating between poor, medium, and good grades. Both anthropogenic and natural factors have high explanatory power for the ecological quality of the Baiyangdian watershed, and the land use type in particular is the main driver of changes in the RSEI area. The explanatory power of these factors was significantly enhanced by the interaction between them, especially the interaction between the land use type and other drivers. Within the drivers of the land use type, the cropland area, woodland area, shrub area, and grassland area have a significant influence. In summary, the area change in different land use types is the main factor influencing the ecological quality of the Baiyangdian watershed. This study has demonstrative value and implications for large-scale shallow lakes and wetlands, ecological barriers in rapidly urbanizing regions, the integrated management of cross-administrative watersheds, and the use of the GEE platform for long time-series and large-scale ecological monitoring and assessment.

The blue and green water resource distribution of the Jing River Basin, a cradle of Chinese civilization on the Loess Plateau, was studied using the Soil and Water Assessment Tool and the Sequential Uncertainty Fitting algorithm (vers. 2). Understanding these resources aids in the ecological preservation of the Yellow River Basin and its high-quality development. Future climate conditions were simulated using the Statistical Downscaling Model (SDSM). The data came from the Shared Socioeconomic Pathway (SSP) projections (SSP1-2.6, SSP2-4.5, and SSP5-8.5) in the Canadian Earth System Model (vers. 5), covering the 2030s, 2060s, and 2090s (based on 2015–2045, 2046–2075, and 2076–2100 climate projections, respectively). The SDSM accurately simulated temperature and precipitation trends, with its temperature predictions being more accurate. The results show that the maximum temperature, minimum temperature, and precipitation tend to increase under the three future climate scenarios, and the amount of blue and green water continues to increase in the future, with the SSP5-8.5 scenario showing the highest amount of blue and green water, and the SSP1-2.6 scenario showing the lowest amount of blue and green water, in terms of the climate scenarios. In terms of temporal distribution, 2090s has the most abundant blue and green water and 2030s has the least blue and green water content. Forecasting blue and green water changes due to climate change is vital for regional water management and risk assessment.