Urban ecosystem dysfunction, habitat fragmentation, and biodiversity loss caused by rapid urbanization have threatened sustainable urban development. Urban habitat quality is one of the important indicators for assessing the urban ecological environment. Therefore, it is of great practical significance to carry out a study on the driving mechanism of urban habitat quality and integrate the results into urban planning. In this study, taking Zhengzhou, China, as an example, the InVEST model was used to analyze the spatial differentiation characteristics of urban habitat quality and Geodetector software was adopted to explore the driving mechanism of habitat quality at different grid-scales. The results show the following: (1) LUCC, altitude, slope, surface roughness, relief amplitude, population, nighttime light, and NDVI are the dominant factors affecting the spatial differentiation of habitat quality. Among them, the impacts of slope, surface roughness, population, nighttime light, and NDVI on habitat quality are highly sensitive to varying grid-scales. At the grid-scale of 1000 to 1250 m, the impacts of the dominant factors on habitat quality is closer to the mean level of multiple scales. (2) The impact of each factor on the spatial distribution of habitat quality is different, and the difference between most factors has always been significant regardless of the variation of grid-scales. The superimposed impact of two factors on the spatial distribution of habitat quality is greater than the impact of the single factor. (3) Combined with the research results and the local conditions of Zhengzhou, we put forward some directions of habitat protection around adjusting urban land use structure, applying nature-based solutions and establishing a systematic thinking model for multi-level urban habitat sustainability.

Greenscaping, a key sustainable practice, helps cities combat rising temperatures and climate change. Urban parks, a pivotal greenscaping element, mitigate the urban heat island (UHI) effect. In this study, we utilized high-resolution remote sensing imagery (GF-2 and Landsat 8, 9) and in situ measurements to analyze the seasonal thermal regulation of different park types in Zhengzhou, China. We calculated vegetation characteristic indices (VCIs) and landscape patterns (LMs) and employed boosted regression tree models to explore their relative contributions to land surface temperature (LST) across different seasons. Our findings revealed that urban parks lowered temperatures by 0.65 °C, 1.41 °C, and 2.84 °C in spring, summer, and autumn, respectively, but raised them by 1.92 °C in winter. Amusement parks, comprehensive parks, large parks, and water-themed parks had significantly lower LSTs. The VCI significantly influenced LST in autumn, with trees having a stronger cooling effect than shrubs. LMs showed a more prominent effect than VCIs on LST during spring, summer, and winter. Parks with longer perimeters, larger and more dispersed green patches, higher plant species richness, higher vegetation heights, and larger canopies were associated with more efficient thermal reduction in an urban setting. The novelty of this study lies in its detailed analysis of the seasonal thermal regulation effects of different types of urban parks, providing new insights for more effective urban greenspace planning and management. Our findings assist urban managers in mitigating the urban surface heat effect through more effective urban greenspace planning, vegetation community design, and maintenance, thereby enhancing cities’ potential resilience to climate change.

Following severe anthropogenic pressure from rapid economic development, wetland biodiversity is now decreasing alarmingly, thus leading to adverse effects. Protected areas (PAs) can be crucial conservation tools to secure wetland biodiversity. However, whether these PAs exhibit high conservation efficiency in buffering wildlife and habitats from human pressures needs to be understood. Given their sensitivity to habitat quality and regional resource changes, threatened waterfowl could be suitable wetland ecosystem indicators. This study examined the conservation effectiveness of Henan Yellow River Wetland National Nature Reserve (HYRWNNR), which is a crucial region on the East Asia–Australia route for global bird migration. We performed Maximum Entropy (MaxEnt) modeling based on field survey data of the 19 threatened waterfowl species, and Human Impact Index (HII) was further mapped with waterfowls distribution to identify the conservation gap and priorities of the HYRWNNR. The results indicated that threatened waterfowl distribution were affected by both environmental factors and human pressure, and a conservation gap existed in the HYRWNNR. Two conservation scenarios were generated based on the spatial pattern of conservation priorities, and their corresponding management strategies were suggested. This study identifies conservation priorities from a novel perspective by synthesizing habitat suitability and human pressure, which can present basic information regarding the HYRWNNR management while supporting waterfowl conservation planning, ultimately promoting wetland habitats sustainability.

The ecological impacts of dam and reservoir construction necessitate systematic environmental quality evaluation (EEQ) to reconcile ecological protection with sustainable development. To address this need, we integrated the Remote Sensing Ecological Index (RSEI)—a comprehensive metric synthesizing greenness, humidity, heat, and dryness—with a Land Use Change Ecological Response (LUCER) model to quantify the long-term EEQ dynamics in reservoir-affected regions. This study utilized Landsat and Sentinel-2 remote sensing imagery with a 10 m resolution from the years 2000, 2005, 2010, 2015, and 2020 to compute the RSEI for the Qianping Reservoir area in Henan Province, investigating the spatiotemporal variations in EEQ. Key findings reveal: (1) Temporal trend: EEQ showed fluctuating improvement, with RSEI projected to rise gradually until 2030. (2) Spatial pattern: A lower ecological quality in central reservoir zones contrasts with higher quality in surrounding mountainous areas. (3) Mechanism: The Land Use Change Ecological Response (LUCER) model reveals that the conversion of cultivated land to forestland and grassland drives significant EEQ improvements, counterbalancing the negative impacts of hydrological fragmentation caused by reservoir construction and urbanization. This study advances RSEI applications in reservoir ecology by establishing a coupled monitoring–prediction framework, providing actionable insights for dam-related ecological restoration and governance.

Cities are major contributors to global carbon emissions; however, urban parks offer substantial potential for carbon sinks. Research on factors influencing carbon capture in urban park vegetation is still limited. This study investigates 81 urban parks in Xinyang, Henan Province, to quantify woody plant carbon storage (CS) and sequestration (CSG). By surveying all vegetation types and quantities in these parks, along with factors like park attributes, community structure, biodiversity, spatial distribution, woody plant connectivity, and spatial complexity, we create statistical models for CS and CSG. The results indicate that the average carbon storage density (CSD) in Xinyang’s urban parks is 4.01 kg/m², while the carbon sequestration density (CSGD) is 0.39 kg·C·m²·yr⁻¹. The dominant tree species are Ligustrum lucidum, Osmanthus fragrans, and Lagerstroemia indica, while species with higher carbon sequestration potential, such as Glyptostrobus pensilis, Populus deltoides, and Albizia kalkora, reveal a discrepancy between common and high-sequestration species. The study shows that park characteristics, community structure, and biodiversity are key factors impacting urban carbon sink capacity. By analyzing the relationship between these factors and carbon sinks in urban park vegetation, we create a comprehensive framework for assessing tree CS and CSG, offering quantitative support to improve carbon capture in urban parks.