Studying the pollen morphology of this remnant and endemic wild species of Cathaya argyrophylla can be of use for paleobiologists. During this study, 23 genotypes sampled from four natural populations in two regions of Hunan Province, China. A total of 460 pollen grains were analyzed for seven quantitative and seven qualitative traits (including five new traits). Three quantitative traits (B, P, and A) (Width of the saccus (B); Length of the polar axis (P); Length of the saccus (A)) and four qualitative traits (O-CO, B-SD, O-CSR, and B-SU) (Pollen corpus outlined in the polar distal view (O-CO); Whether the outline of two sacci was distinct or not in the polar proximal view (B-SD); Roughness degree between corpus from the polar proximal view and the sacci from the polar distal view (O-CSR); Whether the overall size of two sacci was uniform or not (B-SU)) were the diagnostic pollen features that could possible to differentiate one population and classified 23 samples into two, three, or four clusters. Furthermore, 24 environmental factors were evaluated and precipitation factors effected more on pollen morphology than geographic and temperature factors, which including annual precipitation (bio12), precipitation of wettest month and driest month (bio13, bio14), precipitation seasonality (bio15) and monthly averaged precipitation in May (05-precip). The main precipitation and temperature factors exhibited positive and negative correlation with pollen size (B and E (Equatorial diameter (E))), respectively. This article provides deeper insight into intraspecific variability of pollen grains of C. argyrophylla, which have been investigated for the first time. In addition, the insights gained from this study could assist with the seed breeding and population reproduction of the endangered C. argyrophylla tree.

In the past 20 years, the integration process of the Chang-Zhu-Tan region has been accelerating, and land use has undergone significant changes. Land use change is a fundamental factor causing changes in the quality of the ecological environment. It is crucial to analyze land use change in the context of rapid urbanization and its impact on the ecological environment to promote sustainable and high-quality regional development. This study takes the Chang-Zhu-Tan core area, which has the highest development and construction intensity, as the study area. Based on the Google Earth Engine (GEE) platform, the land use information is extracted using Landsat remote sensing image data and the random forest method. The remote sensing ecological index (RSEI) is constructed to analyze the ecological and environmental effects of land use change based on the spatial and temporal changes of land use types and ecological and environmental quality in the Chang-Zhu-Tan core area from 2000 to 2020. The results show that the most critical land use change in the study area from 2000 to 2020 is mainly the sharp increase in construction land, accompanied by a continuous decrease in forest and cropland. During this period, the eco-environmental quality of the study area showed a declining trend, with significant differences in spatial distribution, generally showing a distribution pattern of suburban counties outperforming central urban areas. In addition, the distribution and changes in land use and ecological environment quality coincide spatially. Different land use types have different impacts on ecological environment quality, with the conversion of forest and cropland to construction land being the main reason for the deterioration of eco-environmental quality in the study area. This study provides a basis for the coordinated development of the ecological environment and social economy in the Chang-Zhu-Tan area.

In the context of the worldwide attention on climate change, examining how land use relates to the carbon sink functions of regions is essential. This research innovatively utilizes the 2000–2020 land use data of Changde City, integrating the PLUS and InVEST models to analyze spatiotemporal changes and predict scenarios. It also combines the parameter geodetector and multiscale geographically weighted regression model to dissect driving factor distributions and mechanisms, capture interactions and multiscale impacts, uncover underlying laws, pioneer new paths for similar studies, and support regional ecological sustainability. The results show that from 2000–2020, forest and arable land areas declined while construction land expanded, leading to a yij1,172,200-ton carbon storage reduction in Changde City. Carbon storage decreased under natural development and arable land protection scenarios but increased in the ecological scenario. The main drivers of carbon storage in Changde City are the DEM, slope, and annual average temperature, with their interactions enhancing spatial heterogeneity. Human activities, especially in mountains and urbanizing regions, negatively impact carbon storage. This study aids in optimizing land resource allocation, improving land use efficiency, and promoting coordinated and sustainable development in Changde City’s ecological, economic, and social systems.

The Ecological Green Heart Area of the Chang–Zhu–Tan Urban Agglomeration in Central China faces increasing forest health threats due to rapid urbanization and land use change. This study assessed the spatiotemporal dynamics and drivers of forest health from 2005 to 2023 using a multi-dimensional framework based on vitality, organizational structure, and anti-interference capacity. A forest health index (FHI) was constructed using multi-source data, and the optimal parameter geographic detector (OPGD) model was applied to identify dominant and interacting factors. The results show the following: (1) FHI declined from 0.62 (2005) to 0.55 (2015) and rebounded to 0.60 (2023). (2) Healthier forests were concentrated in the east and center, with degradation in the west and south; (3) Topography was the leading driver (q = 0.17), followed by climate, while socioeconomic factors gained influence over time. (4) Interactions among factors showed strong nonlinear enhancement. This research demonstrates the effectiveness of the OPGD model in capturing spatial heterogeneity and interaction effects, underscoring the need for differentiated, spatially informed conservation and land management strategies. This research provides scientific support for integrating ecological protection with urban planning, contributing to the broader goals of ecosystem resilience, sustainable land use, and regional sustainability.

Carallia brachiata (Lour.) Merr. (1919) is an important medical resource distributed across subtropical Asia. In this study, the complete chloroplast genome of C. brachiata was sequenced, revealing a total length of 162,460 bp, including four regions - a large single copy (89,814 bp), a small single copy (18,804 bp), and a pair of inverted repeats (26,921 bp each). The overall guanine + cytosine content was 35.76%. In total, 130 genes were annotated within the chloroplast genome, comprising 85 protein-coding, 37 tRNA, and 8 rRNA genes. Subsequent phylogenetic analyses revealed that C. brachiata is closely related to Carallia diplopetala.