Quantifying patterns of variation and coordination of plant functional traits can help to understand the mechanisms underlying both invasiveness and adaptation of plants. Little is known about the coordinated variations of performance and functional traits of different organs in invasive plants, especially in response to their adaptation to environmental stressors. To identify the responses of the invasive species Solidago canadensis to drought, 180 individuals were randomly collected from 15 populations and 212 ramets were replanted in a greenhouse to investigate both the response and coordination between root and leaf functional traits. Drought significantly decreased plant growth and most of the root and leaf functional traits, that is, root length, surface area, volume and leaf size, number, and mass fraction, except for the root length ratio and root mass fraction. Phenotypic plasticity was higher in root traits than in leaf traits in response to drought, and populations did not differ significantly. The plasticity of most root functional traits, that is, root length (RL), root surface area (RSA), root volume (RV), and root mass fraction (RMF), were significantly positively correlated with biomass between control and drought. However, the opposite was found for leaf functional traits, that is, specific leaf area (SLA), leaf area ratio (LAR), and leaf mass fraction (LMF). Drought enhanced the relationship between root and leaf, that is, 26 pairwise root–leaf traits were significantly correlated under drought, while only 15 pairwise root–leaf traits were significantly correlated under control conditions. Significant correlations were found between biomass and all measured functional traits except for leaf size. RV, root length ratio, RMF, total area of leaves, and LMF responded differently to water availability. These responses enable S. canadensis to cope with drought conditions and may help to explain the reason of the vast ecological amplitude of this species.

Ecosystem services serve as a bridge between the ecological environment and human society. The quantitative analysis and forecasting of ecosystem services can provide references for regional eco-environmental assessments and land-use planning for the future. In this study, taking Hainan Tropical Rainforest National Park (HTRNP) as an example, the value of regulating ecosystem services (RESs) in 2020 was assessed via ArcGIS 10.1 and the InVEST 3.5 model, and the per-unit value of RESs was calculated for different LULC types. In addition, in accordance with the Overall Planning for HTRNP and the objective of optimizing RESs, the value of RESs in short-term (to 2030) and long-term (to 2050) scenarios was forecast via a linear programming model. The results are as follows: (1) The RES value of HTRNP in 2020 was CNY 2090.67 × 10⁸, with climate regulation accounting for the largest proportion; the spatial distribution of RESs in the eastern and central areas was higher than that in the western area, but different indicators of RESs differed in their spatial patterns in varied geographic units. (2) The natural forest ecosystem in HTRNP accounts for 76.94% of the total area but 84.82% of the total value of RESs. The per-unit value is ranked from highest to lowest as follows: montane rainforests > wetlands > lowland rainforests > lowland secondary rainforests > tropical coniferous forests > deciduous monsoon rainforests > tropical cloud forests > shrub forests > timber forests > economic forests > rubber forests > grasslands > farmlands > settlements. (3) In the short-term scenario, the value of RESs is CNY 2216.64 × 10⁸, an increase of CNY 118.97 × 10⁸ compared to 2020, with an increase rate of 5.67%. In the long-term scenario, the value of RESs is CNY 2472.48 × 10⁸, an increase of CNY 374.81 × 10⁸ compared to 2020, with an increase rate of 17.87%. The results reveal the significance of ecosystem services in the national park and can inform more targeted and scientifically sound decision-making in the future.

A new species of the genus Camellia (Theaceae), Camellia shuangbaiensis G.P.Yang & B.H.Wu, sp. nov., from the central region of Yunnan Province of China is described. Camellia shuangbaiensis is morphologically similar to C. mileensis and C. hongkongensis, but it can be distinguished by its smaller leaves with an ovate, abaxially tomentose lamina, and 14–16 bracteoles and sepals.

Driven jointly by global warming and human activities, wildlife faces the risks of range shifts and population decline. The Qinghai–Tibet Plateau (QTP) is highly sensitive to climate change, and it is essential to construct an indicator framework for climate-adaptive conservation and developing effective conservation policies. Using ensemble species distribution models (eSDMs), we predicted the future potential suitable habitat of two endemic pheasants of the QTP, the White Eared Pheasant Crossoptilon crossoptilon and the Tibetan Eared Pheasant C. harmani, for 2041–2060 under four compound climate–human activity change scenarios, and identified potential climate refugia. The area of highly suitable habitat of both species declined under all future scenarios, with the largest reduction under scenarios characterized by more severe climate change and higher levels of human activity impacts (S1–SSP5-8.5). Meanwhile, areas of moderately and marginally suitable habitat increased under most scenarios, indicating a redistribution of future potential habitat across suitability classes. Under all four future scenarios, the area-weighted mean elevation of highly suitable habitat was lower than at present, declining by 37.13–80.26 m for the White Eared Pheasant and by 170.15–228.20 m for the Tibetan Eared Pheasant. Potential climate refugia identified under scenarios with lower levels of human activity covered larger areas, but only parts of all climate refugia overlapped with existing national nature reserves. Changes in suitable-area extent and climate-refugia stability can serve as spatial assessment indicators for conservation planning, providing a basis for evaluating potential habitat vulnerability, identifying conservation priorities and optimizing conservation plans under climate change.