Insight into the Molecular Mechanism of Flower Color Regulation in Rhododendron latoucheae Franch: A Multi-Omics Approach.

Rhododendron latoucheae Franch. (R. latoucheae) is a valuable woody plant known for its high ornamental value. While purple flowers are a distinct and attractive variant phenotype of R. latoucheae, the underlying mechanism regulating its flower color is still poorly understood. To investigate the molecular regulatory mechanism responsible for the variation in flower color, we selected plants with white-pink and purple petals as the object and conducted analyses of metabolites, key genes, and transcription factors associated with flower color. A combined metabolome-transcriptome analysis was performed, and the expression of key genes was subsequently verified through qRT-PCR experiments. The results of our study demonstrated a significant enrichment of differential metabolites in the flavonoid metabolic pathway. Changes in anthocyanin content followed the same trend as the observed flower color variations, specifically showing significant correlations with the contents of malvidin-3-O-glucoside, dihydromyricetin, gallocatechin, and peonidin-3-O-glucoside. Furthermore, we identified three key structural genes (F3GT1, LAR, ANR) and four transcription factors (bHLH130, bHLH41, bHLH123, MYB4) that are potentially associated with the biosynthesis of flavonoid compounds, thereby influencing the appearance of purple flower color in R. latoucheae.

Effects of landscape conservation on the ecohydrological and water quality functions and services and their driving factors.

Since the implementation of landscape conservation of the green heart area in the Changsha-Zhuzhou-Xiangtan Metropolitan Region, the landscape structure and pattern have changed significantly. The ecosystem service functions in the area have been improved, but the status of ecohydrological and water quality and service functions (EHWQSFs) is still unclear. To clarify the status of EHWQSFs and their driving factors influenced by landscape conservation, this study analysed landscape changes using remote sensing image data from 1998, 2008, and 2018 and the changes and their spatial characteristics using the Soil and Water Assessment Tool (SWAT) and spatial analysis methods. The results showed that the dominant land types in the area were forestland and cropland from 1998 to 2018; the area of forestland and construction land expanded and that of cropland decreased year by year; the annual average surface runoff volume rose, and the annual average actual evapotranspiration and soil water content fell from 1998 to 2008 and rose from 2008 to 2018; and all pollutant indicators decreased significantly after 2008. The areas with higher surface runoff were mainly concentrated in the central and southern regions, those with higher evapotranspiration were in the northwestern and southwestern regions, those with higher soil water content were in the northern region, and those with higher sediment and nitrogen and phosphorus pollutant contents were in the central and southeastern regions. The results showed that land use, land cover and meteorological factors were the most significant drivers on EHWQSFs and illustrated that EHWQSFs in the area decreased after 1998. There was a significant improvement after 2008 and the area currently has a good status. This study not only provides insights into land use, land cover and meteorological factors that have significant impacts on EHWQSFs but also highlights that the landscape conservation of the area can improve ecosystem service functions.

Assessing impacts of the Ecological Retreat project on water conservation in the Yellow River Basin.

The Ecological Retreat (ER) project significantly impacts water conservation functions in the Yellow River Basin (YRB). However, studies on the impact and benefit of different ER modes on ecological water effects still lack systematic and integral disclosure. In our study, CNLUCC (China land use/cover data sets) and the Markov transition matrix were used to simulate land pattern changes from 2000 to 2018. Water yield was chosen as an indicator of water conservation to explore the impact of the ER project by using the water yield module of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. After the ER project, the land pattern changed significantly because massive cropland was transformed into forest and grassland. Thus, the total water yields of the YRB increased by 46.32 × 103 hm3 from 2000 to 2018, and the overall water yield benefit was 12.39% larger than the water loss. Forest rehabilitation (FR) showed the highest average water yield capacity, while grassland restoration (GR) exhibited the most incredible total water conservation benefit. Wetland recovery (WLR) manifested a great capacity to improve average water yield, but its total benefit was far less than FR and GR, while waterbody recovery (WBR) showed a negative impact. The results indicate that FR and GR were effective restoration methods, and WLR showed great potential to improve water yield. By using the random forest and principal components analysis, precipitation (PRE), evaporation (AET and ET0), and variation of forest and grassland proved to be the most critical driving indicators affecting water yield changes. Additionally, the correlation and sensitivity between root depth (R_depth) and water yield indicate that increasing R_Depth can also enhance water conservation. The ER project provides a valuable restoration model for water yield and water conservation benefits. The results can provide theoretical support for eco-hydrology and land ecological restoration studies.

Influence of landscape features on urban land surface temperature: Scale and neighborhood effects.

Higher land surface temperature (LST) in cities than its surrounding areas presents a major sustainability challenge for cities. Adaptation and mitigation of the increased LST require in-depth understanding of the impacts of landscape features on LST. We studied the influences of different landscape features on LST in five large cities across China to investigate how the features of a specific urban landscape (endogenous features), and neighboring environments (exogenous features) impact its LST across a continuum of spatial scales. Surprisingly, results show that the influence of endogenous landscape features (Eendo) on LST can be described consistently across all cities as a nonlinear function of grain size (gs) and neighbor size (ns) (Eendo = ßnsgs-0.5, where ß is a city-specific constant) while the influence of exogenous features (Eexo) depends only on neighbor size (ns) (Eexo = Î³-εns0.5, where γ and ε are city-specific constants). In addition, a simple relationship describing the relative strength of endogenous and exogenous impacts of landscape features on LST was found (Eendo > Eexo if ns > kgs2/5, where k is a city-specific parameter; otherwise, Eendo < Eexo). Overall, vegetation alleviates 40%-60% of the warming effect of built-up while surface wetness intensifies or reduces it depending on climate conditions. This study reveals a set of unifying quantitative relationships that effectively describes landscape impacts on LST across cities, grain and neighbor sizes, which can be instrumental towards the design of sustainable cities to deal with increasing temperature.