Ecological restoration often requires translocating plant material from distant sites. Importing suitable plant material is important for successful establishment and persistence. Yet, published guidelines for seed transfer are available for very few species. Accurately predicting how transferred plants will perform requires multiyear and multi-environment field trials and comprehensive follow-up work, and is therefore infeasible given the number of species used in restoration programs. Alternative methods to predict the outcomes of seed transfer are valuable for species without published guidelines. In this study, we analyzed the genetic structure of an important shrub used in ecological restoration in the Southern Rocky Mountains called alder-leaf mountain mahogany (). We sequenced DNA from 1,440 plants in 48 populations across a broad geographic range. We found that genetic heterogeneity among populations reflected the complex climate and topography across which the species is distributed. We identified temperature and precipitation variables that were useful predictors of genetic differentiation and can be used to generate seed transfer recommendations. These results will be valuable for defining management and restoration practices for mountain mahogany.
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http://dx.doi.org/10.1002/ece3.6978 | DOI Listing |
Plants (Basel)
January 2025
Key Laboratory of Efficient Forage Production Mode, Ministry of Agriculture and Rural Affair, College of Grassland Science, Shanxi Agricultural University, Jinzhong 030801, China.
Grassland degradation is a serious ecological issue in the farming-pastoral ecotone of northern China. Utilizing native grasses for the restoration of degraded grasslands is an effective technological approach. is a superior indigenous grass species for grassland ecological restoration in northern China.
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January 2025
Key Laboratory of Mountain Hazards and Earth Surface Processes, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610299, China.
Climate change has led to an increasing frequency of droughts, potentially undermining soil stability. In such a changing environment, the shallow reinforcement effect of plant roots often fails to meet expectations. This study aims to explore whether this is associated with the alteration of plant traits as a response to environmental change.
View Article and Find Full Text PDFPlants (Basel)
January 2025
State Forestry and Grassland Administration Key Laboratory of Silviculture in Downstream Areas of the Yellow River, College of Forestry, Shandong Agricultural University, Tai'an 271000, China.
Leaves and roots perform assimilation, supporting plant growth and functionality. The variations in their functional traits reflect adaptive responses to environmental conditions, yet limited information is available regarding these trait variations and their coordination in saline environments. In this study, 18 common woody and herbaceous halophyte species from the Yellow River Delta were collected, and their leaf and root functional traits were assessed and compared.
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January 2025
School of Oceanography and Spatial Information, China University of Petroleum East China-Qingdao Campus, Qingdao 266580, China.
Salt marsh vegetation in the Yellow River Delta, including (), (), and (), is essential for the stability of wetland ecosystems. In recent years, salt marsh vegetation has experienced severe degradation, which is primarily due to invasive species and human activities. Therefore, the accurate monitoring of the spatial distribution of these vegetation types is critical for the ecological protection and restoration of the Yellow River Delta.
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January 2025
School of Civil Engineering Architecture and the Environment, Hubei University of Technology, Wuhan 430068, China.
The green vision rate of rural highway greening landscape is a key factor affecting the driver's visual load. Based on this, this paper uses the eye tracking method to study the visual characteristics of drivers in different green vision environments on rural highways in Xianning County. Based on the HSV color space model, this paper obtains four sections of rural highway with a green vision rate of 10~20%, green vision rate of 20~30%, green vision rate of 30~40%, and green vision rate of 40~50%.
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