Many studies reported biotic change along a continental warming gradient. However, the temporal and spatial change of tree diversity and their sensitivity to climate warming might differ from region to region. Understanding of the variation among studies with regard to the magnitude of such biotic changes is minimal, especially in montane ecosystems. Our aim is to better understand changes in spatial heterogeneity and temporal dynamics of mountain tree communities under climate warming over the past four decades. In 2017, we resurveyed and recorded all tree species from 107 long-term monitoring plots that were first studied between 1974 and 1976. These plots were located in montane forests in the Giant Panda National Park (GPNP), China. Our results showed that spatial differences were found in tree species diversity changes response to mean annual temperature change over the past four decades. Tree species richness increased significantly under climate warming in Minshan (MS) and Xiaoxiangling (XXL) with higher warming rate than Qionglai (QLS) and Liangshan (LS). The trees species diversity in MS and XXL were more sensitive to climatic warming. MS and XXL should receive priority protection in the next conservation plan of the GPNP. The GPNP should avoid taking a "one-size-fits-all" approach for diversity conservation due to spatial heterogeneity in plant community dynamics.
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http://dx.doi.org/10.1002/ece3.7106 | DOI Listing |
Front Plant Sci
January 2025
China Eco-city Academy Co., Ltd., Tianjin, China.
The establishment of conservation areas is an important strategy for endangered species conservation. In this study, we investigated the distributions of suitable habitat areas for three level 1 endangered Cupressaceae plants (, , and ) in China and used the Marxan model to delineate the priority conservation areas for each species. The results showed that had the broadest suitable growing area under the current climate in China and is followed by , with an area of 91 × 10 km, and had the smallest suitable habitat areas at only 7 × 10 km.
View Article and Find Full Text PDFGlob Chang Biol
January 2025
Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, China.
Rapid warming in northern lands has led to increased ecosystem carbon uptake. It remains unclear, however, whether and how the beneficial effects of warming on carbon uptake will continue with climate change. Moreover, the role played by water stress in temperature control on ecosystem carbon uptake remains highly uncertain.
View Article and Find Full Text PDFAnn Bot
January 2025
Research Department, Holden Arboretum, Kirtland, OH, USA.
Background: Plants often shift their phenology in response to climate warming, with potentially important ecological consequences. Relative differences in the abilities of native and nonnative plants to track warming temperatures by adjusting their phenologies could have cascading consequences for ecosystems. Our general understanding of nonnative species leads us to believe these species may be more phenologically sensitive than native species, but evidence for this has been mixed, likely due, in part, to the myriad of diverse ecological contexts in which nonnatives have been studied.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
College of Urban and Environmental Sciences, Peking University, Beijing 100871, China.
Wildland fires constitute a major source of ambient fine particulate matter (PM), significantly impacting air quality and public health. As the climate becomes warmer and drier, fire frequency is projected to rise, yet how the associated health impacts of fire-sourced PM (FPM) respond to climate change remains vague. In this study, we modeled the global concentration and associated premature deaths of FPM over the past two decades.
View Article and Find Full Text PDFSci Rep
January 2025
College of Computer and Mathematics, Central South University of Forestry and Technology, Changsha, 410004, China.
Ormosia microphylla is a nationally prioritized wild plant in China but effects of likely future climate change have been poorly studied. Here distribution data of O. microphylla and environmental data with an optimized MaxEnt maximum entropy model were used to predict potentially suitable areas under current and future climate scenarios.
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