Tree-related microhabitats (TreMs) are among the most important structural components of a forest, and have a significant impact on biodiversity and influence ecosystem functioning. Although forests that depend on natural lowland water regimes are severely endangered worldwide, and floodplain forests are considered to be the most complex and biologically rich habitats in the temperate zone, the TreMs in them have yet to be identified. This study investigates the assemblage of TreMs in natural Willow-Poplar riparian forests and analyses the environmental factors that influence their qualitative and quantitative compositions. A total of 90 sample plots (0.05 ha each) were selected at random in old-growth riparian forests that occur along a large unregulated river, the Vistula (Poland). A total of 62 TreM types were identified with a mean number of 16.0 ± 4.6 SD TreM types per plot and a mean density of 829.4 ± 360.1 SD TreM-bearing trees ha. The number of TreMs found on an individual tree depends on its diameter, the number of trunks, its living status (living vs. dead tree) and the species it belongs to. The richness, density and diversity of TreMs found on a plot depends on the density of living trees, the basal area of living or dead trees, the number of tree species, and the percentage of Willows Salix sp. or of multi-trunk trees. Our study records for the first time the assemblage of TreMs in natural Willow-Poplar riparian forests and provides a reference for floodplain habitats. The results indicate that multi-species forests influenced by natural waterflow-related disturbances are hot-spots of TreM richness and abundance, and highlight the urgent need for the protection or restoration of these vanishing habitats.
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http://dx.doi.org/10.1016/j.scitotenv.2021.149881 | DOI Listing |
Sci Rep
January 2025
State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, 830011, China.
Litterfall load is crucial in maintaining ecosystem health, controlling wildfires, and estimating carbon stock in arid regions. However, there is a lack of spatiotemporal analysis of litterfall in arid riparian forests. This study aims to estimate Litterfall load using a BP neural network based on vegetation indices from Landsat 5 and 8 satellite images, litterfall inventory data, slope, and distance to major river tributaries.
View Article and Find Full Text PDFProc Biol Sci
January 2025
Centre for Biodiversity and Sustainability, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK.
Riparian ecosystems harbour unique biodiversity because of their close interconnections with adjacent aquatic ecosystems. Yet, how aquatic ecosystems influence terrestrial biodiversity over different spatial scales is poorly understood, particularly in the tropics. We conducted field campaigns to collect 235 terrestrial invertebrate assemblages along 150 m transects from 47 streams in both Brazil and the UK, compiling one of the largest known datasets of riparian invertebrate community composition at multiple spatial scales.
View Article and Find Full Text PDFMol Ecol
January 2025
Department of Ecosystem Science and Management, Pennsylvania State University, University Park, Pennsylvania, USA.
Ecosystems
January 2025
Oregon State University, Department of Forest Ecosystems & Society, Corvallis, Oregon USA.
J Environ Manage
January 2025
School of Design, Shanghai Jiao Tong University, Shanghai, 200240, China. Electronic address:
This study delves into the multi-scale temporal and spatial variations of soil heat flux (G) within riparian zones and its correlation with net radiation (Rn) across six riparian woodlands in Shanghai, each characterized by distinct vegetation types. The objective is to assess the complex interrelations between G and Rn, and how these relationships are influenced by varying vegetation and seasons. Over the course of a year, data on G and Rn is collected to investigate their dynamics.
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