1. Identifying key landscape pattern indices influencing the NPP: A case study of the upper and middle reaches of the Yellow River.
- Author
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Xue, Shaobo, Ma, Bo, Wang, Chenguang, and Li, Zhanbin
- Subjects
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SHRUBLANDS , *RANDOM forest algorithms , *FRAGMENTED landscapes , *PEARSON correlation (Statistics) , *LANDSCAPES , *WATERSHEDS , *EDGE effects (Ecology) - Abstract
• In 2000–2015, the total NPP values of different vegetation types in the upper and middle reaches of the Yellow River Basin increased. • The NP, LPI, and PLADJ were the core landscape metrics used to assess the NPP changes in forest, Shrubland, and grassland. • In the identification of landscape pattern factors affecting NPP, the random forest algorithm had a better explanation than the Pearson correlation algorithm. Human activities and climate change directly affect the composition, structure, and function of ecosystems and, consequently, their net primary productivity (NPP). In this study, we explored the response relationships between landscape pattern indices and NPP changes in three major vegetation types (forest, grassland, and shrubland) in the upper and middle reaches of the Yellow River Basin using a random forest model. The results showed that landscape fragmentation increased, leading to higher landscape heterogeneity and edge effects. Patch shapes became more irregular, and spatial distribution became more dispersed. From 2000 to 2015, both vegetation types and NPP showed significant spatial heterogeneity in the study area. The number of patches (NP), largest patch index (LPI), and percent-like adjacency (PLADJ) metrics were used to determine the core landscape characteristics to assess the NPP changes in forest, shrubland, and grassland, respectively. This study provides a basis for understanding the relationships among landscape patterns, vegetation types, and NPP and serves as a reference for developing NPP predictive models in the Loess Plateau region. Alterations in vegetation categories have a direct impact on the composition, configuration, and performance of ecosystems., Consequently, the net primary productivity (NPP) of vegetation is markedly affected. In this study, by elucidating the spatiotemporal dynamics of landscape pattern indices and regional NPP, To investigate the response relationships between landscape pattern indices and NPP changes in the upper and middle reaches of the Yellow River Basin, and identify the indices that have the greatest impact on NPP while considering both vegetation type and landscape, we employed a random forest model in three major vegetation types (forest, grassland, and shrubland). This image shows the changes in vegetation types in the upper and middle Yellow River basin from 2000 to 2015 resulting in changes in NPP for different vegetation types and changes in landscape pattern indices that play a dominant role in NPP changes. [Display omitted] [ABSTRACT FROM AUTHOR]
- Published
- 2023
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