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Effects of topographic attributes on landscape pattern metrics based on redundancy ordination gradient analysis

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Abstract

In mountainous areas, the landscape spatial pattern is affected by topography and human activities. To better understand topographic influences on the vegetation structure in the landscape mosaic and interpret the ecological implications of spatial patterns, the relationships between topographic features and landscape pattern indices (LPIs) should be addressed. The objective of this study is to address the effects of topography on LPIs (both planimetric and surface LPIs) by integrating spatial analysis and gradient analysis. To fulfill these objectives, two different mountain research sites located in the Lancang River watershed were chosen, both planimetric and surface landscape metrics were used to quantify natural category (NC) and anthropogenic category (AC) patterns, and the redundancy ordination gradient method was used to address the relationship between LPIs (planimetric and surface metrics) of NC and AC patterns and topographic attributes. The results suggest that topographic attributes play a prominent role in structuring the landscape mosaic. Elevation is a key factor for NC and AC patch patterns in the study area. The results indicate that the fragmentation and isolation of NC patterns increase as elevation decreases. In contrast, the fragmentation and isolation of AC patterns decrease as elevation decreases.

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Acknowledgements

This work was supported by grants from the National Natural Science Foundation of China (41361046 and 41261105), and the West Light Foundation of the Chinese Academy of Sciences. We thank Drs. Ulrich Walz and Sebastian Hoechstetter for their comments on this work. We thank our colleagues working in the Laboratory of Forest Management and Spatial Information, Ghent University, Belgium.

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Correspondence to Zijiang Yang.

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Zhang, Z., Zinda, J.A., Yang, Z. et al. Effects of topographic attributes on landscape pattern metrics based on redundancy ordination gradient analysis. Landscape Ecol Eng 14, 67–77 (2018). https://doi.org/10.1007/s11355-016-0322-6

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