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Article

Effects of Patchiness on Surface Soil Moisture of Alpine Meadow on the Northeastern Qinghai-Tibetan Plateau: Implications for Grassland Restoration

1
State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 320 Donggang West Road, Lanzhou 730000, China
2
University of the Chinese Academy of Sciences, No.19A Yuquan Road, Beijing 100049, China
3
Institute of Fragile Ecosystem and Environment, School of Geographic Sciences, Nantong University, 999 Tongjing Road, Nantong 226007, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(24), 4121; https://doi.org/10.3390/rs12244121
Submission received: 25 November 2020 / Revised: 11 December 2020 / Accepted: 14 December 2020 / Published: 16 December 2020

Abstract

Surface soil moisture (SSM) is a key limiting factor for vegetation growth in alpine meadow on the Qinghai-Tibetan Plateau (QTP). Patches with various sizes and types may cause the redistribution of SSM by changing soil hydrological processes, and then trigger or accelerate alpine grassland degradation. Therefore, it is vital to understand the effects of patchiness on SSM at multi-scales to provide a reference for alpine grassland restoration. However, there is a lack of direct observational evidence concerning the role of the size and type of patches on SSM, and little is known about the effects of patches pattern on SSM at plot scale. Here, we first measured SSM of typical patches with different sizes and types at patch scale and investigated their patterns and SSM spatial distribution through unmanned aerial vehicle (UAV)-mounted multi-type cameras at plot scale. We then analyzed the role of the size and type of patchiness on SSM at both patch and plot scales. Results showed that: (1) in situ measured SSM of typical patches was significantly different (P < 0.01), original vegetation patch (OV) had the highest SSM, followed by isolate vegetation patch (IV), small bare patch (SP), medium bare patch (MP) and large bare patch (LP); (2) the proposed method based on UAV images was able to estimate SSM (0–40 cm) with a satisfactory accuracy (R2 = 0.89, P < 0.001); (3) all landscape indices of OV, with the exception of patch density, were positively correlated with SSM at plot scale, while most of the landscape indices of LP and IV showed negative correlations (P < 0.05). Our results indicated that patchiness intensified the spatial heterogeneity of SSM and potentially accelerated the alpine meadow degradation. Preventing the development of OV into IV and the expansion of LP is a critical task for alpine meadow management and restoration.
Keywords: alpine meadow; patchiness; unmanned aerial vehicle; surface soil moisture; landscape indices; FragMAP alpine meadow; patchiness; unmanned aerial vehicle; surface soil moisture; landscape indices; FragMAP
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MDPI and ACS Style

Zhang, W.; Yi, S.; Qin, Y.; Sun, Y.; Shangguan, D.; Meng, B.; Li, M.; Zhang, J. Effects of Patchiness on Surface Soil Moisture of Alpine Meadow on the Northeastern Qinghai-Tibetan Plateau: Implications for Grassland Restoration. Remote Sens. 2020, 12, 4121. https://doi.org/10.3390/rs12244121

AMA Style

Zhang W, Yi S, Qin Y, Sun Y, Shangguan D, Meng B, Li M, Zhang J. Effects of Patchiness on Surface Soil Moisture of Alpine Meadow on the Northeastern Qinghai-Tibetan Plateau: Implications for Grassland Restoration. Remote Sensing. 2020; 12(24):4121. https://doi.org/10.3390/rs12244121

Chicago/Turabian Style

Zhang, Wei, Shuhua Yi, Yu Qin, Yi Sun, Donghui Shangguan, Baoping Meng, Meng Li, and Jianguo Zhang. 2020. "Effects of Patchiness on Surface Soil Moisture of Alpine Meadow on the Northeastern Qinghai-Tibetan Plateau: Implications for Grassland Restoration" Remote Sensing 12, no. 24: 4121. https://doi.org/10.3390/rs12244121

APA Style

Zhang, W., Yi, S., Qin, Y., Sun, Y., Shangguan, D., Meng, B., Li, M., & Zhang, J. (2020). Effects of Patchiness on Surface Soil Moisture of Alpine Meadow on the Northeastern Qinghai-Tibetan Plateau: Implications for Grassland Restoration. Remote Sensing, 12(24), 4121. https://doi.org/10.3390/rs12244121

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