Scale-dependent effects of landscape pattern on plant diversity in Hunshandak Sandland

Min, Fan; Wang, Qinghui; Mi, Kai; Peng, Yu

doi:10.1007/s10531-017-1351-7

Cited by 19 publications

(10 citation statements)

References 28 publications

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“…Hunshandak Sandland receives an annual precipitation of 250–350 mm, 80–90% of which falls between May and September. Semi-natural grasslands in Hunshandak Sandland are associated with high levels of species-rich habitats at a fine scale, where shelter most plant species, hence prevent the movement of sandy dunes and desertification process 25 . Operative scheme for the rapid assessment of fine-scale (0.25–1 meter) plant species diversity are therefore needed for monitoring of ecological status in species-rich habitats.…”

Section: Methodsmentioning

confidence: 99%

Assessment of plant species diversity based on hyperspectral indices at a fine scale

Peng

Min

Song

et al. 2018

Sci Rep

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Fast and nondestructive approaches of measuring plant species diversity have been a subject of excessive scientific curiosity and disquiet to environmentalists and field ecologists worldwide. In this study, we measured the hyperspectral reflectances and plant species diversity indices at a fine scale (0.8 meter) in central Hunshandak Sandland of Inner Mongolia, China. The first-order derivative value (FD) at each waveband and 37 hyperspectral indices were used to assess plant species diversity. Results demonstrated that the stepwise linear regression of FD can accurately estimate the Simpson (R2 = 0.83), Pielou (R2 = 0.87) and Shannon-Wiener index (R2 = 0.88). Stepwise linear regression of FD (R2 = 0.81, R2 = 0.82) and spectral vegetation indices (R2 = 0.51, R2 = 0.58) significantly predicted the Margalef and Gleason index. It was proposed that the Simpson, Pielou and Shannon-Wiener indices, which are widely used as plant species diversity indicators, can be precisely estimated through hyperspectral indices at a fine scale. This research promotes the development of methods for assessment of plant diversity using hyperspectral data.

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Section: Methodsmentioning

confidence: 99%

Assessment of plant species diversity based on hyperspectral indices at a fine scale

Peng

Min

Song

et al. 2018

Sci Rep

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“…For entire wavebands in the sparse vegetation of sand dunes, the spectral signs that were recorded by a handheld instrument represent a mixture of vegetation and sand dune reflectance. Sand dunes strongly affect these mixed signs, because the community cover of most plots ranged between 25 and 55%, with barren sand dunes occupying a significant part of the plot [51]. Sandy soils have a stronger reflectance than vegetation in the visible spectral range [35,47].…”

Section: Fit To Svhmentioning

confidence: 99%

Identification of the Best Hyperspectral Indices in Estimating Plant Species Richness in Sandy Grasslands

et al. 2019

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Numerous spectral indices have been developed to assess plant diversity. However, since they are developed in different areas and vegetation type, it is difficult to make a comprehensive comparison among these indices. The primary objective of this study was to explore the optimum spectral indices that can predict plant species richness across different communities in sandy grassland. We use 7339 spectral indices (7217 we developed and 122 that were extracted from literature) to predict plant richness using a two-year dataset of plant species and spectra information at 270 plots. For this analysis, we employed cluster analysis, correlation analysis, and stepwise linear regression. The spectral variability within the 420–480 nm and 760–900 nm ranges, the first derivative value at the sensitive bands, and the normalized difference at narrow spectral ranges correlated well with plant species richness. Within the 7339 indices that were investigated, the first-order derivative values at 606 and 583 nm, the reflectance combinations on red bands: (R802 − R465)/(R802 + R681) and (R750 − R550)/(R750 + R550) showed a stable performance in both the independent calibration and validation datasets (R2 > 0.27, p < 0.001, RMSE < 1.7). They can be regarded as the best spectral indices to estimate plant species richness in sandy grasslands. In addition to these spectral variation indices, the first derivative values or the normalized difference of the sensitive bands also reflect plant diversity. These results can help to improve the estimation of plant diversity using satellite-based airborne and hand-held hyperspectral sensors.

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“…Our results suggest that herbaceous diversity differed significantly among different arbor species, Qinghai spruce had a significantly lower diversity despite being an important long-lived dominant evergreen species in this region (Zhao et al 2006). Previous studies have shown the ecosystem service function of Qinghai spruce forests planted for the 'Grain-for-Green' project is decreasing due to irresponsible forest management, such as excessively high density and careless species selection (Bie et al 2013;Fan et al 2017). Our results confirmed this from the perspective of the herb composition.…”

Section: Discussionmentioning

confidence: 65%

The interactions among herbaceous diversity, edaphic factors, and topography under typical afforestation in the transition zone between the qinghai–Tibet Plateau and Loess Plateau

Zhao

Yang

et al. 2021

Journal of Plant Interactions

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The herbaceous layer plays a crucial role in afforestation and could provide important information in the process of restoration. Thus, we investigated herbaceous communities (composition and diversity), related factors (soil properties and topography), and their interactions in the afforestation of the 'Grain-for-Green' program in the transition zone between the Qinghai-Tibet Plateau and Loess Plateau. We found 52 herb species belonging to 41 genera of 18 families, among which perennial herbs dominated. Our results revealed two different restoration mechanisms for Qinghai spruce (Picea crassifolia) and Prince Rupprecht ′ s larch (Larix principisrupprechtii). The community in the Qinghai spruce forest was more competitive and mainly comprised xeric herbs, while the Prince Rupprecht ′ s larch forest provided shadier conditions with higher herb diversity. Soil available nitrogen (AN), available potassium (AK), available phosphorus (AP), slope position, and elevation were significant factors affecting herbaceous diversity. The upper slope position should be the primary consideration since topography exacerbated nutrient loss. Soil water remains the underlying factor of succession, and Prince Rupprecht ′ s larch on hillslopes might be at risk of water stress in the future. Understanding the significance of the herbaceous layer and environmental factors will provide a comprehensive picture of sustainable management on the alpine Loess Plateau.

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Scale-dependent effects of landscape pattern on plant diversity in Hunshandak Sandland

Cited by 19 publications

References 28 publications

Assessment of plant species diversity based on hyperspectral indices at a fine scale

Assessment of plant species diversity based on hyperspectral indices at a fine scale

Identification of the Best Hyperspectral Indices in Estimating Plant Species Richness in Sandy Grasslands

The interactions among herbaceous diversity, edaphic factors, and topography under typical afforestation in the transition zone between the qinghai–Tibet Plateau and Loess Plateau

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