scholarly journals Responses of Desert Grassland Vegetation to Mesquite Removal and Regrowth

2004 ◽  
Vol 57 (5) ◽  
pp. 455 ◽  
Author(s):  
Arthur R. Tiedemann ◽  
James O. Klemmedson
Keyword(s):  
Desert Grassland ◽  
Grassland Vegetation

scholarly journals Quadrat‐based monitoring of desert grassland vegetation at the Jornada Experimental Range, New Mexico, 1915–2016

Ecology ◽  
2021 ◽  
Author(s):  
Erica Christensen ◽  
Darren James ◽  
Connie Maxwell ◽  
Amalia Slaughter ◽  
Peter B. Adler ◽  
...  
Keyword(s):  
New Mexico ◽  
Desert Grassland ◽  
Grassland Vegetation ◽  
Experimental Range

Study on Effect of Drought Based on Time Series on Grassland Vegetation in Eastern Inner Mongolia

2012 ◽  
Vol 518-523 ◽  
pp. 5306-5315 ◽  
Author(s):  
Gui Xiang Liu ◽  
Zhuo Yi ◽  
Feng Ming Yu ◽  
Chun Long Jiang
Keyword(s):  
Time Series ◽  
Inner Mongolia ◽  
Meteorological Data ◽  
Remote Sensing Data ◽  
Desert Grassland ◽  
Grassland Vegetation ◽  
Spi Index ◽  
Growth Status ◽  
Ndvi Index ◽  
Eastern Inner Mongolia

This paper, based on the long sequence meteorological data and the MODIS remote sensing data, calculates the every-ten-day NDVI index and SPI index of the grassland vegetation in the Eastern Inner Mongolia between 2006 and 2010. It applies the SPI index to indicate the degree of drought and the NDVI index to represent the growth status of the grassland vegetation. This paper analyzes the relationship between the NDVI index and the SPI index by the Time Series Spectrum Analysis Method, leading to the conclusion that the vegetations are sensitive to the drought in the green-turning and yellowing period, but relatively not that sensitive in the budding and maturation period, and that, the vegetations in meadow grassland, typical grassland and desert grassland vary in the responses to the drought.

scholarly journals Responses of desert grassland vegetation to mesquite removal and regrowth

2011 ◽  
Vol 57 (5) ◽  
Author(s):  
Arthur Tiedemann ◽  
James Klemmedson
Keyword(s):  
Desert Grassland ◽  
Grassland Vegetation

scholarly journals Responses of desert grassland vegetation to mesquite removal and regrowth

2004 ◽  
Vol 57 (5) ◽  
pp. 455 ◽  
Author(s):  
ARTHUR R. TIEDEMANN ◽  
JAMES O. KLEMMEDSON
Keyword(s):  
Desert Grassland ◽  
Grassland Vegetation

Changes of Grassland Vegetation Growth in Xilin Gol League over 10 Years and Analysis on the Influence Factors

2013 ◽  
Vol 15 (2) ◽  
pp. 270 ◽  
Author(s):  
Haida YU ◽  
Xiuchun YANG ◽  
Bin XU ◽  
Yunxiang JIN ◽  
Tian GAO ◽  
...  
Keyword(s):  
Influence Factors ◽  
Grassland Vegetation ◽  
Vegetation Growth

Changes of soil bacterial and fungal community structure along a natural aridity gradient in desert grassland ecosystems, Inner Mongolia

CATENA ◽  
2021 ◽  
Vol 205 ◽  
pp. 105470
Author(s):  
Shaokun Wang ◽  
Xiaoan Zuo ◽  
Tala Awada ◽  
Eduardo Medima-Roldán ◽  
Keting Feng ◽  
...  
Keyword(s):  
Community Structure ◽  
Fungal Community ◽  
Inner Mongolia ◽  
Desert Grassland ◽  
Aridity Gradient ◽  
Fungal Community Structure ◽  
Grassland Ecosystems ◽  
Soil Bacterial

scholarly journals Using UAV LiDAR to Extract Vegetation Parameters of Inner Mongolian Grassland

2021 ◽  
Vol 13 (4) ◽  
pp. 656
Author(s):  
Xiang Zhang ◽  
Yuhai Bao ◽  
Dongliang Wang ◽  
Xiaoping Xin ◽  
Lei Ding ◽  
...  
Keyword(s):  
Major Effect ◽  
Canopy Height ◽  
Vegetation Coverage ◽  
Accurate Estimation ◽  
Grassland Vegetation ◽  
Pixel Resolution ◽  
Aerial Vehicle ◽  
Grazing Intensities ◽  
Vegetation Parameters ◽  
Mongolian Grassland

The accurate estimation of grassland vegetation parameters at a high spatial resolution is important for the sustainable management of grassland areas. Unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) sensors with a single laser beam emission capability can rapidly detect grassland vegetation parameters, such as canopy height, fractional vegetation coverage (FVC) and aboveground biomass (AGB). However, there have been few reports on the ability to detect grassland vegetation parameters based on RIEGL VUX-1 UAV LiDAR (Riegl VUX-1) systems. In this paper, we investigated the ability of Riegl VUX-1 to model the AGB at a 0.1 m pixel resolution in the Hulun Buir grazing platform under different grazing intensities. The LiDAR-derived minimum, mean, and maximum canopy heights and FVC were used to estimate the AGB across the entire grazing platform. The flight height of the LiDAR-derived vegetation parameters was also analyzed. The following results were determined: (1) The Riegl VUX-1-derived AGB was predicted to range from 29 g/m2 to 563 g/m2 under different grazing conditions. (2) The LiDAR-derived maximum canopy height and FVC were the best predictors of grassland AGB (R2 = 0.54, root-mean-square error (RMSE) = 64.76 g/m2). (3) For different UAV flight altitudes from 40 m to 110 m, different flight heights showed no major effect on the derived canopy height. The LiDAR-derived canopy height decreased from 9.19 cm to 8.17 cm, and the standard deviation of the LiDAR-derived canopy height decreased from 3.31 cm to 2.35 cm with increasing UAV flight altitudes. These conclusions could be useful for estimating grasslands in smaller areas and serving as references for other remote sensing datasets for estimating grasslands in larger areas.

scholarly journals Comprehensive Assessment Indicator of Ecosystem Resilience in Central Asia

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 124
Author(s):  
Xue Fan ◽  
Xingming Hao ◽  
Haichao Hao ◽  
Jingjing Zhang ◽  
Yuanhang Li
Keyword(s):  
Central Asia ◽  
Net Primary Productivity ◽  
Ecosystem Resilience ◽  
Mountainous Areas ◽  
Grassland Vegetation ◽  
High Coverage ◽  
Casa Model ◽  
Assessment Indicator ◽  
Multiple Dimensions ◽  
Resilience Index

The ecosystems in the arid inland areas of Central Asia are fragile and severely degraded. Understanding and assessing ecosystem resilience is a challenge facing ecosystems. Based on the net primary productivity (NPP) data estimated by the CASA model, this study conducted a quantitative analysis of the ecosystem’s resilience and comprehensively reflected its resilience from multiple dimensions. Furthermore, a comprehensive resilience index was constructed. The result showed that plain oasis’s ecosystem resilience is the highest, followed by deserts and mountainous areas. From the perspective of vegetation types, the highest resilience is artificial vegetation and the lowest is forest. In warm deserts, the resilience is higher in shrubs and meadows and lower in grassland vegetation. High coverage and biomass are not the same as the strong adaptability of the ecosystem. Moderate and slightly inelastic areas mainly dominate the ecosystem resilience of the study area. The new method is easy to use. The evaluation result is reliable. It can quantitatively analyze the resilience latitude and recovery rate, a beneficial improvement to the current ecosystem resilience evaluation.

Sign in / Sign up

Export Citation Format

Share Document