The spatiotemporal patterns of vegetation coverage and biomass of the temperate deserts in Central Asia and their relationships with climate controls

Zhang, Chi; Lu, Dengsheng; Chen, Xi; Zhang, Yuanming; Майсупова, Багила; Tao, Ye

doi:10.1016/j.rse.2016.01.002

Cited by 165 publications

(73 citation statements)

References 48 publications

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“…Recently, Zhang et al . () show that vast desert areas in western Central Asia have lost most of its surface biomass after a prolonged drought in the late 1990s. In such dry conditions, lack of recharge to the groundwater that has been the primary source of water supply for natural oases in foothills of mountains removes lifeline for surface vegetation and associated ecosystems.…”

Section: Introductionmentioning

confidence: 99%

WRF simulation and downscaling of local climate in Central Asia

Qiu

Zhang

2017

Intl Journal of Climatology

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Progresses in understanding climate variation and its ecosystem responses and feedback in Central Asia have been limited by availability of high resolution and quality climate data. To ease this limitation, the Weather Research and Forecasting (WRF) model is implemented in Central Asia in this study after repeated yearly sensitivity evaluations. The optimized WRF is used to downscale the ERA‐Interim reanalysis data, producing a new regional dataset of 20 × 20 km spatial resolution covering 1980–2015. The downscaled precipitation and daily maximum and minimum temperatures of seven years from 1980–1986, when the observational data are the most abundant, are compared in statistical measures to station observations and also contrasted with the comparison results between the ERA‐Interim data and the observations. Results of those comparisons show that the downscaled data have overall comparable accuracy in precipitation and daily extreme temperatures to the ERA‐Interim data. An outstanding improvement of the downscaled data is in their describing the variance in precipitation and temperatures at daily to annual timescales, while the downscaled extreme precipitation and temperature events also show more accurate comparisons to the observed at some sub‐regions in Central Asia. The validated WRF model, which can be used to further downscale past as well as future climate data for specific research needs, and the downscaled high resolution and quality data present both a tool and a useful dataset for ecological and detailed climate research in Central Asia.

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Section: Introductionmentioning

confidence: 99%

WRF simulation and downscaling of local climate in Central Asia

Qiu

Zhang

2017

Intl Journal of Climatology

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“…In doing so the aim is the identification of an analytical relationship between on-the-ground AGB estimates and spectral indices sensitive to photosynthetically active radiation and scaling with amount of biomass [39][40][41][42]. A vegetation index is generally derived from the spectral reflectance of two or more bands, and proportional to the value of biophysical parameters like leaf area index (LAI), net primary productivity (NPP), and absorbed photosynthetically active radiation (APAR) [43].…”

Section: Introductionmentioning

confidence: 99%

Estimating Aboveground Biomass and Carbon Stocks in Periurban Andean Secondary Forests Using Very High Resolution Imagery

Clerici

Rubiano

Abd-Elrahman

et al. 2016

Forests

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Periurban forests are key to offsetting anthropogenic carbon emissions, but they are under constant threat from urbanization. In particular, secondary Neotropical forest types in Andean periurban areas have a high potential to store carbon, but are currently poorly characterized. To address this lack of information, we developed a method to estimate periurban aboveground biomass (AGB)-a proxy for multiple ecosystem services-of secondary Andean forests near Bogotá, Colombia, based on very high resolution (VHR) GeoEye-1, Pleiades-1A imagery and field-measured plot data. Specifically, we tested a series of different pre-processing workflows to derive six vegetation indices that were regressed against in situ estimates of AGB. Overall, the coupling of linear models and the Ratio Vegetation Index produced the most satisfactory results. Atmospheric and topographic correction proved to be key in improving model fit, especially in high aerosol and rugged terrain such as the Andes. Methods and findings provide baseline AGB and carbon stock information for little studied periurban Andean secondary forests. The methodological approach can also be used for integrating limited forest monitoring plot AGB data with very high resolution imagery for cost-effective modelling of ecosystem service provision from forests, monitoring reforestation and forest cover change, and for carbon offset assessments.

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“…The reason for such discrepancy was that different vegetation types had very different spectral reflectances in the red and near-infrared wavebands, as defined in the NDVI34. Another underlying reason was that different vegetation types had different sensitivities to climate factors, and vegetation that was especially sensitive to hydrothermal conditions was likely to fluctuate markedly in NDVI and biomass35. For example, Li and Yang5 found that desert steppe was most strongly affected by warmer temperatures, hence the decreased NDVI that occurred mainly in drier summers (May and June) in inner Mongolia.…”

Section: Discussionmentioning

confidence: 99%

Quantifying influences of physiographic factors on temperate dryland vegetation, Northwest China

Zhang

et al. 2017

Sci Rep

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Variability in satellite measurements of terrestrial greenness in drylands is widely observed in land surface processes and global change studies. Yet the underlying causes differ and are not fully understood. Here, we used the GeogDetector model, a new spatial statistical approach, to examine the individual and combined influences of physiographic factors on dryland vegetation greenness changes, and to identify the most suitable characteristics of each principal factor for stimulating vegetation growth. Our results indicated that dryland greenness was predominantly affected by precipitation, soil type, vegetation type, and temperature, either separately or in concert. The interaction between pairs of physiographic factors enhanced the influence of any single factor and displayed significantly non-linear influences on vegetation greenness. Our results also implied that vegetation greenness could be promoted by adopting favorable ranges or types of major physiographical factors, thus beneficial for ecological conservation and restoration that aimed at mitigating environmental degradation.

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The spatiotemporal patterns of vegetation coverage and biomass of the temperate deserts in Central Asia and their relationships with climate controls

Cited by 165 publications

References 48 publications

WRF simulation and downscaling of local climate in Central Asia

WRF simulation and downscaling of local climate in Central Asia

Estimating Aboveground Biomass and Carbon Stocks in Periurban Andean Secondary Forests Using Very High Resolution Imagery

Quantifying influences of physiographic factors on temperate dryland vegetation, Northwest China

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