Shengli Tao

Rapid loss of lakes on the Mongolian Plateau

Significance The Mongolian Plateau, composed mainly of Inner Mongolia in China and the Republic of Mongolia, has been experiencing remarkable lake shrinkage during the recent decades because of intensive human activities and climate changes. This study provides a comprehensive satellite-based evaluation of lake shrinkage across the plateau, and finds a greater decreasing rate of the number of lakes in Inner Mongolia than in Mongolia (34.0% vs. 17.6%) between the late 1980s and 2010, due mainly to an unsustainable mining boom and agricultural irrigation in the former. Disastrous damages to the natural systems are threatening the livelihood of local people, and we thus call for an urgent action to prevent further deterioration. Lakes are widely distributed on the Mongolian Plateau and, as critical water sources, have sustained Mongolian pastures for hundreds of years. However, the plateau has experienced significant lake shrinkage and grassland degradation during the past several decades. To quantify the changes in all of the lakes on the plateau and the associated driving factors, we performed a satellite-based survey using multitemporal Landsat images from the 1970s to 2000s, combined with ground-based censuses. Our results document a rapid loss of lakes on the plateau in the past decades: the number of lakes with a water surface area >1 km2 decreased from 785 in the late 1980s to 577 in 2010, with a greater rate of decrease (34.0%) in Inner Mongolia of China than in Mongolia (17.6%). This decrease has been particularly pronounced since the late 1990s in Inner Mongolia and the number of lakes >10 km2 has declined by 30.0%. The statistical analyses suggested that in Mongolia precipitation was the dominant driver for the lake changes, and in Inner Mongolia coal mining was most important in its grassland area and irrigation was the leading factor in its cultivated area. The deterioration of lakes is expected to continue in the following decades not only because of changing climate but also increasing exploitation of underground mineral and groundwater resources on the plateau. To protect grasslands and the indigenous nomads, effective action is urgently required to save these valuable lakes from further deterioration.

A geometric method for wood-leaf separation using terrestrial and simulated Lidar data

Abstract Terrestrial light detection and ranging (lidar) can be used to record the three-dimensional structures of trees. Wood-leaf separation, which aims to classify lidar points into wood and leaf components, is an essential prerequisite for deriving individual tree characteristics. Previous research has tended to use intensity (including a multi-wavelength approach) and waveform information for wood-leaf separation, but use of the most fundamental information from a lidar point cloud, i.e., the x-, y-, and z- coordinates of each point, for this purpose has been poorly explored. In this study, we introduce a geometric method for wood-leaf separation using the x-, y-, and z- coordinates of each point. The separation results indicate that first-, second-, and third-order branches can be extracted from the raw point cloud by this new method, suggesting that it might provide a promising solution for wood-leaf separation.

Global patterns, trends, and drivers of water use efficiency from 2000 to 2013

Water use efficiency (WUE; gross primary production [GPP]/evapotranspiration [ET]) estimates the tradeoff between carbon gain and water loss during photosynthesis and is an important link of the carbon and water cycles. Understanding the spatiotemporal patterns and drivers of WUE is helpful for projecting the responses of ecosystems to climate change. Here we examine the spatiotemporal patterns, trends, and drivers of WUE at the global scale from 2000 to 2013 using the gridded GPP and ET data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). Our results show that the global WUE has an average value of 1.70 g C/kg H2O with large spatial variability during the 14-year period. WUE exhibits large variability with latitude. WUE also varies much with elevation: it first remains relatively constant as the elevation varies from 0 to 1000 m and then decreases dramatically. WUE generally increases as precipitation and specific humidity increase; whereas it decreases after reaching maxima as temperature and solar radiation increases. In most land areas, the temporal trend of WUE is positively correlated with precipitation and specific humidity over the 14-year period; while it has a negative relationship with temperature and solar radiation related to global warming and dimming. On average, WUE shows an increasing trend of 0.0025 g C·kg−1 H2O·yr−1 globally. Our global-scale assessment of WUE has implications for improving our understanding of the linkages between the water and carbon cycles and for better projecting the responses of ecosystems to climate change.

An invariability-area relationship sheds new light on the spatial scaling of ecological stability

The spatial scaling of stability is key to understanding ecological sustainability across scales and the sensitivity of ecosystems to habitat destruction. Here we propose the invariability–area relationship (IAR) as a novel approach to investigate the spatial scaling of stability. The shape and slope of IAR are largely determined by patterns of spatial synchrony across scales. When synchrony decays exponentially with distance, IARs exhibit three phases, characterized by steeper increases in invariability at both small and large scales. Such triphasic IARs are observed for primary productivity from plot to continental scales. When synchrony decays as a power law with distance, IARs are quasilinear on a log–log scale. Such quasilinear IARs are observed for North American bird biomass at both species and community levels. The IAR provides a quantitative tool to predict the effects of habitat loss on population and ecosystem stability and to detect regime shifts in spatial ecological systems, which are goals of relevance to conservation and policy.

Carbon stocks and changes of dead organic matter in China's forests

Forests play an important role in global carbon cycles. However, the lack of available information on carbon stocks in dead organic matter, including woody debris and litter, reduces the reliability of assessing the carbon cycles in entire forest ecosystems. Here we estimate that the national DOM carbon stock in the period of 2004–2008 is 925 ± 54 Tg, with an average density of 5.95 ± 0.35 Mg C ha−1. Over the past two decades from periods of 1984−1988 to 2004−2008, the national dead organic matter carbon stock has increased by 6.7 ± 2.2 Tg carbon per year, primarily due to increasing forest area. Temperature and precipitation increase the carbon density of woody debris, but decrease that of litter. Additionally, the woody debris increases significantly with above ground biomass and forest age. Our results can improve estimates of the carbon budget in Chinas forests and for better understanding of effects of climate and stand characteristics on dead organic matter distribution.Reliable estimates of the total forest carbon (C) pool are lacking due to insufficient information on dead organic matter (DOM). Here, the authors estimate that the current DOM C stock in China is 925 ± 54 Tg and that it grew by 6.7 ± 2.2 Tg C/yr over the past two decades primarily due to increasing forest area

Quantifying individual tree growth and tree competition using bi-temporal airborne laser scanning data: a case study in the Sierra Nevada Mountains, California

ABSTRACT Improved monitoring and understanding of tree growth and its responses to controlling factors are important for tree growth modeling. Airborne Laser Scanning (ALS) can be used to enhance the efficiency and accuracy of large-scale forest surveys in delineating three-dimensional forest structures and under-canopy terrains. This study proposed an ALS-based framework to quantify tree growth and competition. Bi-temporal ALS data were used to quantify tree growth in height (ΔH), crown area (ΔA), crown volume (ΔV), and tree competition for 114,000 individual trees in two conifer-dominant Sierra Nevada forests. We analyzed the correlations between tree growth attributes and controlling factors (i.e. tree sizes, competition, forest structure, and topographic parameters) at multiple levels. At the individual tree level, ΔH had no consistent correlations with controlling factors, ΔA and ΔV were positively related to original tree sizes (R > 0.3) and negatively related to competition indices (R < −0.3). At the forest-stand level, ΔH and ΔA were highly correlated to topographic wetness index (|R| > 0.7), ΔV was positively related to original tree sizes (|R| > 0.8). Multivariate regression models were simulated at individual tree level for ΔH, ΔA, and ΔV with the R2 ranged from 0.1 to 0.43. The ALS-based tree height estimation and growth analysis results were consistent with field measurements.

Derivation, Validation, and Sensitivity Analysis of Terrestrial Laser Scanning-Based Leaf Area Index

Abstract. Terrestrial laser scanning (TLS) is a promising tool, used to retrieve leaf area index (LAI). However, the accuracy of LAI estimations based on TLS is still difficult to validate, because high-fidelity destructive measurements of leaf area are lacking. A comprehensive analysis of the sensitivity of TLS-based LAI estimates against various influencing factors (e.g., noise points, woody points, and voxel size) has yet to be reported. We acquired the true LAI by destructively measuring all leaves of 17 magnolia trees. We also improved a voxel-based method to estimate the LAI from the TLS data. We further assessed the sensitivity of LAI estimates against denoising, separation of woody points from foliage points, and voxel size. Our results showed that TLS-based LAI estimations were significantly related to the destructively sampled LAI (R2 = 0.832, RMSE = 0.693). Denoising improved the TLS-based LAI accuracy with a decrease of 0.415 in RMSE. Conversely, wood-leaf separation showed little effect on the accuracy of LAI estimation. The voxel size was an important parameter affecting the accuracy of TLS-based LAI, and our new method for determining voxel size (R2 = 0.832) proved to be more effective than the existing 2 methods (R2 = 0.661 and 0.581).

Global patterns of woody residence time and its influence on model simulation of aboveground biomass

Woody residence time (τw) is an important parameter that expresses the balance between mature forest recruitment/growth and mortality. Using field data collected from the literature, this study explored the global forest τw and investigated its influence on model simulations of aboveground biomass (AGB) at a global scale. Specifically, τw was found to be related to forest age, annual temperature, and precipitation at a global scale, but its determinants were different among various plant function types. The estimated global forest τw based on the filed data showed large spatial heterogeneity, which plays an important role in model simulation of AGB by a dynamic global vegetation model (DGVM). The τw could change the resulting AGB in tenfold based on a site-level test using the Monte Carlo method. At the global level, different parameterization schemes of the Integrated Biosphere Simulator using the estimated τw resulted in a twofold change in the AGB simulation for 2100. Our results highlight the influences of various biotic and abiotic variables on forest τw. The estimation of τw in our study may help improve the model simulations and reduce the parameters uncertainty over the projection of future AGB in the current DGVM or Earth System Models. A clearer understanding of the responses of τw to climate change and the corresponding sophisticated description of forest growth/mortality in model structure is also needed for the improvement of carbon stock prediction in future studies.