Engineering topics

Wang, Yingping

Publications and source records attributed to Wang, Yingping.

9 records

DOE OSTI2019

A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change

Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in temperature, precipitation, CO2 and nitrogen across major terrestrial vegetation types of the world. Most experiments manipulated single rather than multiple global change drivers in temperate ecosystems of the USA, Europe and China. The magnitudes of warming and elevated CO2 treatments were consistent with the ranges of future projections, whereas those of precipitation changes and nitrogen inputs often exceeded the projected ranges. Increases in global change drivers consistently accelerated, but decreased precipitation slowed down carbon-cycle processes. Nonlinear (including synergistic and antagonistic) effects among global change drivers were rare. Belowground carbon allocation responded negatively to increased precipitation and nitrogen addition and positively to decreased precipitation and elevated CO2. The sensitivities of carbon variables to multiple global change drivers depended on the background climate and ecosystem condition, suggesting that Earth system models should be evaluated using site-specific conditions for best uses of this large dataset. Together, this synthesis underscores an urgent need to explore the interactions among multiple global change drivers in underrepresented regions such as semi-arid ecosystems, forests in the tropics and subtropics, and Arctic tundra when forecasting future terrestrial carbon-climate feedback.

Song, Jian↗

DOE OSTI2018

Enhanced peak growth of global vegetation and its key mechanisms

The annual peak growth of vegetation is critical in characterizing the capacity of terrestrial ecosystem productivity and shaping the seasonality of atmospheric CO 2 concentrations. The recent greening of global lands suggests an increasing trend of terrestrial vegetation growth, but whether or not the peak growth has been globally enhanced still remains unclear. Here, we use two global datasets of gross primary productivity (GPP) and a satellite-derived Normalized Difference Vegetation Index (NDVI) to characterize recent changes in annual peak vegetation growth (that is, GPP max and NDVI max ). We demonstrate that the peak in the growth of global vegetation has been linearly increasing during the past three decades. About 65% of the NDVI max variation is evenly explained by expanding croplands (21%), rising CO 2 (22%) and intensifying nitrogen deposition (22%). The contribution of expanding croplands to the peak growth trend is substantiated by measurements from eddy-flux towers, sun-induced chlorophyll fluorescence and a global database of plant traits, all of which show that croplands have a higher photosynthetic capacity than other vegetation types. The large contribution of CO 2 is also supported by a meta-analysis of 466 manipulative experiments and 15 terrestrial biosphere models. Moreover, we show that the contribution of GPP max to the change in annual GPP is less in the tropics than in other regions. These multiple lines of evidence reveal an increasing trend in the peak growth of global vegetation. These results draw attention to the vital roles of agricultural intensification and atmospheric changes in reshaping the seasonality of global vegetation growth.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites

Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. For this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Climate mitigation from vegetation biophysical feedbacks during the past three decades

The surface air temperature response to vegetation changes has been studied for the extreme case of land-cover change; yet, it has never been quantified for the slow but persistent increase in leaf area index (LAI) observed over the past 30 years (Earth greening). We isolate the fingerprint of increasing LAI on surface air temperature using a coupled land–atmosphere global climate model prescribed with satellite LAI observations. Furthermore, we found that the global greening has slowed down the rise in global land-surface air temperature by 0.09 ± 0.02 °C since 1982. This net cooling effect is the sum of cooling from increased evapotranspiration (70%), changed atmospheric circulation (44%), decreased shortwave transmissivity (21%), and warming from increased longwave air emissivity (-29%) and decreased albedo (-6%). The global cooling originated from the regions where LAI has increased, including boreal Eurasia, Europe, India, northwest Amazonia, and the Sahel. Increasing LAI did not, but, significantly change surface air temperature in eastern North America and East Asia, where the effects of large-scale atmospheric circulation changes mask local vegetation feedbacks. Overall, the sum of biophysical feedbacks related to the greening of the Earth mitigated 12% of global land-surface warming for the past 30 years.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Divergent predictions of carbon storage between two global land models: Attribution of the causes through traceability analysis

Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models' performance. In this study, we applied a traceability analysis which decomposes carbon cycle models into traceable components, for two global land models (CABLE and CLM-CASA') to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, CLM-CASA' predicted – 31 % larger carbon storage capacity than CABLE. Since ecosystem carbon storage capacity is a product of net primary productivity (NPP) and ecosystem residence time ( τ E ), the predicted difference in the storage capacity between the two models results from differences in either NPP or τ E or both. Our analysis showed that CLM-CASA'simulated 37 % higher NPP than CABLE. On the other hand, τ E , which was a function of the baseline carbon residence time ( τ ' E ) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA'. This difference in τ E was mainly caused by longer τ ' E of woody biomass (23 vs. 14 years in CLM-CASA'), and higher proportion of NPP allocated to woody biomass (23 vs. 16 %). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ ' E . Altogether, the traceability analysis showed that the major causes of different carbon storage estimations were found to be parameters setting related to carbon input and baseline carbon residence times between two models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Greening of the Earth and its drivers

Global environmental change is rapidly altering the dynamics of terrestrial vegetation, with consequences for the functioning of the Earth system and provision of ecosystem services 1, 2 . Yet how global vegetation is responding to the changing environment is not well established. Here we use three long-term satellite leaf area index (LAI) records and ten global ecosystem models to investigate four key drivers of LAI trends during 1982 2009. We show a persistent and widespread increase of growing season integrated LAI (greening) over 25% to 50% of the global vegetated area, whereas less than 4% of the globe shows decreasing LAI (browning). Factorial simulations with multiple global ecosystem models suggest that CO 2 fertilization effects explain 70% of the observed greening trend, followed by nitrogen deposition (9%), climate change (8%) and land cover change (LCC) (4%). CO 2 fertilization effects explain most of the greening trends in the tropics, whereas climate change resulted in greening of the high latitudes and the Tibetan Plateau. LCC contributed most to the regional greening observed in southeast China and the eastern United States. In conclusion, the regional effects of unexplained factors suggest that the next generation of ecosystem models will need to explore the impacts of forest demography, differences in regional management intensities for cropland and pastures, and other emerging productivity constraints such as phosphorus availability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Seasonal responses of terrestrial ecosystem water‐use efficiency to climate change

Abstract Ecosystem water‐use efficiency ( EWUE ) is an indicator of carbon–water interactions and is defined as the ratio of carbon assimilation ( GPP ) to evapotranspiration ( ET ). Previous research suggests an increasing long‐term trend in annual EWUE over many regions and is largely attributed to the physiological effects of rising CO 2 . The seasonal trends in EWUE , however, have not yet been analyzed. In this study, we investigate seasonal EWUE trends and responses to various drivers during 1982–2008. The seasonal cycle for two variants of EWUE , water‐use efficiency ( WUE , GPP / ET ), and transpiration‐based WUE ( WUE t , the ratio of GPP and transpiration), is analyzed from 0.5° gridded fields from four process‐based models and satellite‐based products, as well as a network of 63 local flux tower observations. WUE derived from flux tower observations shows moderate seasonal variation for most latitude bands, which is in agreement with satellite‐based products. In contrast, the seasonal EWUE trends are not well captured by the same satellite‐based products. Trend analysis, based on process‐model factorial simulations separating effects of climate, CO 2 , and nitrogen deposition ( NDEP ), further suggests that the seasonal EWUE trends are mainly associated with seasonal trends of climate, whereas CO 2 and NDEP do not show obvious seasonal difference in EWUE trends. About 66% grid cells show positive annual WUE trends, mainly over mid‐ and high northern latitudes. In these regions, spring climate change has amplified the effect of CO 2 in increasing WUE by more than 0.005 gC m −2 mm −1 yr −1 for 41% pixels. Multiple regression analysis further shows that the increase in springtime WUE in the northern hemisphere is the result of GPP increasing faster than ET because of the higher temperature sensitivity of GPP relative to ET . The partitioning of annual EWUE to seasonal components provides new insight into the relative sensitivities of GPP and ET to climate, CO 2, and NDEP .

Huang, Mengtian↗

DOE OSTI2016

Multi-decadal trends in global terrestrial evapotranspiration and its components

In this study, evapotranspiration (ET) is the process by which liquid water becomes water vapor and energetically this accounts for much of incoming solar radiation. If this ET did not occur temperatures would be higher, so understanding ET trends is crucial to predict future temperatures. Recent studies have reported prolonged declines in ET in recent decades, although these declines may relate to climate variability. Here, we used a well-validated diagnostic model to estimate daily ET during 1981–2012, and its three components: transpiration from vegetation (E t ), direct evaporation from the soil (E s ) and vaporization of intercepted rainfall from vegetation (E i ). During this period, ET over land has increased significantly (p < 0.01), caused by increases in E t and E i , which are partially counteracted by E s decreasing. These contrasting trends are primarily driven by increases in vegetation leaf area index, dominated by greening. The overall increase in E t over land is about twofold of the decrease in E s . These opposing trends are not simulated by most Coupled Model Intercomparison Project phase 5 (CMIP5) models, and highlight the importance of realistically representing vegetation changes in earth system models for predicting future changes in the energy and water cycle.

15 GEOTHERMAL ENERGY↗

DOE OSTI2015

Using Ecosystem Experiments to Improve Vegetation Models

Ecosystem responses to rising CO2 concentrations are a major source of uncertainty in climate change projections. Data from ecosystem-scale Free-Air CO2 Enrichment (FACE) experiments provide a unique opportunity to reduce this uncertainty. The recent FACE Model–Data Synthesis project aimed to use the information gathered in two forest FACE experiments to assess and improve land ecosystem models. A new 'assumption-centred' model intercomparison approach was used, in which participating models were evaluated against experimental data based on the ways in which they represent key ecological processes. Identifying and evaluating the main assumptions caused differences among models, and the assumption-centered approach produced a clear roadmap for reducing model uncertainty. We explain this approach and summarize the resulting research agenda. We encourage the application of this approach in other model intercomparison projects to fundamentally improve predictive understanding of the Earth system.

54 ENVIRONMENTAL SCIENCES↗