Warming Changed Soil Respiration Dynamics of Alpine Meadow Ecosystem on the Tibetan Plateau

Alpine meadow system underlain by permafrost on the Tibetan Plateau contains vast soil organic carbon and is sensitive to global warming.However,the dynamics of annual soil respiration(Rs)under long-term warming and the determined factors are still not very clear.Using opentop chambers(OTC),we assessed the effects of two-year experimental warming on the soil CO2 emission and the Q10 value(temperature sensitivity coefficient)under different warming magnitudes.Our study showed that the soil CO2 efflux rate in the warmed plots were 1.22 and 2.32 times higher compared to that of controlled plots.However,the Q10 value decreased by 45.06%and 50.34%respectively as the warming magnitude increased.These results suggested that soil moisture decreasing under global warming would enhance soil CO2 emission and lower the temperature sensitivity of soil respiration rate of the alpine meadow ecosystem in the permafrost region on the Tibetan Plateau.Thus,it is necessary to take into account the combined effect of ground surface warming and soil moisture decrease on the Rs in order to comprehensively evaluate the carbon emissions of the alpine meadow ecosystem,especially in short and medium terms.

大规模风电场对草地碳循环的影响

Deployment of wind energy is an essential renewable energy source that mitigates climate change and reduces air pollution[1].Over the last several decades,wind energy development has increased worldwide,expanding from~20 to~900 GW(gigawatt)during 2001–2022[1].

An Interactive Visual Analytics Framework for Multi-Field Data in a Geo-Spatial Context

Climate research produces a wealth of multivariate data. These data often have a geospatial reference and so it is of interest to show them within their geospatial context. One can consider this configuration as a multifield visualization problem, where the geo-space provides the expanse of the field. However, there is a limit on the amount of multivariate information that can be fit within a certain spatial location, and the use of linked multivariate information displays has previously been devised to bridge this gap. In this paper we focus on the interactions in the geographical display, present an implementation that uses Google Earth, and demonstrate it within a tightly linked parallel coordinates display. Several other visual representations, such as pie and bar charts are integrated into the Google Earth display and can be interactively manipulated. Further, we also demonstrate new brushing and visualization techniques for parallel coordinates, such as fixed-window brushing and correlation-enhanced display. We conceived our system with a team of climate researchers, who already made a few important discoveries using it. This demonstrates our system＇s great potential to enable scientific discoveries, possibly also in other domains where data have a geospatial reference.

Modeling the impacts of temperature and precipitation changes on soil CO_2 fluxes from a Switchgrass stand recently converted from cropland

Switchgrass（Panicum virgatum L.） is a perennial C_4 grass native to North America and successfully adapted to diverse environmental conditions. It offers the potential to reduce soil surface carbon dioxide（CO_2） fluxes and mitigate climate change. However, information on how these CO_2 fluxes respond to changing climate is still lacking. In this study, CO_2 fluxes were monitored continuously from 2011 through 2014 using high frequency measurements from Switchgrass land seeded in 2008 on an experimental site that has been previously used for soybean（Glycine max L.） in South Dakota, USA. DAYCENT, a process-based model, was used to simulate CO_2 fluxes. An improved methodology CPTE[Combining Parameter estimation（PEST） with ＂Trial and Error＂ method] was used to calibrate DAYCENT. The calibrated DAYCENT model was used for simulating future CO_2 emissions based on different climate change scenarios. This study showed that：（i） the measured soil CO_2 fluxes from Switchgrass land were higher for 2012 which was a drought year, and these fluxes when simulated using DAYCENT for long-term（2015–2070） provided a pattern of polynomial curve;（ii） the simulated CO_2 fluxes provided different patterns with temperature and precipitation changes in a long-term,（iii） the future CO_2 fluxes from Switchgrass land under different changing climate scenarios were not significantly different, therefore, it can be concluded that Switchgrass grown for longer durations could reduce changes in CO_2 fluxes from soil as a result of temperature and precipitation changes to some extent.