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Water relations in plant communities are influenced both by contrasting functional groups (grasses and shrubs) and by climate change via complex effects on interception, uptake, and transpiration. ...

Author(s): Xu, X; Riley, WJ; Koven, CD; Jia, G | Abstract: Vegetation phenology plays an important role in regulating land-atmosphere energy, water, and trace-gas exchanges. Changes in spring greenup (SG) have been documented in the past half-century in response to ongoing climate change. We use normalized difference vegetation index generated from NOAA's advanced very high resolution radiometer data in the Global Inventory Modeling and Monitoring Study project over the 1982–2005 period, coupled with climate reanalysis (Climate Research Unit-National Centers for Environmental Prediction) to investigate the SG responses to preseason climate change in northern temperate and boreal regions. We compared these observed responses to the simulated SG responses to preseason climate inferred from the Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) over 1982–2005. The observationally inferred SG suggests that there has been an advance of about 1ndays per decade between 1982 and 2005 in the northern midlatitude to high latitude, with significant spatial heterogeneity. The spatial heterogeneity of the SG advance results from heterogeneity in the change of the preseason climate as well as varied vegetation responses to the preseason climate across biomes. The SG to preseason temperature sensitivity is highest in forests other than deciduous needleleaf forests, followed by temperate grasslands and woody savannas. The SG in deciduous needleleaf forests, open shrublands, and tundra is relatively insensitive to preseason temperature. Although the extent of regions where the SG is sensitive to preseason precipitation is smaller than the extent of regions where the SG is sensitive to preseason temperature, the biomes that are more sensitive to temperature are also more sensitive to precipitation, suggesting the interactive control of temperature and precipitation. In the mean, the CMIP5 ESMs reproduced the dominant latitudinal preseason climate trends and SG advances. However, large biases in individual ESMs for the preseason period, climate, and SG sensitivity imply needed model improvements to climate prediction and phenological process parameterizations.

Forest conversion-driven biophysical processes have been examined in various case studies that largely depend on sensitivity analysis of climate modeling. However, much remains unknown in the real world due to the complicated process and uncertainty in magnitude, especially in the temperate bioclimate regions. This study applied satellite-based observation to investigate the biophysical climate response to potential forest conversion in China, especially on the spatial and temporal patterns and underlying mechanisms. We evaluated the differences of land surface temperature (ΔLST) between adjacent forest and cropland, in terms of the latitudinal and seasonal patterns. Compared to cropland, the temperate forest to the south of 40°N showed the cooling effect of −0.61 ± 0.02°C (95% confidence interval, and hereafter), and it presented the warming effect of 0.48 ± 0.06°C to the north of 48°N (the transition zone was between 40°N and 48°N). Seasonal analysis further demonstrated that the cooling effects of temperate forest in China in spring (March, April, May), summer (June, July, August), and autumn (September, October, November) were −0.53 ± 0.02°C, −0.55 ± 0.02°C, and −0.30 ± 0.02°C, respectively, while the forest caused the warming effect of 0.10 ± 0.04°C in winter (December, January, February). However, the biophysical climate response to forest conversion in temperate regions was complex and showed highly spatial and temporal heterogeneity. We further assessed the role of two major biophysical processes, i.e., albedo and evapotranspiration (ET), in shaping land surface temperature from surface energy budget perspective. Results showed that the latitudinal, seasonal, and spatiotemporal patterns of ΔLST was determined by the net effect of ET-induced latent heat changes and albedo-induced solar radiation absorption changes.

Forests have been recognized to sequester a substantial amount of carbon (C) from the atmosphere. However, considerable uncertainty remains regarding the magnitude and time course of the C sink. Revealing the intrinsic relationship between forest age and C sink is crucial for reducing uncertainties in prediction of forest C sink potential. In this study, we developed a stepwise data assimilation approach to combine a process-based Terrestrial ECOsystem Regional model, observations from multiple sources, and stochastic sampling to inversely estimate carbon cycle parameters including carbon sink at different forest ages for evergreen needle-leaved forests in China. The new approach is effective to estimate age-dependent parameter of maximal light-use efficiency (R2 = 0.99) and, accordingly, can quantify a relationship between forest age and the vegetation and soil C sinks. The estimated ecosystem C sink increases rapidly with age, peaks at 0.451 kg C m−2 yr−1 at age 22 years (ranging from 0.421 to 0.465 kg C m−2 yr−1), and gradually decreases thereafter. The dynamic patterns of C sinks in vegetation and soil are significantly different. C sink in vegetation first increases rapidly with age and then decreases. C sink in soil, however, increases continuously with age; it acts as a C source when the age is less than 20 years, after which it acts as a sink. For the evergreen needle-leaved forest, the highest C sink efficiency (i.e., C sink per unit net primary productivity) is approximately 60%, with age between 11 and 43 years. Overall, the inverse estimation of carbon cycle parameters can make reasonable estimates of age-dependent C sequestration in forests.

Rapid urbanization has resulted in the permanent conversion of large areas of cropland and natural vegetation to impervious surfaces and therefore greatly modified land surface properties and land-atmosphere interactions. This study sought to examine the urbanization process using Landsat images from 2001 to 2010 in metropolitan JingjinTang (JJT), a rapidly expanding urban cluster in northern China. We aggregated the original results of land use data as fractional cover information in 1 km and 10 km grids. Annual and seasonal land surface temperatures (LSTs) were processed from Moderate Resolution Imaging Spectroradiometer products. We used moving window and gradient analysis methods to examine the differences in LST between urban and other land types, further identifying LST increases in gradients of urbanization levels. Urban extent increased by 1.6 times, and approximately 45% newly developed areas were converted from croplands during this process. Emerging urban land in JJT has caused approximately 0.85 ± 0.68°C warming in terms of annual mean LST, and the greatest warming occurred in the summer. An increase in urban land of 10% in a 1 km grid in JJT would cause approximately a 0.21°C increase in annual LST. Urbanization also led to increases in daytime LSTs and nighttime LSTs by approximately 1.03 ± 1.38°C and 0.78 ± 1.02°C, respectively. The warming trend induced by urbanization exhibits clear seasonal and diurnal differences, and this warming trend is most likely caused by the cumulative effects of changes in land properties, radiation storage, and anthropogenic heat release by urbanization.

[1] Carbon sequestration occurs only when terrestrial ecosystems are at nonsteady states. Despite of their ubiquity in the real world, the nonsteady states of ecosystems have not been well quantified, especially at regional and global scales. In this study, we developed a two-step data assimilation scheme to estimate carbon sink strength in China's forest ecosystems. Specifically, the two-step scheme consists of a steady state step and a nonsteady state step. In the steady state step, we constrained a process-based model (Terrestrial Ecosystem Regional (TECO-R) model) against biometric data (net primary production NPP, biomass, litter, and soil organic carbon) in mature forests. With a subset of the parameter values estimated from the steady state data assimilation being fixed, the nonsteady state data assimilation was performed to estimate carbon sequestration in China's forest ecosystems. Our results indicated that 17 out of the 22 total parameters in the TECO-R model were well constrained by the biometric data with the steady state data assimilation. When observations from both mature and developing forests were used, all the 10 parameters related to carbon sequestration in vegetation and soil carbon pools were well constrained at the nonsteady state step. The estimated mean vegetation carbon sink in China's forests is 89.7 ± 16.8 gC m−2 yr−1, comparable with the values estimated from the forest inventory and other process-based regional models. The estimated mean soil and litter carbon sinks in China's forests are 14.1 ± 20.7 and 4.7 ± 6.5 gC m−2 yr−1. This study demonstrated that a two-step data assimilation scheme can be a potent tool to estimate regional carbon sequestration in nonsteady state ecosystems.

[1] In this paper, the Weather Research and Forecasting Model, coupled to the Urban Canopy Model, is employed to simulate the impact of urbanization on the regional climate over three vast city agglomerations in China. Based on high-resolution land use and land cover data, two scenarios are designed to represent the nonurban and current urban land use distributions. By comparing the results of two nested, high-resolution numerical experiments, the spatial and temporal changes on surface air temperature, heat stress index, surface energy budget, and precipitation due to urbanization are analyzed and quantified. Urban expansion increases the surface air temperature in urban areas by about 1C, and this climatic forcing of urbanization on temperature is more pronounced in summer and nighttime than other seasons and daytime. The heat stress intensity, which reflects the combined effects of temperature and humidity, is enhanced by about 0.5 units in urban areas. The regional incoming solar radiation increases after urban expansion, which may be caused by the reduction of cloud fraction. The increased temperature and roughness of the urban surface lead to enhanced convergence. Meanwhile, the planetary boundary layer is deepened, and water vapor is mixed more evenly in the lower atmosphere. The deficit of water vapor leads to less convective available potential energy and more convective inhibition energy. Finally, these combined effects may reduce the rainfall amount over urban areas, mainly in summer, and change the regional precipitation pattern to a certain extent.

[1] Only a few studies to date have collectively examined the vegetation biomass and production of arctic tundra ecosystems and their relationships to broadly ranging climate variables. An additional complicating factor for studying vegetation of arctic tundra is the high spatial variability associated with small patterned-ground features, resulting from intense freeze-thaw processes. In this study, we sampled and analyzed the aboveground plant biomass components of patterned-ground ecosystems in the Arctic of northern Alaska and Canada along an 1800-km north-south gradient that spans approximately 11°C of mean July temperatures. Vegetation biomass was analyzed as functions of the summer warmth index (SWI–sum of mean monthly temperatures > 0°C). The total absolute biomass (g m−2) and biomass of shrubs increased monotonically with SWI, however, biomass of nonvascular species (mosses and lichens), were a parabolic function of SWI, with greatest values at the ends of the gradient. The components of plant biomass on patterned-ground features (i.e., on nonsorted circles or within small polygons) were constrained to a greater degree with colder climate than undisturbed tundra, likely due to the effect of frost heave disturbances on the vegetation. There were also clear differences in the relative abundances of vascular versus nonvascular plants on and off patterned-ground features along the SWI gradient. The spatial patterns of biomass differ among plant functional groups and suggest that plant community responses to temperature, and land-surface processes that produce patterned-ground features, are quite complex.

[1] Here we analyzed a time series of 21-yr satellite data for three bioclimate subzones in northern Alaska and confirmed a long-term trend of increase in vegetation greenness for the Alaskan tundra that has been detected globally for the northern latitudes. There was a 16.9% (±5.6%) increase in peak vegetation greenness across the region that corresponded to simultaneous increases in temperatures. We also examined the changes for four specific vegetation types using an 11-yr finer resolution (1-km) satellite data and found that the temporal changes in peak and time-integrated greenness were greatest in areas of moist nonacidic tundra. These changes in greenness between 1981 and 2001 correspond approximately to a 171 g/m2 (±81 g/m2) increases in aboveground plant biomass for Alaskan tundra. This remotely sensed interpretation is conducted in the absence of long-term biomass records in the region.

[1] We examined the effects of summer warmth on leaf area index (LAI), total aboveground phytomass (TAP), and normalized difference vegetation index (NDVI) across the Arctic bioclimate zone in Alaska and extrapolated our results to the circumpolar Arctic. Phytomass, LAI, and within homogeneous areas of vegetation on acidic and nonacidic soils were regressed against the total summer warmth index (SWI) at 12 climate stations in northern Alaska (SWI = sum of mean monthly temperatures greater than 0°C). SWI varies from 9°C at Barrow to 37°C at Happy Valley. A 5°C increase in the SWI is correlated with about a 120 g m−2 increase in the aboveground phytomass for zonal vegetation on acidic sites and about 60 g m−2 on nonacidic sites. Shrubs account for most of the increase on acidic substrates, whereas mosses account for most of the increase on nonacidic soils. LAI is positively correlated with SWI on acidic sites but not on nonacidic sites. The NDVI is positively correlated with SWI on both acidic and nonacidic soils, but the NDVI on nonacidic parent material is consistently lower than the NDVI on acidic substrates. Extrapolation to the whole Arctic using a five-subzone zonation approach to stratify the circumpolar NDVI and phytomass data showed that 60% of the aboveground phytomass is concentrated in the low-shrub tundra (subzone 5), whereas the high Arctic (subzones 1–3) has only 9% of the total. Estimated phytomass densities in subzones 1–5 are 47, 256, 102, 454, and 791 g m−2, respectively. Climate warming will likely result in increased phytomass, LAI, and NDVI on zonal sites. These changes will be most noticeable in acidic areas with abundant shrub phytomass.