Nan Cong

Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends

The purpose of this study was to evaluate 10 process-based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared with flux-tower-based estimates by Jung et al. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO2 trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO2 sensitivity of NPP is compared to the results from four Free-Air CO2 Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein et al. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 ± 15 Pg C yr(-1) ) than JU11 (118 ± 6 Pg C yr(-1) ). In response to rising atmospheric CO2 concentration, modeled NPP increases on average by 16% (5-20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO2 than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr(-1) is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr(-1) ). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980-2009. Both model-to-model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is -3.0 ± 1.5 Pg C yr(-1) °C(-1) , within the uncertainty of what derived from RLS (-3.9 ± 1.1 Pg C yr(-1) °C(-1) ). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO2 and climate, the agreement between modeled and observation-based GPP and NBP can be fortuitous. Carbon-nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO2 concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models.

Evidence for a weakening relationship between interannual temperature variability and northern vegetation activity.

Satellite-derived Normalized Difference Vegetation Index (NDVI), a proxy of vegetation productivity, is known to be correlated with temperature in northern ecosystems. This relationship, however, may change over time following alternations in other environmental factors. Here we show that above 30°N, the strength of the relationship between the interannual variability of growing season NDVI and temperature (partial correlation coefficient RNDVI-GT) declined substantially between 1982 and 2011. This decrease in RNDVI-GT is mainly observed in temperate and arctic ecosystems, and is also partly reproduced by process-based ecosystem model results. In the temperate ecosystem, the decrease in RNDVI-GT coincides with an increase in drought. In the arctic ecosystem, it may be related to a nonlinear response of photosynthesis to temperature, increase of hot extreme days and shrub expansion over grass-dominated tundra. Our results caution the use of results from interannual time scales to constrain the decadal response of plants to ongoing warming.

Earlier-Season Vegetation Has Greater Temperature Sensitivity of Spring Phenology in Northern Hemisphere

In recent decades, satellite-derived start of vegetation growing season (SOS) has advanced in many northern temperate and boreal regions. Both the magnitude of temperature increase and the sensitivity of the greenness phenology to temperature–the phenological change per unit temperature–can contribute the advancement. To determine the temperature-sensitivity, we examined the satellite-derived SOS and the potentially effective pre-season temperature (T eff) from 1982 to 2008 for vegetated land between 30°N and 80°N. Earlier season vegetation types, i.e., the vegetation types with earlier SOSmean (mean SOS for 1982–2008), showed greater advancement of SOS during 1982–2008. The advancing rate of SOS against year was also greater in the vegetation with earlier SOSmean even the T eff increase was the same. These results suggest that the spring phenology of vegetation may have high temperature sensitivity in a warmer area. Therefore it is important to consider temperature-sensitivity in assessing broad-scale phenological responses to climatic warming. Further studies are needed to explore the mechanisms and ecological consequences of the temperature-sensitivity of start of growing season in a warming climate.

Varying responses of vegetation activity to climate changes on the Tibetan Plateau grassland

Vegetation activity on the Tibetan Plateau grassland has been substantially enhanced as a result of climate change, as revealed by satellite observations of vegetation greenness (i.e., the normalized difference vegetation index, NDVI). However, little is known about the temporal variations in the relationships between NDVI and temperature and precipitation, and understanding this is essential for predicting how future climate change would affect vegetation activity. Using NDVI data and meteorological records from 1982 to 2011, we found that the inter-annual partial correlation coefficient between growing season (May–September) NDVI and temperature (RNDVI-T) in a 15-year moving window for alpine meadow showed little change, likely caused by the increasing RNDVI-T in spring (May–June) and autumn (September) and decreasing RNDVI-T in summer (July–August). Growing season RNDVI-T for alpine steppe increased slightly, mainly due to increasing RNDVI-T in spring and autumn. The partial correlation coefficient between growing season NDVI and precipitation (RNDVI-P) for alpine meadow increased slightly, mainly in spring and summer, and RNDVI-P for alpine steppe increased, mainly in spring. Moreover, RNDVI-T for the growing season was significantly higher in those 15-year windows with more precipitation for alpine steppe. RNDVI-P for the growing season was significantly higher in those 15-year windows with higher temperature, and this tendency was stronger for alpine meadow than for alpine steppe. These results indicate that the impact of warming on vegetation activity of Tibetan Plateau grassland is more positive (or less negative) during periods with more precipitation and that the impact of increasing precipitation is more positive (or less negative) during periods with higher temperature. Such positive effects of the interactions between temperature and precipitation indicate that the projected warmer and wetter future climate will enhance vegetation activity of Tibetan Plateau grassland.

Spatial variations in responses of vegetation autumn phenology to climate change on the Tibetan Plateau

Aims Information about changes in the start and end of the vegetation growing season (SOS and EOS) is crucial for assessing ecosystem responses to climate change because of the high sensitivity of both to climate and their extensive influence on ecological processes in temperate and cold regions. climatic warming substantially advanced SOS on the tibetan Plateau from 1982 to 2011. However, it is unclear why EOS showed little delay despite increasing temperature over this period. Methods We used multiple methods to determine EOS from the satelliteobserved normalized-difference vegetation index and investigated the relationships between EOS and its potential drivers on the tibetan Plateau over 1982–2011. Important findings We found a slight but non-significant delay in regionally averaged EOS of 0.7 day decade−1 (P = 0.18) and a widespread but weak delaying trend across the Plateau over this period. the inter-annual variations in regionally averaged EOS were driven mainly by preseason temperature (partial R = 0.62, P < 0.01), and precipitation and insolation showed weak impact on EOS (P > 0.10). Pre-season warming delayed EOS mainly in the eastern half and north-western area of the plateau. In the south-west, EOS was significantly and positively related to SOS, suggesting potentially indirect effects of winter weather conditions on the following autumn’s phenology through regulation of spring phenology. EOS was more strongly related with pre-season temperature in colder and wetter areas, reflecting vegetation adaptation to local climate. Interestingly, preseason temperature had weaker delaying effects on EOS for vegetation with a shorter growing season, for which SOS had a stronger control on inter-annual variations in EOS than for vegetation with a longer growing season. this indicates that shorter-season tibetan Plateau vegetation may have lower plasticity in adjusting the length of its growing season, whenever it begins, and that climate change is more likely to shift the growing season than extend it for that vegetation.