# Constraints to Vegetation Growth Reduced by Region-Specific Changes in Seasonal Climate
## 4 Discussion
Chi-squared tests performed on the two data sets at seasonal scales yielded the following \(p\)-values: December January February (0.22), March April May (0.05), June July August (0.26), and September October November (0.01). Third, the projected changes in LAI and climate are already apparent in the observational era. Satellite data show that LAI has increased from 1982 to 2005 for all three regions (Figure 14b,d,f); the CRU product shows warming in the temperature-limited region (Figure 14a), increased precipitation in the precipitation-limited region (Figure 14c), and reduced cloud cover in the radiation-limited region (Figure 14e). Consistent with these changes in climate and the biosphere, terrestrial ecosystems have been shown as net sink for carbon in recent decades [45; 46]. Thus, the 21 st century changes to climate and greening do not appear anomalous or implausible, when viewed in the context of recent history. Numerous processes, including extreme climatic events [47], could reduce the projected changes in LAI and GPP. But the paleoclimate record also shows that profound changes in vegetation have occurred in the past, particularly in high latitudes, where the temperature-limited region appears to benefit the most from physical climate changes, mediated through vegetation physiological mechanisms. The early Eocene greenhouse climate, for example, supported redwoods at 78\({}^{\circ}\) N paleo-latitude under CO\({}_{2}\) levels that are similar to the modern levels [42]. The deep-time perspective,  
Figure 13: Performance of Earth system models used in CMIP5 against observations (1982–2005) in each of the climate-limiting regions. CMIP5 seasonality for climate and vegetation are ensemble means of each of the parameters. Shading represents standard deviation around the ensemble mean from the CMIP5 models. Observed seasonality in climate and vegetation over the same period is calculated from Climate Research Unit (CRU) (temperature, precipitation), CRU National Centers for Environmental Prediction version (CRUNCEP) (radiation), and Global Inventory Modeling and Mapping Studies Leaf Area Index (GIMMS) LAI. albeit associated with different time scales and continental configurations, therefore, does not appear to rule out the sort of major changes to vegetation seen in the 21 st century projections [48]. We focused on two elemental components of terrestrial ecosystems--the amount of leafy material and gross carbon fixation--but do not provide insights into respiratory and net carbon fluxes, carbon stocks, such as biomass and soil carbon, and vegetation dynamics. The CMIP5 models, especially low-resolution models, cannot count the extreme events, such as forest fires or hurricanes. The FACE experiments also suggest that non-climate limiting factors, such as nitrogen and phosphorous [49], might supersede climate limitations in the future (although the inclusion of a nitrogen cycle produces results that are within the uncertainties of the full ensemble; see red lines in Figures 3 and 4). The available state-of-the-art Earth system models; however, depict a late 21 st century world in which vegetation physiology interacts with pervasive changes to annual and seasonal climate to create a greener land surface. Figure 14: Performance of Earth system models in capturing the observed trends in climate and vegetation. Observed trends in annual mean climate and satellite-derived LAI from 1982 to 2005 are shown as average responses over the three climate-limiting regions. Ensemble mean of CMIP5 models over the same period do not capture the inter-annual variability, but appear to capture the overall trends in climate and vegetation. The first year of each series is set to zero to emphasize the magnitude of the trend and deviation between the trend lines. The \(p\)-values indicate the level of significance for the trends in observations only (CRU, CRUNCEP, GIMMS, and cloud cover data from NDP026). Shading around the CMIP5 ensemble mean indicates 25–75 percentile.