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Global climate change is expected to shift regional rainfall patterns, influencing species distributions where they depend on water availability. Comparative studies have demonstrated that C4 grasses inhabit drier habitats than C3 relatives, but that both C3 and C4 photosynthesis are susceptible to drought. However, C4 plants may show advantages in hydraulic performance in dry environments. We investigated the effects of seasonal variation in water availability on leaf physiology, using a common garden experiment in the Eastern Cape of South Africa to compare 12 locally occurring grass species from C4 and C3 sister lineages. Photosynthesis was always higher in the C4 than C3 grasses across every month, but the difference was not statistically significant during the wettest months. Surprisingly, stomatal conductance was typically lower in the C3 than C4 grasses, with the peak monthly average for C3 species being similar to that of C4 leaves. In water-limited, rain-fed plots, the photosynthesis of C4 leaves was between 2.0 and 7.4 μmol m−2 s−1 higher, stomatal conductance almost double, and transpiration 60% higher than for C3 plants. Although C4 average instantaneous water-use efficiencies were higher (2.4-8.1 mmol mol−1) than C3 averages (0.7-6.8 mmol mol−1), differences were not as great as we expected and were statistically significant only as drought became established. Photosynthesis declined earlier during drought among C3 than C4 species, coincident with decreases in stomatal conductance and transpiration. Eventual decreases in photosynthesis among C4 plants were linked with declining midday leaf water potentials. However, during the same phase of drought, C3 species showed significant decreases in hydrodynamic gradients that suggested hydraulic failure. Thus, our results indicate that stomatal and hydraulic behaviour during drought enhances the differences in photosynthesis between C4 and C3 species. We suggest that these drought responses are important for understanding the advantages of C4 photosynthesis under field conditions. [ABSTRACT FROM AUTHOR]

The response of plant respiration ( R) to temperature is an important component of the biosphere's response to climate change. At present, most global models assume that R increases exponentially with temperature and does not thermally acclimate. Although we now know that acclimation does occur, quantitative incorporation of acclimation into models has been lacking. Using a dataset for 19 species grown at four temperatures (7, 14, 21, and 28 °C), we have assessed whether sustained differences in growth temperature systematically alter the slope and/or intercepts of the generalized log–log plots of leaf R vs. leaf mass per unit leaf area (LMA) and vs. leaf nitrogen (N) concentration. The extent to which variations in growth temperature account for the scatter observed in log–log R–LMA–N scaling relationships was also assessed. We show that thermal history accounts for up to 20% of the scatter in scaling relationships used to predict R, with the impact of thermal history on R–LMA–N generalized scaling relationships being highly predictable. This finding enabled us to quantitatively incorporate acclimation of R into a coupled global climate–vegetation model. We show that accounting for acclimation of R has negligible impact on predicted annual rates of global R, net primary productivity (NPP) or future atmospheric CO2 concentrations. However, our analysis suggests that accounting for acclimation is important when considering carbon fluxes among thermally contrasting biomes (e.g. accounting for acclimation decreases predicted rates of R by up to 20% in high-temperature biomes). We conclude that acclimation of R needs to be accounted for when predicting potential responses of terrestrial carbon exchange to climatic change at a regional level. [ABSTRACT FROM AUTHOR]

This study tests the ability of five Dynamic Global Vegetation Models (DGVMs), forced with observed climatology and atmospheric CO2, to model the contemporary global carbon cycle. The DGVMs are also coupled to a fast ‘climate analogue model’, based on the Hadley Centre General Circulation Model (GCM), and run into the future for four Special Report Emission Scenarios (SRES): A1FI, A2, B1, B2. Results show that all DGVMs are consistent with the contemporary global land carbon budget. Under the more extreme projections of future environmental change, the responses of the DGVMs diverge markedly. In particular, large uncertainties are associated with the response of tropical vegetation to drought and boreal ecosystems to elevated temperatures and changing soil moisture status. The DGVMs show more divergence in their response to regional changes in climate than to increases in atmospheric CO2 content. All models simulate a release of land carbon in response to climate, when physiological effects of elevated atmospheric CO2 on plant production are not considered, implying a positive terrestrial climate-carbon cycle feedback. All DGVMs simulate a reduction in global net primary production (NPP) and a decrease in soil residence time in the tropics and extra-tropics in response to future climate. When both counteracting effects of climate and atmospheric CO2 on ecosystem function are considered, all the DGVMs simulate cumulative net land carbon uptake over the 21st century for the four SRES emission scenarios. However, for the most extreme A1FI emissions scenario, three out of five DGVMs simulate an annual net source of CO2 from the land to the atmosphere in the final decades of the 21st century. For this scenario, cumulative land uptake differs by 494 Pg C among DGVMs over the 21st century. This uncertainty is equivalent to over 50 years of anthropogenic emissions at current levels. [ABSTRACT FROM AUTHOR]

Measurements of the net CO2 flux between terrestrial ecosystems and the atmosphere using the eddy covariance technique have the potential to underpin our interpretation of regional CO2 source–sink patterns, CO2 flux responses to forcings, and predictions of the future terrestrial C balance. Information contained in FLUXNET eddy covariance data has multiple uses for the development and application of global carbon models, including evaluation/validation, calibration, process parameterization, and data assimilation. This paper reviews examples of these uses, compares global estimates of the dynamics of the global carbon cycle, and suggests ways of improving the utility of such data for global carbon modelling. Net ecosystem exchange of CO2 (NEE) predicted by different terrestrial biosphere models compares favourably with FLUXNET observations at diurnal and seasonal timescales. However, complete model validation, particularly over the full annual cycle, requires information on the balance between assimilation and decomposition processes, information not readily available for most FLUXNET sites. Site history, when known, can greatly help constrain the model-data comparison. Flux measurements made over four vegetation types were used to calibrate the land-surface scheme of the Goddard Institute for Space Studies global climate model, significantly improving simulated climate and demonstrating the utility of diurnal FLUXNET data for climate modelling. Land-surface temperatures in many regions cool due to higher canopy conductances and latent heat fluxes, and the spatial distribution of CO2 uptake provides a significant additional constraint on the realism of simulated surface fluxes. FLUXNET data are used to calibrate a global production efficiency model (PEM). [ABSTRACT FROM AUTHOR]

We present a first assessment of the potential impacts of anthropogenic climate change on the endemic flora of Namibia, and on its vegetation structure and function, for a projected climate in ∼2050 and ∼2080. We used both niche-based models (NBM) to evaluate the sensitivity of 159 endemic species to climate change (of an original 1020 plant species modeled) and a dynamic global vegetation model (DGVM) to assess the impacts of climate change on vegetation structure and ecosystem functioning. Endemic species modeled by NBM are moderately sensitive to projected climate change. Fewer than 5% are predicted to experience complete range loss by 2080, although more than 47% of the species are expected to be vulnerable (range reduction >30%) by 2080 if they are assumed unable to migrate. Disaggregation of results by life-form showed distinct patterns. Endemic species of perennial herb, geophyte and tree life-formsare predicted to be negatively impacted in Namibia, whereas annual herb and succulent endemic species remain relatively stable by 2050 and 2080. Endemic annual herb species are even predicted to extend their range north-eastward into the tree and shrub savanna with migration, and tolerance of novel substrates. The current protected area network is predicted to meet its mandate by protecting most of the current endemicity in Namibia into the future. Vegetation simulated by DGVM is projected to experience a reduction in cover, net primary productivity and leaf area index throughout much of the country by 2050, with important implications for the faunal component of Namibia's ecosystems, and the agricultural sector. The plant functional type (PFT) composition of the major biomes may be substantially affected by climate change and rising atmospheric CO2– currently widespread deciduous broad leaved trees and C4 PFTs decline, with the C4 PFT particularly negatively affected by rising atmospheric CO2 impacts by ∼2080 and deciduous broad leaved trees more likely directly impacted by drying and warming. The C3 PFT may increase in prominence in the northwestern quadrant of the country by ∼2080 as CO2 concentrations increase. These results suggest that substantial changes in species diversity, vegetation structure and ecosystem functioning can be expected in Namibia with anticipated climate change, although endemic plant richness may persist in the topographically diverse central escarpment region. [ABSTRACT FROM AUTHOR]

Vegetation phenology is affected by climate change and in turn feeds back on climate by affecting the annual carbon uptake by vegetation. To quantify the impact of phenology on terrestrial carbon fluxes, we calibrate a bud-burst model and embed it in the Sheffield dynamic global vegetation model (SDGVM) in order to perform carbon budget calculations. Bud-burst dates derived from the VEGETATION sensor onboard the SPOT-4 satellite are used to calibrate a range of bud-burst models. This dataset has been recently developed using a new methodology based on the normalized difference water index, which is able to distinguish snowmelt from the onset of vegetation activity after winter. After calibration, a simple spring warming model was found to perform as well as more complex models accounting for a chilling requirement, and hence it was used for the carbon flux calculations. The root mean square difference (RMSD) between the calibrated model and the VEGETATION dataset was 6.5 days, and was 6.9 days between the calibrated model and independent ground observations of bud-burst available at nine locations over Siberia. The effects of bud-burst model uncertainties on the carbon budget were evaluated using the SDGVM. The 6.5 days RMSD in the bud-burst date (a 6% variation in the growing season length), treated as a random noise, translates into about 41 g cm−2 yr−1 in net primary production (NPP), which corresponds to 8% of the mean NPP. This is a moderate impact and suggests the calibrated model is accurate enough for carbon budget calculations. In addition to random differences between the calibrated model and VEGETATION data, systematic errors between the calibrated bud-burst model and true ground behaviour may occur, because of bias in the temperature dataset or because the bud-burst detected by VEGETATION is because of some other phenological indicator. A systematic error of 1 day in bud-burst translates into a 10 g cm−2 yr−1 error in NPP (about 2%). Based on the limited available ground data, any systematic error because of the use of VEGETATION data should not lead to significant errors in the calculated carbon flux. In contrast, widely used methods based on the normalized difference vegetation index from the advanced very high resolution radiometer satellite are likely to confuse snowmelt and vegetation greening, leading to errors of up to 15 days in bud-burst date, with consequent large errors in carbon flux calculations. [ABSTRACT FROM AUTHOR]

Abstract The distribution and abundance of trees can be strongly affected by disturbance such as fire. In mixed tree/grass ecosystems, recurrent grass-fuelled fires can strongly suppress tree saplings and therefore control tree dominance. We propose that changes in atmospheric [CO2 ] could influence tree cover in such metastable ecosystems by altering their postburn recovery rates relative to flammable herbaceous growth forms such as grasses. Slow sapling recovery rates at low [CO2 ] would favour the spread of grasses and a reduction of tree cover. To test the possible importance of [CO2 ]/fire interactions, we first used a Dynamic Global Vegetation Model (DGVM) to simulate biomass in grassy ecosystems in South Africa with and without fire. The results indicate that fire has a major effect under higher rainfall conditions suggesting an important role for fire/[CO2 ] interactions. We then used a demographic model of the effects of fire on mesic savanna trees to test the importance of grass/tree differences in postburn recovery rates. We adjusted grass and tree growth in the model according to the DGVM output of net primary production at different [CO2 ] relative to current conditions. The simulations predicted elimination of trees at [CO2 ] typical of the last glacial period (180 ppm) because tree growth rate is too slow (15 years) to grow to a fire-proof size of ca. 3 m. Simulated grass growth would produce an adequate fuel load for a burn in only 2 years. Simulations of preindustrial [CO2 ] (270 ppm) predict occurrence of trees but at low densities. The greatest increase in trees occurs from preindustrial to current [CO2 ] (360 ppm). The simulations are consistent with palaeo-records which indicate that trees disappeared from sites that are currently savannas in South Africa in the last glacial. Savanna trees reappeared in the Holocene. There has also been a large increase... [ABSTRACT FROM AUTHOR]

Summary The possible responses of ecosystem processes to rising atmospheric CO2 concentration and climate change are illustrated using six dynamic global vegetation models that explicitly represent the interactions of ecosystem carbon and water exchanges with vegetation dynamics. The models are driven by the IPCC IS92a scenario of rising CO2 (), and by climate changes resulting from effective CO2 concentrations corresponding to IS92a, simulated by the coupled ocean atmosphere model HadCM2-SUL. Simulations with changing CO2 alone show a widely distributed terrestrial carbon sink of 1.4–3.8 Pg C y-1 during the 1990s, rising to 3.7–8.6 Pg C y-1 a century later. Simulations including climate change show a reduced sink both today (0.6–3.0 Pg C y-1) and a century later (0.3–6.6 Pg C y-1) as a result of the impacts of climate change on NEP of tropical and southern hemisphere ecosystems. In all models, the rate of increase of NEP begins to level off around 2030 as a consequence of the ‘diminishing return’ of physiological CO2 effects at high CO2 concentrations. Four out of the six models show a further, climate-induced decline in NEP resulting from increased heterotrophic respiration and declining tropical NPP after 2050. Changes in vegetation structure influence the magnitude and spatial pattern of the carbon sink and, in combination with changing climate, also freshwater availability (runoff). It is shown that these changes, once set in motion, would continue to evolve for at least a century even if atmospheric CO2 concentration and climate could be instantaneously stabilized. The results should be considered illustrative in the sense that the choice of CO2 concentration scenario was arbitrary and only one climate model scenario was used. However, the results serve to indicate a range of possible biospheric responses to CO2 and climate change. They reveal major uncertainties about the response of NEP to climate change resulting, primarily, from differences in the way that modelled global NPP responds to a changing climate. The simulations illustrate, however, that the magnitude of possible biospheric influences on the carbon balance requires that this factor is taken into account for future scenarios of atmospheric CO2 and climate change. [ABSTRACT FROM AUTHOR]

SummaryDuring the past century, annual mean temperature has increased by 0.75°C and precipitation has shown marked variation throughout the Mediterranean basin. These historical climate changes may have had significant, but presently undefined, impacts on the productivity and structure of sclerophyllous shrubland, an important vegetation type in the region. We used a vegetation model for this functional type to examine climate change impacts, and their interaction with the concurrent historical rise in atmospheric CO2. Using only climate and soil texture as data inputs, model predictions showed good agreement with observations of seasonal and regional variation in leaf and canopy physiology, net primary productivity (NPP), leaf area index (LAI) and soil water. Model simulations for shrubland sites indicated that potential NPP has risen by 25% and LAI by 7% during the past century, although the absolute increase in LAI was small. Sensitivity analysis suggested that the increase in atmospheric CO2 since 1900 was the primary cause of these changes, and that simulated climate change alone had negative impacts on both NPP and LAI. Effects of rising CO2 were mediated by significant increases in the efficiency of water-use in NPP throughout the region, as a consequence of the direct effect of CO2 on leaf gas exchange. This increase in efficiency compensated for limitation of NPP by drought, except in areas where drought was most severe. However, while water was used more efficiently, total canopy water loss rose slightly or remained unaffected in model simulations, because increases in LAI with CO2 counteracted the effects of reduced stomatal conductance on transpiration. Model simulations for the Mediterranean region indicate that the recent rise in atmospheric CO2 may already have had significant impacts on productivity, structure and water relations of sclerophyllous shrub vegetation, which... [ABSTRACT FROM AUTHOR]

Abstract Evaluating the role of terrestrial ecosystems in the global carbon cycle requires a detailed understanding of carbon exchange between vegetation, soil, and the atmosphere. Global climatic change may modify the net carbon balance of terrestrial ecosystems, causing feedbacks on atmospheric CO2 and climate. We describe a model for investigating terrestrial carbon exchange and its response to climatic variation based on the processes of plant photosynthesis, carbon allocation, litter production, and soil organic carbon decomposition. The model is used to produce geographical patterns of net primary production (NPP), carbon stocks in vegetation and soils, and the seasonal variations in net ecosystem production (NEP) under both contemporary and future climates. For contemporary climate, the estimated global NPP is 57.0 Gt C y–1 , carbon stocks in vegetation and soils are 640 Gt C and 1358 Gt C, respectively, and NEP varies from –0.5 Gt C in October to 1.6 Gt C in July. For a doubled atmospheric CO2 concentration and the corresponding climate, we predict that global NPP will rise to 69.6 Gt C y–1 , carbon stocks in vegetation and soils will increase by, respectively, 133 Gt C and 160 Gt C, and the seasonal amplitude of NEP will increase by 76%. A doubling of atmospheric CO2 without climate change may enhance NPP by 25% and result in a substantial increase in carbon stocks in vegetation and soils. Climate change without CO2 elevation will reduce the global NPP and soil carbon stocks, but leads to an increase in vegetation carbon because of a forest extension and NPP enhancement in the north. By combining the effects of CO2 doubling, climate change, and the consequent redistribution of vegetation, we predict a strong enhancement in NPP and carbon stocks of terrestrial ecosystems. This study simulates the possible variation in the carbon exchange at equilibrium... [ABSTRACT FROM AUTHOR]

Global climate change is expected to shift regional rainfall patterns, influencing species distributions where they depend on water availability. Comparative studies have demonstrated that C4 grasses inhabit drier habitats than C3 relatives, but that both C3 and C4 photosynthesis are susceptible to drought. However, C4 plants may show advantages in hydraulic performance in dry environments. We investigated the effects of seasonal variation in water availability on leaf physiology, using a common garden experiment in the Eastern Cape of South Africa to compare 12 locally occurring grass species from C4 and C3 sister lineages. Photosynthesis was always higher in the C4 than C3 grasses across every month, but the difference was not statistically significant during the wettest months. Surprisingly, stomatal conductance was typically lower in the C3 than C4 grasses, with the peak monthly average for C3 species being similar to that of C4 leaves. In water-limited, rain-fed plots, the photosynthesis of C4 leaves was between 2.0 and 7.4 μmol m(-2) s(-1) higher, stomatal conductance almost double, and transpiration 60% higher than for C3 plants. Although C4 average instantaneous water-use efficiencies were higher (2.4-8.1 mmol mol(-1)) than C3 averages (0.7-6.8 mmol mol(-1)), differences were not as great as we expected and were statistically significant only as drought became established. Photosynthesis declined earlier during drought among C3 than C4 species, coincident with decreases in stomatal conductance and transpiration. Eventual decreases in photosynthesis among C4 plants were linked with declining midday leaf water potentials. However, during the same phase of drought, C3 species showed significant decreases in hydrodynamic gradients that suggested hydraulic failure. Thus, our results indicate that stomatal and hydraulic behaviour during drought enhances the differences in photosynthesis between C4 and C3 species. We suggest that these drought responses are important for understanding the advantages of C4 photosynthesis under field conditions., (© 2014 The Authors Global Change Biology Published by John Wiley & Sons Ltd.)

The biospheric water and carbon cycles are intimately coupled, so simulating carbon fluxes by vegetation also requires modelling of the water fluxes, with each component influencing the other. Observations of river streamflow integrate information at the catchment scale and are widely available over a long period; they therefore provide an important source of information for validating or calibrating vegetation models. In this paper, we analyse the performance of the Sheffield dynamic global vegetation model (SDGVM) for predicting river streamflow and quantifying how this information helps to constrain carbon flux predictions. The SDGVM is run for 29 large catchments in the United Kingdom. Annual streamflow estimates are compared with long time-series observations. In 23 out of the 29 catchments, the bias between model and observations is less than 50 mm, equivalent to less than 10% of precipitation. In the remaining catchments, larger errors are because of combinations of unpredictable causes, in particular various human activities and measurement issues and, in two cases, unidentified causes. In one of the catchments, we assess to what extent a knowledge of annual streamflow can constrain model parameters and in turn constrain estimates of gross primary production (GPP). For this purpose, we assume the model parameters are uncertain and constrain them by the streamflow observations using the generalized likelihood uncertainty estimation method. Comparing the probability density function of GPP with and without constraint shows that streamflow effectively constrains GPP, mainly by setting a low probability to GPP values below about 1100 g C -1  m 2  yr -1 . In other words, streamflow observations allow the rejection of low values of GPP, so that the potential range of possible GPP values is almost halved.