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The world's forests store large amounts of carbon (C), and growing forests can reduce atmospheric CO 2 by storing C in their biomass. This has provided the impetus for world-wide tree planting initiatives to offset fossil-fuel emissions. However, forests interact with their environment in complex and multifaceted ways that must be considered for a balanced assessment of the value of planting trees. First, one needs to consider the potential reversibility of C sequestration in trees through either harvesting or tree death from natural factors. If carbon storage is only temporary, future temperatures will actually be higher than without tree plantings, but cumulative warming will be reduced, contributing both positively and negatively to future climate-change impacts. Alternatively, forests could be used for bioenergy or wood products to replace fossil-fuel use which would obviate the need to consider the possible reversibility of any benefits. Forests also affect the Earth's energy balance through either absorbing or reflecting incoming solar radiation. As forests generally absorb more incoming radiation than bare ground or grasslands, this constitutes an important warming effect that substantially reduces the benefit of C storage, especially in snow-covered regions. Forests also affect other local ecosystem services, such as conserving biodiversity, modifying water and nutrient cycles, and preventing erosion that could be either beneficial or harmful depending on specific circumstances. Considering all these factors, tree plantings may be beneficial or detrimental for mitigating climate-change impacts, but the range of possibilities makes generalisations difficult. Their net benefit depends on many factors that differ between specific circumstances. One can, therefore, neither uncritically endorse tree planting everywhere, nor condemn it as counter-productive. Our aim is to provide key information to enable appropriate assessments to be made under specific circumstances. We conclude our discussion by providing a step-by-step guide for assessing the merit of tree plantings under specific circumstances., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Rain-fed pastoral systems are tightly connected to meteorological conditions. It is, therefore, likely that climate change, including changing atmospheric CO2 concentration, temperature, precipitation and patterns of climate extremes, will greatly affect pastoral systems. However, exact impacts on the productivity and carbon dynamics of these systems are still poorly understood, particularly over longtime scales. The present study assesses the potential effects of future climatic conditions on productivity and soil organic carbon (SOC) stocks of mowed and rotationally grazed grasslands in France. We used the CenW ecosystem model to simulate carbon, water, and nitrogen cycles in response to changes in environmental drivers and management practices. We first evaluated model responses to individual changes in each key meteorological variable to get better insights into the role and importance of each individual variable. Then, we used 3 sets of meteorological variables corresponding to 3 Representative Concentration Pathways (RCP 2.6, RCP 4.5 and RCP 8.5) for long-term model runs from 1975 to 2100. Finally, we used the same three RCPs to analyze the responses of modelled grasslands to extreme climate events. We found that increasing temperature slightly increased grasslands productivities but strongly reduced SOC stocks. A reduction in precipitation led to reductions of biomass and milk production but increased SOC. Conversely, doubling CO2 concentration strongly increased biomass and milk production and marginally reduced SOC. These SOC trends were unexpected. They arose because both increasing precipitation and CO2 increased photosynthetic carbon gain, but they had an even greater effect on the proportion of biomass that could be grazed. The amount of carbon remaining on site and able to contribute to SOC formation was actually reduced under both higher precipitation and CO2. The simulations under the three RCPs indicated that grassland productivity was increased, but that required higher N fertilizer application rates and also led to substantial SOC losses. We thus conclude that, while milk productivity may continue at current rates under climate change, or even increase slightly, there could be some soil C losses over the 21st century. In addition, under the highest-emission scenario, the increasing importance of extreme climate conditions (heat waves and droughts) might render conditions at our site in some years as unsuitable for milk production. It highlights the importance of tailoring farming practices to achieve the dual goals of maintaining agricultural production while safeguarding soil C stocks., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Puche et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Climate warming can reduce global soil carbon stocks by enhancing microbial decomposition. However, the magnitude of this loss remains uncertain because the temperature sensitivity of the decomposition of the major fraction of soil carbon, namely resistant carbon, is not fully known. It is now believed that the resistance of soil carbon mostly depends on microbial accessibility of soil carbon with physical protection being the primary control of the decomposition of protected carbon, which is insensitive to temperature changes. However, it is still unclear whether the temperature sensitivity of the decomposition of unprotected carbon, for example, carbon that is not protected by the soil mineral matrix, may depend on the chemical recalcitrance of carbon compounds. In particular, the carbon-quality temperature (CQT) hypothesis asserts that recalcitrant low-quality carbon is more temperature-sensitive to decomposition than labile high-quality carbon. If the hypothesis is correct, climate warming could amplify the loss of unprotected, but chemically recalcitrant, carbon and the resultant CO 2 release from soils to the atmosphere. Previous research has supported this hypothesis based on reported negative relationships between temperature sensitivity and carbon quality, defined as the decomposition rate at a reference temperature. Here we show that negative relationships can arise simply from the arbitrary choice of reference temperature, inherently invalidating those tests. To avoid this artefact, we defined the carbon quality of different compounds as their uncatalysed reaction rates in the absence of enzymes. Taking the uncatalysed rate as the carbon quality index, we found that the CQT hypothesis is not supported for enzyme-catalysed reactions, which showed no relationship between carbon quality and temperature sensitivity. The lack of correlation in enzyme-catalysed reactions implies similar temperature sensitivity for microbial decomposition of soil carbon, regardless of its quality, thereby allaying concerns of acceleration of warming-induced decomposition of recalcitrant carbon., (© 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20 th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those 'next users' of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO 2 sink to a net CO 2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers., (© 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Previous soil sampling from grazed pastures in New Zealand compared the changes of soil organic carbon (SOC) in adjacent irrigated and unirrigated portions of the same paddocks. It showed that irrigated portions had lower SOC stocks than unirrigated portions, with an average difference of 7.0 tC ha -1 or 0.6 tC ha -1  yr -1 . These findings have formed the basis of an assessment for the net effect of conversion of New Zealand's grazed pastures to irrigation. However, since cattle could move freely between irrigated and unirrigated portions of the studied paddocks, there could have been different grazing intensities and/or excreta transfer between the irrigated and unirrigated portions of the same paddocks. Both these factors could have affected SOC stocks. In this study, we used the process-based model, CenW, to simulate the consequences of this possible carbon transfer via animal excreta and different grazing intensities. We found that the observed increase of 0.6 tC ha -1  yr -1 in SOC stock in the unirrigated portions could result from a transfer of 20% excreta from the irrigated to unirrigated portions (with an area ratio of 6:1) of a paddock and with the unirrigated portions being grazed only lightly with 2.0 tDM ha -1 in foliage biomass residuals remaining after grazing. That means that the observed higher SOC stocks in the unirrigated portions could potentially be attributable to the behaviour of grazing animals. We suggest that a realistic extent of carbon transfer and/or differences in grazing intensities could be sufficient to account for the observed differences in SOC stocks even if irrigation per se caused no differences in carbon stocks. It is therefore inappropriate to ascribe the change of SOC to irrigation effects based on experimental findings where SOC changes can be affected by the behaviour of grazing animals., Competing Interests: Declaration of competing interest The authors declare that there is no conflict of interest., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Simulation models represent soil organic carbon (SOC) dynamics in global carbon (C) cycle scenarios to support climate-change studies. It is imperative to increase confidence in long-term predictions of SOC dynamics by reducing the uncertainty in model estimates. We evaluated SOC simulated from an ensemble of 26 process-based C models by comparing simulations to experimental data from seven long-term bare-fallow (vegetation-free) plots at six sites: Denmark (two sites), France, Russia, Sweden and the United Kingdom. The decay of SOC in these plots has been monitored for decades since the last inputs of plant material, providing the opportunity to test decomposition without the continuous input of new organic material. The models were run independently over multi-year simulation periods (from 28 to 80 years) in a blind test with no calibration (Bln) and with the following three calibration scenarios, each providing different levels of information and/or allowing different levels of model fitting: (a) calibrating decomposition parameters separately at each experimental site (Spe); (b) using a generic, knowledge-based, parameterization applicable in the Central European region (Gen); and (c) using a combination of both (a) and (b) strategies (Mix). We addressed uncertainties from different modelling approaches with or without spin-up initialization of SOC. Changes in the multi-model median (MMM) of SOC were used as descriptors of the ensemble performance. On average across sites, Gen proved adequate in describing changes in SOC, with MMM equal to average SOC (and standard deviation) of 39.2 (±15.5) Mg C/ha compared to the observed mean of 36.0 (±19.7) Mg C/ha (last observed year), indicating sufficiently reliable SOC estimates. Moving to Mix (37.5 ± 16.7 Mg C/ha) and Spe (36.8 ± 19.8 Mg C/ha) provided only marginal gains in accuracy, but modellers would need to apply more knowledge and a greater calibration effort than in Gen, thereby limiting the wider applicability of models., (© 2020 John Wiley & Sons Ltd.)

Plant leaf respiration is one of the critical components of the carbon cycle in terrestrial ecosystems. To predict changes of carbon emissions from leaves to the atmosphere under a warming climate, it is, therefore, important to understand the thermodynamics of the temperature response of leaf respiration. In this study, we measured the short-term temperature response of leaf respiration from five different urban tree species in a subtropical region of southern China. We applied two models, including an empirical model (the Kavanau model) and a mechanistic model (Macromolecular Rate Theory, MMRT), to investigate the thermodynamic properties in different plant species. Both models are equivalent in fitting measurements of the temperature response of leaf respiration with no significant difference ( p = 0.67) in model efficiency, while MMRT provides an easy way to determine the thermodynamic properties, i.e., enthalpy, entropy, and Gibbs free energy of activation, for plant respiration. We found a conserved temperature response in the five studied plant species, showing no difference in thermodynamic properties and the relative temperature sensitivity for different species at low temperatures (<42°C). However, divergent temperature response among species happened at high temperatures over 42°C, showing more than two-fold differences in relative respiration rate compared to that below 42°C, although the causes of the divergent temperature response remain unclear. Notably, the convergent temperature response at low temperatures could provide useful information for land surface models to improve predictions of climate change effects on plant respiration., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Xu, Liáng, Kirschbaum, Fang and Yu.)

Background: Some of New Zealand's exotic pine ( Pinus radiata D.Don) forests were planted for erosion mitigation but cultural, legislative, environmental, and profitability limitations in some parts of the landscape have led to reassessment of their suitability. There is limited information to support landowner decisions on the viability of natural regeneration of native forest post-pine-harvest., Methods: We evaluated scenarios of post-harvest natural regeneration, compared to remaining in pine production, using erosion susceptibility determined from historical occurrence of landslides, gullies and earthflows, biophysical growth modelling of mānuka-kānuka ( Leptospermum scoparium-Kunzea ericoides (A.Rich) Joy Thomps.) shrubland using the process-based CenW model, and cost-benefit analyses using NZFARM with two land use change scenarios, at two levels of erosion mitigation ± honey profits., Results: In our study area, the Gisborne Region (North Island of New Zealand), ~27% of the land has moderate-very high susceptibility to landslides, 14-22% a high probability of contributing material to waterways, and 19% moderate-very high gully erosion susceptibility. Pines grow 10 times faster than naturally regenerating mānuka-kānuka shrubland, but mānuka-kānuka is used for honey not wood production. Natural regeneration resulted in losses of $150-250 ha -1 yr -1 compared to the current profitability of pine production. Honey production offset some reduction in pine revenue, but not fully. Thus, the viability of shifting from pines to native forest is highly dependent on landowner impetus and value for non-market ecosystem services (such as cultural and biodiversity values) provided by native forest., Conclusions: A mosaic of land uses within a property may sufficiently offset income losses with other benefits, whereby highly erosion-prone land is shifted from rotational pine forest production to permanent native forest cover with honey production where possible. At the regional scale in Gisborne, the conversion of the most highly susceptible land under production forestry (315-556 ha) to natural regeneration has the potential for wider benefits for soil conservation reducing erosion by 1-2.5 t yr -1 of sediment facilitating achievement of cleaner water aspirations and habitat provision., Competing Interests: Competing interests The authors declare that they have no competing interests.

Many temperate grasslands are used for dairying, and ongoing research aims to better understand these systems in order to increase animal production and soil organic carbon (SOC) stocks. However, it is difficult to fully understand management effects on SOC because most changes are slow and difficult to distinguish from natural variability, even if changes are important over years to decades. Eddy covariance (EC) measurements can overcome this problem by continuously measuring net carbon exchange from pastures, but net balances are very sensitive to even small systematic measurement errors. Combining EC measurements with detailed process-based modelling can reduce the risks inherent in total reliance on EC measurements. Modelling can also reveal information about the underlying processes that drive observed fluxes. Here, we describe carbon exchange patterns of five paddocks situated at four different locations in New Zealand and France where EC data and detailed physiological modelling were available. The work showed that respiration by grazing animals was often only incompletely captured in EC measurements. This was most problematic when fluxes were based on gap-filling, which could have estimated incorrect fluxes during grazing periods based on observations from periods without grazing. We then aimed to extract plant physiological insights from these studies. We found appreciable carbon uptake rates even at temperatures below 0 °C. After grazing, carbon uptake was reduced for up to 2 weeks. This reduction was larger than expected from reduced leaf area after grazing, but the factors contributing to that difference have not yet been identified. Detailed physiological models can also extrapolate findings to new management regimes, environmental conditions or plant attributes. This overcomes the limitation of experimental studies, which are necessarily restricted to actual site and weather conditions allowing models to make further progress on predicting management effects on SOC., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

In New Zealand, pasture renewal is a routine management method for maintaining pasture productivity. However, knowledge of the renewal effects on soil organic carbon (SOC) stocks is still limited. Here we use a process-based model, CenW, to comprehensively assess the effects of pasture renewal on the carbon balance of a temperate pasture in the Waikato region of New Zealand. We investigated the effects of renewal frequency, length of fallow period, renewal timing, and the importance and quantification of age-related reductions in productivity. Our results suggest that SOC change depends on the combined effects of renewal on gross primary productivity (GPP), autotrophic and heterotrophic respiration, carbon removal by grazing and carbon allocation to roots. Pasture renewal reduces grazing removal proportionately more than GPP because newly established plants need to allocate more carbon to re-build their root system following renewal which limits foliage production. That lengthens the time before above-ground biomass has grown sufficiently to be grazed again. New plants have a lower ratio of autotrophic respiration to GPP, however, which partly compensates for the GPP loss during renewal. Our simulations suggested an average SOC loss of 0.16 tC ha -1  yr -1 if pastures were renewed every 25 years, but could gain an average of 0.3 tC ha -1  yr -1 if pastures were renewed every year. For maximizing pasture production, the optimal renewal frequency depends on the rate of pasture deterioration with more rapid deterioration rates favouring more frequent renewal. Additionally, the length of the fallow period, renewal timing, and associated environmental conditions are important factors that can affect SOC temporally, but the importance of those effects diminishes at the annual or longer time scales. A major uncertainty for a full understanding of the renewal effect on SOC lies in the rate of pasture deterioration with time since previous renewal., Competing Interests: Declaration of competing interest The authors declare that there is no conflict of interest., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N 2 O) emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2-4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N 2 O emissions. Results showed that across sites and crop/grassland types, 23%-40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N 2 O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N 2 O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2-4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N 2 O emissions. Yield-scaled N 2 O emissions (N 2 O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The potential of using process-based model ensembles to predict jointly productivity and N 2 O emissions at field scale is discussed., (© 2017 John Wiley & Sons Ltd.)

Many short-term experiments have been conducted under increasing CO2 but results have been varied and have not yet led to a conclusive quantitative understanding of the CO2 response of plant growth. This may have been partly due to a lack of explicit consideration of the positive feedback inherent in plant growth during periods of exponential growth. This feedback can increase an initial physiological enhancement of relative growth rate (RGR) into a much larger biomass enhancement. To overcome this problem, we re-analysed existing experimental data from 78 publications. We calculated the RGRs of C3 plants and their relative enhancement under elevated CO2 and derived response indices that were independent of the duration of experiments and the RGR at normal atmospheric CO2. The RGR of unstressed plants increased by 14±2% under doubled CO2, with observed RGR enhancement linearly correlated with calculated photosynthetic enhancements (based on the Farquhar-von Caemmerer-Berry photosynthesis model), but at only half their numeric values. Calculated RGR enhancements did not change significantly for temperatures from 12 to 40°C, but were reduced under nutrient limitation, and were increased under water stress or low irradiance. We concluded that short-term experiments can offer simple and cost-effective insights into plant CO2 responses, provided they are analysed by calculating relative changes in RGR during the strictly exponential initial growth phase.

We used two years of eddy covariance (EC) measurements collected over an intensively grazed dairy pasture to better understand the key drivers of changes in soil organic carbon stocks. Analysing grazing systems with EC measurements poses significant challenges as the respiration from grazing animals can result in large short-term CO2 fluxes. As paddocks are grazed only periodically, EC observations derive from a mosaic of paddocks with very different exchange rates. This violates the assumptions implicit in the use of EC methodology. To test whether these challenges could be overcome, and to develop a tool for wider scenario testing, we compared EC measurements with simulation runs with the detailed ecosystem model CenW 4.1. Simulations were run separately for 26 paddocks around the EC tower and coupled to a footprint analysis to estimate net fluxes at the EC tower. Overall, we obtained good agreement between modelled and measured fluxes, especially for the comparison of evapotranspiration rates, with model efficiency of 0.96 for weekly averaged values of the validation data. For net ecosystem productivity (NEP) comparisons, observations were omitted when cattle grazed the paddocks immediately around the tower. With those points omitted, model efficiencies for weekly averaged values of the validation data were 0.78, 0.67 and 0.54 for daytime, night-time and 24-hour NEP, respectively. While not included for model parameterisation, simulated gross primary production also agreed closely with values inferred from eddy covariance measurements (model efficiency of 0.84 for weekly averages). The study confirmed that CenW simulations could adequately model carbon and water exchange in grazed pastures. It highlighted the critical role of animal respiration for net CO2 fluxes, and showed that EC studies of grazed pastures need to consider the best approach of accounting for this important flux to avoid unbalanced accounting., (Copyright © 2015. Published by Elsevier B.V.)

A recent study by Keppler et al. (2006; Nature 439, 187-191) demonstrated CH 4 emission from living and dead plant tissues under aerobic conditions. This work included some calculations to extrapolate the findings from the laboratory to the global scale and led various commentators to question the value of planting trees as a greenhouse mitigation option. The experimental work of Keppler et al. (2006) appears to be largely sound, although some concerns remain about the quantification of emission rates. However, whilst accepting their basic findings, we are critical of the method used for extrapolating results to a global scale. Using the same basic information, we present alternative calculations to estimate global aerobic plant CH 4 emissions as 10-60 Mt CH 4 year -1 . This estimate is much smaller than the 62-236 Mt CH 4 year -1 reported in the original study and can be more readily reconciled within the uncertainties in the established sources and sinks in the global CH 4 budget. We also assessed their findings in terms of their possible relevance for planting trees as a greenhouse mitigation option. We conclude that consideration of aerobic CH 4 emissions from plants would reduce the benefit of planting trees by between 0 and 4.4%. Hence, any offset from CH 4 emission is small in comparison to the significant benefit from carbon sequestration. However, much critical information is still lacking about aerobic CH 4 emission from plants. For example, we do not yet know the underlying mechanism for aerobic CH 4 emission, how CH 4 emissions change with light, temperature and the physiological state of leaves, whether emissions change over time under constant conditions, whether they are related to photosynthesis and how they relate to the chemical composition of biomass. Therefore, the present calculations must be seen as a preliminary attempt to assess the global significance from a basis of limited information and are likely to be revised as further information becomes available.

Net primary production links the biosphere and the climate system through the global cycling of carbon, water and nutrients. Accurate quantification of net primary productivity (NPP) is therefore critical in understanding the response of the world's ecosystems to global climate change, and how changes in ecosystems might themselves feed back to the climate system.

To grow, plants need both carbon, which is fixed in photosynthesis, and inorganic nutrients, which are generally obtained from the soil. Much interest currently exists in trying to understand the uptake and storage of carbon by terrestrial ecosystems. This paper investigates to what extent carbon gain and storage are modified by soil nutrient availability. This issue is investigated in relation to both short-term carbon fluxes on the time scale of interannual variability and long-term ecosystem carbon stocks on time scales of several thousand years.We conclude from simulations with an ecosystem model (CenW) that interannual variations in carbon gain can be significantly affected by feedback effects through the nutrient cycle. This feedback effect operates principally through an imbalance between carbon and nutrient dynamics. In years that allow high carbon gain, nutrient supply typically does not match the increased carbon supply so that foliar nutrient concentrations are reduced. This lowers productivity below that which could be expected if foliar nutrient concentration remained the same. The importance of these feedback effects is shown to be greatest at intermediate levels of water availability and nutrient supply, and is relatively more important for net ecosystem carbon exchange than for net primary production.We conclude that the long-term build-up of carbon stocks in ecosystems is often controlled by the rate at which nutrients can be gained. This conclusion is based on data from published studies showing that the slow build-up of carbon matches the gain in nitrogen, phosphorus and sulfur, and on our simulations of system carbon stocks in response to fertiliser addition.The paper concludes with a discussion of the importance and feasibility of including these processes into models at different scales, including the broad continental scale. For modelling net ecosystem exchange for Australia, it is regarded as feasible and desirable to use models that are constrained by these system-internal feedback effects. Such models have already been used for large-scale simulations in Australia and other countries.